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Lur Epelde Sierra

EVALUATION OF THE EFFICIENCY OF METALPHYTOREMEDIATION PROCESSES WITH

MICROBIOLOGICAL INDICATORSOF SOIL HEALTH

Vitoria-Gasteiz, 2010

TESIS DOCTORALESN.º 71

Evaluation of thE EfficiEncy of mEtalphytorEmEdiation procEssEs

with microbiological indicatorsof soil hEalth

Lur Epelde Sierra

Universidad del País vasco

First published: 1st november 2010

Edition: 55 copies

© Administration of the Autonomous Community of the Basque Country Environment, Territorial Planning, Agriculture and Fishing Department

Internet: www.euskadi.net

Published: Eusko Jaurlaritzaren Argitalpen Zerbitzu Nagusia Servicio Central de Publicaciones del Gobierno Vasco Donostia-San Sebastián, 1 - 01010 Vitoria-Gasteiz

Printed by: Eusko Printing Service, S.L. www.eps-grupo.com

ISBN: 978-84-457-3092-8

Legal record: VI 479-2010

A catalogue record of this book is available in the catalogue of the General Library of the Basque Governement: <http://www.euskadi.net/ejgvbiblioteka>.

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LABURPENA

Gure gizartearen biziraupen eta ongizatea, nahitaez, lurzoru ekosistemaren osasunari lotuta

daude. Zoritxarrez, lurzoruaren kutsaduraren arazoa maila kezkagarrira iritsi da azken

hamarkadetan, baliabide honen funtzionaltasun eta iraunkortasuna kolokan jarriaz.

Fitoerremediazioa kostu ekonomiko baxua, ingurugiroarekiko begirunea eta gizartearen

aldetik harrera ona dituen teknologia izateaz gain, lurzoru kutsatuen erremediaziorako

potentzial handikoa da. Nabarmendu beharra dago edozein prozesu fitoerremediatzaileren

gorengo helburua ez dela izan behar kutsatzailea ezabatzea soilik, baizik eta batez ere

lurzoruaren osasuna berreskuratzea; baliabide honek bere funtzioak modu iraunkorrean

burutzeko duen ahalmena berreskuratzea, alegia, ikuspegi antropozentriko zein

ekozentrikotik begiratuta. Lurzoruaren propietate biologikoek - komunitate mikrobianoen

biomasa, aktibitate eta biodibertsitatearekin zerikusia dutenek, batez ere - potentzial handia

dute lurzoru ekosistemaren osasunaren bioadierazle gisa. Lan honen helburua metalekin

kutsaturiko lurzoruak fitoerremediatzeko estrategia desberdinen ebaluazioa burutzea da,

horretarako lurzoru ekosistemaren osasunaren adierazle gisa potentzial handia duten

lurzoruaren hainbat propietate mikrobiologiko baliatuz.

Gure emaitzek adierazten dutenez, metalek sorturiko kutsadurak lurzoru

ekosistemaren osasunean eragin negatiboa izaten du sarritan eta eragin negatibo hau

praktika fitoerremediatzaileak erabiliz hein handi batean edota guztiz lehengoratu daiteke.

Meatze-inguruneetan aurkitzen diren landareak lurzoruko metal-kontzentrazio altuak

jasateko gai dira, eta fitoerauzketa zein fitoegonkortze prozesuetarako hautagai ezin hobeak

dira. Hain zuzen: (i) Zn eta Cd-aren fitoerauzketa jarraiturako, Thlaspi caerulescens

landarearen “Lanestosa” ekotipoaren izaera hipermetatzailea baieztatu da, eta hortaz,

fitoerauzketarako duen ahalmena (era berean, metalen fitoerauzketarako basartoa bezalako

biomasa altuko laboreak erabiltzea ere baliozko izan daiteke); (ii) kelatzaile bidezko

fitoerauzketari dagokionez, EDDSak EDTAk baino ahalmen txikiagoa du karduan Pb-aren

metaketa eragiteko (bestalde, EDDSak toxikotasun baxuagoa du lurzoruko komunitate

mikrobianoentzako); metalen kimiofitoegonkortzeari buruz, medeapen sintetiko eta

organikoen erabilerak Zn, Pb eta Cd-aren toxikotasuna murrizten du, Lolium perenne-aren

hazkuntza osasuntsua ahalbidetuz; eta (iv), metalak jasateko estrategia desberdinak dituzten

landare pseudometalofitoen konbinazioen erabilerak etorkizun handiko aukera dirudi

metalekin kutsaturiko lurzoruen birlandatze/fitoerremediaziorako. Azkenik, lurzoruko

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propietate mikrobiologikoen sentsibilitate, asalduren aurrean azkar erantzuteko ahalmen eta

izaera bateratzaileari esker, tresna hobezinak dira prozesu fitoerremediatzaileen efizientzia

ebaluatzeko.

RESUMEN

La supervivencia y el bienestar de nuestra sociedad están inextricablemente ligados a

la salud del ecosistema edáfico. Por desgracia, en las últimas décadas, el problema de la

contaminación del suelo ha alcanzado una magnitud alarmante, afectando sin duda

gravemente a la funcionalidad y sostenibilidad de este recurso. La fitorremediación es una

fitotecnología barata, medioambientalmente respetuosa, socialmente aceptada, y de gran

potencial para la remediación de suelos contaminados. Es preciso enfatizar que el objetivo

último de cualquier proceso fitorremediador no debe ser exclusivamente eliminar el

contaminante, sino sobre todo recuperar la salud del suelo, entendida ésta como la

capacidad de este recurso para realizar sus funciones, desde una doble perspectiva

antropocéntrica-ecocéntrica, de forma sostenible. Las propiedades biológicas del suelo, en

especial aquellas relacionadas con la biomasa, actividad y biodiversidad de las comunidades

microbianas edáficas, presentan un gran potencial como herramientas bioindicadoras de la

salud del ecosistema edáfico. El objetivo de este trabajo fue evaluar la eficacia de distintas

estrategias fitorremediadoras de suelos contaminados con metales mediante la utilización

de una gama diversa de propiedades microbiológicas del suelo con potencial indicador de la

salud del ecosistema edáfico.

Nuestros resultados indican que frecuentemente la contaminación por metales tiene

un impacto negativo considerable sobre la salud del ecosistema edáfico, la cual puede ser

parcial o totalmente restablecida mediante prácticas fitorremediadoras. Las plantas

presentes en entornos mineros se caracterizan por su tolerancia a niveles elevados de

metales en el suelo y son candidatas ideales para procesos fitoextractores y

fitoestabilizadores. Concretamente: (i) para la fitoextración en continuo de Zn y Cd, el

ecotipo “Lanestosa” de Thlaspi caerulescens ha confirmado su carácter hiperacumulador y,

por ende, su capacidad fitoextractora (si bien la utilización de cultivares de elevada biomasa

como el sorgo puede ser una estrategia igualmente válida para fitoextraer metales); (ii) en lo

concerniente a la fitoextracción inducida por quelantes, el EDDS tiene menor capacidad

que el EDTA para inducir la acumulación de Pb en cardo (por otra parte, el EDDS es

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menos tóxico para las comunidades microbianas edáficas); (iii) en relación con la

quimiofitoestabilización de metales, la adición de enmiendas sintéticas y orgánicas reduce la

toxicidad del Zn, Pb y Cd, permitiendo el establecimiento de una cubierta sana de Lolium

perenne; y (iv) la opción de utilizar combinaciones de plantas pesudometalofitas con distintas

estrategias de tolerancia a metales para la revegetación/fitorremediación de suelos

contaminados con metales parece altamente prometedora. Por último, la sensibilidad,

rapidez de respuesta frente a perturbaciones y carácter integrador de las propiedades

microbiológicas del suelo hacen de ellas herramientas bioindicadoras óptimas para la

evaluación de la eficiencia de procesos fitorremediadores.

ABSTRACT

The survival and well-being of our society are inextricably linked to the health of the

soil ecosystem. Unfortunately, in the last decades, soil pollution has become a huge

environmental problem that is at the moment seriously affecting the health and

sustainability of our soils. Phytoremediation is considered a cost-effective, environmentally-

friendly, socially accepted phytotechnology of great potential for the remediation of

polluted soils. It must be highlighted that the ultimate goal of any phytoremediation

process must be not only to remove the pollutant from the soil but, most importantly, to

recover soil health, i.e. the capacity of the soil to sustainably carry out its functions from an

anthropocentric and ecocentric point of view. The soil biological properties, particularly

those related to the biomass, activity and diversity of the soil microbial communities, have

great potential as bioindicators of soil health. The main objective of the current work was

to assess the efficiency of different phytoremediation strategies of metal polluted soils

through the determination of a variety of soil microbiological properties with potential as

bioindicators of soil health.

Our results indicate that metal pollution frequently has a considerable adverse impact

on soil health; such health can be partially or totally recovered through phytoremediation

practices. Plants growing in mining sites are characterized by their tolerance to high levels

of soil metals and are, consequently, ideal candidates for phytoextraction and

phytostabilization processes. In particular: (i) for continuous Zn and Cd phytoextraction,

the local Lanestosa ecotype of Thlaspi caerulescens has confirmed its hyperaccumulator

condition as well as its capacity for phytoextraction (nonetheless, the utilization of high

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biomass cultivars such as sorghum can be an equally valid strategy to phytoextract metals);

(ii) regarding chelate-induced phytoextraction, EDDS has a lower capacity than EDTA to

induce Pb accumulation in cardoon (on the other hand, EDDS is less toxic for the soil

microbial communities); (iii) concerning chemophytostabilization, the addition of synthetic

and organic amendments reduces the toxicity caused by Zn, Pb and Cd, thus allowing the

establishment of a healthy Lolium perenne cover; and (iv) the possibility of using

combinations of pseudometallophytes with different strategies of metal tolerance for the

revegetation/phytoremediation of metal polluted soils appears highly promising. Finally,

the sensitivity, rapid response and integrative character of the soil microbiological

properties make them invaluable bioindicators for the assessment of the efficiency of

phytoremediation processes.

Índice

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1. GENERALINTRODUCCTION/INTRODUCCIÓNGENERAL....................................... 1.1. Heavy metal phytoremediation: microbial indicatos of soil health for the

assessmentofremediationefficiency............................................................................. . 1.1.1... Microbial.indicators.of.soil.health....................................................................... . 1.1.2... Heavy.metal.phytoremediation............................................................................ . . 1.1.2.1... Continuous.metal.phytoextraction....................................................... . . 1.1.2.2... Chelate.induced.phytoextraction........................................................ .. . . 1.1.2.3... Phytostabilization................................................................................ . 1.1.3... Conclusions......................................................................................................... 1.2. Contextoyplanteamientodeltrabajodelatesis......................................................... . 1.2.1... Tradición.minera.en.la.CAPV............................................................................. . 1.2.2... Contaminación.del.suelo.en.la.CAPV................................................................. . 1.2.3... Aspectos.legales.de.la.contaminación.del.suelo.................................................. . 1.2.4... Recuperación.de.emplazamientos.contaminados.en.la.CAPV............................ . 1.2.5... Situación.de.la.fitorremediación.a.nivel.global..................................................

2. HIPOTESIAETAHELBURUAK........................................................................................... 2.1. Hipotesia.......................................................................................................................... 2.2. Helburuorokorra........................................................................................................... 2.3. Helburuespezifikoak.....................................................................................................2. HIPÓTESISYOBJETIVOS.................................................................................................... 2.1. Hipótesis.......................................................................................................................... 2.2. Objetivogeneral.............................................................................................................. 2.3. Objetivosespecificos......................................................................................................2. HYPOTHESISANDOBJECTIVES....................................................................................... 2.1. Hypothesis....................................................................................................................... 2.2. Mainobjective................................................................................................................. 2.3. Specificobjectives..........................................................................................................

3. ESCENARIOYPROCEDIMIENTOSGENERALES.......................................................... 3.1. Escenariodeestudioycondicionesdecultivo.............................................................. . 3.1.1... Escenario............................................................................................................. . 3.1.2.. Condiciones.de.cultivo........................................................................................ 3.2. Parámetrosanalíticos..................................................................................................... . 3.2.1... Propiedades.físico-químicas.y.microbiológicas.con.potencial.indicador.de.la.

salud.del.ecosistema.edáfico................................................................................ . . 3.2.1.1. Propiedades microbiológicas con potencial indicador de la salud

del ecosistema edáfico ....................................................................... 3.2.1.2. Propiedades físico-químicas con potencial indicador de la salud del

ecosistema edáfico............................................................................... . 3.2.2... Parámetros.fisiológicos.de.plantas....................................................................... . 3.2.3... Concentración.de.metales.en.suelo.y.planta.......................................................

4. INTERACTIONS BETWEEN PLANT AND RHIZOSPHERE MICROBIALCOMMUNITIESINAMETALLIFEROUSSOIL...............................................................

. 4.1. Abstract..........................................................................................................................

. 4.2. Introduction...................................................................................................................

. 4.3. Materialsandmethods..................................................................................................

. . 4.3.1... Field.characterization.........................................................................................

. . 4.3.2... Plant.parameters.................................................................................................

. . 4.3.3... Soil.microbial.and.physicochemical.parameters................................................

. . 4.3.4... Statistical.analysis...............................................................................................

. 4.4. Results.............................................................................................................................

. . 4.4.1... Soil.microbial.and.physicochemical.properties..................................................

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evaluation of the efficiency of metal phytoremediation processes with microbiological indicators of soil health

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. . 4.4.2... Interactions.between.plants.and.soil.microbial.and.physicochemical.properties


. 4.5. Discussion.......................................................................................................................

. 4.6. Conclusions....................................................................................................................

5. FUNCTIONAL DIVERSITY AS INDICATOR OF THE RECOVERY OF SOILHEALTH DERIVED FROM Thlaspi caerulescens GROWTH AND METALPHYTOEXTRACTION...........................................................................................................

. 5.1. Abstract..........................................................................................................................

. 5.2. Introduction...................................................................................................................


. . 5.3.1... Soil.characterization.and.contamination.............................................................

. . 5.3.2... Experimental.design.and.plant.growth...............................................................

. . 5.3.3... Soil.physicochemical.parameters.and.metal.determination...............................

. . 5.3.4... Soil.biological.parameters..................................................................................

. . 5.3.5... Plant.physiological.parameters.and.metal.accumulation....................................


. 5.4. Results.............................................................................................................................

. . 5.4.1... Thlaspi.caerulescens.growth.and.physiological.parameters...............................

. . 5.4.2... Thlaspi.caerulescens.metal.uptake.....................................................................

. . 5.4.3... Soil.physicochemical.parameters.......................................................................

. . 5.4.4... Soil.enzyme.activities.........................................................................................

. . 5.4.5... Community-level.physiological.profiles............................................................

. 5.5. Discussion.......................................................................................................................

. . 5.5.1... Metal.phytoextraction.........................................................................................

. . 5.5.2... Impact.of.metal.pollution.on.biological.indicators.of.soil.health.......................

. . 5.5.3... Effect. of. T.. caerulescens. growth. and. metal. phytoextraction. on. biological.indicators.of.soil.health.......................................................................................

. 5.6. Conclusions....................................................................................................................

6. IMPACTOFMETALPOLLUTIONANDThlaspi caerulescensPHYTOEXTRACTIONONSOILMICROBIALCOMMUNITIES............................................................................

. 6.1. Abstract..........................................................................................................................

. 6.2. Introduction...................................................................................................................


. . 6.3.1... Experimental.design...........................................................................................

. . 6.3.2... Soil.metal.concentrations....................................................................................

. . 6.3.3... Soil.microbial.parameters...................................................................................



. 6.4. Results.............................................................................................................................

. . 6.4.1... Plant.physiological.parameters.and.metal.concentrations..................................

. . 6.4.2... Soil.physicochemical.and.microbial.parameters................................................

. 6.5. Discussion.......................................................................................................................

. . 6.5.1... Metal.phytoextraction.........................................................................................

. . 6.5.2... Impact.of.metal.pollution.on.soil.properties.......................................................

. . 6.5.3... Effect.of.T..caerulescens.growth.and.metal.phytoextraction.on.soil.properties.

. 6.6. Conclusions....................................................................................................................

7. SOILMICROBIALCOMMUNITYASBIOINDICATOROFTHERECOVERYOFSOIL FUNCTIONING DERIVED FROM METAL PHYTOEXTRACTION WITHSORGHUM...............................................................................................................................

. 7.1. Abstract..........................................................................................................................

. 7.2. Introduction...................................................................................................................

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Índice

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. . 7.3.1... Soil.characterization.and.experimental.design...................................................


. . 7.3.3... Soil.parameters...................................................................................................


. 7.4. Results.............................................................................................................................

. . 7.4.1... Metal.phytoextraction.by.sorghum.plants..........................................................

. . 7.4.2... Effect.of.metal.pollution.and.phytoextraction.on.soil.parameters......................

. 7.5. Discussion.......................................................................................................................

. . 7.5.1... Metal.phytoextraction.by.sorghum.plants..........................................................

. . 7.5.2... Effect.of.metal.pollution.and.phytoextraction.on.soil.parameters......................

. 7.6. Conclusions....................................................................................................................

8. EFFECTSOFCHELATESONPLANTSANDSOILMICROBIALCOMMUNITY:COMPARISONOFEDTAANDEDDSFORLEADPHYTOEXTRACTION..................

. 8.1. Abstract..........................................................................................................................

. 8.2. Introduction...................................................................................................................


. . 8.3.1... Greenhouse.experiment......................................................................................

. . 8.3.2... Plant.metal.accumulation....................................................................................

. . 8.3.3... Soil.solution.analysis..........................................................................................

. . 8.3.4... Soil.biological.indicators....................................................................................


. 8.4. Results.............................................................................................................................

. . 8.4.1... Chelate.effects.on.soil.Pb.mobilization..............................................................

. . 8.4.2... Pb.accumulation.in.cardoon.plants.....................................................................

. . 8.4.3... Plant.biomass......................................................................................................


. 8.5. Discussion.......................................................................................................................

. . 8.5.1... Chelate.effects.on.soil.Pb.mobilization..............................................................

. . 8.5.2... Pb.accumulation.in.cardoon.plants.....................................................................

. . 8.5.3... Plant.biomass......................................................................................................


. 8.6. Conclusions....................................................................................................................

9. EVALUATIONOFTHEEFFICIENCYOFAPHYTOSTABILIZATIONPROCESSWITHBIOLOGICALINDICATORSOFSOILHEALTH.................................................

. 9.1. Abstract..........................................................................................................................

. 9.2. Introduction...................................................................................................................


. . 9.3.1... Experimental.design...........................................................................................

. . 9.3.2... Soil.physicochemical.and.biological.characterization........................................


. 9.4. Results.............................................................................................................................

. . 9.4.1... CaCl2-extractable.metal.concentrations.in.soil...................................................


. . 9.4.3... Soil.physicochemical.and.biological.parameters................................................

. 9.5. Discussion.......................................................................................................................

. 9.6. Conclusions....................................................................................................................

10.LINKS BETWEEN PSEUDOMETALLOPHYTESAND RHIZOSPHERE MICRO-BIALCOMMUNITIESINAMETALLIFEROUSSOIL....................................................

. 10.1. Abstract..........................................................................................................................

. 10.2. Introduction...................................................................................................................

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evaluation of the efficiency of metal phytoremediation processes with microbiological indicators of soil health

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. . 10.3.1...Soil.characterization.and.experimental.design...................................................

. . 10.3.2...Plant.parameters.................................................................................................

. . 10.3.3...Soil.physicochemical.and.microbial.properties..................................................

. . 10.3.4...Soil.ecosystem.health.........................................................................................

. . 10.3.5...Statistical.analysis...............................................................................................

. 10.4. Results.............................................................................................................................

. . 10.4.1...Plant.parameters.and.soil.properties...................................................................

. . 10.4.2...Soil.ecosystem.health.........................................................................................

. . . 10.4.2.1. Sorghum productivity essay ............................................................... 10.4.2.2. Soil stability ....................................................................................... 10.4.2.3. Attributes of ecosystem health and overall ecosystem health............. 10.5. Discussion........................................................................................................................ . 10.5.1...Soil.and.plant.parameters.................................................................................... . 10.5.2...Soil.ecosystem.health.......................................................................................... 10.6. Conclusions....................................................................................................................

11. SÍNTESIS..................................................................................................................................

12.ONDORIOANAGUSIAKETATESIA................................................................................... 12.1. Ondorioak....................................................................................................................... 12.2. Tesia................................................................................................................................12.CONCLUSIONESPRINCIPALESYTESIS......................................................................... 12.1. Conclusiones.................................................................................................................... 12.2. Tesis.................................................................................................................................12.MAINCONCLUSIONSANDTHESIS................................................................................... 12.1. Conclusions..................................................................................................................... 12.2. Thesis..............................................................................................................................

BIBLIOGRAFIA/BIBLIOGRAFÍA/REFERENCES..................................................................

AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK...........................................

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1. General introduction / introducción General

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1. GENERAL INTRODUCTION/INTRODUCCIÓN GENERAL

NOTA INTRODUCTORIA: el capítulo “1. Introducción General” se divide en dos apartados: (1.1) una breve introducción (en inglés) a los indicadores microbianos de la salud del suelo y a la fitorremediación de suelos contaminados con metales (Epelde et al., publicada en el libro Advances in Applied Bioremediation; Springer, en prensa, doi: 10.1007/978-3-540-89621-0_16) en la que se incluyen asimismo, al objeto de ilustrar algunos conceptos, resultados de experimentos; (1.2) una segunda parte (en castellano) en la que se contextualiza el marco en el que se encuadra este trabajo dentro de la problemática particular de los suelos contaminados en la CAPV y la situación de la fitorremediación a nivel global.

1.1 Heavy metal phytoremediation: microbial indicators of soil health for the assessment of remediation efficiency

1.1.1 Microbial indicators of soil health

In the last few years, there has been a growing interest in the definition and

evaluation of soil health, in part stimulated by an increasing awareness that soil is a

critical component of the Earth´s biosphere, functioning not only in the production

of food and fiber but also in the maintenance of local, regional, and worldwide

environmental quality (Doran and Parkin, 1994; Alkorta et al., 2003a). Although its

definition is currently a topic of much debate and confusion, a commonly used

definition of soil quality/health that appears in many bibliographic references reads

as follows: “the continued capacity of a specific kind of soil to function as a vital

living system, within natural or managed ecosystem boundaries, to sustain plant and

animal productivity, to maintain and enhance the quality of air and water

environments, and to support human health and habitation” (Doran and Parkin,

1996; Doran and Safley, 1997). The terms “soil quality” and “soil health” are often

used interchangeably, but the former focuses more on the capacity of the soil to

meet defined human needs, such as the growth of a particular crop, while, by

contrast, the latter (i) relates more to the soil´s continued capacity to sustain plant

growth and maintain its functions (Coleman et al., 1998) and (ii) captures the

ecological attributes of the soil, mainly, those associated with its biota, such as

evaluation of the efficiency of metal phytoremediation processes with microbioloGical indicators of soil health

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biodiversity, food web structure, activity, range of function, etc. (Pankhurst et al.,

1997). Furthermore, the term “soil health” conveys the idea of soil as a living

system, a concept of the utmost importance since, after all, the soil contains vast

assemblages of organisms that are responsible for many of its vital functions, such

as decomposition and recycling of nutrients from dead plant and animal tissues,

nitrogen fixation, maintenance of soil structure, detoxification of pollutants, and so

on (Alkorta et al., 2003b).

Unfortunately, our soils are presently being degraded through salinization,

erosion, sealing, pollution, loss of organic matter and biodiversity, etc., leading to

the deterioration of the soil´s physical, chemical and biological properties

worldwide. Actually, the quantity and quality of the soil´s ecosystem services and

functions are nowadays being diminished at an alarming rate, making soil

degradation an environmental issue that demands immediate attention and response.

In this respect, history has repeatedly shown that mismanagement of the soil

resource base can lead to poverty, malnutrition and economic disaster (Bezdicek et

al., 1996). Within a community, a strong link can be found between soil

quality/health, food quantity and quality, and the health, well-being, and prosperity

of its citizens (Janke and Papendick, 1994). Indeed, the quality of life on Earth is

inextricably linked to the health of our soils.

In particular, the release of contaminants into our soils by human activities has

increased enormously over the past several decades, overwhelming the self-cleaning

capacity of the soil ecosystem and, as a consequence, resulting in the accumulation

of dangerous toxic substances. Accordingly, in our time, soil pollution attracts

considerable public attention since the magnitude of the problem calls for

immediate action (Garbisu and Alkorta, 2003).

In this context, it is urgently imperative to have reliable indicators for the

assessment and monitoring of soil health. To date, emphasis has mostly been placed

on physical and chemical soil properties as indicators of soil health, but biological

parameters are becoming increasingly used due to their being more sensitive to

changes in the soil as well as to their capacity to provide information that integrates

many environmental factors (Alkorta et al., 2003b; Hernández-Allica et al., 2006a;

Mijangos et al., 2006). Many biological parameters have been proposed as


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bioindicators of soil health, such as microbial biomass, basal and substrate-induced

respiration, mineralizable nitrogen, soil enzyme activities, abundance of soil

microflora and fauna, root pathogens, structural and functional biodiversity, food

web structure, plant growth and diversity, and so on (Pankhurst et al., 1997).

Microbial parameters, particularly those related to the size, activity and biodiversity

of the soil microbial communities, are most relevant as indicators of soil health.

After all, microbially mediated processes are central to the functions that soil

performs and, what´s more, microorganisms are responsible for 70-85% of the soil

biological activity (Reichle, 1977).

In any event, and because the pedosphere, hydrosphere, atmosphere and

biosphere are overlapping, intimately associated in the ecosystem, environmental

compartments, whatever occurs in the soil has a profound effect not only on soil

health but also on ecosystem health (Huang et al., 1998). The concept of ecosystem

health has been elaborated as a comprehensive, multiscale, dynamic, hierarchical

measure of system (i) vigor, which may be quantified in terms of productivity,

throughput of material and energy in the system, etc.; (ii) resilience, which may be

determined in terms of the system´s ability to maintain its structure and pattern of

behaviour in the presence of stress; and (ii) organization, which may be assessed in

terms of both the diversity of components and their degree of mutual dependence

(Mageau et al., 1995; Costanza et al., 1998; Rapport, 1998; Alkorta et al., 2004a).

Moreover, a healthy ecosystem must have the following attributes: (i) it should be

free of the “ecosystem distress syndrome”, that comprises a group of signs (e.g.,

leaching of soil nutrients, reduced species diversity, shifts in species composition to

opportunistic species, reduced productivity, increased pest and disease loads) by

which ecosystem breakdown is recognized; (ii) it should be self-sustaining; (iii) it

should not adversely affect or degrade surrounding systems (Costanza et al., 1992;

Hildén and Rapport, 1993; Rapport et al., 1997; Alkorta et al., 2004a). Although soil

health must not be equated with ecosystem health, the application of the ecosystem

health approach to studies of soil status and condition can indeed provide useful

information to, for instance, assess the impact of pollution on soil functioning and

to establish the efficiency of a certain remediation procedure.


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As abovementioned, vigor can be measured in terms of productivity,

throughput of material and energy in the system, etc. In the soil, these processes

might be investigated by methods that focus either on broad physiological

properties, such as soil respiration or nitrogen mineralization, or on specific enzyme

reactions carried out by soil microorganisms (Kandeler, 2007). Soil respiration is

related to ecosystem productivity, soil fertility, and regional and global carbon cycles

(Luo and Zhou, 2006). Soil enzyme activities, which control the rates of soil nutrient

cycling, provide a unique integrative biological assessment of soil function,

especially those catalyzing a wide range of soil biological processes, such as

dehydrogenase, urease, phosphatase, etc. (Nannipieri et al., 2002).

Resilience is included in the concept of stability, which comprises both resilience, the property of the system to recover after disturbance, and resistance, the inherent

capacity of the system to withstand disturbance. This concept can be applied to

those studies dealing with the impact of pollution on soil health. Interestingly, two

theories diverge with respect to the stability of ecological processes: (i) according to

the first theory, non-stressed systems are more stable, thanks to the large resources

they dispose to maintain function in case of stress (Loreau, 2000); (ii) the second

theory predicts that stressed systems are more stable because, due to first stress,

they have gained abilities to cope with stress and thus maintain function (Odum,

1981).

Finally, organization refers to ecosystem complexity and is affected by both the

diversity of species and the number of pathways of material exchange between each

component (Costanza et al., 1998). From an ecological perspective, in the soil

ecosystem, functional diversity, as opposed to structural diversity, provides more

relevant information (Torsvik and Øvreås, 2007). There are different methods to

determine the functional diversity of soil microbial communities such as, for

instance, community level physiological profiles (Preston-Mafham et al., 2002), soil

enzyme activities (Larson et al., 2002), and a variety of culture-independent

molecular techniques (Malik et al., 2008).

In this Chapter, the possibility of using microbial indicators of soil health to

assess the efficiency of metal phytoremediation processes is discussed.


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1.1.2 Heavy metal phytoremediation

Heavy metals are present in soil as natural components or as a result of human

activity, with the primary sources of metal pollution being the burning of fossil

fuels, mining and smelting of metalliferous ores, electroplating, downwash from

power lines, municipal wastes, fertilizers, pesticides and sewage (Garbisu and

Alkorta, 2001; Alkorta et al., 2004b). Actually, metal pollution has become one of

the most serious environmental problems today (Alkorta et al., 2004b). For instance,

arsenic, a nonessential metalloid, is an environmental pollutant of prime concern

which is causing a global epidemic of poisoning, with tens of thousands of people

having developed skin lesions, cancers and other symptoms (Pearce, 2003; Alkorta

et al., 2004c; Rozas et al., 2006).

Some metals are essential for life (e.g., they provide essential cofactors for

metalloproteins and enzymes) but, at high concentrations, metals are toxic for both

higher organisms and microorganisms (Garbisu and Alkorta, 1997). Indeed, at high

concentrations, metals can act in a deleterious manner by blocking essential

functional groups, displacing other metal ions, or modifying the active conformation

of biological molecules (Collins and Stotzky, 1989). Besides, due to their immutable

nature (metals are unique in that they do not undergo either chemically or

biologically induced degradation that could reduce their toxicity but rather

transform from one oxidation state or organic complex to another) (Alkorta et al.,

2006) and persistence in soil (with residence times in the order of thousands of

years) (McGrath, 1987), metals are a group of pollutants of much concern (Garbisu

and Alkorta, 1997; 2003). In soil, rather than total metal concentration, a major

factor governing metal toxicity is biovailability (Alkorta et al., 2006).


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Figure 1.1 is included as an example of the impact of metal pollution on soil

microbial communities (in particular, on the cultivable portion of the soil

heterotrophic microbial community). In this Figure 1.1, the average well colour

development (AWCD) curves, obtained from the carbon substrates utilization

patterns (i.e., community level physiological profiles - CLPP) of the Biolog

EcoPlatesTM, are presented. The data correspond to a soil artificially polluted with

250, 500, 100, 2000 and 4000 mg Zn kg-1 DW soil as ZnCl2, and show that 250 and

500 mg Zn kg-1 did not cause a negative impact on the soil functional microbial

diversity. On the contrary, 1000 mg Zn kg-1 and especially 2000 and 4000 mg Zn kg-

1 clearly affected the capacity of the cultivable portion of the soil heterotrophic

microbial community to utilize carbon substrates.

Figure 1.1: Effect of Zn pollution on average well colour development (AWCD) curves obtained with Biolog EcoPlatesTM. Soils were polluted with 250, 500, 100, 2000 and 4000 mg Zn kg-1 DW

soil as ZnCl2.

Traditional physicochemical methods for the remediation of metal polluted

soils are, in general, very expensive, which has stimulated the development of

innovative biological technologies to economically remediate these soils


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(Hernández-Allica et al., 2006a). Bioremediation, “a managed treatment process that

uses microorganisms to degrade and transform chemicals in contaminated soil,

aquifer material, sludges and residues” (Dasappa and Loehr, 1991), offers an

effective, non-destructive, economical clean-up technique for the remediation of

polluted sites, that must be considered an important tool in our attempts to mitigate

environmental contamination (Garbisu and Alkorta, 1997, 1999, 2003). But

although many studies have been carried out to investigate the possibility of using

microorganisms to aid in the remediation of metal polluted environments,

microorganisms do not solve the critical problem of the removal of metals from the

polluted soil. As a matter of fact, bacteria can only transform metals from one

oxidation state or organic complex to another, but not extract them from the

polluted soil (Garbisu et al., 2002).

Luckily, to overcome this limitation of bacterial metal soil remediation, the

possibility of using plants that can literally extract the metals from the polluted soil

was raised. In this respect, phytoremediation, “the use of green plants to remove

pollutants from the environment or to render them harmless” (Cunningham and

Berti, 1993; Raskin et al., 1994), is currently viewed as the ecologically responsible

alternative to the environmentally destructive physicochemical remediation methods

(Meagher, 2000). This phytotechnology has been reported as an effective, non-

intrusive, inexpensive, aesthetically pleasing, socially accepted remediation process

(Garbisu et al., 2002). The technical aspects of phytoremediation, together with the

advantages and limitations of this technology, have been extensively reviewed

elsewhere (Chaney et al., 1997; Raskin et al., 1997; Salt et al., 1998; Alkorta and

Garbisu, 2001; Garbisu and Alkorta, 2001; Garbisu et al., 2002; McGrath et al.,

2002; Alkorta et al. 2004b, 2004d; Pilon-Smits, 2005).

Within the field of phytoremediation, several categories have been defined:

phytoextraction, phytofiltration, phytostabilization, phytovolatilization,

phytodegradation, phytotransformation, etc. (Garbisu et al., 2002). Regarding soil

metal remediation, two of these categories are most relevant: phytoextraction and

phytostabilization.


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Figure 1.2: Strategies for metal phytoremediation.

Finally, it is most important to emphasize that, from an ecocentric point of

view, the ultimate goal of any soil remediation process must be not only to remove

the pollutant(s) from the soil but to restore soil health (Hernández-Allica et al.,

2006a; Epelde et al., 2008a).

1.1.2.1 Continuous metal phytoextraction

The term “phytoextraction” refers to the utilization of plants to remove

pollutants (mostly, metals) from soils. In particular, “continuous phytoextraction” is

based on the utilization of metal hyperaccumulating plants (hyperaccumulators) that

have the capacity to accumulate, translocate and tolerate high amounts of metals

over the complete growth cycle (Figure 1.3; Salt et al., 1995; Baker et al., 2000). In

this respect, Thlaspi caerulescens (i.e., alpine pennycress or alpine pennygrass), a

hyperaccumulating plant extensively studied due to its remarkable capacity to

phytoextract Zn and Cd from polluted soils (Hernández-Allica et al., 2006a, b;

Epelde et al., 2008a), has been suggested as model species for research on metal

phytoextraction (Assunção et al., 2003).

Phytoextraction Phytostabilization


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Figure 1.3: Continuous phytoextraction with Thlaspi caerulescens.

With a local ecotype of T. caerulescens, termed “Lanestosa”, from the Basque

Country (northern Spain), we carried out a microcosms study to (i) evaluate the

potential of such ecotype for Zn phytoextraction and (ii) assess the effect of the

phytoextraction process, which includes both plant growth and metal

phytoextraction, on microbial indicators of soil health. To this aim, T. caerulescens seedlings were transplanted to 2.5 kg pots that had been artificially polluted with

1000 mg Zn kg-1 DW soil and fertilized with 120 mg kg-1 DW soil of N, P and K.

After three months of growth, on average, T. caerulescens plants accumulated 5,654

mg Zn kg-1 DW shoot and extracted 28.9 mg of Zn pot-1. In addition, CLPPs were

obtained from Biolog EcoPlatesTM at the end of the experiment. Table 1.1 shows

the values of AWCD, richness (S) and Shannon´s diversity (H’) calculated from

Biolog EcoPlatesTM data at an incubation time of 52 h. As observed in this Table

1.1, in the absence of plants, Zn pollution led to lower values of all these

parameters, as compared to values of control non-polluted soils. Nevertheless, as a

result of T. caerulescens growth and metal phytoextraction, all these values were

recovered, indicating that the cultivable portion of the soil heterotrophic microbial

community had recovered its capacity to use carbon substrates (its functional

diversity). For all parameters of microbial functional diversity, the presence of plants

proved more important than the amount of metal phytoextracted from the soil

(actually, in this experiment, such amount was very low). As compared to bare soil,

vegetated soils are commonly described as having higher rates of microbial activity,

due to the presence of additional surfaces for microbial colonization and organic

compounds released by the plant roots (Tate, 1995; Grayston et al., 1997; Delorme

Met

al u

ptak

e

Harvest Growth Phase

Plant biomass


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et al., 2001). In similar phytoextraction experiments with T. caerulescens plants, higher

values of biological activity were found in rhizosphere versus non-rhizosphere soil

(Gremion et al., 2004; Keller and Hammer, 2004; Hernández-Allica et al., 2006a;

Wang et al., 2006; Epelde et al., 2008a). Finally, regarding the recovery of soil health

derived from a phytoextraction process, as reflected by the values of soil microbial

parameters, an ideal target should be to return to the conditions of a valid control

soil, i.e. a vegetated, unpolluted soil of similar physicochemical properties and

subjected to the same edaphoclimatic conditions.

Table 1.1: Values of average well colour development (AWCD) and diversity indexes calculated from Biolog EcoPlatesTM absorbance data at 52 h incubation time, in soils from a Zn

phytoextraction experiment with Thlaspi caerulescens Lanestosa plants. S = richness; H’ = Shannon´s diversity. Mean values (n = 3) ± standard errors. Values followed with different letters are

significantly different (P<0.05 or lower) according to Fisher´s PLSD-test.

AWCD S H’

Control, non-polluted 0.91 ± 0.01ab 24 ± 1a 3.0 ± 0.1a

Metal polluted, unplanted 0.78 ± 0.03a 18 ± 0b 2.8 ± 0.0a

Metal polluted, planted 1.01 ± 0.05b 24 ± 2a 3.1 ± 0.1a

From a remediation point of view, phytoextraction demands a sufficient

harvestable biomass. Unfortunately, most metal hyperaccumulators (e.g., T. caerulescens) are, in general, relatively small, have slow rates of biomass production

and lack any established cultivation, pest management or harvesting practices

(Wenzel et al., 1999). Consequently, nowadays, fast-growing, high biomass crop

plant species that accumulate moderate levels of metals in their shoots are actively

being tested for phytoextraction (Hernández-Allica et al., 2008). After all, in some

cases, a greater shoot biomass has been reported to more than compensate for a

lower shoot metal concentration (Ebbs and Kochian, 1997).

1.1.2.2 Chelate induced phytoextraction

The discovery that the application of chelating agents to the soil increases

plant metal uptake and translocation (Figure 1.4) opened a wide range of

possibilities for phytoextraction (Blaylock et al., 1997), most importantly, that of


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using high biomass plants for the remediation of metal polluted soils, particularly

with low bioavailable metals such as Pb (Hernández-Allica et al., 2007). However,

side-effects related to the addition of chelating agents to the soil, such as metal

leaching and toxic effects on soil microbial communities, have usually been

neglected (Römkens, 2002). In this respect, most studies on chelate-induced

phytoextraction have focused on EDTA (ethylenediaminetetracetic acid)-mediated

Pb phytoextraction (McGrath et al., 2002). Nevertheless, EDTA and the formed

EDTA-Pb complexes present low biodegradability and a high solubility, resulting in

an elevated risk of adverse environmental effects due to metal mobilization and long

persistence (Alkorta et al., 2004d). EDDS (ethylenediaminedisuccinate) has been

proposed as an alternative for chelate-induced metal phytoextraction (Grčman et al.,

2003; Santos et al., 2006). EDDS has been shown to be easily biodegradable

(Jaworska et al., 1999), to form strong complexes with transition metals and

radionuclides (Jones and Williams, 2001), to cause a much lower leaching of Pb

down the soil profile than EDTA (Grčman et al., 2003), and to be less toxic to soil

microorganisms (Grčman et al., 2003). In any case, environmentally safe methods of

chelate-induced phytoextraction must clearly be developed before steps towards

further development and commercialization of this remediation technology are

taken (Alkorta et al., 2004d).

Figure 1.4: Chelate-induced phytoextraction with Cynara cardunculus.

As an example, Figure 1.5 shows the response of several soil microbial

parameters to EDTA and EDDS addition (1 g kg-1 DW soil) in a microcosm

chelate-induced phytoextraction experiment, with Cynara cardunculus plants, carried

out in a soil artificially polluted with 1000 mg Pb kg-1 DW soil. EDTA was much

more effective (428.4 mg Pb kg-1 DW shoot) than EDDS (20.8 mg Pb kg-1 DW

Met

alup

take

Plantbiomass

Harvest Growth Phase


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shoot) for the induction of Pb shoot accumulation (6.3 mg Pb kg-1 DW shoot in

control pots). However, soil microbial parameters, especially dehydrogenase activity

(which, on average, was halved) and basal respiration, were more negatively affected

by EDTA than EDDS (Figure 1.5). Dehydrogenase activity, which occurs in every

viable microbial cell, and basal respiration are both used as indicators of overall

microbiological activity in the soil (Nannipieri et al., 2002).

Figure 1.5: Effect of chelating agents (EDTA, EDDS) on soil biological parameters in a chelate-induced Pb phytoextraction experiment with Cynara cardunculus plants. Controls: no chelating agents added. Values of control soils are used as reference points (values found at these control

soils = 100%). Resp: basal respiration (indicator of soil microbial activity); SIR: substrate-induced respiration (indicator of potentially active microbial biomass); Min N: potentially mineralizable N

(indicator of potential rate of N mineralization); DH: dehydrogenase (indicator of overall microbiological activity of soil); Glu: β-Glucosidase (an enzyme that plays a central role in the hydrolysis of polymers of plant residues, i.e. cellobiose); Aryl-S: arylsulfatase (an enzyme that

catalyses the hydrolysis of organic sulphate ester releasing sulphate); Acid-P: acid phosphatase (an enzyme that releases phosphate from organic phosphorus).

Then, apart from being effective for the induction of metal phytoextraction,

chelating agents for enhanced phytoextraction must be as innocuous as possible for

the soil biota. After all, the addition of chelating agents to the soil may increase, for

0

20

40

60

80

100

Resp

SIR

Min N

Acid-PDH

Glu

Aryl-S

Control

EDTA

EDDS


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instance, metal availability for soil microorganisms (Welp and Brümmer, 1997) and,

since soil microorganisms depend directly or indirectly on the soil solution for

uptake of food and water, elevated metal concentrations in the soil solution might

lead to toxic effects on the soil microbiota (Römkens et al., 2002).

1.1.2.3 Phytostabilization

The remediation of metal polluted soils, particularly those presenting high

levels of metal pollution, using phytoextraction procedures usually takes many years,

most probably, decades. In fact, to overcome this often considered Achilles heel of

phytoextraction, i.e. the long time needed for effective remediation, it has been

suggested that this phytotechnology should be combined with a profit making

operation such as forestry or bioenergy production (Robinson et al., 2003). In any

case, an alternative phytotechnology for the remediation of metal polluted soils is

phytostabilization or the use of plants to reduce the biovailability of pollutants in

the environment. More specifically, phytostabilization refers to the immobilization

of a contaminant in the rhizosphere through absorption and accumulation by roots,

adsorption onto roots, or precipitation within the root zone of plants, so that

contaminant migration via wind and water erosion, leaching and soil dispersion are

prevented (EPA, 2000). Thus, although metals are not removed from the soil, their

adverse environmental effects are reduced. The choice of metal phytoremediation

strategy (phytoextraction versus phytostabilization) will depend on a variety of

factors: type of metal(s) present in the soil, level of metal pollution, future use of the

site, etc. Interestingly, the combination of both strategies, so that the limitations of

one strategy might be overcomed by the advantages of the other strategy, appears a

most promising approach.

Chemophytostabilization, the combination of a chemical method (such as the

addition of organic or inorganic amendments to the soil) with phytostabilization

(Knox et al., 2000), is most promising for the remediation of metal polluted soils.

Amendments, such as different sources of organic matter, are added to the soil in an

attempt to reduce metal bioavailability by formation of insoluble metal organic

complexes with humic acids, thereby lessening the risk of metal toxicity to plants

and microbes (Stevenson et al., 1972; Kirkham, 1977). The combination of both


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approaches is very interesting as the chemicals bind the excess of metals, control pH

and provide plant nutrients, and the plants prevent wind erosion, reduce leaching,

and accumulate metals in their roots.

We have previously reported the phytostimulatory effect of plants on soil

microbial communities within the context of the phytoremediation of metal

polluted soils (Hernández-Allica et al., 2006a; Epelde et al., 2008a). However, for a

chemophytostabilization procedure, it is essential to also take into account the

effects of amendments on the soil microbial community. In this respect, we carried

out a microcosm study with a moderately polluted mine soil (1000 mg Zn kg-1 DW

soil, 340 mg Pb kg-1 DW soil, 2.6 mg Cd kg-1 DW soil) amended with cow slurry

[i.e., cow slurry, having 12% dry matter (DM), 3.25% DM nitrogen, 0.9% DM

phosphorus, and 3% DM potassium, was applied at a dose of 0.1 L kg-1 DW soil] or

a chemical fertilizer (i.e., urea plus PK14% fertilizer at similar nutrient doses than

those applied as cow slurry). Twenty weeks after amendment addition, bioavailable

(CaCl2 extractable) soil metal concentrations had decreased considerably: a 45, 62

and 38% reduction in biovailable Zn, Pb and Cd, respectively, was observed for the

chemically fertilized soils; a 34, 50 and 33 reduction in bioavailable Zn, Pb and Cd,

respectively, was found in those soils fertilized with cow slurry. At the same time,

values of dehydrogenase activity increased in both amended soils (i.e., control, no

amendment added, soil: 0.2 mg INTF kg-1 DW soil 20 h-1; soil with chemical

fertilizer: 12.0 mg INTF kg-1 DW soil 20 h-1; soil with cow slurry: 77.4 mg INTF kg-

1 DW soil 20 h-1), indicating the stimulatory effect of both amendments on soil

microbiological activity.


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Figure 1.6: Metabolic fingerprints of substrate utilization patterns obtained with the Biolog EcoPlatesTM at an incubation time of 44 hours, from control (no amendment), chemical fertilizer-amended (NPK = urea plus PK14%) and cow slurry-amended mine soil. For clarity purposes, only

those substrates showing significant differences (P<0.05) among treatments, according to ANOVA, are presented.

Since soil microbial biodiversity has a key role in the maintenance of soil

fertility, functioning and resilience, in the same chemophytostabilization study, we

also determined the microbial functional diversity, through CLPPs obtained with

the Biolog EcoPlatesTM, of control and amended soils. Figure 1.6 shows the

metabolic fingerprints of the CLPPs displayed by control and amended (cow slurry

or chemical fertilizer) soils. In this Figure 1.6, for clarity purposes, only those

substrates showing significant differences among treatments are presented. As

observed in this Figure 1.6, the addition of urea plus PK14% led to a different

pattern of carbon substrates utilization by the cultivable portion of the soil

heterotrophic microbial community. The addition of cow slurry resulted in higher

values of functional diversity in the polluted mine soil (Fig. 1.6). In this case, the

easily mineralizable organic matter might have favoured the soil microbial functional


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diversity. The addition of manure and compost to the soil has previously been

reported to significantly increase values of microbial functional diversity according

to BiologTM data (Gómez et al., 2006; Toyota and Kuninaga, 2006).

1.1.3 Conclusions

Despite the logical interest in improving the metal extraction capacity of metal

phytoremediating plants (phytoextraction) or reducing metal bioavailability, leaching

and dispersion using plants (phytostabilization), it should never be forgotten that

the ultimate goal of any soil remediation process must be not only to remove the

contaminant(s) from the polluted soil but, most importantly, to restore the

continued capacity of the soil to perform or function according to its potential (i.e.,

to recover soil health). In fact, in some cases, it might be possible to recover soil

health without decreasing soil metal concentrations to levels indicated in the

different regulations (most current regulations governing metal toxicity in soils are

still based on the total metal concentration in the soil, whose validity as a basis for

metal limits in soil is certainly questionable).

In this respect, although to date, emphasis has been placed on physical and

chemical soil properties as indicators of soil health, biological parameters are

becoming increasingly used due to their being more sensitive to changes in the soil

as well as to their capacity to provide information that integrates many

environmental factors. In particular, those biological indicators related to the size,

activity and diversity of the soil microbial communities are most promising since

microorganisms are, to a large extent, responsible for soil functioning. Microbial

indicators of soil health are valid tools to evaluate the success of phytoextraction

and phytostabilization processes.

Finally, it is important to point out that metal polluted and phytoremediated

soils are interesting scenarios to deepen into the still poorly understood plant-

microbe interactions that occur belowground and which fulfil vital roles in the

functioning of terrestrial ecosystems. After all, disturbed environments usually

provide a better insight into the workings of the system.


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1.2 Contextualización

1.2.1 Tradición minera en la CAPV

La contaminación del suelo de origen minero, en torno a la que se desarrolla

gran parte de este trabajo, adquiere una especial relevancia en la CAPV como se

deriva de la enorme importancia que históricamente ha tenido la actividad minera en

nuestra Comunidad. Ciertamente, a lo largo de la historia, se han explotado en la

CAPV yacimientos minerales en muy diversas zonas de nuestra geografía: los

Montes de Triano (municipios de Gallarta, Ortuella, Muskiz, Sopuerta y Galdames),

la zona de Ollargan (Bilbao), Legazpi, Oñati, Zerain, Irún, etc. En la Figura 1.7, se

puede observar la distribución de los emplazamientos mineros en la CAPV

recogidos en el Sistema de Cartografía Ambiental del Gobierno Vasco (Gesplan). La

mayoría de ellos son de hierro (Fe), aunque también son abundantes los de zinc

(Zn) y plomo (Pb), como pueden ser las minas de Arditurri (Oiartzun), Mina Troya

(Mutiloa) y Mina Legorreta (Legorreta) en Gipuzkoa, o la zona de Carranza y

Lanestosa en Bizkaia.

Figura 1.7: Explotaciones mineras en la CAPV. Fuente: Gesplan, Gobierno Vasco.

En estos yacimientos, a medida que se iban agotando los minerales de mayor

pureza, cuya extracción no requería grandes infraestructuras, se pasó a utilizar


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minerales con menor porcentaje metálico utilizando técnicas más innovadoras. El

proceso de extracción del mineral comenzaba con las perforaciones que realizaban

los barrenadores en la roca, para luego introducir los explosivos y así fragmentarla

mediante voladuras controladas. Posteriormente, se procedía al troceado de la roca

desprendida y se llenaban los cestos en los que se cargaba el mineral. Luego, para el

lavado del mineral, se utilizaban trómeles, grandes cilindros de chapa terminados en

un cono y colocados con una ligera inclinación. El mineral a lavar se introducía por

el extremo superior y el agua en dirección contraria, arrastrando así la arcilla.

Finalmente, el mineral debía transportarse desde el monte donde se encontraban los

criaderos hasta la costa, lugar donde generalmente se embarcaba rumbo a las

siderurgias inglesas. Para el transporte del mineral se utilizaban “planos inclinados”

(vagonetas unidas entre sí que se deslizaban sobre unos raíles en un plano de

pronunciado desnivel y que funcionaban por contrapeso) y líneas de baldes (tranvías

aéreos movidos por un motor). La construcción de una red de trenes mineros fue

posiblemente la mayor inversión que tuvieron que hacer las compañías mineras. Los

cargaderos, estructuras de madera sobre las que las vagonetas podían desplazarse y

descargar directamente a las bodegas del barco, suponían el punto final de la cadena

productiva.

Los cotos de Bizkaia siempre fueron los más productivos. En los Montes de

Triano la actividad minera se inició con los romanos. Hasta el siglo XIX, la

explotación de los minerales se realizaba artesanalmente por los vecinos de los

pueblos cercanos, sin ninguna ley que regulara esta extracción. A partir de mediados

del siglo XIX se empezaron a utilizar sistemas mecanizados que permitieron la

extracción industrial de mineral. Esto fue posible gracias a la privatización de los

yacimientos mineros y la implantación de nuevos sistemas de explotación de

carácter capitalista con financiación, maquinaria e ingeniería extranjera.

La extracción y elaboración de mineral en el siglo XX tuvo muchos altibajos.

Durante la primera guerra mundial (1914-1918), se orientó la siderurgia a la

producción de munición para los aliados. Acabada esta guerra, la demanda de

mineral de hierro se desplomó. En la Segunda Guerra Mundial (1939-1945) las

exportaciones de mineral se dirigieron hacia la Alemania de Hitler. De nuevo, pocos

años después de que acabara la Segunda Guerra Mundial, la exportación de hierro


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cesó, esta vez definitivamente, y las pocas minas que aún quedaban activas se

dedicaron a abastecer únicamente a la siderurgia local.

El sector siderometalúrgico vasco cubría una amplia gama de productos (aceros

especiales, tubos sin soldadura, aceros moldeados, tubos soldados, etc.). En 1979 se

censaron 10.979 empresas dedicadas a estas actividades, de las cuales casi la mitad se

localizaban en Bizkaia (destacando la margen izquierda de la Ría del Nervión, donde

esta industria cubría grandes extensiones) y un tercio en Gipuzkoa. En 1975 el sector

daba empleo a 243.294 personas, cifra que suponía el 46.7% de la población activa

vasca. A partir de entonces, un lento declive culminó a principios de los 90 con el

cierre de la última mina y de la empresa siderúrgica más emblemática de la zona:

Altos Hornos de Vizcaya.

Figura 1.8: (a) Extracción de mineral y (b) fundición de acero. Fuente:

http://www.museominero.net/.

Indiscutiblemente, la actividad minera de hierro, así como de metales no

férricos, ha constituido un componente trascendental del desarrollo industrial-

económico de la CAPV. Los beneficios económicos, sociales y culturales de esta

actividad han sido inmensos. Sin embargo, tras su caída, la atención se cierne

inevitablemente sobre las “heridas medioambientales abiertas” resultado de dicha

actividad.

Hoy en día, algunos emplazamientos mineros y zonas anteriormente ocupadas

por la industria siderúrgica han sido rehabilitadas. Por ejemplo, en la zona minera de

La Arboleda (Bizkaia), se ha emprendido una mejora sustancial del terreno,

acondicionándolo y plantando numerosas especies de arbustos y árboles autóctonos.

Este paisaje caótico de belleza singular, tiene ahora un uso recreativo. En lo referente

b) a)


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a emplazamientos industriales rehabilitados, sirvan de ejemplo los desarrollos

urbanísticos en el eje de la Ría del Nervión (e.g., las exitosas construcciones del

“Palacio Euskalduna” y el “Museo Guggenheim Bilbao” donde antes se alzaban los

“Astilleros del Nervión” y los “tinglados” de las navieras bilbaínas, respectivamente).

Sin embargo, la mayoría de los emplazamientos fueron abandonados después

de la acción devoradora de la minería, dejando tras de sí focos importantes de

contaminación. Además del evidente impacto visual que estos emplazamientos

producen en el paisaje, los residuos mineros aportan al entorno una cantidad

significativa de elementos contaminantes, bien presentes de forma natural en los

mismos emplazamientos o procedentes de los productos auxiliares empleados

durante la actividad minera. Este tipo de contaminación, aunque también se

presenta en forma difusa, está sobre todo localizada en vertederos no siempre

suficientemente controlados. En general, este tipo de enclaves mineros presentan

una fuerte pendiente, carecen de una cobertura vegetal estabilizada y son

especialmente proclives a la erosión y lixiviación, acrecentando así el riesgo de

dispersión de los metales a otros suelos y ecosistemas. Como ejemplo encontramos

los emplazamientos anexos a la zona recreativa de La Arboleda o las minas

abandonadas de Carranza.

Nota: Parte de la información incluida en este apartado ha sido extraída de Castilla y Asensio, 2007 y de la página web http://www.hiru.com/historia/ondarea, 2009.

1.2.2 Contaminación del suelo en la CAPV

En la CAPV, la escasez de suelo útil y la elevada densidad de población han

producido una ocupación masiva del suelo. Además, esta ocupación ha estado ligada

a un rápido desarrollo industrial basado en la transformación del metal, madera e

industria química, que se realizó sin ninguna planificación urbanística, en una época

en la que la preocupación por los problemas medioambientales simplemente no

existía. El vertido incontrolado de los residuos que estas actividades industriales han

generado y generan en nuestra Comunidad ha originado graves consecuencias

medioambientales. Entre ellas, cabe destacar la preocupante contaminación de los

suelos con un conjunto muy variado de compuestos tóxicos orgánicos (PAHs,

PCBs, etc.) e inorgánicos (metales).


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Según el Inventario de Emplazamientos con Actividades Potencialmente Contaminantes del Suelo elaborado por el Gobierno Vasco (2008), en la CAPV hay identificados un

total de 12.964 emplazamientos (7.898 hectáreas; 1.1% de la superficie total de la

CAPV; 16.5% de la superficie de suelo útil) susceptibles de estar alterados en su

calidad. Entre los diferentes tipos de emplazamientos inventariados se distinguen: (i)

los emplazamientos industriales activos (suponen un 75% de los emplazamientos

inventariados); (ii) vertederos (muy extensos en superficie); (iii) emplazamientos

industriales sin actividad en el momento presente (de los cuales el 79% corresponde

a antiguas zonas mineras); y (iv) emplazamientos modificados (parcelas en las que en

el pasado se han desarrollado actividades potencialmente contaminantes del suelo,

pero que en la actualidad albergan otros usos diferentes). Estos emplazamientos se

encuentran muy concentrados en núcleos urbanos y zonas adyacentes. De hecho, las

áreas funcionales del Bilbao Metropolitano, Donostia-San Sebastián y Álava Central

acaparan aproximadamente el 75% de la superficie potencialmente contaminada

inventariada de la CAPV.


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Figura 1.9: Distribución de los suelos potencialmente contaminados en la CAPV. Fuente: IHOBE.

A partir de muestreos llevados a cabo en estos emplazamientos

potencialmente contaminantes, se estimó que la superficie total realmente alterada

y/o contaminada de la CAPV se encuentra entre 1.279 y 3.120 hectáreas. Los

metales están entre los contaminantes más comunes en suelos y aguas subterráneas

de la CAPV (presentes en el 34% de casos en los que el suelo se encontraba alterado

y/o contaminado), aunque también es habitual la presencia de aceite mineral,

hidrocarburos aromáticos policíclicos y compuestos orgánicos aromáticos volátiles.

No se dispone de estudios que aporten datos cuantitativos objetivos en relación con

las presiones ejercidas por las fuentes de contaminación difusa.

1.2.3 Aspectos legales de la contaminación del suelo

La aparición a principios de los años 90 de los primeros casos de

contaminación de suelos en la CAPV puso en evidencia la necesidad de adoptar

medidas en el ámbito de la protección del medio ambiente. Así, la propuesta del Plan


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Director para la Protección del Suelo de 1994 fue de gran ayuda como directriz clave en la

implantación de la política de protección del suelo frente a la contaminación.

Hoy en día, la protección del suelo frente a la contaminación en la CAPV se

regula fundamentalmente a través de la Ley 1/2005, de 4 de febrero, de prevención y corrección de la contaminación del suelo, aunque los conceptos básicos relativos a esta

materia ya se habían incluido en la Ley 3/1998, de 27 de febrero, general de protección del medio ambiente del País Vasco. A nivel estatal, la regulación específica en materia de

protección de suelo frente a la contaminación se condensa en dos normas: la Ley 10/1998, de 21 de abril, de residuos y el Real Decreto 9/2005, de 14 de enero, por el que se aprueba la relación de actividades potencialmente contaminantes del suelo y los estándares y criterios para la declaración de suelos contaminados. Por último, la Comisión Europea ha publicado

recientemente una propuesta de directiva marco para la protección del suelo que va

acompañada de una estrategia temática y una evaluación de impacto.

La Ley 1/2005 concedió al suelo un marco de protección comparable a aquél

que ya gozaban otros medios como el aire o el agua y pretende remediar la herencia

de suelos contaminados, así como asegurar la protección de la salud humana y del

medio ambiente, evitando en el futuro que el escaso suelo de la CAPV sufra más

agresiones por contaminación. En dicha Ley 1/2005 se establecen límites para una

gran cantidad de compuestos contaminantes. Para poder afirmar si un suelo está o

no contaminado, se establecen unos estándares que se corresponden con los límites

superiores del intervalo de concentraciones en que una determinada sustancia se

encuentra de forma natural en los suelos de la CAPV (valores indicativos de

evaluación VIE-A). En dicha Ley 1/2005 también se establecen los estándares que

indican la concentración de una sustancia en el suelo por encima de la cual el suelo

está alterado y puede estar contaminado, pudiendo suponer un riesgo para la salud

humana (valores VIE-B). En este último caso se requerirá la realización de un

análisis de riesgos para confirmar si el suelo está contaminado. Los estándares VIE-

B se especifican dependiendo del uso al que se destina el suelo (industrial, parque

público, urbano, área de juego, otros). Por último, a las concentraciones por encima

de los valores VIE-C el suelo puede declararse contaminado sin necesidad de

realizar un análisis de riesgos.


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En cumplimiento de los mandatos de la Ley 1/2005 y las metas y objetivos

marcados en la Estrategia Vasca de Desarrollo Sostenible (2002-2020) y el Programa Marco Ambiental (2002-2006), se diseñó el Plan de Suelos Contaminados del País Vasco 2007-2012. El Plan de Suelos Contaminados tiene como meta la protección del suelo contra la

contaminación (la incorporación de sustancias químicas de origen antrópico) y

consta de cuatro objetivos estratégicos: prevenir (dotando a los agentes de

información y motivación para que lleven a cabo pautas más sostenibles), recuperar

(teniendo en cuenta el futuro uso de los suelos), reutilizar (dando nuevos usos a

suelos contaminados desocupados) y valorizar (asignando usos no contaminantes y

de alto valor añadido a los suelos). Además, desarrolla instrumentos tendentes a

reducir el sellado o artificialización del suelo. Para cumplir esos objetivos, el Plan de Suelos plantea tres programas: (i) EZAGUTU, para la obtención, actualización y

gestión de la información sobre la calidad de los suelos, para la generación de

conocimiento científico y técnico, y para la comunicación de este conocimiento a

través de programas de sensibilización, información y formación; (ii) ERAGIN, para

la búsqueda de mejoras en el diseño y la aplicación normativa junto a una mayor

integración de políticas; (iii) EKIN, que incorpora las acciones que contribuyen de

una manera más práctica y directa a la consecución de los cuatro objetivos

estratégicos.

Los avances en la política de suelos contaminados en la CAPV se resumen a

continuación: (i) la gestión de la información relativa a la calidad del suelo

(inventario de emplazamientos con actividades potencialmente contaminantes del

suelo; desarrollo de un sistema de información de la calidad del suelo); (ii) la

generación de conocimiento (elaboración de guías metodológicas y técnicas para la

investigación y recuperación de suelos contaminados; incorporación de líneas de

investigación prioritarias relacionadas con la protección del suelo contra la

contaminación); (iii) la información y formación de agentes implicados en la

protección del suelo; (iv) la elaboración, desarrollo y aplicación del marco legal; (v)

la integración del criterio “calidad del suelo” en otras políticas y coordinación con

otras administraciones; (vi) la prevención de la contaminación del suelo; (vii) la

construcción de infraestructuras (estudio de viabilidad y prediseño de un centro de

gestión de suelos contaminados); (viii) el diseño y puesta en marcha de instrumentos

económicos; y (ix) la reutilización y valorización de suelos alterados en su calidad.


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1.2.4 Recuperación de emplazamientos contaminados en la CAPV

Si bien la legislación desarrollada ha permitido poner los cimientos para la

prevención y corrección de la contaminación del suelo, pretender acabar con dicha

contaminación a corto plazo es un objetivo al cual han renunciado en la actualidad

todos aquellos países que se encuentran a la vanguardia de las políticas de

protección del suelo. En cualquier caso, en la mayor parte de los casos, la prioridad

de actuación se establece sobre los suelos que en el pasado han soportado

actividades susceptibles de contaminar el suelo. Se trata en general de solares e

instalaciones industriales (ruinas en numerosas ocasiones) en el momento del cese,

cuando son sometidas a un proceso de modificación del uso, o al ser objeto de

reutilización; por lo tanto, al requerirse una nueva licencia de actividad debe iniciarse

el citado procedimiento. En este sentido, las intervenciones urbanísticas han

resultado ser el motor de las investigaciones llevadas a cabo en los suelos. De hecho,

en aproximadamente el 50% de emplazamientos inventariados como

potencialmente contaminantes se prevén intervenciones urbanísticas en los

próximos años. Por otro lado, también hay terrenos potencialmente contaminados

fuera del circuito urbanístico, que se localizan en zonas rurales y naturales en las que

los efectos sobre los ecosistemas pueden ser relevantes. Aun así, abordar el

saneamiento de todas las parcelas en las cuales tras una investigación se demuestre la

existencia de un riesgo inaceptable requerirá de una estrategia bien planificada que permita una solución progresiva.

La Ley 1/2005 determina el procedimiento a llevar a cabo para conocer la

calidad del suelo: el proceso comienza con una fase exploratoria, donde se incluye

una investigación histórica sobre las actividades desarrolladas sobre el suelo y se

obtienen datos de las características relevantes del medio físico. Al mismo tiempo, se

realiza una campaña de muestreo y análisis que permita acotar la lista de sustancias

contaminantes presentes en la totalidad del suelo objeto de investigación y su

posible distribución espacial, indicando asimismo su concentración. Si del resultado

de la investigación exploratoria se dedujera la superación de los valores VIE-B para

el uso al que esté destinado el suelo, se dará comienzo a la fase detallada. La


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investigación detallada deberá permitir la correcta delimitación del tipo,

concentración y distribución de las sustancias contaminantes en el suelo y en el resto

de los medios que puedan haberse visto afectados por la contaminación, así como la

cuantificación de los riesgos para la salud de las personas y el medio ambiente

derivados de su presencia. Cuando un suelo fuese declarado contaminado, el órgano

ambiental de la Comunidad Autónoma ordenará la adopción de las medidas de

recuperación necesarias atendiendo a los resultados de las investigaciones y análisis

de riesgos que se hayan realizado.

Por otra parte, la construcción de Celdas de Seguridad para el confinamiento

de tierras contaminadas con residuos de la producción del pesticida Lindane resultó

ser un hito en la breve historia de la remediación de suelos contaminados en la

CAPV. El hexaclorociclohexano (HCH) es el residuo de la fabricación del pesticida

Lindane. Este residuo tóxico presenta serios riesgos para la salud humana y el medio

ambiente. Durante varias décadas, dos empresas ubicadas en la CAPV, Bilbao

Chemicals en Barakaldo y Nexana en Erandio, estuvieron fabricando dicho

pesticida, efectuando una serie de vertidos incontrolados del residuo en más de 37

puntos de la geografía vasca, principalmente en municipios de las márgenes

izquierda y derecha de la Ría del Nervión. La producción total de residuos se estimó

en 95.900 toneladas, de las cuales 18.900 se destinaron a procesos de

aprovechamiento, mientras que el resto fue vertido incontroladamente. Las

soluciones posibles no resultaban viables técnica o económicamente, por lo que se

determinó almacenar las tierras contaminadas en Celdas de Seguridad. Dichas celdas

se construyeron en Argalario (Barakaldo, siendo está la que mayor cantidad de

tierras confinó, 412.000 m3; Figura 1.10a) y en el aeropuerto de Loiu (con 110.000

m3 de tierras contaminadas). Otro elemento clave del proyecto fue la eliminación del

HCH en su estado puro. A tal efecto, se utilizó el proceso de decloración catalizada

por base, propiedad de la Agencia Americana de Medio ambiente. Este proceso

consiste en destruir el HCH a una temperatura de 150°C mediante una reacción

química que lo convierte en cloruro de sodio (sal), triclorobenzeno (TCB) y agua.

Así, durante los dos años de funcionamiento de la estación, se eliminaron 3.200

toneladas de Lindane. Finalmente, 1.074 toneladas de TCB fueron comercializados

como materia prima para la industria química, mientras que la sal sirvió para la

producción de agua salobre.


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En los últimos años, la cantidad de materiales/suelos excavados y gestionados

como residuos peligrosos y el número de emplazamientos contaminados

recuperados en la CAPV está aumentando de forma considerable. Un ejemplo típico

del tipo de actuaciones llevadas a cabo en la CAPV es la desarrollada en el término

municipal de Pasaia (Gipuzkoa) entre 2002 y 2008, en el sitio en el que se ubicaban

las empresas Funpasaia, S.A. (dedicada a la fundición de hierro, talleres mecánicos y

calderería), Laffort y Cía, S.A. (productos enológicos y aromas para la alimentación)

y Campsa (depósito y distribución de combustible), ocupando una superficie de

36.797 m2. Tras realizar las pertinentes investigaciones y análisis de riesgos, se

determinó que el suelo estaba contaminado con TPHs, PCBs, PAHs y metales,

suponiendo un riesgo inaceptable para la salud humana considerando el uso

residencial previsto. El proyecto de recuperación incluyó la excavación y gestión de

los residuos derivados: 16.755.880 kg de residuos no peligrosos, 125.000 kg de

residuos peligrosos y 376.900 kg de agua con hidrocarburos (ver Figura 1.10b).

Figura 1.10: (a) Celda de seguridad de Argalario y (b) gestión de depósitos enterrados durante el saneamiento de Pasaia. Fuente: (a) http://ec.europa.eu/, (b) TERRANOVA S.L.

En la actualidad, la práctica habitual en la CAPV en lo que a recuperación de

suelos contaminados se refiere consiste en su excavación y traslado a vertedero

controlado. No obstante, existen algunas experiencias (por desgracia, todavía un

número insuficiente) de tratamiento de suelos contaminados propiamente dicho en

la CAPV. A este respecto, uno de los tratamientos aplicados on site más comunes es

el “lavado de suelo”, aplicado recientemente, por ejemplo, por la empresa Hera AG

Ambiental en terrenos contaminados por hidrocarburos que previamente habían

estado ocupados por instalaciones de la empresa CHL en Muskiz (Bizkaia). El

a) b)

b)


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lavado de suelo consiste en separar y, a continuación, limpiar (con agua, detergentes,

etc.) exclusivamente aquellas fracciones del suelo que estén más contaminadas (las

fracciones de grano fino como el limo o la arcilla absorben más compuestos

químicos contaminantes que las fracciones de grano grueso como la arena o la

grava). El proceso se realiza en una “unidad de lavado” y permite reducir el volumen

de suelo que requiere una limpieza en profundidad. No obstante, técnicas físico-

químicas como ésta tienen un fuerte efecto adverso en la estructura y funcionalidad

del suelo. Por ello, el uso de tecnologías avanzadas para el tratamiento de suelo

contaminado (en especial in situ) y el desarrollo del concepto de “mejores

tecnologías disponibles” a un coste asumible, constituyen en la actualidad uno de los

retos de mayor importancia de la política de protección del suelo en la CAPV. Sin

duda, el futuro inmediato en este campo se dirige hacia la minimización de riesgos

mediante tecnologías de bajo coste, mucho más que hacia sistemas de

descontaminación en profundidad.

1.2.5 Situación de la fitorremediación a nivel global

Si bien hasta el momento no ha sido utilizada a escala comercial en la CAPV,

la fitorremediación, como técnica de remediación de suelos contaminados, es una

alternativa medioambientalmente respetuosa (utiliza energía solar), estéticamente

agradable, que genera pocos residuos y se puede aplicar in situ en extensiones

amplias. Una vez que las plantas han extraído del suelo las sustancias químicas

contaminantes, éstas pueden tener distintos destinos dentro de la planta:

almacenarse en las raíces, los tallos y las hojas; transformarse en sustancias menos

perjudiciales en el interior de la planta; o bien transformarse en gases que se liberan

al aire cuando la planta transpira. El término fitorremediación se utilizó por primera

vez en los años 80 para describir el uso de plantas para remediar suelos

contaminados o degradados, pero hubo que esperar hasta mediados de los 90 para

observar un rápido desarrollo metodológico en este campo. En la actualidad, la

investigación en fitorremediación implica a cientos de científicos y decenas de

instituciones de investigación y empresas privadas.


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La investigación en fitorremediación discurre por diferentes caminos en

Europa y Estados Unidos. De hecho, aunque los investigadores europeos se han

puesto al mismo nivel que los estadounidenses en lo referente a los fundamentos e

investigación básica en fitorremediación, Estados Unidos tiene una trayectoria

mucho más amplia en cuanto a su aplicación. Asimismo, es importante reseñar que

países emergentes con crecientes problemas de contaminación, como pueden ser

China o India, están prestando cada vez más atención a este tipo de fitotecnologías

(Tang, 2007; Prasad, 2007).

En concreto, hay muy pocas demostraciones prácticas de fitoextracción de

metales más allá de ensayos a pequeña escala y a corto plazo. Las dos

aproximaciones más utilizadas han sido el empleo de (i) especies hiperacumuladoras

como Thlaspi caerulescens (Zn, Cd), Alyssum spp. (Ni, Co; Figura 1.11) y Pteris vittata

(As), y (ii) plantas de alto crecimiento (árboles) como Salix y Populus spp.

Figura 1.11: Fitoextracción de suelos contaminados con Ni (Oregon, EEUU) mediante Alyssum

murale. Fuente: Chaney y cols., 1998.

Una alternativa más realista actualmente para la recuperación de suelos

contaminados con altos niveles de metales es la fitoestabilización, empleando

especies de plantas tolerantes que, a su vez, no transloquen grandes concentraciones

de metales a las partes aéreas (comestibles) al objeto de minimizar su incorporación

a la cadena trófica. Uno de los ejemplos más significativos en Europa es el caso del

proyecto de rehabilitación de la zona minera de La Combe du Saut, en el sur de

Francia (Figura 1.12). En esta mina se extrajo principalmente oro y arsénico. Al

clausurarse la mina en 2004, la cantidad de residuos dejados tras de sí en una

extensión de 120 hectáreas se estimó en 15 millones de toneladas. Las plumas más

contaminadas se trataron mediante métodos de excavación y confinamiento. Por


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otro lado, la contaminación residual y difusa remanente se trató con la

implementación de la tecnología de la fitoestabilización. Para ello, se seleccionaron

especies de plantas presentes en la zona (tratando de incluir plantas de distintos

grupos: gramíneas, leguminosas, etc.). Asimismo, se añadieron granallas de acero

como enmienda, pues presentan un gran potencial para la inmovilización de

arsénico.

Figura 1.12: Remediación de la Combe du Saut (Francia), (a) antes y (b) después. Fuente: www.difpolmine.org.

En Estados Unidos, la fitorremediación se ha aplicado al tratamiento de varios

emplazamientos Superfund, denominados así por incluirse en la lista de una ley

federal diseñada para remediar una serie de emplazamientos sin control o

abandonados con residuos peligrosos para las personas o los ecosistemas. El XII Informe Anual de Tecnologías de Tratamiento para la Remediación de Emplazamientos Contaminados (EPA, 2007) indica que, entre 1982 y 2005, se ha observado una

tendencia creciente hacia los tratamientos in situ. Además, los tratamientos de

incineración van disminuyendo (un 6% entre 2002 y 2005 frente a un 29% entre

1982 y 2002), mientras que los tratamientos denominados innovadores (entre los

que se encuentra la fitorremediación) van en aumento, llegando al 48% en 2005 (la

fitorremediación se utilizó en el 3% de los tratamientos innovadores entre 1982 y

2005).

b)

a)


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D. Glass Associates Inc. estimó (1999) el mercado estadounidense de la

fitorremediación en 3-7 millones de dólares, de los cuales 2-3 millones se atribuían a

la eliminación de contaminantes orgánicos de aguas subterráneas y 1-2 millones a la

eliminación de metales del suelo. Asimismo, auguraba perspectivas de rápido

crecimiento al mercado de las fitotecnologías tanto en Estados Unidos como en

Europa y Canadá. Desgraciadamente, que nosotros sepamos, en la última década, no

se ha realizado ningún análisis de mercado en profundidad sobre las perspectivas

futuras de la fitorremediación. Lo cierto es que, hasta el momento, se han realizado

pocos proyectos de fitorremediación de suelos contaminados a nivel comercial. De

hecho, aunque existen una serie de compañías (e.g., Phytotech Inc., Ecolotree Inc.,

Edenspace Inc.) que ofertan técnicas de fitorremediación como parte de su actividad

comercial (suelen especializarse en unos contaminantes y tecnologías específicos), la

realidad es que todavía hay muchos aspectos de esta incipiente tecnología que deben

ser estudiados/desarrollados.

La búsqueda de plantas tolerantes y acumuladoras/estabilizadoras de metales

sigue siendo, hoy en día, un aspecto fundamental en el desarrollo de la

fitorremediación de metales. Según Peer y cols. (2005), en este momento, la

fitoextracción parece factible para el arsénico y el níquel, mientras que para el resto

de metales la tecnología está lejos de ser aplicable a nivel comercial. De hecho, la

gran mayoría de las especies hiperacumuladoras descubiertas hasta ahora son

hiperacumuladoras de Ni (do Nascimento y Xing, 2006). Mientras tanto, las especies

de plantas capaces de acumular niveles altos de Zn, Pb, Cd, Co, Cu, etc. son mucho

menos numerosas (McGrath y cols., 2001a). Muchos grupos de investigación están

trabajando activamente para esclarecer los mecanismos genéticos y celulares de la

acumulación, transporte y tolerancia a metales de plantas diversas. Por desgracia, la

mayoría de especies hiperacumuladoras son de crecimiento lento y de pequeña

biomasa; por ello, la transferencia de sus genes de tolerancia y acumulación a plantas

de crecimiento rápido y gran biomasa parece a priori una estrategia prometedora

para mejorar la eficacia de los procesos fitoextractores (Chaney y cols. 2007). Sin

embargo, en este punto, es inevitable tener en consideración los conocidos

problemas, de índole diversa, asociados a la utilización de plantas transgénicas.


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En cuanto a la fitoextracción inducida por quelantes se refiere, se debe

investigar en la búsqueda y diseño de agentes quelantes medioambientalmente

respetuosos, de baja toxicidad, que sean a su vez fácilmente biodegradables (Hauser

y cols., 2007). Es innegable que la tasa de degradación de los agentes quelantes es un

aspecto crucial para el futuro de la fitoextracción inducida por quelantes, como se

deriva de los problemas actuales de lixiviación asociados a esta fitotecnología. Entre

otros factores, una prevención efectiva de esta lixiviación es de suma importancia

para la aceptación y posterior aplicación comercial de la fitoextracción inducida; no

obstante, hasta el momento, no se ha hallado ninguna solución satisfactoria a esta

cuestión (Alkorta et al., 2004d).

Para mejorar el rendimiento económico de los procesos fitoextractores de

metales es deseable que el metal a extraer tenga un buen precio en el mercado

(como es el caso del talio, oro, manganeso, cobalto, níquel) que incentive su

recuperación. Otra alternativa de futuro es la utilización de plantas

fitorremediadoras con capacidad para realísticamente generar productos que puedan

tener un valor económico como, por ejemplo, suplemento alimenticio,

acondicionador de suelo, aditivo energético, etc. (Bañuelos, 2006).

Indudablemente, la eficacia y utilidad de este tipo de fitotecnologías está

determinada por el contexto socioeconómico y ecológico en donde se enmarca la

problemática del suelo contaminado en cuestión. En cualquier caso, parece probable

que la fitorremediación continúe siendo en el futuro una tecnología (i) que requiere

periodos de tiempo relativamente largos; (ii) que esté limitada a la parte más

superficial del suelo (a la profundidad a la que penetren las raíces); y (iii) donde la

viabilidad de las plantas y, por ende, del éxito del proceso, dependa estrechamente

de las condiciones edafoclimáticas.

En cualquier, la fitorremediación resulta adecuada para una

sorprendentemente amplia variedad de contextos (e.g., para su aplicación en

extensiones rurales o urbanas amplias que no precisen de una remediación

inmediata, como algunos emplazamientos mineros; para emplazamientos en zonas

protegidas o de alto valor ecológico; para países en vías de desarrollo que necesiten

de una tecnología barata; como tecnología de prevención en zonas circundantes a

un foco de contaminación; etc.), por lo que es esperable y deseable que tenga un

desarrollo considerable durante el siglo XXI.

2. hipotesia eta helburuak / hipótesis y objetivos / hypothesis and objetives

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2. HIPOTESIA ETA HELBURUAK

2.1 Hipotesia

2.2 Helburu orokorra

Lan honen helburu orokorra metalekin kutsaturiko lurzoruetan prozesu

fitoerremediatzaileen efizientzia ebaluatzea izan zen, lurzoru ekosistemaren

osasunaren bioadierazle izateko potentziala duten lurzoruaren hainbat propietate

mikrobiologiko baliatuz.

2.3 Helburu espezifikoak

• Meatze-inguruneetako landare pseudometalofitoak: landare

pseudometalofitoek metalen aurrean duten erantzun fisiologikoaren

kuantifikazioa eta beraien potentzial fitoerremediatzailearen azterketa.

Landare pseudometalofitoen eta errizosferako mikrobio-komunitateen arteko

elkarrekintzen azterketa (4. Kapitulua).

• Fitoerauzketa jarraitua landare hipermetatzaileen bidez: metalek lurzoru

ekosistemaren osasunean duten eraginaren eta Thlaspi caerulescens espezie

hipermetatzailearen bidez egindako fitoerauzketa jarraituaren

eraginkortasunaren neurketa, horretarako lurzoru ekosistemaren osasunaren

Lurzoruko propietate mikrobiologikoek informazio erabakigarria ematen dutelurzoruaren egitura eta prozesuei buruz. Beraz, balio nabarmena dute lurzoruekosistemaren osasunaren bioadierazle gisa, kutsadurak lurzoruaren osasuneanduen eragina aztertzeko bereziki. Horregatik hain zuzen, uste dugu lurzorukopropietate mikrobiologikoak erabilgarritasun handiko eta garrantzi ekologikogoreneko tresnak izan daitezkeela metalekin kutsaturiko lurzoruen prozesufitoerremediatzaileen efizientzia ebaluatzeko.


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bioadierazle izateko potentziala duten lurzoruaren propietate mikrobiologikoak

baliatuz (5. eta 6. Kapituluak).

• Fitoerauzketa jarraitua biomasa altuko laboreen bidez: Basartoak (Sorghum bicolor x sudanense) Zn eta Cd-aren fitoerauzketa jarraiturako duen

potentzialaren azterketa. Lurzoruaren propietate mikrobiologikoen erabilera

(i) metalek lurzoru ekosistemaren osasunean duten eragina eta (ii) prozesu

fitoerauzlearen eraginkortasuna ebaluatzeko (7. Kapitulua).

• Kelatzaileek eragindako fitoerauzketa biomasa altuko laboreen bidez: EDTA

versus EDDSren ahalmenaren ebaluazioa Pb-arekin artifizialki kutsaturiko

lurzoru batean metala solubilizatu eta kardu landareetan (Cynara cardunculus) honen metaketa eragiteko. Bi kelatzaile hauek karduan eta lurzoruko

mikroorganismoengan eragiten duten toxikotasunaren azterketa (8.

Kapitulua).

• Kimiofitoegonkortzea labore belarkaren bidez: lurzoruko propietate

mikrobiologikoen erabilera prozesu kimiofitoegonkortzaile baten

eraginkortasunaren bioadierazle gisa, Lolium perenne eta medeapen sintetiko

versus organiko batekin, Zn, Pb eta Cd-arekin kutsatutako lurzoru bat

erremediatzeko (9. Kapitulua).

• Meatze-lurren fitoerremediazioa metalak jasateko estrategia desberdinak dituzten

landare pseudometalofitoen konbinazioen erabileraren bidez: meatze-lurren

fitoerremediaziorako (fitoerauzketa eta fitoegonkortzea) metalak jasateko estrategia

desberdinak dituzten landare pseudometalofitoen (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) konbinazioak erabiltzeko aukeraren ebaluazioa, lurzoru

ekosistemaren osasunaren bioadierazle izateko potentziala duten lurzoruaren

propietate mikrobiologikoak erabiliz (10. Kapitulua).

• Lurzoruaren osasuna eta ekosistemaren osasuna kontzeptuak uztartzea

ahalbidetuko duen metodologia baten diseinua (10. Kapitulua).


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2. HIPÓTESIS Y OBJETIVOS

2.1 Hipótesis

2.2 Objetivo general

El objetivo general de este trabajo fue evaluar la eficacia de distintas estrategias

de fitorremediación de suelos contaminados con metales mediante la determinación

de un conjunto de propiedades microbiológicas del suelo con potencial bioindicador

de la salud del ecosistema edáfico.

2.3 Objetivos específicos

• Plantas pseudometalofitas en entornos mineros: cuantificación de la

respuesta fisiológica de plantas pseudometalofitas a la presencia de metales y

análisis de su potencial fitorremediador. Estudio de las interacciones entre

plantas pseudometalofitas y sus correspondientes comunidades microbianas

rizosféricas (Capítulo 4).

• Fitoextracción en continuo con plantas hiperacumuladoras: evaluación del

impacto de metales sobre la salud del ecosistema edáfico y de la eficacia de

un proceso de fitoextracción en continuo con la especie hiperacumuladora

Thlaspi caerulescens, mediante el empleo de propiedades microbiológicas del

Las propiedades microbiológicas del suelo aportan información crucial sobre la estructura y los procesos del suelo, por lo que tienen un notable valor como bioindicadores de la salud del ecosistema edáfico y, en particular, del impacto de la contaminación sobre dicha salud. Es por ello que consideramos que las propiedades microbiológicas del suelo pueden ser herramientas metodológicas de gran utilidad y máxima relevancia ecológica a la hora de evaluar la eficacia de procesos fitorremediadores de suelos contaminados con metales.


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suelo con potencial bioindicador de la salud del ecosistema edáfico

(Capítulos 5 y 6).

• Fitoextracción en continuo con cultivares de alta biomasa: estudio del

potencial del sorgo (Sorghum bicolor x sudanense) para la fitoextracción en

continuo de Zn y Cd. Evaluación mediante el empleo de propiedades

microbiológicas del suelo del (i) efecto de los metales sobre la salud del

ecosistema edáfico y (ii) la eficacia del proceso fitoextractor (Capítulo 7).

• Fitoextracción inducida por quelantes con cultivares de alta biomasa:

evaluación de la capacidad del EDTA versus EDDS para solubilizar Pb de un

suelo artificialmente contaminado con este metal e inducir su acumulación en

plantas de cardo (Cynara cardunculus). Estudio de la toxicidad de estos dos

quelantes sobre el cardo y los microorganismos del suelo (Capítulo 8).

• Quimiofitoestabilización con cultivares herbáceos: utilización de propiedades

microbiológicas del suelo como herramienta monitorizadora de la eficacia de

un proceso quimiofitoestabilizador, con Lolium perenne y enmienda sintética

versus orgánica, para remediar un suelo minero contaminado con Zn, Pb y Cd

(Capítulo 9).

• Fitorremediación de suelos mineros mediante el empleo de combinaciones

de plantas pseudometalofitas con distintas estrategias de tolerancia a metales:

evaluación de la posibilidad de utilizar combinaciones de plantas

pseudometalofitas con distintas estrategias de tolerancia a metales (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) para la fitorremediación

(fitoextracción y/o fitoestabilización) de suelos mineros, mediante el empleo

de propiedades microbiológicas del suelo con potencial bioindicador de la

salud del ecosistema edáfico (Capítulo 10).

• Diseño de una metodología que permita vincular los conceptos de salud del

suelo y salud del ecosistema (Capítulo 10).


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2. HYPOTHESIS AND OBJECTIVES

2.1 Hypothesis

2.2 Main objective

The main objective of the current work was to assess the efficiency of different

phytoremediation strategies of metal polluted soils through the determination of a

variety of soil microbiological properties with potencial as bioindicators of soil

health.

2.3 Specific objectives

• Pseudometallophytes in mining sites: evaluation of the physiological

response of pseudometallophytes in the presence of metals and analysis of

their phytoremediation potential. Study of the interactions between

pseudometallophytes and their corresponding rhizosphere microbial

communities (Chapter 4).

• Continuous phytoextraction with hyperaccumulators: assessment of the

impact of metals on soil health as well as of the efficiency of a continuous

phytoextraction process with the hyperaccumulator Thlaspi caerulescens through the determination of a variety of soil microbiological properties with

potential as bioindicators of soil health (Chapters 5 and 6).

• Continuous phytoextraction with high biomass cultivars: study of the

potential of sorghum (Sorghum bicolor x sudanense) for continuous

phytoextraction of Zn and Cd. Assessment, through the determination of

Soil microbiological properties provide invaluable information on soil structureand processes, and consequently are most useful as bioindicators of soil health and,in particular, of the impact of pollutants on such health. Therefore, we consider thatsoil microbiological properties can be valid, ecologically-relevant methodological toolsto assess the efficiency of phytoremediation processes of soils polluted with metals.


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soil microbiological properties, of (i) the effect of metals on soil health and

(ii) the efficiency of the phytoextraction process (Chapter 7).

• Chelate-induced phytoextraction with high biomass cultivars: assessment of

the capacity of EDTA versus EDDS to solubilize Pb from an artificially

polluted soil and to induce Pb accumulation in cardoon (Cynara cardunculus) plants. Study of the toxicity of both chelating agents on cardoon plants and

soil microorganisms (Chapter 8).

• Chemophytostabilization with herbaceous cultivars: utilization of soil

microbiological properties as monitoring tools of the efficiency of a

chemophytostabilization process, with Lolium perenne and synthetic versus organic amendment, to remediate a mine soil polluted with Zn, Pb and Cd

(Chapter 9).

• Phytoremediation of mine soils using combinations of pseudometallophytes

with different strategies of metal tolerance: assessment of the possibility of

using combinations of pseudometallophytes with different strategies of metal

tolerance (Thlaspi caerulescens, Rumex acetosa, Festuca rubra) for the

phytoremediation (phytoextraction and/or phytostabilization) of mine soils,

through the determination of soil microbiological properties with potential as

bioindicators of soil health (Chapter 10).

• Design of a methodology to link the concepts of soil health and ecosystem

health (Chapter 10).

3. escenario y procedimientos Generales

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3. ESCENARIO Y PROCEDIMIENTOS GENERALES

NOTA INTRODUCTORIA: en el presente capítulo se describe el emplazamiento minero en el cual hemos realizado estudios en campo y muestreado suelo crónicamente contaminado con metales para posteriores experimentos en invernadero. Asimismo, se detallan las condiciones de cultivo de los diversos ensayos llevados a cabo en invernadero en este trabajo. Parte de estos experimentos han sido realizados con muestras de suelo de praderas localizadas en Derio y Larrauri (Bizkaia) que posteriormente han sido contaminadas de forma artificial. Por otro lado, en este capítulo, se incluye una breve descripción de las propiedades microbiológicas del suelo con potencial bioindicador de la salud del ecosistema edáfico empleadas en este trabajo. Los materiales y métodos particulares de cada experimento se describen con mayor detalle en los capítulos correspondientes. Finalmente, las referencias bibliográficas de los métodos aquí descritos se mencionan en los artículos correspondientes.

3.1 Escenario de estudio y condiciones de cultivo

3.1.1 Escenario

El emplazamiento minero en torno al cual se ha desarrollado parte de este

trabajo (Capítulos 4, 9 y 10) pertenece a una antigua explotación de Pb, conocida

localmente como “mina Txomin” (Figura 3.1), que está localizada en el municipio

vizcaíno de Lanestosa (latitud 43°13´; longitud 3°26´). Al parecer, esta mina,

actualmente abandonada, estuvo operativa desde las primeras décadas del siglo XX

hasta finales de los años 70; no obstante, se carece de documentos que den

constancia del periodo exacto de actividad minera así como de su magnitud e

intensidad. Dentro de la mina, la zona de estudio está situada en una zona

montañosa, con pendientes de entre 30 y 50%, a unos 440 metros sobre el nivel del

mar, en las laderas de orientación oeste que drenan sobre el río Kalera. En el área de

explotación, se encuentran diseminados distintos emplazamientos de extracción y

procesado del mineral como cortas de extracción a cielo abierto, galerías

subterráneas de extracción, balsas de lavado de mineral y decantación de lodo,

escombreras de deposición de escoria y lodo, etc. La dispersión de estos

emplazamientos potencialmente contaminantes, junto con la orografía de la zona

expuesta a vientos frecuentemente moderados, ha dado como resultado varias


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hectáreas de suelo con distinto grado de contaminación por metales (especialmente

Zn, Pb y Cd).

Figura 3.1: Emplazamiento minero de Lanestosa. Fuente: NEIKER-Tecnalia.

Esta gran superficie de suelo contaminado, unida al hecho de que el uso del

suelo en esa zona es casi exclusivamente de tipo rural, ofrece una excelente

oportunidad para la aplicación de la fitorremediación como tecnología de bajo coste

y medioambientalmente respetuosa para recuperar emplazamientos contaminados

con metales. Asimismo, es importante enfatizar que la mina actúa como preciado

banco de germoplasma de especies de plantas de gran potencial para su utilización

en fitotecnologías diversas y para investigaciones sobre los mecanismos de

adaptación y tolerancia a metales en plantas. En efecto, dentro de la mina, las zonas

con mayor concentración de metales en suelo se encuentran colonizadas por un tipo

de vegetación (dominada por la especie Festuca rubra) que presenta un alto grado de

tolerancia a metales. Estas especies altamente tolerantes, en combinación con

diferentes prácticas agrícolas, pueden ser por ejemplo empleadas para la

revegetación de suelos desnudos en los que la alta concentración de metal, unida a la

escasez de nutrientes, haya impedido el establecimiento de una cubierta vegetal

estable. Por otro lado, en las zonas de la mina contaminadas con niveles moderados

de metales, la comunidad vegetal es mucho más diversa, siendo las especies más

abundantes en términos de individuos Festuca rubra, Agrostis capilaris, Thlaspi caerulescens, Jasione montana, Ulex europaeus, Rumex acetosa, Pteridium aquilinum y Plantago lanceolata (Barrutia, 2008). Algunas de las especies que se encuentran en estos

emplazamientos mineros, amén de un alto grado de tolerancia a metales, presentan


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la rara habilidad de concentrar concentraciones elevadas de metal en sus partes

aéreas, lo que les convierte en potenciales candidatas para su empleo en procesos

fitoextractores (e.g., Thlaspi caerulescens, Rumex acetosa; Figura 3.2).

Figura 3.2: Rumex acetosa – acumuladora (panel izquierdo), (b) Thlaspi caerulescens – hiperacumuladora (panel derecho). Fuente: NEIKER-Tecnalia.

Por otro lado, como se ha mencionado anteriormente, parte de los

experimentos de fitorremediación en este trabajo (Capítulos 5-8) han sido realizados

con suelo artificialmente contaminado con metales. En estos casos, el suelo se

muestreó (capa superficial: 0-30 cm) en una pradera natural localizada en el

municipio vizcaíno de Derio (latitud 43°17´; longitud 2°52´; 65 m por encima del

nivel del mar). Excepcionalmente, el suelo utilizado en el ensayo descrito en el

Capítulo 8 fue muestrado en una pradera de similares características localizada en

Larrauri (Bizkaia; latitud 43°22´; longitud 2°48´; 85 m por encima del nivel del mar).

La Figura 3.3 muestra de forma esquemática el procedimiento empleado para

muestrear suelo (las imágenes corresponden a la pradera de Derio): (a) se seleccionó

una zona de la pradera, homogénea visualmente y de acuerdo a caracterización

físico-química previa; (b) posteriormente, se excavó la tierra a una profundidad de

30 cm; (c) se tamizó por un tamiz de 4 cm de diámetro; y finalmente (d) se

contaminó artificialmente con metales, utilizando una hormigonera para facilitar su

homogeneización. Después de un periodo de estabilización en oscuridad y a

temperatura y humedad constantes, variable en su duración según el ensayo, el suelo


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se trasladó al invernadero, distribuyó en tiestos y, finalmente, se establecieron los

tratamientos correspondientes en cada experimento.

Figura 3.1: Emplazamiento minero de Lanestosa

Figura 3.3: Muestreo de suelo para su utilización en ensayos a escala microcosmos: (a) detalle de la

pradera de Derio, (b) cava, (c) tamizado y (d) contaminación artificial con hormigonera. Fuente: NEIKER-Tecnalia.

3.1.2 Condiciones de cultivo

Las semillas de las especies de gramíneas utilizadas en los distintos estudios

(i.e., Sorghum bicolor, Lolium perenne, Festuca rubra) se sembraron directamente en los

tiestos de ensayo. Sin embargo, las semillas del resto de especies estudiadas (i.e., Thlaspi caerulescens, Rumex acetosa, Cynara cardunculus) fueron germinadas en una

cámara de germinación en bandejas (en mezcla de perlita:vermiculita 2:3 v/v o en

compost John Innes Nº 2 autoclavado) previamente a su transplante a los tiestos de

ensayo. Las condiciones de la cámara de germinación fueron las siguientes:

temperatura de 20/16 ºC día/noche, humedad relativa de 70%, y una intensidad de

b)

c) d)

a)


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PAR (radiación fotosintéticamente activa) de 300 μmol fotón m-2 s-1 obtenida con

lámparas frías blancas.

Figura 3.4: Invernaderos de NEIKER-Tecnalia, Derio. Fuente: NEIKER-Tecnalia.

Los ensayos a escala microcosmos se realizaron en los invernaderos de

NEIKER-Tecnalia en Derio, Bizkaia (Figura 3.4). Estos invernaderos disponen de

un sistema automático de ventilación y calefacción, así como de un sistema

electrónico de monitorización de ambos parámetros localizado en el interior de la

nave. La temperatura mínima establecida fue de 14ºC/18ºC noche/día, y la máxima

de 16ºC/20ºC noche/día. La temperatura para la apertura de las compuertas fue de

20ºC/25ºC noche/día. Excepcionalmente, el ensayo presentado en el Capítulo 5 de

este trabajo se realizó en el invernadero de la Facultad de Ciencia y Tecnología de la

Universidad del País Vasco (EHU/UPV), acondicionado a una temperatura entre

18-25 ºC durante el día y 17-24 ºC por la noche, con un fotoperiodo de 14 horas de

luz. La iluminación natural fue suplementada con lámparas frías blancas para

alcanzar una intensidad de PAR mínima de 400 μmol fotón m-2 s-1.

3.2 Parámetros analíticos

3.2.1 Propiedades físico-químicas y microbiológicas con potencial indicador de la salud del ecosistema edáfico

Una vez finalizada la fase de crecimiento en los ensayos, el material vegetal se

cosechó, lavó y secó, previamente a la determinación de su peso seco. Por otro lado,

el suelo muestreado en los ensayos se separó en dos partes: (i) una porción destinada


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a los análisis de parámetros físico-químicos, la cual se secó al aire y tamizó por un

tamiz de 2 mm de diámetro; (ii) una segunda parte destinada a los análisis de

parámetros microbiológicos, que fue tamizada en fresco por un tamiz de 2 mm de

diámetro. Las muestras destinadas a la determinación de parámetros

microbiológicos se almacenaron a 4ºC hasta su posterior análisis.

En relación con los indicadores de la salud del suelo, tradicionalmente, la

calidad/salud* del suelo se ha venido determinando en base a la cuantificación de

parámetros físico-químicos con potencial indicador. Sin embargo, los suelos son

sistemas vivos que contienen, por ejemplo, una enorme cantidad de microorganismos

responsables en último término del 80-90% de la actividad biológica y los procesos

edáficos. Estos procesos biológicos no sólo están íntimamente unidos al

mantenimiento de la estructura y fertilidad del suelo sino que, además, son

potencialmente más sensibles y responden con mayor rapidez frente a los

cambios/perturbaciones introducidos en el ecosistema suelo. Asimismo, una de las

más importantes ventajas de los procesos y parámetros (micro)biológicos para su

utilización como bioindicadores** es su carácter integrador, que agrupa la totalidad de

los parámetros físicos, químicos y biológicos que definen un ecosistema. Los

principales indicadores biológicos de la salud del suelo son (Alkorta y cols., 2003b):

biomasa microbiana; respiración del suelo; nitrógeno potencialmente mineralizable;

actividades enzimáticas; abundancia de microflora; abundancia de fauna del suelo

(macro-, meso-, microfauna); enfermedades de raíces (patógenos de plantas);

biodiversidad del suelo (estructural y funcional); estructura de la red trófica;

biodiversidad de plantas y composición florística; y crecimiento de plantas.

*Calidad/salud: “calidad del suelo” se define como el grado de aptitud de un determinado suelo para desempeñar una función específica (e.g., producir una cosecha); por el contrario, el término “salud del suelo” engloba las características o atributos ecológicos de un suelo que tienen implicaciones más allá de su calidad o capacidad para desempeñar una función específica y que son responsables de su funcionamiento, sostenibilidad e integridad ecológica. El término “calidad” es más utilizado desde una perspectiva antropocéntrica, mientras que el término “salud” se contempla habitualmente desde una perspectiva biocéntrica-ecocéntrica.


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**Un bioindicador (o, más correctamente, indicador biológico) se define como “un organismo, parte de un organismo, producto de un organismo, grupo de organismos o procesos biológicos que pueden ser utilizados para obtener información sobre todo o parte del medio ambiente”.

3.2.1.1Propiedades microbiológicas con potencial indicador de la salud del ecosistema edáfico

Actividades enzimáticas

Los enzimas del suelo son los mediadores y catalizadores de la mayoría de los

procesos del suelo y, por lo tanto, presentan un gran potencial para suministrar una

evaluación integradora de la salud del ecosistema edáfico. La mayor parte de los

enzimas encontrados en los suelos son hidrolasas, pero también se han encontrado

oxidorreductasas, transferasas y liasas. Aunque es bien cierto que algunos enzimas

existen únicamente como parte de células viables, suministrando así información

sobre la actividad del componente biológico presente en ese momento en el suelo

(e.g., deshidrogenasa), la mayoría de los enzimas se encuentran tanto en células

viables como en forma extracelular (componente abiótico) en la solución del suelo o

complejadas a la matriz edáfica. Gracias a esta última característica es posible

incorporar un componente “histórico” a los ensayos enzimáticos, de forma que se

reflejen los cambios acumulados en el tiempo sobre la salud del ecosistema edáfico.

La mayoría de los métodos de determinación de actividad enzimática se basan

en la determinación colorimétrica del producto liberado por la actividad cuando el

suelo tamponado es incubado a una temperatura óptima, en condiciones de

substrato saturantes (Figura 3.5a). Existe un amplio grupo de enzimas que pueden

ser utilizados como bioindicadores de la salud del ecosistema edáfico: hidrolasas

(fosfatasas, sulfatasas, ureasa, proteasas, peptidasas, deaminasas, celulasas),

oxidorreductasas (deshidrogenasas, fenol oxidasas, peroxidasas, catalasas), liasas y

transferasas (Burns y Dick, 2002).

En este trabajo se han determinado las siguientes actividades enzimáticas:

• Actividad deshidrogenasa (Capítulos 4, 7, 8, 9 y 10; método descrito en detalle en

los Capítulos 4 y 9), la cual forma parte integral de las células intactas y refleja

la totalidad de las actividades oxidativas de la microflora edáfica, de

importancia crucial para la oxidación de la materia orgánica del suelo. En otras


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palabras, representa la actividad metabólica oxidativa in situ de los organismos

del suelo.

• Actividad fostatasa ácida (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en

los Capítulos 5 y 9) y alcalina (método descrito en detalle en el Capítulo 5),

implicadas en la liberación de fosfato disponible para las plantas a partir de la

materia orgánica del suelo.

• Actividad β-glucosidasa (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en

los Capítulos 5 y 9), implicada en la liberación de glucosa. Este enzima

hidroliza polímeros de los residuos vegetales (i.e., celobiosa y maltosa)

aportando los esqueletos de carbono y energía esenciales para el crecimiento

de los organismos heterótrofos del suelo. Asimismo, este enzima inicia los

procesos que conducen a la mineralización y/o estabilización del carbono

residual vegetal.

• Actividad ureasa (Capítulos 4, 5 y 10; método descrito en detalle en el Capítulo

5), enzima importante en el ciclo del nitrógeno que cataliza la hidrólisis de urea

en CO2 y NH3.

• Actividad arilsulfatasa (Capítulos 4, 5, 8, 9 y 10; método descrito en detalle en los

Capítulos 5 y 9), responsable de la mineralización de ésteres orgánicos de

azufre para producir sulfato inorgánico. Los ésteres de sulfato microbianos son

propios de hongos y no de bacterias, por lo que una elevada actividad

arilsulfatasa puede relacionarse con la presencia de hongos.

Nitrógeno potencialmente mineralizable

El proceso de mineralización de nitrógeno se puede definir como la

conversión de nitrógeno orgánico a formas minerales disponibles para las plantas. El

primer paso de esta transformación consiste en pasar del nitrógeno orgánico a

amonio, y es realizado exclusivamente por microorganismos heterótrofos, siendo

posible tanto en condiciones aeróbicas como en anaeróbicas. El nitrógeno

potencialmente mineralizable es un parámetro con gran valor indicador de la

fertilidad del suelo. El método utilizado en los Capítulos 8 y 9 contempla la


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mineralización de nitrógeno orgánico ocurrida durante una semana en condiciones

de anaerobiosis.

Respiración (basal e inducida por substrato)

La respiración del suelo es un parámetro bien establecido para monitorizar la

descomposición de la materia orgánica. No obstante, la interpretación de los datos

de respiración en términos de salud del ecosistema edáfico es ciertamente

problemática pues, en ocasiones, además de que su aumento puede indicar

condiciones de estrés, la descomposición de la materia orgánica puede no ser

deseable, mientras que en otras la liberación de nutrientes producida por dicha

descomposición en el tiempo preciso en que las plantas los demandan es, sin duda,

una característica deseable. En el método de determinación utilizado en este trabajo,

el suelo se introduce en un tarro de vidrio de cierre hermético junto con un vasito

con una solución de sosa, donde se atrapa el CO2 producido durante la respiración.

Transcurrido el tiempo correspondiente se valora la sosa remanente con ácido

clorhídrico (Figura 3.5b). La respiración basal del suelo se ha medido en los

Capítulos 6, 7 y 8, estando descrita en detalle en este último.

La respiración inducida por substrato se basa en proveer a la biomasa

microbiana con una concentración saturante de un substrato fácilmente

mineralizable (generalmente, glucosa) y el posterior seguimiento de la respiración

durante un periodo relativamente corto. La tasa de respiración en presencia de una

concentración saturante de substrato representa la velocidad de reacción máxima y

es, por ende, proporcional a la biomasa microbiana potencialmente activa. La

respiración inducida se ha medido en este trabajo utilizando por un lado glucosa

como substrato (Capítulos 6, 7 y 8; método descrito en detalle en el Capítulo 8) y

por otro empleando una solución modelo de rizodepósito (Capítulo 7). Esta

solución de rizodepósito (que contiene 50 mM fructosa, 50 mM glucosa, 50 mM

sucrosa, 25 mM ácido succínico, 25 mM ácido málico, 12.5 mM arginina, 12.5 mM

serina y 12.5 mM cisteína) aporta a priori datos de mayor relevancia ecológica que la

glucosa para el estudio de las comunidades microbianas rizosféricas.


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Carbono de la biomasa microbiana

La biomasa microbiana se refiere al componente vivo de la materia orgánica

del suelo. La biomasa microbiana del suelo responde rápidamente a condiciones

cambiantes en el suelo, tales como la adición de substratos o el aumento del

contenido en metales. Así, la biomasa microbiana parece ser una medida más

sensible frente a los cambios producidos en la salud del ecosistema edáfico que la

proporcionada por el contenido en materia orgánica total.

En el método de fumigación/extracción aquí empleado, el suelo se fumiga con

cloroformo, al objeto de permeabilizar las membranas celulares. El aumento en el

carbono orgánico extraíble, comparado con un control sin fumigar, es la medida de

la biomasa microbiana total. Este método se ha utilizado en los Capítulos 4, 9 y 10

(se describe en detalle en el Capítulo 4).

Figura 3.5: Equipamientos para (a) actividades enzimáticas, (b) respiración y (c) perfiles fisiológicos a nivel de comunidad microbiana obtenidos con placas EcoBiologTM. Fuente:

NEIKER-Tecnalia.

Abundancia de genes por PCR a tiempo-real

La técnica de PCR a tiempo-real se puede utilizar para cuantificar la

abundancia de genes taxonómicos y funcionales en el suelo. Este análisis combina la

detección a tiempo final de la PCR tradicional con tecnologías de detección por

fluorescencia, para así medir la acumulación de copias “a tiempo-real” en cada ciclo

b) c) a)


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de amplificación de la PCR. El número de copias detectado en la fase exponencial

temprana es proporcional a la concentración presente en la muestra inicial. La

información cuantitativa que se genera es de gran ayuda para entender los roles y las

contribuciones de grupos microbianos y funcionales particulares al funcionamiento

del ecosistema edáfico.

El grupo de Ecología Microbiana Terrestre del Prof. George A. Kowalchuk

(Centro de Ecología Terrestre del Instituto de Ecología de Holanda, Heteren) tiene

gran experiencia en ésta y similares técnicas moleculares aplicadas a muestras de

suelo. Con su colaboración, se utilizó este método en los Capítulos 6 y 10, donde se

cuantificaron genes para bacterias totales, oxidadores de amonio y degradadores de

quitina, así como para hongos totales.

Perfiles fisiológicos a nivel de comunidad (Biolog EcoPlatesTM)

Los perfiles fisiológicos de utilización de fuentes de carbono son ampliamente

utilizados a modo de huella digital catabólica en estudios sobre el efecto de

diferentes variables en la salud del ecosistema edáfico. Las Biolog EcoplatesTM,

comercialmente disponibles, constan de 31 pocillos (por triplicado) que contienen

distintos substratos de carbono (aminas/amidas, aminoácidos, carbohidratos, ácidos

carboxílicos, polímeros), más un pocillo como blanco para cada réplica. El tetrazolio

presente en las Biolog EcoplatesTM se reduce con NADH para formar una

coloración morada. La tasa y la extensión de formación de color morado en cada

pocillo indican la tasa y la extensión a la que ocurre la respiración microbiana

utilizando el substrato presente en el citado pocillo (Figura 3.5c). Este método se ha

utilizado en los Capítulos 4, 5, 7, 8, 9 y 10, estando descrito con más detalle en los

Capítulos 5 y 8.

Microarray de genes funcionales (Geochip)

Los microarrays son una tecnología revolucionaria innovadora basada en la

síntesis o fijación de sondas que representan los genes sobre un substrato sólido,

que posteriormente son expuestas a las moléculas diana. El nivel de hibridación

entre la sonda específica y la molécula diana se indica mediante fluorescencia y se


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mide por análisis de imagen (Figura 3.6a). Recientemente, el grupo de investigación

del Dr. Jizhong Zhou del Instituto de Genómica Ambiental de la Universidad de

Oklahoma ha diseñado, construido y evaluado un microarray de genes funcionales,

denominado Geochip, que contiene más de 24.000 sondas de genes implicados en

diversos procesos biogeoquímicos, ecológicos y medioambientales (ciclos del

carbono, nitrógeno y azufre; utilización de fósforo; degradación de contaminantes

orgánicos; reducción y resistencia a metales; etc.). El Geochip es de suma utilidad a

la hora de estudiar las relaciones entre la diversidad microbiana (más concretamente,

la diversidad de genes) y los procesos y funciones del ecosistema suelo. Este

microarray de genes funcionales se ha utilizado en el Capítulo 6.

Figura 3.6: (a) Microarray Geochip, (b) cubeta de DGGE y (c) gel de DGGE. Fuente: NEIKER-Tecnalia.

Huella genética de las comunidades microbianas (DGGE)

La electroforesis en gel de gradiente desnaturalizante es un método molecular

que separa productos de DNA de la misma extensión pero de distinta secuencia

(pertenecientes a distintas especies) generados por PCR (Figura 3.6b, c). Los

cebadores utilizados pueden amplificar tanto secuencias de genes de RNA

ribosómico como de genes funcionales, sirviendo de descriptores de la diversidad

b) c)

a)


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estructural o funcional, respectivamente. La separación se basa en la movilidad

disminuida de moléculas de DNA en un gradiente de compuestos desnaturalizantes.

Así, se visualizan una serie de bandas con las que se obtiene una huella de la

comunidad microbiana objeto de estudio. Con la colaboración del grupo del Prof.

George A. Kowalchuk, se ha aplicado la técnica del DGGE en la caracterización de

las comunidades de bacterias (cebadores F968-GC/R1378; Capítulos 6 y 10) y

hongos edáficos (cebadores FR1_GC/FF390; Capítulo 10) del suelo.

Ensayos de estabilidad (resiliencia-resistencia) del ecosistema suelo

La estabilidad de un suelo se define como la habilidad para mantener su

estructura y funcionamiento en presencia de una perturbación. El concepto de

estabilidad incluye tanto el de resiliencia, la capacidad del sistema para recuperarse tras

una perturbación, como el de resistencia, la capacidad innata del sistema para soportar

la perturbación. Se puede medir tras la aplicación de un estrés (por ejemplo, un

calentamiento transitorio a 40 ºC o una adición de un metal tóxico) para

posteriormente ver la evolución de parámetros como, por ejemplo, la respiración

basal o la tasa potencial de nitrificación (esta última se calcula cuantificando la

oxidación de amonio por acumulación de nitrito durante un tiempo de incubación

determinado). A partir de estos datos se pueden calcular diversos índices de

resistencia y resiliencia del suelo. Este ensayo se ha utilizado en el Capítulo 10 como

parte de una evaluación integrada de la salud del ecosistema edáfico, junto con otros

atributos, léase, vigor y organización.

Bioensayos de productividad y toxicidad con plantas

La capacidad de un suelo para mantener el crecimiento de plantas es un

indicador de gran utilidad para evaluar su salud. De hecho, en los sistemas agrícolas,

se considera que la evolución de la productividad de los cultivos es uno de los

indicadores biológicos de más valor a la hora de monitorizar la calidad del suelo. En

este trabajo, la productividad del suelo se ha medido utilizando alfalfa como especie

modelo en el Capítulo 6 y sorgo en el Capítulo 10.


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Por otro lado, los índices de germinación pueden aportar información valiosa

sobre la fitotoxicidad de un determinado suelo derivada de, por ejemplo,

contaminación por metales. El ensayo de germinación con la especie Lepidium sativum (en el que se cuantifica tanto la germinación como el crecimiento radicular

después de la exposición a un extracto del suelo) se ha utilizado como medida de

fitotoxicidad en el Capítulo 7.

3.2.1.2 Propiedades físico-químicas con potencial indicador de la salud del ecosistema edáfico

Los parámetros físico-químicos, siendo los más estudiados tradicionalmente

(por ello, y por ser los indicadores microbiológicos el objeto principal de este

trabajo, no se describen en detalle en este apartado) siguen aportando información

de gran valor a la hora de evaluar la salud del ecosistema edáfico. Así, al finalizar los

ensayos, y siguiendo métodos oficiales de análisis, se midieron diversos parámetros

físico-químicos en las muestras de suelo: pH, variable fundamental que establece los

límites para el desarrollo de las plantas y los microorganismos del suelo; contenido en materia orgánica y carbono orgánico soluble en agua, componentes del suelo determinantes

de su fertilidad; nutrientes como nitrógeno total, nitratos, fósforo y potasio extraíble; capacidad de intercambio catiónico, relacionada con la disponibilidad de nutrientes;

conductividad eléctrica, que define los límites de actividad vegetal y microbiana; textura,

de importancia para la retención y transporte de agua, nutrientes y compuestos

químicos; capacidad de retención hídrica, determinante para conocer la cantidad de agua

disponible, etc. Análogamente, todos los suelos objeto de estudio fueron

caracterizados físico-químicamente antes del comienzo de los ensayos.

3.2.2 Parámetros fisiológicos de plantas

La fitotoxicidad causada por los metales sobre las plantas se puede estudiar en

base a medidas de fluorescencia y contenido en pigmentos. Asimismo, es posible

evaluar la tolerancia y fitotoxicidad causada por metales en plantas monitorizando la

evolución de compuestos antioxidantes. En colaboración con el grupo del Prof. José

María Becerril del Departamento de Biología Vegetal y Ecología, Universidad del

País Vasco, en diversos ensayos, se realizaron medidas de fluorescencia (Capítulos 5

y 6) y se cuantificó la presencia de una serie de pigmentos fotosintéticos (clorofilas a


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y b, carotenoides, violaxantina, anteraxantina, zeaxantina, γ- y α-tocoferol) y

antioxidantes lipofílicos (carotenoides y tocoferol) (Capítulos 4, 5, 6 y 9; en los

Capítulos 5 y 9 se midieron solamente clorofilas y carotenoides). Las medidas de

fluorescencia se realizaron con un fluorímetro portátil. La toma de muestras para los

análisis fisiológicos se realizó en tejido adaptado a la oscuridad durante 12 h a

temperatura ambiente. Las muestras vegetales (0.02 g de hoja) se congelaron en

nitrógeno liquido y almacenaron a -80ºC hasta su análisis por HPLC de fase reversa.

Figura 3.7: (a) Rhizons tipo MOM, (b) espectrómetro de absorción atómica de llama. Fuente: NEIKER-Tecnalia.

3.2.3 Concentración de metales en suelo y planta

Al final de cada ensayo, se midió la concentración total (digeridas bien con

“aqua regia” o bien con una mezcla de HNO3/HClO4) y extraíble en CaCl2 de los

diferentes metales en el suelo, para así poder evaluar su variación tras la aplicación

de las distintas técnicas fitorremediadoras. Además, en el Capítulo 8 se utilizaron

Rhizons tipo MOM (Figura 3.7a) para medir la concentración de metal en la

solución del suelo. Asimismo, en el Capítulo 10 se incluye un procedimiento de

extracción secuencial de los metales del suelo (i.e., fracción soluble/intercambiable;

fracción unida a carbonatos; fracción unida a óxidos de Fe y Mn; fracción unida a

materia orgánica; fracción residual). Por otro lado, los tallos y raíces cosechados en

los ensayos fueron digeridos con una mezcla de HNO3/HClO4.

Posteriormente, la concentración de metales en las digestiones y extracciones

se determinó mediante Espectrometría de Absorción Atómica de Llama (FAAS,

Varian Spectra AA-250 plus; Figura 3.7b) y Espectrometría de Emisión Atómica por

plasma (ICP-AES, Varian VISTA-MPX).

b) a)

4. interactions between plant and rhizosphere microbial communities in a metalliferous soil

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4. INTERACTIONS BETWEEN PLANT AND RHIZOSPHERE MICROBIAL COMMUNITIES IN A METALLIFEROUS SOIL

Epelde et al., submitted to Journal of Soils and Sediments

4.1 Abstract

The main objective was to study the relationships between

pseudometallophytes and their rhizosphere microbial communities in a mine soil

chronically polluted with high levels of Cd, Pb and Zn. Physiological response (as

reflected by the content of lipophilic antioxidants and photosynthetic pigments) and

phytoremediation potential of the studied pseudometallophytes were also

investigated.

Several plant consortia consisting of 1-4 metallicolous pseudometallophytes

with different metal-tolerance strategies (Thlaspi caerulescens: hyperaccumulator; Jasione montana: accumulator; Rumex acetosa: indicator; and Festuca rubra: excluder), together

with their corresponding rhizosphere microbial communities, were collected from a

severely polluted mine area. Plant biomass, as well as lipophilic antioxidants

(carotenoids and tocopherols) and photosynthetic pigments were measured. The

following physicochemical and microbial properties were determined in rhizosphere

soil to study the relationships between aboveground plant and belowground

microbial communities: pH, water soluble organic C, microbial biomass C, enzyme

activities (dehydrogenase, β-glucosidase, arylsulphatase, acid phosphatase, urease)

and community-level physiological profiles with Biolog EcoplatesTM. Soil and plant

(shoot) metal concentrations (total and bioavailable) were also determined.

No correlation was found between number of plant species present in the

plant consortia and soil properties. However, most belowground biological

parameters were correlated with plant biomass. It was found that the higher the

values of most soil microbial parameters, the lower the biomass of T. caerulescens. Anyway, soil microbial properties had a stronger effect on plant biomass rather than

the other way around (35.2% versus 14.9%). Biomass values for R. acetosa were

positively linked to enzyme activities and S and AWCD values calculated from


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Biolog EcoPlatesTM. Jasione montana biomass was positively influenced by biomass C,

while F. rubra biomass increased towards sites with higher-than average values of

acid phosphatase, arylsulphatase and dehydrogenase. On the contrary, biomass

values for T. caerulescens increased towards sites with lower-than-average values of

soil microbial properties. Likewise, soil microbial and physicochemical properties

were highly related. T. caerulescens confirmed its ability to hyperaccumulate Zn in

shoots, reaching a maximum concentration of up to 2.7% on a DW basis. J. montana

and R. acetosa also accumulated considerable amounts of Pb and Zn. Thlaspi caerulescens showed some features related to stress tolerance, such as elevated levels

of A+Z/VAZ ratio and tocopherol per chlorophyll content.

The studied metallicolous populations are tolerant to metal pollution and offer

potential for the development of phytoextraction and phytostabilization

technologies. T. caerulescens appears very tolerant to metal stress and most suitable

for metal phytoextraction; the other three species enhance soil functionality. The

rhizosphere microbial communities adapted to survive in highly polluted mine soils

are determinant for the growth of pseudometallophytes. An ecological

understanding of how contaminants, ecosystem functions and biological

communities interact in the long-term is needed for proper management of these

fragile metalliferous ecosystems.

4.2 Introduction

In mining sites, toxic heavy metals are known to adversely affect the number,

activity and diversity of soil organisms, as well as to restrict the growth of all but the

most tolerant plants (Wong, 2003). Interestingly, the endemic biodiversity present in

many metalliferous sites offers huge potential for the development of environmental

technologies such as, for instance, the phytoremediation of metal-polluted soils.

Unfortunately, sound decisions regarding the future management of fragile

metalliferous ecosystems are impeded by a lack of ecological understanding of how

contaminants, ecosystem functions and biological communities interact in the long-

term (Ramsey et al., 2005).


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Metallophytes are plant species with the capacity to grow in metalliferous soils,

as they have evolved a complex array of mechanisms to avoid the detrimental

effects of excessively high internal metal concentrations via exclusion or uptake and

detoxification (Clemens, 2001). On the other hand, most of the plant species from

metalliferous soils are pseudometallophytes (plants that colonize both metalliferous

and non-metalliferous environments). These tolerant pseudometallophyte

populations are nowadays showing high rates of population decline, making actions

towards their conservation imperative (Whiting et al., 2004). On the other hand, soil

microorganisms are also able to develop tolerance against heavy metals: the

mechanisms of resistance are generally efflux “pumping” and enzymatic

detoxification to convert toxic to less toxic or less available metal-ion species (Silver

and Phung, 1996).

Aboveground plant and belowground microbial communities of terrestrial

ecosystems are closely related. Plants provide a source of carbon (C) and other

nutrients for the soil decomposer community in the form of plant litter and root

exudates; changes in aboveground plant diversity can alter belowground soil

microbial diversity (Bartelt-Ryser, 2005; Rodríguez-Loinaz et al., 2008). In turn,

belowground microbial communities decompose soil organic matter (OM), stabilize

soil structure and, through its essential role in the cycling of elements, release

nutrients for plant growth (Porazinska et al., 2003), thus affecting vegetation

structure. Regrettably, so far, only a few studies have addressed the interactions

between aboveground and belowground communities in polluted environments

(Phillips et al., 2008; Yang et al., 2007).

The main objective of the current work was to study the relationships between

several metallicolous populations and their rhizosphere microbial communities (in

terms of activity, abundance and functional diversity) in a Zn-Pb mine soil

chronically polluted with high levels of Cd, Pb and Zn. We focused on the

rhizosphere microbial communities of a few plant consortia, naturally found in a

metal-polluted mine, consisting of 1 to 4 metallicolous pseudometallophytes with

different metal-tolerance strategies, i.e. Thlaspi caerulescens: hyperaccumulator; Jasione montana: accumulator; Rumex acetosa: indicator; and Festuca rubra: excluder. In

addition, physiological response (as reflected by the content of lipophilic


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antioxidants and photosynthetic pigments) and phytoremediation potential of these

four metallicolous pseudometallophytes were also investigated. To our knowledge,

this is the first report on the interactions between plant and rhizosphere microbial

communities in a metal-polluted mine soil under field conditions.

4.3 Materials and methods

4.3.1 Field characterization

The study was carried out in a spontaneously revegetated abandoned mine,

heavily polluted with Cd, Pb and Zn, located in Lanestosa, Biscay, northern Spain

(latitude 43°13´; longitude 3°26´). Within the mine, an experimental area of

approximately 300 m2 was chosen for this study based on the richness of plant

species observed in that area. Initially, a systematic soil sampling (upper 0-10 cm)

was carried out by means of dividing the experimental area into four quadrants and

then, within each of them, 10 soil cores (diameter: 2.5 cm) were collected at random

and mixed together to form a composite sample (i.e., 4 composite samples: one per

quadrant). Immediately after collection, soil samples were sieved to <2 mm, air-

dried at 30 ºC, and subjected to physicochemical characterization according to

standard methods (MAPA, 1994). The soil was sandy loam, with the following

physicochemical properties (mean value ± SE; n = 4): pH = 6.6 ± 0.0, OM content

= 4.77 ± 0.27%, total nitrogen (N) content = 0.19 ± 0.02%, C/N ratio = 15 ± 1,

phosphorus (P) content = 1.49 ± 0.32 mg kg-1 DW soil, and potassium (K+)

content = 28.50 ± 2.66 mg kg-1 DW soil. Total concentrations of heavy metals in

soil samples were determined using flame atomic absorption spectrometry (AAS,

Varian) following digestion with a mixture of HNO3/HClO4 (Zhao et al., 1994).

The following values (mean value ± SE; n = 4) of total metal concentration were

found (mg kg-1 DW soil): 48 ± 14, 26,328 ± 6,165, and 113,620 ± 14,514 for Cd, Pb

and Zn, respectively.

4.3.2 Plant parameters

For this study, as abovementioned, four metallicolous species with different

metal-tolerance strategies were chosen: Thlaspi caerulescens J. & C. Presl. (Brassicaceae;


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metal hyperaccumulator); Jasione montana L. (Campanulaceae; metal accumulator);

Rumex acetosa L. (Polygonaceae; metal indicator); and Festuca rubra L. (Poaceae; metal

excluder). Thirty-three (33) points were selected to study native consortia (Figure

4.1) consisting of 1-4 of these plant species, taking into account that sampling points

had to be at least 1 m apart from each other. For each of the following

combinations, 1-5 samples were taken: T, J, R, F, TR, TF, JR, RF, TJR, TJF, TRF,

JRF and TJRF (T = T. caerulescens; J = J. montana; R = R. acetosa; F = F. rubra). Blocks

containing both aboveground plant consortia and belowground rhizosphere soil

were carefully sampled and taken to the laboratory.

Figure 4.1: Examples of plant consortia present in the experimental area: (a) Rumex acetosa; (b) Thlaspi caerulescens; (c) Rumex acetosa and Festuca rubra; (d) Thlaspi caerulescens, Jasione montana and Rumex

acetosa.


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Shoots from each plant species were harvested, washed thoroughly with

deionized water and gently dried with paper towels. Fresh weights (FW) were

recorded and, subsequently, shoots were oven-dried at 70 ºC for 48 h to calculate

dry weights (DW). Subsamples (0.4 g) of dried shoot tissue were digested with a

mixture of HNO3/HClO4 (Zhao et al., 1994) and, finally, Cd, Pb and Zn were

determined using AAS. Leaf samples were collected and kept in the dark for 12 h at

room temperature (20–22ºC) to reduce the effects of diurnal variations in

antioxidants and pigments composition and to provide comparable “artificial

predawn conditions” (García-Plazaola et al., 2000; Tausz et al., 2003). Then,

approximately 0.02 g FW leaf was collected, frozen in liquid nitrogen and stored at -

80º C until analysis. Lipophilic antioxidants (carotenoids and tocopherols) and

photosynthetic pigments [a and b chlorophylls (Chl), carotenoids (Carot),

violaxanthin (V), antheraxanthin (A), zeaxanthin (Z), γ- and α-tocopherols (Toc)]

were extracted and measured by reverse-phase HPLC following the method of

García-Plazaola and Becerril (1999), with the modifications described in García-

Plazaola and Becerril (2001).

4.3.3 Soil microbial and physicochemical parameters

Rhizosphere soil was carefully sampled by collecting all the soil adhering to

roots after gentle shaking. For the analysis of microbial parameters, soils were sieved

to <2 mm and stored fresh at 4 ºC until analysis. Microbial biomass C, an indicator

of soil microbial biomass, was measured by the fumigation-extraction method

(Vance et al. 1987): a moist sample, equivalent to 5 g DW soil, was fumigated for 24

h with amylene stabilized CHCl3 and extracted with 20 ml of 0.5 M K2SO4. Then,

3.5 ml of chromium reagent [i.e., chromium (VI) oxide (0.06% w/v); sulfuric acid

(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min.

Finally, organic C concentration was determined colorimetrically at 445 nm.

Microbial biomass C was calculated as the difference between C concentration of

the fumigated and unfumigated extracts (an extractability of 0.38 was assumed) (Wu

et al. 1990).

Regarding soil enzyme activities (soil enzymes can be used as indicators of the

functional status or condition of the soil environment; see Naseby and Lynch,


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2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.

(2002): a moist sample, corresponding to 1 g DW soil, was mixed with 0.4 ml of

buffer (100 mM THAM, pH 7) and 0.4 ml of substrate [iodonitrotetrazolium

chloride (0.5% w/v)]. The mixture was incubated at 25 ºC for 3 h and the reaction

stopped with 8 ml of methanol. After centrifugation (3500 x g, 3 min), the

absorbance value of the samples was read at 490 nm. β-glucosidase (EC 3.2.1.21),

arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC 3.1.3.2) activities were

determined according to Dick et al. (1996) and Taylor et al. (2002), as described in

Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined according to

Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).

It has been reported that measurements of functional diversity (such as

community level physiological profiles, CLPPs) are likely to provide information

more relevant to the functioning of the soil ecosystem than species diversity (Zak et

al. 1994). In this respect, substrate utilization patterns determined with the

commercially available Biolog EcoPlatesTM look at the ability of microbial

populations to aerobically degrade a multitude of carbon sources (Dobler et al.

2001). For the analysis of CLPPs, Biolog EcoPlatesTM were used following Epelde

et al. (2008a). Average well colour development (AWCD) and species richness (S =

number of substrates with an absorbance value >0.25; this value marked the

beginning of the exponential phase in the Biolog EcoPlatesTM) were calculated at a

44 h incubation time (at approximately this incubation time, the highest rate of

microbial growth was observed in the Biolog EcoPlatesTM).

For the analysis of soil physicochemical parameters, soils were air-dried at 30

ºC for 48 h, sieved to <2 mm and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v,

soil:water) was measured following standard methods (MAPA 1994). Water-soluble

organic carbon (WSOC) was extracted by shaking soil (horizontal shaker at 175

rpm) with distilled water (1:5 w/v) for 1 h and then measured as described above

for microbial biomass C. Total concentrations of heavy metals in soil were

determined as above. For the estimation of metal bioavailability, CaCl2-extractable

(0.01 M) metal fractions in soil were determined as described by Houba et al. (2000)

and then analyzed by AAS.


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4.3.4 Statistical analysis

To study the influence of soil characteristics on biomass of each plant species

(influence of belowground on aboveground), multivariate relationships between

physicochemical and microbial soil properties and plant biomass were explored. As

the beta-diversity along ordination axes was short, a redundancy analysis (RDA) was

chosen (ter Braak, 1994). The statistical significance of all canonical axes combined

by means of non-parametric Monte Carlo permutation test (Leps and Šmilauer,

2003) was also tested. To explore the individual and shared effects of soil

physicochemical and microbial properties to the revealed patterns in plant biomass

data, we employed variation partitioning procedures (Pereira et al., 2008). In the

same way, we quantified how much of the variability in the values of soil

physicochemical properties could be attributed to the individual or joint effect of

both soil microbial properties and plant biomass data (influence belowground on

belowground and influence aboveground on belowground). Finally, we measured

how much of the variation in values of soil microbial properties could be attributed

to the individual or joint effect of both soil physicochemical parameters and plant

biomass data (influence belowground on belowground and influence aboveground

on belowground). Likewise, in order to study physiological response of each

particular pseudometallophyte, we explored the relationships between the content

values of all lipophilic antioxidants and photosynthetic pigments here determined

and shoot metal concentrations for each of the 4 pseudometallophytes, considering

all 33 samples as a whole, by means of a principal component analysis (PCA)

applied on the correlation matrix of these variables. All multivariate analyses were

done by running Canoco for Windows 4.5 (ter Braak and Šmilauer, 2002).

Differences in shoot metal concentration, lipophilic antioxidants and

photosynthetic pigments among species were analyzed by one-way ANOVA using

Microsoft Stat View Software (SAS Institute). Fisher´s PLSD-test was used to

establish the significance of the differences among means. Pearson’s correlations

were calculated using SPSS Programme (Inso Corporation).


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4.4 Results

4.4.1 Soil microbial and physicochemical properties

Regarding total metal concentrations in the rhizosphere soil of the 33 studied

sampling points, the observed values varied considerably, i.e. from 13.4 to 57.0 mg

Cd kg-1 DW; from 5,959 to 58,928 mg Pb kg-1 DW; and from 27,150 to 203,110 mg

Zn kg-1 DW. Similarly, regarding metal bioavailability, CaCl2-extractable metal

concentrations in rhizosphere soil were also highly variable among the 33 sampling

points: from 1.33 to 6.94 mg Cd kg-1 DW; from 9.8 to 33.5 mg Pb kg-1 DW; from

412 to 1,102 mg Zn kg-1 DW. On average, 20.7, 0.3 and 2.9% of total Cd, Pb and

Zn, respectively, appeared in a bioavailable (CaCl2-extractable) form (Table 4.1).

Values of soil pH ranged between 6.04 and 6.99, while WSOC values ranged from

33 to 285 mg C kg-1 DW soil. Likewise, values of microbial biomass C, enzyme

activities, and CLPPs showed great variability among the 33 rhizosphere soils (Table

4.1). Table 4.1: Physicochemical and microbial properties of the 33 studied rhizosphere soils.

Mean ± SE Interval

Total Cd (mg kg-1 DW soil) 33.0 ± 2.0 13.4 - 57.0

CaCl2 extractable Cd (mg kg-1 DW soil) 3.04 ± 0.23 1.33 - 6.94

Total Pb (mg kg-1 DW soil) 24,175 ± 2,241 5,959 - 58,928

CaCl2 extractable Pb (mg kg-1 DW soil) 21.4 ± 1.0 9.8 - 33.5

Total Zn (mg kg-1 DW soil) 97,735 ± 6,594 27,150 - 203,110

CaCl2 extractable Zn (mg kg-1 DW soil) 761 ± 25 412 - 1,102

pH 6.47 ± 0.04 6.04 – 6.99

WSOC (mg C kg-1 DW soil) 101 ± 10 33 - 285

Microbial biomass C (mg C kg-1 DW soil) 312 ± 24 87 - 590

Dehydrogenase (mg INTF kg-1 20 h-1) 436 ± 40 65 - 916

β-glucosidase (mg ρ-nitrophenol kg-1 h-1) 169 ± 21 29 - 569

Arylsulphatase (mg ρ-nitrophenol kg-1 h-1) 146 ± 17 57 - 448

Acid phosphatase (mg ρ-nitrophenol kg-1 h-1) 274 ± 26 76 - 726

Urease (mg N-NH4+ kg-1 h-1) 14.7 ± 1.7 2.7 - 42.5

AWCD (Biolog EcoPlatesTM) 0.26 ± 0.03 0.04 - 0.59

S (Biolog EcoPlatesTM) 11 ± 1 1 - 21


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4.4.2 Interactions between plants and soil microbial and physicochemical properties

No correlation was found between number of plant species present in the

different plant consortia (richness) and soil properties (neither physicochemical nor

microbial). However, total plant biomass was positively correlated with microbial

biomass C (R = 0.575, P < 0.001), dehydrogenase activity (R = 0.605, P < 0.001),

acid phosphatase activity (R = 0.553, P < 0.001), urease activity (R = 0.362, P <

0.038), AWCD (R = 0.447, P < 0.009), S-BiologTM (R = 0.390, P < 0.025), CaCl2

extractable Zn (R = 0.355, P < 0.042) and WSOC (R = 0.441, P < 0.010). The

correlation was negative for soil pH (R = -0.596, P < 0.001).

After partialling out the influence of selected sets of co-variables, most of the

explained variation in plant biomass data was attributable to changes in soil

microbial properties (which, per se, explained 35.2% of the total inertia) (Figure 4.2).

However, most of the explained variation in soil microbial properties was due to

changes in soil physicochemical variables (49.0%), with values of plant biomass

exerting only a minor influence (14.9%). In turn, physicochemical properties were

also influenced by microbial properties (38.5%; Figure 4.2).

Figure 4.2: Results of the variation partitioning, RDA analyses. Explained (Exp) percentages indicate the explained variation of the response variable by the RDA. For each set of response

variables (plant biomass; soil microbial properties; soil physicochemical properties), the remaining sets were considered as co-variables in successive RDAs. When P < 0.05, numbers shown in arrows

quantify the effects of each set of explaining factors, after partialling out the effect of the other variables, expressed as percent contribution to the total inertia in the response variable.

Physico-chemical propertie

s

Microbial propertie

s

Plant biomass

49.0% (P = 0.002) 35.2% (P = 0.032)

14.9% (P = 0.010)

Exp. = 67.7% P = 0.002

Exp. = 62.1% P = 0.046

P = 0.266 P = 0.626

Non-significant effects

Exp. = 48.2% P = 0.024

38.5% (P = 0.008)


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Figure 4.3 shows the influence of soil microbial properties on the biomass of

the different pseudometallophytes (influence of belowground on aboveground).

Biomass values for R. acetosa increased towards the positive region of RDA-1 axis,

being positively linked to enzyme activities and S and AWCD values calculated from

Biolog EcoPlatesTM. On the contrary, biomass values for T. caerulescens increased

towards sites with lower-than-average values of soil microbial properties. Along

RDA-2, J. montana biomass was positively influenced by microbial biomass C.

Finally, F. rubra biomass increased towards sites with higher-than average values of

acid phosphatase, arylsulphatase and dehydrogenase.

Figure 4.3: Triplot of the redundancy analysis performed on plant biomass data as response variable, soil microbial properties as explanatory variables, and soil physicochemical properties as

covariables. Closed symbols represent the 33 samples, whereas thick vectors represent plant biomass and thin arrows represent soil microbial properties. AWCD: average well colour development; S: richness from Biolog EcoPlatesTM; Glu: β-glucosidase; Ure: urease; Sul:

arylsulphatase; Pho: phosphatase; DH: dehydrogenase; MBC: microbial biomass C.


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Although the percentage of explained variability is considerably lower, the

influence of plant biomass on soil microbial properties is shown in Figure 4.4

(influence of aboveground on belowground). R. acetosa biomass positively influenced

most enzyme activities (except for β-glucosidase) and S and AWCD values

calculated from Biolog EcoPlatesTM. Meanwhile, microbial biomass C and β-

glucosidase activity increased towards sites with higher values of F. rubra and J. montana biomass. Lastly, T. caerulescens biomass negatively influenced most of the

microbial parameters here measured.

Figure 4.4: Triplot of the redundancy analysis performed on soil microbial properties as response variable, plant biomass data as explanatory variables, and soil physicochemical properties as covariables. Closed symbols represent the 33 samples, whereas thick vectors represent soil microbial properties and thin arrows represent plant biomass. AWCD: average well colour development; S: richness from Biolog EcoPlatesTM; Glu: β-glucosidase; Ure: urease; Sul:

arylsulphatase; Pho: phosphatase; DH: dehydrogenase; MBC: microbial biomass C.


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Soil microbial and physicochemical properties were interrelated. When

performing RDAs (data not shown), soil microbial parameters were negatively

influenced by most of the soil metal contents (except for CaCl2-extractable Zn

concentration) and soil pH, and positively by WSOC. Soil physicochemical

parameters (apart from CaCl2-extractable Zn and WSOC) were negatively

influenced by soil microbial parameters.


Shoot metal concentrations for the four pseudometallophytes are shown in

Figure 4.5. Highest Cd shoot concentrations were found in T. caerulescens with a

mean value of 30 ± 4 mg kg-1 DW. The other three species had Cd concentrations

below 5 mg kg-1 DW shoot. T. caerulescens also showed the highest shoot Zn

concentrations with a mean value of 19,339 ± 756 mg kg-1 DW. On the contrary,

lowest values of Zn shoot concentrations were found in F. rubra (1,021 ± 116 mg

kg-1 DW). Regarding shoot Pb concentrations, highest values were found in T. caerulescens and J. montana (lowest values again corresponded to F. rubra).


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Figure 4.5: Shoot metal concentrations [mean values ± SE; T. caerulescens (n=18), J. montana (n=16), R. acetosa (n=21), F. rubra (n=20)]. Bars followed with different letters are significantly different

according to Fisher´s PLSD-test.

Figure 4.6 shows multivariate relationships between shoot metal

concentration, photosynthetic pigments and lipophilic antioxidant indexes. Many of

these indexes [i.e., Zea/Chl (a+b), A+Z/VAZ, and both γ- and α-Toc/Chl (a+b)] increased towards the positive region of PCA-1, which accounted for 41% of the

variance, and were positively correlated with shoot metal concentrations (by


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contrast, shoot chlorophyll contents were negatively correlated). At the same time,

the indexes V/Chl (a+b), VAZ/Chl (a+b), A/Chl (a+b) and Carot tot/Chl (a+b) extended along the positive region of PCA-2, which accounted for 30% of the

variance. The different plant species separated from each other along PCA-1, which

could simply be due to differences in shoot metal concentration. However, this

separation among species was still observed when removing data of shoot metal

concentration from the PCA (data not shown), implying that differences among

species regarding contents of photosynthetic pigments and antioxidant metabolites

did occur.

Figure 4.6: Biplot of PCA performed on shoot metal concentrations (thick vectors) and content of lipophilic antioxidants and photosynthetic pigments indexes (thin vectors). Chl: chlorophyll a+b;

Carot: carotenoids; V: violaxanthin; A: antheraxanthin; Z: zeaxanthin; A-Toc: α-tocopherol; G-Toc: γ -tocopherol.


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In fact, it can be seen in Table 4.2 that T. caerulescens showed significantly lower

values of VAZ/Chl and V/Chl and higher values of Z/Chl, A+Z/VAZ, γ-Toc/Chl

and α-Toc/Chl than the rest of the species (in the case of Zea/Chl, the difference

with J. montana was not statistically significant). Remarkably, total tocopherol values

in T. caerulescens were 118, 57 and 79% higher than in J. montana, R. acetosa and F. rubra, respectively. T. caerulescens and J. montana showed significantly lower values of

chlorophylls than R. acetosa and F. rubra (Table 4.2). Also, R. acetosa showed the

highest and lowest values of Ant/Chl and Carot tot/Chl, respectively (Table 4.2).

Table 4.2: Content of lipophilic antioxidants and photosynthetic pigments in the four

pseudometallophytes [mean values ± SE; T. caerulescens (n=18), J. montana (n=16), R. acetosa (n=21), F. rubra (n=20)]. Values followed with different letters are significantly different according to

Fisher´s PLSD-test. Chl (a+b): chlorophyll a+b; Carot: carotenoids; V: violaxanthin; A: antheraxanthin; Z: zeaxanthin; VAZ: violaxanthin + antheraxanthin + zeaxanthin; Toc: tocopherol.

T. caerulescens R. acetosa J. montana F. rubra

Chl (a+b)a 1165 ± 66a 2132 ± 54b 1363 ± 85a 1913 ± 122b

Carot/Chl (a+b)b 381 ± 9a 360 ± 4b 362 ± 6ab 378 ± 5a

V/Chl (a+b)b 66.5 ± 3.2a 81.3 ± 2.5b 79.5 ± 3.3b 83.3 ± 2.5b

A/Chl (a+b)b 2.57 ± 0.28a 3.44 ± 0.29b 2.42 ± 0.20a 2.55 ± 0.15a

Z/Chl (a+b)b 4.11 ± 0.77a 2.20 ± 0.22b 2.94 ± 0.30ab 2.14 ± 0.15b

VAZ/Chl (a+b)b 73.2 ± 3.8a 86.9 ± 2.7b 84.9 ± 3.6b 87.9 ± 2.6b

A+Z/VAZ (a+b)b 87.4 ± 11.2a 64.4 ± 4.8b 62.0 ± 4.5b 53.0 ± 2.4b

γ-Toc/Chl (a+b)b 15.61 ± 1.97a 3.11 ± 0.38b 4.77 ± 0.86b 3.46 ± 0.51b

α-Toc/Chl (a+b)b 382 ± 45a 128 ± 8b 162 ± 25b 126 ± 9b apmol mg-1 FW leaf bmmol mol-1

4.5 Discussion

The studied mine field was severely polluted with Cd, Pb and Zn, surpassing

by far, as expected, the maximum Cd, Pb and Zn concentrations usually found in

non-polluted soils of the Basque Country (0.8 mg Cd kg-1 soil, 16+0.7L+2.1H mg

Pb kg-1 soil, 50+2L mg Zn kg-1 soil; L and H refer to clay and OM content,

respectively) (IHOBE, 1998). A considerable portion of the metals was found in the

non CaCl2-extractable fraction, an unavailable form for plants. It is well-known that


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Pb usually appears in soil non-bioavailable fractions, but Cd and Zn frequently

appear in more bioavailable fractions (Sun et al., 2001). In the studied soil a

considerable amount of Zn seems to be present in a hypogene assemblage

consisting of sphalerite, galena, pyrite, dolomite, calcite, and quartz (Grandia et al.,

2003).

On the other hand, the high metal concentrations found in the mine soil could

well be responsible for its relatively high values of OM content (4.77 ± 0.27%) and

very low values of N, P and K+ content, as heavy metals might affect biological

mineralization cycles (Chander and Brookes, 1991).

Previous studies (Bardgett et al., 1998; Kowalchuk et al., 2002; Wardle et al.,

1999) have shown that the composition of belowground soil microbial communities

may depend on aboveground plant species composition, mainly through the

development of rhizobacteria induced by the release of specific sugars and amino

acids into the rhizosphere. Besides, plant composition, plant richness and

abundance may also affect soil microbial communities. In our study, plant richness

did not have any effect on soil microbial properties (or physicochemical properties),

probably due to the low number of species present in the plant consortia (1-4) as

well as the limited number of replicates per plant consortia found in the

experimental area. However, plant biomass was positively correlated with most

microbial parameters measured (also with WSOC and negatively with soil pH). The

redundancy analysis suggested that the biomass of each plant species influenced in a

different way soil microbial parameters. Particularly, the higher the biomass of T. caerulescens the lower the values of microbial biomass C, β-glucosidase, urease and

microbial functional diversity (AWCD and S-BiologTM). Being an endemic ecotype

of T. caerulescens, it might well be that microbial communities associated with its

rhizosphere are very specific and low in functional diversity. These results are of use

for the selection of phytoremediation strategies. For instance, T. caerulescens appears

as a metal hyperacumulator most suitable for phytoextraction (see below). Instead,

from the point of view of a biologically active and healthy soil, revegetation with R. acetosa would be the best choice. It must always be remembered that the objective of

any soil remediation process must be not only to remove the contaminant(s) from


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the soil but, most importantly, to restore the continued capacity of the soil to

perform or function according to its potential (Epelde et al. 2009a).

Most importantly, soil microbial parameters had a stronger effect on plant

biomass rather than the other way round (35.2% versus 14.9%). This could be due

to the extremely harsh conditions present in the mine soil, making microbial activity

of vital importance for plant development. Indeed, positive effects of microbes on

plant productivity are most common in nutrient poor ecosystems where they

enhance the supply of growth limiting nutrients such as N and P to plants (van der

Heijden et al. 2008). Under such limiting conditions, up to 90% of the P and N for

plant growth might be provided by soil microbes, emphasizing their importance for

plant productivity in those areas (van der Heijden et al. 2008). In our case, this

appears to be the case except for T. caerulescens, as higher biomass values of this

species were found with lower values of soil microbial properties. This might

indicate that T. caerulescens is more adapted to survive in these metal polluted

environments, without the need of much support from soil microbes. In any case,

links among plant communities, microbial communities, nutrient availability and

ecosystem processes are never unidirectional and rarely simple (Hooper et al. 2000,

Naeem et al. 2000).

The influence of soil physicochemical properties (including metal

concentrations) on soil microbial properties and viceversa is worth-mentioning. An

increasing body of evidence suggests that heavy metals have a strong impact on

both bacterial and fungal communities (Kozdroj and van Elsas 2001). Nonetheless,

soil microorganisms have developed highly efficient systems for metal detoxification

which, in bacteria, can be grouped into five categories: intracellular sequestration,

export, reduced permeability, extracellular sequestration, and extracellular

detoxification (Rough et al. 1995). Heavy metal contamination provides a strong

pressure that selects for the recruitment of multiple resistance phenotypes that

encode resistance to the predominant metals in the site (Ryan et al. 2005). In our

study, CaCl2-extractable Zn positively influenced soil microbial parameters. Unlike

Cd and Pb, Zn is an essential trace element; however, it has been reported to be

highly toxic at elevated concentrations (Tang et al., 2009). Microorganisms are

intimately involved in metal biogeochemistry with a variety of processes determining


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mobility and bioavailability (Gadd 2004). Microorganisms can affect metal

speciation thanks to their ability to effect and/or mediate mobilization or

immobilization processes (the balance between mobilization and immobilization

varies depending on the organisms involved, their environment and

physicochemical conditions) that influence the balance of metal species between

soluble and insoluble phases (Gadd 2004).

Also, except for metal concentrations themselves, both soil pH and WSOC

had a negative and positive influence on soil microbial properties, respectively. In a

study by Wang et al. (2006), a relationship between soil biological activities (alkaline

phosphatase activity, arylsulphatase activity, nitrification potential, respiration) and

soil pH was well characterized by linear or quadratic regression models with R

values ranging from 0.57 to 0.99. Certainly, the labile fraction of soil OM included

in WSOC provides nutrients for the soil microbial community (Bol et al., 2003).

Apart from that, despite the elevated levels of soil metal pollution present in

the mine soil, the four pseudometallophytes were able to spontaneously grow under

such metalliferous conditions. T. caerulescens confirmed its ability to hyperaccumulate

Zn in shoots, reaching a maximum concentration of up to 2.7% on a DW basis.

Indeed, T. caerulescens exceeded the threshold value for hyperaccumulation indicated

by Baker et al. (2000) for Zn (10,000 mg Zn kg-1 DW shoot) in all cases, and for Pb

(1,000 mg Pb kg-1 DW shoot) when present alone (in the absence of the other three

species). Regrettably, hyperaccumulating plants such as T. caerulescens are, in general,

relatively small, have slow rates of biomass production, and lack any established

cultivation, pest management or harvesting practices (Wenzel et al., 1999), making

their application for metal phytoextraction complicated.

Both J. montana and R. acetosa accumulated considerable amounts of Pb and

Zn. R. acetosa is an species that usually behaves as a Zn indicator, but in the current

study, due to the extremely high levels of metals present in the experimental area, no

correlation between soil Zn concentration and shoot Zn concentration was

observed. This population of R. acetosa has previously been reported to have great

potential for Zn phytoextraction (Barrutia et al., 2009).

The grass F. rubra, a metal excluder, was able to tolerate the high levels of

metal pollution by physiologically restricting the entry of heavy metals, thus making


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it a good candidate for phytostabilization of soils heavily polluted with metals such

as those from mining areas (phytostabilization is a phytoremediation method that

converts soil metal pollutants into inert, immobile forms using metal excluder

plants) (Salt et al., 1995).

None of the studied plants showed severe phytotoxic symptoms according to

the values of photosynthetic pigments and antioxidant metabolites, confirming their

adaptation to the harsh environmental conditions present in the mine. However, as

reflected by the values of photosynthetic pigments and antioxidant metabolites,

some differences were observed: sorrel, R. acetosa, stood out among the other

species because of its elevated content of antheraxanthin per chlorophyll (A/Chl).

Anteraxanthin, together with zeaxanthin, is related to membrane stabilization

(Havaux, 1998) and antioxidant activity (Havaux and Niyougi, 1999) as well as to

chlorophyll quenching (Yamamoto and Bassi, 1996; Goss et al., 2006). Zeaxanthin

per chlorophyll ratio (Z/Chl) was high in T. caerulescens. Moreover, this species

showed some other noteworthy features such as elevated levels of A+Z/VAZ ratio

and tocopherol per chlorophyll content. Interestingly, these two parameters have

been related to stress tolerance. The deepoxidation index (A+Z/VAZ ratio) is

frequently used as an estimation of excess energy dissipation (García-Plazaola et al.,

2007) and was higher in T. caerulescens mainly due to the low V/Chl and high Z/Chl

ratios found in its leaves. Energy dissipation in the antenna mediated by the

xanthophyll cycle is one of the main mechanisms to prevent photooxidative damage

in plants; the other main mechanism is the induction of antioxidant response

(several enzymes and low molecular weight scavengers such as tocopherol). The

elevated total Toc/Chl ratio observed in T. caerulescens was the result of high values

of both γ-tocopherol and α-tocopherol. Tocopherol, vitamin E, might play a

protective role to membrane systems in plant cells (Collin et al., 2008; Havaux et al.,

2005) and also to PSII reaction centre against photoinhibition (Krieger-Liszkay and

Trebst; 2006). Indeed, tocopherol is an important part of the plants machinery to

maintain integrity and normal function of photosynthetic apparatus (Liu et al.;

2008). Then, high levels of tocopherol might provide protection against

environmental stresses, e.g. metal pollution. In fact, tocopherol content has been

positively correlated with tolerance to low temperature, water deficit or salt stress in

different plant species (Guo et al., 2006; Munné-Bosch et al., 1999; Yamaguchi-


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Shinozaki and Shinozaki, 1994) and recently suggested to be involved in Cd

tolerance of Arabidopsis thaliana (Collin et al., 2008). These particular features

observed in T. caerulescens suggest that this species is probably better protected

against environmental stress than the others. This is the first time that antioxidant

metabolites are studied in T. caerulescens under field conditions and the interesting

results obtained should encourage the scientific community to further study the

physiology of this plant in order to better understand its peculiar behaviour.

4.6 Conclusions

The study of metalliferous environments is of great relevance since it can

provide invaluable information on ecological impact of heavy metals on ecosystem

function, physiological strategies used by metal-tolerant organisms, and novel tools

for remediation of metal polluted sites. The studied pseudometallophytes are

tolerant to metal pollution and offer potential for the development of

phytoextraction and phytostabilization technologies. The suitability of each species

for phytoremediation is also different regarding the recovery of soil health. Soil

microbial parameters are related to plant biomass, but not to plant richness.

Rhizosphere microbial communities influence more the growth of plants, instead

of the other way round. Soil microbial and physicochemical properties are

interrelated. An ecological understanding of how contaminants, ecosystem

functions and biological communities interact in the long-term is needed for

proper management of these fragile metalliferous ecosystems.

5. functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens Growth and metal phytoextraction

89

91

5. FUNCTIONAL DIVERSITY AS INDICATOR OF THE RECOVERY OF SOIL HEALTH DERIVED FROM Thlaspi

caerulescens GROWTH AND METAL PHYTOEXTRACTION

Epelde et al. (2008), published in Applied Soil Ecology 39, 299-310

5.1 Abstract

Continuous phytoextraction has lately drawn a lot of attention due to its

potential for the remediation of metal polluted soils. Although when assessing the

success of a phytoextraction process, up till now, emphasis has mostly been placed

on metal removal, it is important to highlight that the ultimate objective of a

phytoextraction process must be to restore soil health. Consequently, a short-term

microcosm study was carried out to evaluate the capacity of an actively growing

ecotype of the Zn and Cd hyperaccumulator Thlaspi caerulescens (Lanestosa ecotype)

to phytoextract metals from soil and, above all, to assess the potential of soil

functional diversity (through the determination of soil enzyme activities and

community level physiological profiles) to both determine the toxic effect of metals

on soil condition and to monitor the efficiency of a metal phytoextraction process.

T. caerulescens plants grown in metal polluted soils showed a shoot metal

concentration of 337 mg of Cd, 5670 mg of Zn and 76.6 mg of Pb per kg of dry

weight tissue. Apart from confirming its great potential for Zn and Cd

phytoextraction, the presence of T. caerulescens, as compared to the metal

phytoextraction itself, had the major effect on soil biological parameters. Actually, in

metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140, 37 and

164% increase in the activity of β-glucosidase, arylsulphatase, acid phosphatase,

alkaline phosphatase and urease, respectively. Metal pollution did not cause a clear

inhibition of soil enzyme activities. Contrasting results were obtained with

EcoPlatesTM versus soil enzyme activities. Actually, the presence of metals led to

significantly lower values of Shannon´s index calculated from enzyme activities and

non-significant higher values of this same index when calculated from EcoPlatesTM


90

92

data. It was concluded that biological indicators of soil health are valid tools to

evaluate the success of a metal phytoextraction process.

5.2 Introduction

Continuous phytoextraction (a technology based on the utilization of metal

hyperaccumulating plants that have the capacity to accumulate, translocate and

tolerate high amounts of metals over the complete growth cycle) appears a cost-

effective, non-intrusive, socially accepted, aesthetically pleasing phytotechnology

with great potential for the remediation of metal polluted soils. Thlaspi caerulescens, a

hyperaccumulating plant extensively studied due to its remarkable capacity to

phytoextract zinc and cadmium from polluted soils, has been suggested as a model

species for research on metal phytoextraction (Assunção et al., 2003) and much

screened in the search for new ecotypes with greater capacities to phytoextract

metals (McGrath et al., 2001b; Lombi et al., 2002).

Up to now, when assessing the success of a phytoextraction process,

emphasis has mostly been placed on metal removal. However, the ultimate objective

of a phytoextraction process must be not only to remove the metal from the soil

but, most importantly, to restore soil health, i.e. the continued capacity of soil to

function as a vital living system, within ecosystem and land-use boundaries, to

sustain biological productivity, promote the quality of air and water environments,

and maintain plant, animal, and human health (Doran and Safley, 1997). Hence,

indicators of soil health are needed to properly assess the efficiency of a

phytoextraction process. Biological indicators of soil health, especially those related

to the activity, size and diversity of soil microbial communities, are becoming

increasingly used due to their sensitivity and capacity to provide information that

integrates many environmental factors (Alkorta et al., 2003b).

In this respect, soil enzyme activities have been reported to provide a unique

integrative biochemical assessment of soil function and condition (Dick et al., 1997;

Naseby and Lynch, 2002) and to be useful as indicators of soil functional diversity

(Bending et al., 2002, 2004; Sowerby et al., 2005). In addition, soil microbial

functional diversity can be determined through the utilization of community level


91

93

physiological profiles (CLPPs) which reflect the potential of the culturable portion

of the microbial community to respond to carbon substrates (Bending et al., 2004).

The so-called Biolog EcoPlatesTM were developed for CLPP of terrestrial

communities (Insam, 1997) and contain 31 useful carbon sources for soil

community analysis. Regarding the degradative capabilities of soil bacterial

communities, it has been reported that, in heavy-metal-affected bacterial

communities, relatively rare degradative capabilities are even rarer than in unaffected

communities, while the reverse is true for more common capabilities (Burkhardt et

al., 1993).

The main objective of the current work was to evaluate the potential of soil

functional diversity (through the determination of soil enzyme activities and CLPPs)

in order to determine the toxic effect of metals on soil condition and, above all, to

monitor the efficiency of a metal phytoextraction process, i.e. its capacity to restore

soil health.


5.3.1 Soil characterization and contamination

A short-term (5 months) microcosm phytoextraction study was carried out

with soil collected from the top layer (0-30 cm) of a natural polyphita grassland

located in Derio (Basque Country, northern Spain). Immediately after collection, the

soil was sieved to <4 mm, air-dried at 30 ºC for 48 h, and subjected to

physicochemical characterization according to standard methods (MAPA, 1994).

The soil was a clay loam, with a pH of 5.2, an organic matter (OM) content of

4.12%, a total nitrogen (N) content of 0.23%, a C/N ratio of 10.4, a phosphorus (P)

content of 26.4 mg kg-1 and an electrical conductivity of 0.08 dS m-1.

Subsequently, the soil was artificially contaminated with a mixture of zinc

(Zn), lead (Pb) and cadmium (Cd) as follows: 1,000 mg Zn kg-1 dry weight (DW)

soil as Zn(NO3)2 + 500 mg Pb kg-1 DW soil as Pb(NO3)2 + 100 mg Cd kg-1 DW

soil as Cd(NO3)2. Control non-polluted (both planted and unplanted) soil was

amended with 100 mg Zn kg-1 DW soil as Zn(NO3)2 (to support the growth of T. caerulescens) and 3.45 g KNO3 kg-1 DW soil (to compensate for the amount of nitrate


92

94

added to the artificially polluted soil). Metal polluted and control (non-polluted)

soils were then stored at room temperature for 1 week.

5.3.2 Experimental design and plant growth

T. caerulescens J. & C. Presl. seeds of a local ecotype, named Lanestosa, collected

from an area formerly occupied by a nowadays abandoned Zn/Pb smelter in the

province of Biscay, Basque Country, northern Spain, were germinated for two

weeks (on a mixture of perlite and vermiculite, 2:3 v/v, moistened with deionized

water) in a greenhouse under the following controlled conditions: temperature

25/18 ºC day/night, relative humidity 60/80% day/night, and a photosynthetic

photon flux density of 400 µmol photon m-2 s-1 by supplementing natural

illumination with white cold lamps (Philips SON-T AGRO 400, Belgium). Then,

seedlings were transplanted to John Innes No. 2 compost and allowed to grow for 1

month. Finally, three T. caerulescens plants were transferred to study pots containing

1.5 kg (DW) of metal polluted or control (non-polluted) soil and allowed to grow

for five months. Unplanted pots were also included in the experiment as additional

controls. Four different treatments (i.e., NM-UP: no metal, unplanted; NM-P: no

metal, planted; M-UP: metal, unplanted; M-P: metal, planted) were conducted in

triplicate. The experiment was carried out for five months under the

abovementioned greenhouse controlled conditions. Throughout the experimental

period, plants were bottom watered periodically as needed.

5.3.3 Soil physicochemical parameters and metal determination

Soil was sampled at the end of the phytoextraction experiment, i.e. 5 months

after transplanting. Immediately after sampling, soils were air-dried at 30 ºC for 48

h, sieved to <2 mm and stored at 4 ºC until analysis.

Soil pH, OM content, total N, cation exchange capacity (CEC), electrical

conductivity (EC), Olsen P, and extractable potassium (K+), calcium (Ca2+) and

magnesium (Mg2+) were measured following standard methods (Watanabe and

Olsen, 1965; MAPA, 1994).


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95

Total concentrations of heavy metals in soil were determined using inductively

coupled plasma atomic emission spectrometry (ICP-AES, Varian) following aqua

regia digestion (McGrath and Cunliffe, 1985). For the determination of the

phytoavailable fraction of metals, pore water metal content was extracted using 0.01

M CaCl2 as described by Houba et al. (2000) and analyzed by ICP-AES.

5.3.4 Soil biological parameters

Regarding soil enzyme activities, β-glucosidase (EC 3.2.1.21), arylsulphatase

(EC 3.1.6.1) and alkaline and acid phosphatase (EC 3.1.3.1 and EC 3.1.3.2) were

determined according to Dick et al. (1996) and Taylor et al. (2002). Urease (EC

3.2.1.21) activity was determined according to Kandeler and Gerber (1988). All

enzyme activities were determined at optimum conditions of pH, temperature and

substrate concentration in order to get an assessment of their maximum potential

activity in the soil.

For β-glucosidase, arylsulphatase and acid and alkaline phosphatase, 1 g DW

soil was mixed with 1.6 ml of buffer (i.e., 20 mM modified universal buffer-MUB,

pH 6.0, for β-glucosidase; 500 mM acetate buffer, pH 5.8, for arylsulphatase; 20

mM MUB, pH 6.5, for acid phosphatase; 20 mM MUB, pH 11, for alkaline

phosphatase) and 0.4 ml of substrate [i.e., 4-nitrophenyl-β-D-glucopyranoside (1.5%

w/v) for β-glucosidase; potassium 4-nitrophenyl sulphate (1.3% w/v) for

arylsulphatase; 4-nitrophenyl phosphate disodium salt (1.85% w/v) for acid and

alkaline phosphatase]. The mixture was incubated at 37 °C for 45 min and the

reaction stopped with 0.4 ml of 500 mM CaCl2 and 1.6 ml of 500 mM NaOH. After

centrifugation (3500 x g, 3 min), the absorbance value of the samples was read at

410 nm.

For urease activity, 1 g DW soil was mixed with 1.75 ml of 100 mM borate

buffer (pH 10.0) and 0.25 ml of 820 mM urea. The mixture was then incubated at

37 °C for 1 h and the reaction stopped with 6 ml of acidified 2 M KCl. After

centrifugation (3500 x g, 3 min), 0.25 ml of the supernatant fraction was mixed with

3.75 ml of distilled water and 2 ml of a reagent composed of a sodium

salicylate/sodium nitroprusiate mixture (17% w/v and 0.12% w/v, respectively), 0.3


94

96

M NaOH and distilled water (1:1:1 v/v/v). Finally, 0.8 ml of sodium

dichloroisocyanurate was added to the reaction mixture. After 30 min, the

absorbance value of the samples was read at 670 nm.

From the values of these five enzyme activities, soil functional diversity was

determined using the Shannon´s diversity index (H’=-∑pilog2pi) (Magurran, 2004) as

indicated by Bending et al. (2004), where pi = the ratio of the activity of a particular

enzyme to the sum of activities of all enzymes. Since the five enzymes here tested

did show activity in all the analyzed samples, then, in this work, Shannon´s diversity

index reflects the “evenness” or distribution of the enzyme activities (Bending et al.,

2004). The order of magnitude of the values obtained for the different enzyme

activities varies considerably depending on the specific activity being determined,

thus leading to some enzyme activities having more weight than others. To resolve

this problem, the percentage of the mean value found for that specific enzyme

activity in the NM-P soil was used for the calculation of the Shannon´s diversity

index. This NM-P soil was taken as the 100% reference since it can be considered a

suitable target where the polluted soils should return after the phytoextraction

procedure (i.e., a vegetated, unpolluted soil of similar physicochemical properties

and subjected to the same edaphoclimatic conditions). Consequently, in this study,

H’ values for enzyme activities indicate how far the remaining soils are from the

target NM-P soil regarding soil enzymes distribution.

For the analysis of CLPPs, Biolog EcoPlatesTM were used. Soil samples were

extracted by agitating in an orbital shaker (125 rev min-1) 1 g DW soil with 10 ml of

autoclaved Mili-Q ultra pure water for 1 h. After shaking, samples were left to settle

down and then a 1:100 dilution (1 ml soil suspension:100 ml autoclaved Mili-Q ultra

pure water) was inoculated onto the Biolog EcoPlatesTM. The plates were incubated

at 30 ºC and colour development was read at 595 nm using a micro plate reader

(Anthos Zenyth 3100). For each reading time, raw absorbance data were corrected

by subtracting the zero hour reading point and the absorbance value given by the

control well. Average well colour development (AWCD) was determined by

calculating the mean of every well’s absorbance value at each reading time. The

plates corresponding to an incubation time of 48 h were chosen for further

calculations (at approximately this incubation time, the highest rate of microbial


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97

growth was observed in the Biolog EcoPlatesTM). The number of utilized substrates

(i.e., the number of substrates with an absorbance value > 0.1; this value marked the

beginning of the exponential phase in the Biolog EcoPlatesTM), equivalent to species

richness, S, was calculated at this 48 h incubation time. Similarly, Shannon´s

diversity (H’) and evenness (J’=H’/Hmax=H’/log2S) indexes were calculated,

considering absorbance values at each well as equivalent to species abundance.

Additionally, kinetic parameters were estimated by fitting the curve of

“corrected absorbance versus time” at 48 h incubation time to a density-dependent

logistic growth equation (Lindstrom et al., 1998):

where K = asymptote that the “corrected absorbance versus time” curve

approaches, r = exponential rate of absorbance changes (slope), t = time following

inoculation of the microplates, and s = time to reach the midpoint of the

exponential portion of the curve (i.e., when y = K/2). Substrates with a corrected

absorbance < 0.1 at 48 h incubation time were omitted from the data set.

Parameters were estimated using the data analysis Origin Program (Microcal

Software, Inc., Northampton, MA). Curve parameters with standard errors greater

than the parameter values or χ2 (goodness of fit) values > 0.01 were omitted from

further analysis. These kinetic parameters were calculated for both the AWCD curve

and for the absorbance curves of each individual substrate present in the Biolog-

EcoPlatesTM.

5.3.5 Plant physiological parameters and metal accumulation

Plants were harvested at the end of the experiment, i.e. 5 months after

transplanting. Shoots and roots were harvested separately and their fresh weights

(FW) recorded. Leaf samples were collected and kept in the dark for 12 h at room

temperature (20-22 ºC) to reduce the effects of diurnal variations in pigments and

provide comparable conditions, “artificial predawn conditions”, as described in

García-Plazaola et al. (2000) and Tausz et al. (2003). Then, leaf discs (diameter: 3

mm) were collected, frozen in liquid N, and stored at -80 ºC until pigment analysis.

⎟⎠⎞⎜

⎝⎛ −−+

==)(1

595 stre

K nmODy


96

98

Fluorescence measurements were done in dark-adapted leaves after 12 h at room

temperature. Maximal photochemical efficiency of PSII (Fv/Fm) was determined

using a portable modulated fluorimeter (OS 5-FL, Optisciences, Tyngsboro, USA).

Initial (F0) and maximal (Fm) fluorescence were measured with a saturating pulse of

0.8 s. This measurement represents the maximal photochemical efficiency of PSII

after a period of dark recovery and thus it can be considered as proportional to the

degree of “chronic photoinhibition” (Werner et al., 2002). Pigments (chlorophylls

a+b) were extracted in acetone and analysed by reverse phase HPLC following the

method of García-Plazaola and Becerril (1999), with the modifications of García-

Plazaola and Becerril (2001).

For plant metal analysis, shoots and roots were washed thoroughly with

deionized water to remove soil particles. Roots were also washed with 1 mM H-

EDTA (pH 4.5-5.0) at 4 ºC for 30 min to remove metals from the root apoplast

(Jarvis et al., 2001). Subsequently, shoots and roots were oven-dried at 70 ºC for 48

h and their dry weights recorded. Subsamples (0.2 g) of dried plant tissue were

digested with a mixture of HNO3/HClO4 (Zhao et al., 1994) and, subsequently, Cd,

Zn, and Pb in the digest were determined using ICP-AES.


Differences among treatments (i.e., NM-UP, NM-P, M-UP and M-P) were

analyzed by one-way ANOVA (Microsoft Stat View Software, SAS Institute)

followed by Fischer´s PLSD-test to establish the significance of the differences

among means (the results of this Fischer´s PLSD-test are shown in Tables, as letter

superscripts). Data from enzyme activities and Biolog EcoPlatesTM (at 48 h

incubation time) were used to perform principal component analysis (PCA). One-

way ANOVAs and Fischer´s PLSD-tests were applied to PCA data in order to

determine the significance of the differences among treatments.


97

98

5.4 Results

5.4.1 Thlaspi caerulescens growth and physiological parameters

T. caerulescens plants showed significantly (P<0.05) higher values of shoot and

root biomass in metal polluted than in control pots (Table 5.1). Actually, mean

values of plant biomass (g DW pot-1) were 2.2 and 1.9 times higher for shoots and

roots, respectively, in metal polluted than in control pots.

Table 5.1. Shoot and root biomass (g DW pot-1; 3 plants pot-1) of T. caerulescens plants in control non-polluted and metal polluted pots at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.

Shoot

(g DW pot-1) Root

(g DW pot-1)

NM-P 6.09 ± 1.33a 1.35 ± 0.19a

M-P 13.2 ± 1.16b 2.56 ± 0.53b

Nonetheless, fluorescence (Fv/Fm) values for plants growing in both metal

polluted and control pots were normal and identical (i.e., 0.80 ± 0.01), indicating

that plants had an optimal physiological status and showed no symptoms of

phytotoxicity. In turn, at the end of the experiment, chlorophyll a+b values were

higher in metal polluted than in control pots (i.e., 1012.50 ± 2.50 and 708.64 ± 9.12

μmol m-2 for metal polluted and control pots, respectively).

5.4.2 Thlaspi caerulescens metal uptake T. caerulescens plants grown in metal polluted soils showed a shoot metal

concentration of 337 mg of Cd, 5670 mg of Zn and 76.6 mg of Pb per kg of dry

weight tissue (Table 5.2). Cadmium and Zn were efficiently translocated from roots

to shoots, i.e. the translocation factor (TF = shoot metal concentration/root metal

concentration) was 1.6 and 4.1 for Cd and Zn, respectively. On the contrary, most

of the Pb was retained in the roots, as indicated by a TF value of 0.16. Finally, 4.45

mg of Cd, 74.8 mg of Zn, and 1.01 mg of Pb were accumulated in T. caerulescens shoots per pot. The bioconcentration factor (BF = shoot metal concentration/soil

metal concentration) achieved by the T. caerulescens plants was 4.9, 8.4 and 0.2 for

Cd, Zn and Pb, respectively.


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99

Table 5.2. Shoot and root metal concentrations (mg kg-1 DW tissue) of T. caerulescens plants in metal polluted and control pots at the end of the phytoextraction experiment. NM-P: no metal, planted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.

Shoots (mg kg-1 DW tissue)

Roots

(mg kg-1 DW tissue) Cd Zn Pb Cd Zn Pb

NM-P 0.3 ± 0.0a 1550 ± 133a 0.6 ± 0.2a 1.1 ± 0.2a 417 ± 31.8a 4.7 ± 0.9a

M-P 337 ± 54.6b 5670 ± 537b 76.6 ± 8.8b 209 ± 5.4b 1400 ± 132b 479 ± 25.4b

5.4.3 Soil physicochemical parameters

In the presence of metals, significantly lower values of extractable K+ were

observed in both planted and unplanted pots (Table 5.3), as compared to control

non-polluted pots, most likely due to the addition of KNO3 to these control pots

(see Materials and Methods). Planted pots showed significantly higher and lower

values of soil pH and Olsen P, respectively, than unplanted pots in both control and

metal polluted soils (Table 5.3). In metal polluted pots, T. caerulescens growth resulted

in significantly lower values of CEC.

At the end of the experiment, in the metal polluted soils, a 32, 37, and 42 %

reduction in total Cd, Zn and Pb, respectively, was observed in planted pots, as

compared to unplanted ones (Table 5.4). On the contrary, in these metal polluted

soils, the concentration of phytoavailable (CaCl2 extractable) Cd was not

significantly different between planted and unplanted pots (Table 5.4). Instead,

phytoavailable Zn and Pb concentrations were 14 and 27% lower, respectively, in

planted versus unplanted pots.


99

10

1

Tab

le 5

.3. S

oil p

H, o

rgan

ic m

atte

r (O

M) c

onte

nt, t

otal

nitro

gen

(N),

catio

n ex

chan

ge c

apac

ity (C

EC)

, elec

trica

l con

duct

ivity

(EC)

, and

ext

ract

able

phos

phor

us (P

), po

tass

ium

(K+),

calci

um (C

a2+) a

nd m

agne

sium

(Mg2

+) m

easu

red

at th

e en

d of

the

phyt

oext

ract

ion

expe

rimen

t. N

M-U

P: n

o m

etal,

unp

lante

d; N

M-P

: no

met

al,

plan

ted;

M-U

P: m

etal,

unp

lante

d; M

-P: m

etal,

plan

ted.

Valu

es f

ollo

wed

with

diff

eren

t let

ters

are

sig

nific

antly

diff

eren

t (P<

0.05

or

low

er) a

ccor

ding

to F

ische

r´s

PLSD

-test

. Mea

n va

lues

(n =

3) ±

stan

dard

err

ors.

pH

O

M

Tot

al N

C

EC

E

C

P K

+

Ca2

+

Mg2

+

(%)

(%)

(meq

100

ml-1

) (µ

S cm

-1)

(mg

kg-1)

(mg

kg-1)

(mg

kg-1)

(mg

kg-1)

NM

-UP

4.40

± 0

.09a

b 5.

37 ±

0.3

6a

0.26

± 0

.01a

10

.5 ±

0.3

3a

3260

± 1

56a

19.7

± 0

.54a

73

2 ±

15.

3a

1230

± 6

8.4a

14

0 ±

7.3

6ab

NM

-P

4.77

± 0

.05c

5.

31 ±

0.3

6a

0.24

± 0

.00a

9.

92 ±

0.4

0a

2870

± 4

2.2a

b 14

.0 ±

0.9

4b

610

± 4

5.5b

12

20 ±

39.

4a

165

± 6

.84a

M-U

P 4.

30 ±

0.0

5a

5.44

± 0

.17a

0.

26 ±

0.0

1a

9.61

± 0

.08a

28

80 ±

120

ab

18.0

± 0

.47a

13

1 ±

6.4

8c

1200

± 1

3.2a

13

1 ±

4.6

4b

M-P

4.

63 ±

0.0

7bc

5.66

± 0

.15a

0.

25 ±

0.0

0a

8.15

± 0

.31b

25

70 ±

32.

5b

12.0

± 0

.47b

66

.0 ±

4.3

2c

1100

± 4

4.9a

15

4 ±

7.7

9ab

Tab

le 5

.4.

Tota

l (a

qua

regi

a di

gest

ed)

and

phyt

oava

ilabl

e (C

aCl 2

extra

ctab

le) m

etal

conc

entra

tions

(m

g kg

-1 D

W s

oil)

in s

oil

sam

ples

at

the

end

of t

he

phyt

oext

ract

ion

expe

rimen

t. A

t the

beg

inni

ng o

f the

exp

erim

ent,

soils

wer

e ar

tifici

ally

cont

amin

ated

with

a m

ixtu

re o

f met

als c

onta

inin

g 1,

000

mg

Zn

kg-1 D

W so

il,

500

mg

Pb k

g-1 D

W s

oil,

and

100

mg

Cd k

g-1 D

W s

oil.

NM

-UP:

no

met

al, u

nplan

ted;

NM

-P: n

o m

etal,

plan

ted;

M-U

P: m

etal,

unp

lante

d; M

-P: m

etal,

plan

ted.

V

alues

follo

wed

with

diff

eren

t let

ters

are

sign

ifica

ntly

diffe

rent

(P<

0.05

or l

ower

) acc

ordi

ng to

Fisc

her´

s PLS

D-te

st. M

ean

valu

es (n

= 3

) ± st

anda

rd e

rror

s.

T

otal

(m

g kg

-1 D

W so

il)

Ph

ytoa

vaila

ble

(mg

kg-1 D

W so

il)

C

d Zn

Pb

Cd

Zn

Pb

NM

-UP

0.80

± 0

.01a

77

.0 ±

29.

1a

46.8

± 2

5.4a

0.27

± 0

.01a

62

.8 ±

5.4

0a

2.81

± 0

.09a

NM

-P

0.80

± 0

.01a

11

9 ±

14.

6a

25.5

± 3

.27a

0.39

± 0

.07a

44

.2 ±

1.5

1a

2.90

± 0

.10a

M-U

P 10

1 ±

6.4

2b

1060

± 6

3.4b

59

1 ±

18.

6b

77

.6 ±

1.9

3b

572

± 2

4.1b

47

.1 ±

1.0

9b

M-P

68

.3 ±

10.

3c

672

± 1

31c

344

± 5

7.3c

79.9

± 1

.44b

49

5 ±

22.

8c

34.2

± 3

.29c


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5.4.4 Soil enzyme activities

T. caerulescens growth led to significantly higher values of arylsulphatase, and

acid and alkaline phosphatase activities in both metal polluted and control soils

(Table 5.5), and also significantly higher values of β-glucosidase activity in metal

polluted soils (Table 5.5). Table 5.5. Soil enzyme activities at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.

β-Glucosidase Arylsulphatase Acid phosphatase Alkaline phosphatase Urease

(mg ρ-Nitrophenol kg-1 h-1) (mg N-NH4+ kg-1

h-1)

NM-UP 81.0 ± 10.6a 67.3 ± 15.7ab 348 ± 48.0a 167 ± 10.5a 31.0 ± 5.8ab

NM-P 133 ± 12.8ab 120 ± 11.8c 743 ± 81.3b 241 ± 20.2b 45.3 ± 10.8a

M-UP 87.3 ± 3.3a 44.6 ± 1.3a 311 ± 24.9a 182 ± 6.4a 9.6 ± 1.8b

M-P 222 ± 52.2b 96.0 ± 8.2bc 745 ± 30.7b 250 ± 22.6b 25.3 ± 6.6ab

In metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140,

37 and 164% increase in the activity of β-glucosidase, arylsulphatase, acid

phosphatase, alkaline phosphatase and urease, respectively. In control soils, T. caerulescens growth led to a 64, 78, 114, 44 and 46% increase in the activity of β-

glucosidase, arylsulphatase, acid phosphatase, alkaline phosphatase and urease,

respectively.

In order to provide a visual illustration of the overall soil biochemical

functionality, together with an integrated fingerprint of the effect of treatments on

soil functional diversity, a sun ray plot is presented in Figure 1 using the target NM-

P soil as 100% reference. The presence of T. caerulescens plants led to higher values of

all enzyme activities here tested in both metal polluted and control soils (Fig. 5.1).

The shape of the sun-ray plot was different in metal polluted soils, as compared to

control soils, indicating a distinct pattern of soil enzyme activity.


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Figure 5.1. Sun ray plot of soil enzyme activities at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. A value of 100 corresponds to the mean value obtained for each specific enzyme activity in the target NM-P soil.

The application of PCA to enzyme data (data not shown) significantly

(P<0.05) separated M-P from all the other treatments along PC1 (PC1 accounted

for 73% of the variance). Also, along PC1, the PCA significantly separated NM-P

from NM-UP pots. In turn, the PCA significantly separated M-UP pots from

control non-polluted pots along PC2 (but PC2 accounted for only 16% of the

variance). Finally, along PC2, NM-P pots were significantly separated from metal

polluted pots.

5.4.5 Community-level physiological profiles

Figure 5.2 shows the AWCD curves obtained with the Biolog EcoPlatesTM. In

this Figure, it can be observed that, at approximately an incubation time of 48 h, the

highest rate of microbial growth was achieved in the Biolog EcoPlatesTM. In

unplanted pots, the AWCD value at 48 h for metal polluted soils was slightly higher

(the difference was not statistically significant) than that obtained for control soils.


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In planted pots, the AWCD value at 48 h for metal polluted soils was very similar to

that obtained for control soils. T. caerulescens growth resulted in significantly higher

absorbance values, in both metal polluted and control soils, than those observed in

unplanted pots (Fig. 5.2).

Figure 5.2. Average well colour development (AWCD) curves at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) at an incubation time of 48 h according to Fischer´s PLSD-test.

Figure 5.3 shows the metabolic fingerprint of the CLPPs displayed by planted

and unplanted pots at the end of the experiment (only those substrates showing

significant differences among treatments are presented). In relation to the pattern of

individual substrates´ utilization, D-cellobiose, ketobutyric acid, D-malic acid and

glucose-1-phosphate were utilized to a significantly greater extent (P<0.05) by the

culturable portion of the soil microbial community in M-P pots than in all the other

treatments (according to Fisher´s PLSD test).


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Figure 3. Metabolic fingerprints of substrate utilization patterns obtained with the EcoPlatesTM at an incubation time of 48 h [only those substrates showing significant differences (P<0.05) among treatments, according to ANOVA, are presented]. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted.

The kinetic parameters obtained from fitting the “AWCD versus time” curve to

the density-dependent logistic growth equation indicated above are presented in

Table 5.6. In control non-polluted soils, K values were found to be significantly

higher in planted versus unplanted pots. The presence of T. caerulescens led to

significantly lower values of s in metal polluted soils.


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Table 5.6. Kinetic parameters K, r and s obtained from fitting the “AWCD versus time” curve to the density-dependent logistic growth equation. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.

K r s

NM-UP 0.90 ± 0.15a 0.12 ± 0.01a 51.5 ± 1.88ab

NM-P 1.20 ± 0.01b 0.13 ± 0.00a 48.5 ± 0.82a

M-UP 0.99 ± 0.07ab 0.12 ± 0.01a 53.6 ± 1.89b

M-P 1.20 ± 0.01b 0.13 ± 0.00a 48.5 ± 0.67a

The application of PCA to the absorbance data obtained with the Biolog

EcoPlatesTM at 48 h incubation time (Fig. 5.4a) significantly (P<0.05) separated M-P

pots from all the other treatments along PC1 (PC1 accounted for 68% of the

variance). Furthermore, along PC2, NM-P pots were significantly separated from all

the other pots (but PC2 accounted for only 21% of the variance).

The value of the kinetic parameter r provides information on how rapidly a

carbon source can be metabolised by a community once the density has reached the

level at which colour production begins. Therefore, r may be the most useful

parameter for comparing the relative functional responses of different communities

(Preston-Mafham et al., 2002). In consequence, another PCA was carried out using

the values of r (Fig. 5.4b), finding out that NM-UP pots were significantly (P<0.05)

separated from all the other treatments along PC1.


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Figure 5.4. Principal component analysis from (A) absorbance values obtained with the EcoPlatesTM at an incubation time of 48 h and (B) the values of the kinetic parameter r. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. In (A): PC1 and PC2 account for 68 and 21% of the variance, respectively. In (B): PC1 and PC2 account for 48 and 18% of the variance, respectively.


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Finally, Table 5.7 shows the diversity indexes calculated from both soil enzyme

activities and Biolog EcoPlatesTM. At the end of the experiment, it was observed

that the presence of metals had led to significantly lower values of the H’ index

obtained from soil enzyme activities in both planted and unplanted pots (Table 5.7).

Table 5.7. Diversity indexes calculated from EcoPlatesTM absorbance data at 48 h incubation time and from soil enzyme activities. S = richness; H’ = Shannon´s diversity; J’ = Shannon´s evenness. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P<0.05 or lower) according to Fischer´s PLSD-test. Mean values (n = 3) ± standard errors.

S - Biolog H’ - Biolog J’ - Biolog H’ - Enzymes

NM-UP 13.3 ± 1.76a 3.47 ± 0.25a 0.93 ± 0.02a 2.31 ± 0.01a

NM-P 17.3 ± 0.88ab 3.83 ± 0.08a 0.93 ± 0.00a 2.30 ± 0.01a

M-UP 18.3 ± 1.33ab 3.88 ± 0.09a 0.93 ± 0.01a 2.18 ± 0.02b

M-P 27.7 ± 2.33b 4.23 ± 0.14a 0.93 ± 0.00a 2.19 ± 0.02b

5.5 Discussion

5.5.1 Metal phytoextraction

T. caerulescens (Lanestosa ecotype) plants proved a high metal tolerance and

capacity to grow at an optimum rate at elevated soil metal concentrations. Indeed, in

the presence of metals, T. caerulescens plants achieved a considerable biomass and

showed no reduction of photochemical efficiency together with higher values of

photosynthetic pigments than those observed in control soils. Furthermore, they

had a very prolific root system, covering with fine roots the whole area of the pot.

Most importantly, our local ecotype Lanestosa showed a high capacity to

accumulate Zn and Cd, particularly the latter. Actually, the threshold value of 100

mg Cd kg-1 DW shoot indicated by Baker et al. (2000) for Cd hyperaccumulators

was exceeded. For both metals, the shoot-to-root metal concentration ratio was well

over 1 as it is usually the case with hyperaccumulating plants (McGrath and Zhao,

2003). However, for all metals here studied, the bioconcentration factor was <10,

the threshold value considered for a phytoextraction process to be feasible

(McGrath et al., 2006). These results contrast with those previously reported by us


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for this very same ecotype (Hernández-Allica et al. 2006a). In that study, Lanestosa

plants appeared as Zn hyperaccumulators (with a zinc BF of 16.7) but not of Cd.

This disagreement is most likely due to different experimental designs (e.g., a

chronically polluted mine soil versus an artificially polluted, recently spiked grassland

soil) and metal concentrations.

Regarding soil metal concentrations in planted pots, at the end of the

experiment, total metal values had suffered a more pronounced decrease than values

of phytoavailable metal fractions. Although T. caerulescens plants do not seem to

access specific metal pools in the soil (Gerard et al., 2000; Hutchinson et al., 2000;

Schwartz et al., 2003), in our study, due to a considerable metal uptake, the kinetics

of replenishment of the depleted phytoavailable metal pool may have led to

depletion of pools thought to be otherwise poorly available to plants, as previously

suggested (Whiting et al., 2001; Hammer and Keller, 2002). In addition, soil pH

increased in planted pots, thus resulting in lower metal bioavailability. Consequently,

in agreement with other works (Luo et al., 2000; Wang et al., 2006), in our study,

metal hyperaccumulation was not achieved through soil acidification.

5.5.2 Impact of metal pollution on biological indicators of soil health

In this study, metal pollution did not cause a clear inhibition of soil enzyme

activities (i.e., in both planted and unplanted pots, values of enzyme activity were

lower in metal polluted versus control soils only for arylsulphatase and urease; in any

case, the differences were not statistically significant) (Table 5.5). Metals are toxic to

living organisms primarily due to their protein-binding capacity and hence ability to

inhibit enzymes (Dick et al., 1997). But the nature and degree of inhibition of soil

enzymes by metals is strongly related to soil type. Actually, metals have a varying

impact on soil enzyme activity depending not only on their total concentration in

the soil but rather on their capacity to interact with enzyme protein. Therefore, their

impact depends on soil pH, OM levels, and interaction with other soil minerals and

OM (Tate, 2002). Usually, inhibition of enzyme activity in metal polluted soils

reflects the “bioavailability” of the metals, because the mechanisms that protect soil

enzymes from inhibition by metals are likely to be the same mechanisms limiting

metal uptake by plants and soil organisms (Speir and Ross, 2002). As a consequence,


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soil enzyme activities are surrogate measurements of the impact of metals on soil

biota as a whole or of their uptake by, and their toxicity to, plants (Speir and Ross,

2002).

Then, since the impact of metals on soil enzymes is strongly dependent on soil

type, it is not surprising that the sensitivity of specific soil enzymes to metal

pollution varies considerably depending on the study. Kandeler et al. (1996) found

that C-acquiring enzymes (cellulase, xylanase, β-glucosidase) were the least affected

by soil pollution, phosphatase and sulfatase the most affected, and, finally, N-

acquiring enzymes (urease) had an intermediate response. In a study on metal

polluted grassland soil (Kuperman and Carreiro, 1997), β-glucosidase was the most

depressed, while phosphatase and endocellulase activities were the least.

Nonetheless, in general, arylsulphatase appears most sensitive to metal pollution,

while acid phosphatase and urease are less affected (Dick et al., 1997).

Regarding soil functional diversity, contrasting results were obtained with

EcoPlatesTM versus soil enzyme activities (Table 5.7). Indeed, it was observed that the

presence of metals led to significantly lower values of H’ obtained from enzyme

activities and non-significant higher values of S and H’ obtained from EcoPlatesTM.

This is not an unexpected result because EcoPlatesTM reflect the potential of only

the culturable portion of the microbial community to respond to substrates, while

enzyme analyses reflect the status of the whole microbial community. Interestingly,

Burkhardt et al. (1993) reported that in heavy-metal-affected bacterial communities,

relatively rare degradative capabilities, irrespective of their nature, are even rarer

than in unaffected communities, while the reverse is true for more common

capabilities. But although EcoPlatesTM data are not necessarily related to the

functional potential of the most abundant soil bacteria (Smalla et al., 1998), they

provide a useful assessment of biological responses to metal pollution. In turn,

enzymes are one of the more reactive components of the soil ecosystem and

potentially excellent indicators of the soil’s microbial functional status and diversity

(Sowerby et al., 2005). It must be remembered that values of soil enzyme activities

come from laboratory measurements of sieved soil samples under optimal

conditions of temperature, pH, substrate concentration, etc. and then do not


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provide data on actual enzyme activities in the soil, but an assessment of their

maximum potential activity (Vaughan and Malcolm, 1984).

5.5.3 Effect of T. caerulescens growth and metal phytoextraction on biological indicators of soil health

In metal polluted soils, T. caerulescens growth and metal phytoextraction (M-P

pots) led to significantly higher values of β-glucosidase, arylsulphatase, and acid and

alkaline phosphatase than those found in M-UP pots (Table 5.5). Likewise, values of

urease activity were higher (although in this case the differences were not statistically

significant) in M-P than M-UP pots. By contrast, the H’ index obtained from soil

enzyme activities did not differentiate between M-P and M-UP pots, most likely due

to the fact that, in our study, such index only reflects the evenness or distribution of

the enzyme activities. Then, as a consequence of the phytoextraction process (which

involves both T. caerulescens growth and metal phytoextraction), the activity of five

soil enzymes which have a key function in the cycling of C, N, P and S in the soil

increased, as compared to the activity of those same enzymes in the metal polluted

unplanted soil. Since urease, acid and alkaline phosphatase, and arylsulphatase are

involved in the release of bioavailable forms of N, P and S, respectively, then it was

concluded that, as a result of our phytoextraction process, soil fertility, an important

attribute of a healthy soil, was probably improved in our phytoremediated soils.

Interestingly, D-cellobiose, ketobutyric acid, D-malic acid and glucose-1-

phosphate were utilized to a greater extent by the culturable portion of the soil

microbial community in M-P pots than in all the other treatments (Fig. 5.3). In this

respect, in hyperaccumulators, levels of citric, malic, malonic and oxalic acids have

been correlated with elevated concentrations of Ni or Zn in the biomass (Lee et al.,

1978; Tolrá et al., 1996). Nonetheless, T. caerulescens plants appear to have

constitutively high concentrations of malic acid/malate in their tissues (Shen et al.,

1997; Boominathan and Doran, 2003).

As observed in Figures 5.1 and 5.2, the presence of T. caerulescens plants, as

compared to the metal phytoextraction itself, had the major effect on soil biological

parameters. As compared to bare soil, vegetated soils have frequently been reported


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to have higher rates of microbial activity due to the presence of additional surfaces

for microbial colonization and organic compounds released by the plant roots (Tate,

1995; Delorme et al., 2001). In our study, the establishment of a vegetation cover by

the fifth month of growth led to significantly higher values of many of the biological

indicators of soil health here measured, as compared to unvegetated soils. The H’

index obtained from soil enzyme activities did not differentiate between planted and

unplanted pots, again most likely due to its reflecting only the distribution of the

enzyme activities. Gremion et al. (2004) and Wang et al. (2006) also observed that

rhizosphere soil had higher biological activities than non-rhizosphere soil in similar

phytoextraction experiments. In our study, the increase in soil pH found in planted

pots may also partly explain why they had higher biological activities than unplanted

pots, as suggested by Wang et al. (2006).

Finally, since colour development typically follows a sigmoidal trend with time,

Lindstrom et al. (1998) developed a sigmoidal growth model and used the

parameters of the model for statistical analyses. Being independent of incubation

time, kinetic analysis removes the need for a decision on the optimum incubation

time for analysis (Garland, 1996; Verschuere, 1997) and has been suggested to give a

more effective description of the whole-community substrate utilization patterns

(Haack et al., 1995; Garland, 1997). Then, in theory, with the kinetic approach, a

more detailed understanding of the nature of the colour response may be feasible.

However, this concept should be approached with caution given the general lack of

understanding concerning the physiological or ecological basis for differences in the

kinetic parameters and the known selective bias due to growth in the plates (Smalla

et al., 1998). In our study, the PCA carried out using the values of r was not able to

clearly discriminate between treatments (Fig. 5.4b). On the contrary, when a PCA

was applied to the absorbance data obtained with the Biolog EcoPlatesTM, clear

differences between treatments were found. This supports the findings of Garland

et al. (2001) that, despite the potential utility of the kinetic approach for the analysis

of CLPP results, kinetic analysis does not appear to be the best approach for rapid

classification of samples. Our data indicate that the utilization of single point plate

readings at a set point in the AWCD curve is a better tool for classification.


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5. 6 Conclusions

T. caerulescens (Lanestosa ecotype) plants proved a high metal tolerance and

capacity to grow at an optimum rate at elevated soil metal concentrations. Most

importantly, our ecotype Lanestosa showed a high capacity to accumulate Zn and

Cd, particularly the latter.

In our study, metal pollution did not cause a clear inhibition of soil enzyme

activities. Contrasting results were obtained with EcoPlatesTM versus soil enzyme

activities. Actually, the presence of metals led to significantly lower values of H’

obtained from enzyme activities and non-significant higher values of S and H’

obtained from EcoPlatesTM. Interestingly, D-cellobiose, ketobutyric acid, D-malic

acid and glucose-1-phosphate were utilized to a greater extent by the culturable

portion of the soil microbial community in M-P pots than in all the other

treatments.

As a consequence of the phytoextraction process (which involves both T. caerulescens growth and metal phytoextraction), the activity of five soil enzymes which

have a key function in the cycling of C, N, P and S in the soil increased. In any

event, the presence of T. caerulescens plants, as compared to the metal

phytoextraction itself, had the major effect on soil biological parameters. Actually, in

metal polluted soils, the presence of T. caerulescens led to a 154, 115, 140, 37 and

164% increase in the activity of β-glucosidase, arylsulphatase, acid phosphatase,

alkaline phosphatase and urease, respectively. In control soils, T. caerulescens growth

led to a 64, 78, 114, 44 and 46% increase in the activity of β-glucosidase,

arylsulphatase, acid phosphatase, alkaline phosphatase and urease, respectively.

Biological indicators of soil health, such as soil enzymes and community level

physiological profiles, are valid tools to evaluate the success of a continuous metal

phytoextraction process.

6. impact of metal pollution and Thlaspi caerulescens phytoextraction on soil microbial communities

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6. IMPACT OF METAL POLLUTION AND Thlaspi caerulescens PHYTOEXTRACTION ON SOIL MICROBIAL COMMUNITIES

Epelde et al., in preparation for publication

6.1 Abstract

Metal phytoextraction using hyperaccumulating plants has great potential for

the remediation of metal polluted soils. When assessing the success of a

phytoextraction process, emphasis must be placed on the recovery of soil health. In

this respect, soil microbial parameters can be used as valuable bioindicators of the

effects of pollutants on soil health. Consequently, a short-term microcosm

experiment was carried out to study the impact of Zn and/or Cd pollution and T. caerulescens phytoextraction on soil health through the determination of soil microbial

properties: basal respiration; substrate-induced respiration (SIR); respiration

quotient (QR); structural genetic diversity of soil bacteria with PCR-DGGE; gene

abundance from real-time PCR for total bacteria, ammonia-oxidizing bacteria and

chitin-degrading bacteria; and Geochip functional gene array. T. caerulescens confirmed its great potential for Zn and Cd phytoextraction: shoots accumulated up

to 8,211 and 1,763 mg kg-1 DW of Zn and Cd, respectively (besides, plants showed

most promising bioconcentration factors: up to 17.4 for Zn and 8.0 for Cd). Zn

pollution led to decreased levels of both basal respiration and SIR. T. caerulescens growth and metal phytoextraction increased the values of these two parameters. In

soils polluted with 1,000 mg Zn kg-1 and 250 mg Cd kg-1 DW, both metals had a

clear effect on structural genetic diversity of soil bacteria. Functional diversity

(number of genes detected) and redundancy, regardless of gene category, increased

as a result of metal pollution. The abundance of Zn and/or Cd resistance genes

detected was higher in T. caerulescens planted versus unplanted soils, even in the

absence of metals.


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6.2 Introduction

Soil metal pollution is an environmental problem of worldwide concern. Due

to their immutable nature and toxicity, heavy metals persist in the soil environment

for very long periods of time and adversely affect the growth and survival of

(micro)organisms, with concomitant negative effects on soil fertility and functioning

(Epelde et al., 2009a).

Phytoremediation, the use of green plants to remove pollutants from the

environment or to render them harmless (Cunningham and Berti, 1993), has great

potential for the remediation of polluted soils. Within the phytoremediation field,

the term “phytoextraction” refers to the utilization of plants to transport and

concentrate pollutants, mainly metals, from the soil into the above-ground shoots

(Salt et al., 1995). Thlaspi caerulescens, a hyperaccumulating plant extensively studied

due to its remarkable capacity to phytoextract zinc (Zn) and cadmium (Cd) from

polluted soils (Hernández-Allica et al., 2006a, b; Epelde et al., 2008a), has been

suggested as a model species for research on metal phytoextraction (Assunção et al.,

2003).

Traditionally, when evaluating the success of a phytoextraction process,

emphasis has mostly been placed on metal removal from soil. However, most

importantly, the ultimate goal of any phytoextraction process must be not only to

remove the metal(s) from the soil but to restore soil health (i.e., the soil´s continued

capacity to sustain plant growth and maintain its functions) (Coleman et al., 1998).

Soil microbial properties, particularly those reflecting the biomass, activity and

diversity of the soil microbial communities, have great potential as bioindicators of

the effects of disturbances (e.g., metal pollution) on soil health. Likewise, DNA

microarray technologies are rapidly becoming important tools for the analysis of

complex microbial communities inhabiting various environments (Wilson et al.,

2002; Zhou, 2003). A recently developed functional gene array, termed GeoChip

(He et al., 2007), appears most promising for the assessment of the impact of

pollutants on soil health (as well as for the assessment of the efficiency of

remediation methods) since it contains probes from genes with known biological

functions (e.g., nitrogen, carbon, sulfur and phosphorus cycling; metal reduction and

resistance; degradation of organic contaminants) and has been reported as a high-


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throughput, powerful genomic technology for research on biogeochemical,

ecological and environmental processes (Rhee et al., 2004; Li et al., 2005; He et al.,

2007; Yergeau et al., 2007b; Wu et al., 2008; Zhou et al., 2008).

The main objective of the current work was to determine the impact of metal

(Cd and Zn) pollution and T. caerulescens phytoextraction on soil health through the

determination of a variety of soil microbial properties with potential as bioindicators

of soil functioning (i.e., soil respiration; substrate-induced respiration; microbial

respiration quotient; structural genetic diversity of soil bacteria with PCR-DGGE;

gene copy abundance from real-time PCR for total bacteria, ammonia-oxidizing

bacteria and chitin-degrading bacteria; and Geochip functional gene array). The

capacity of T. caerulescens to phytoextract Zn and Cd from polluted soil was also

studied.


6.3.1 Experimental design

A short-term (4 months) microcosm phytoextraction experiment was carried

out with soil collected from the top layer (0-30 cm) of a natural grassland located in

Derio (Basque Country, northern Spain). Immediately after collection, the soil was

sieved to <4 mm, air-dried at 30 ºC for 48 h, and subjected to physicochemical

characterization according to standard methods (MAPA, 1994). The soil was a clay

loam, with a pH of 5.2, an organic matter (OM) content of 4.12%, a total nitrogen

(N) content of 0.23%, a C/N ratio of 10.4, a phosphorus (P) content of 26.4 mg kg-

1, and an electrical conductivity of 0.08 dS m-1. Subsequently, the soil was artificially

polluted with combinations of different concentrations of Zn (250, 500 and 1,000

mg kg-1 DW) as ZnCl2 and Cd (0, 50, 250 mg kg-1 DW) as CdCl2. Thus, the

following 9 combinations were studied (in mg kg-1 DW): (1) 250 Zn + 0 Cd

(control-unpolluted; a small concentration of Zn was added to support T. caerulescens growth); (2) 250 Zn + 50 Cd; (3) 250 Zn + 250 Cd; (4) 500 Zn + 0 Cd; (5) 500 Zn

+ 50 Cd; (6) 500 Zn + 250 Cd; (7) 1,000 Zn + 0 Cd; (8) 1,000 Zn + 50 Cd; and (9)

1,000 Zn + 250 Cd. Then, metal polluted soils were stored at a constant room

temperature and 15% relative humidity for 6 months. Study pots (17 cm diameter x


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13 cm height) were filled with 1.5 kg (DW) of each of these polluted soils, which

were then fertilized with 120 mg kg-1 of N, P, and K+, and subsequently allowed to

precondition, under the greenhouse conditions described below, for one week.

On the other hand, T. caerulescens J. & C. Presl. seeds of a local ecotype, named

Lanestosa, were germinated for two weeks (on a mixture of perlite and vermiculite,

2:3 v/v, moistened with deionized water) in a growth chamber under the following

controlled conditions: 20/16 ºC day/night temperature, 70% relative humidity, and

a photosynthetic photon flux density of 300 µmol photon m-2 s-1 by supplementing

natural illumination with white cold lamps. Then, half of the study pots were

planted with five of these T. caerulescens seedlings per pot while the other half were

kept unplanted as controls. Then, 18 treatments were studied (in quadruplicate) in

this experiment: 9 metal combinations (see above) for planted pots and 9 metal

combinations for unplanted pots. Plants were then allowed to grow for 4 months in

a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Basque

Country) at a latitude of 43º 17’ N, a longitude of 2º 52’ W, and an altitude of 65 m

above sea-level. The climate in this region is Atlantic temperate. Minimal

temperature set points controlling air-heating were 14/18 ºC night/day, and

maximal temperature set points were 18/20 ºC night/day. Vent opening

temperatures were 20/25 ºC night/day. During the experiment, average temperature

was 15/24 ºC night/day, average relative humidity 60%, and average

photosynthetically active radiation 459 µmol photon m-2 s-1.

After these 4 months, shoot and roots were harvested by cutting the shoots

exactly at the swelling formed in the root to shoot junction. Then, plant

physiological parameters and shoot and root metal contents were determined (see

below). Half of the soil present in the study pots was sampled and soil

physicochemical and microbial properties determined (see below). The remaining

half was used to grow alfalfa (Medicago sativa L.) in order to assess the capacity of

that phytoremediated soil to support plant growth at the end of the phytoextraction

experiment: 1 g (approximately, 100 seeds) of alfalfa seeds was sown in each study

pot. Alfalfa plants were then allowed to grow under the same greenhouse conditions

described above for two months (plants were bottom watered periodically as


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needed). Finally, shoots were harvested (as above), washed thoroughly with

deionized water, oven-dried at 70 ºC for 48 h and their dry weights recorded.

6.3.2 Soil metal concentrations

Soil was sampled at the end of the phytoextraction experiment, i.e. 4 months

after T. caerulescens plant transplant. For soil physicochemical analysis, soils were air-

dried at 30 ºC, sieved to <2 mm, and stored at 4 ºC until analysis. Soil pH, OM

content, total N, nitrates content, extractable P and potassium (K+) were measured

following standard methods (MAPA, 1994).

Total concentrations of heavy metals in soil were determined using flame

atomic absorption spectrometry (AAS, Varian) following digestion with a mixture of

HNO3/HClO4 (Zhao et al., 1994). Likewise, the CaCl2-extractable (0.01 M CaCl2)

fraction of metals was determined according to Houba et al. (2000) and analyzed by

AAS.

6.3.3 Soil microbial parameters

For analysis of microbial parameters, soils were sieved to <2 mm and stored

fresh at 4 ºC until analysis. Soil basal respiration was determined according to ISO

16072 Norm at 30 ºC and a water holding capacity (WHC) of 60%. Substrate-

induced respiration (SIR) was determined, with glucose as substrate, following ISO

17155 Norm. Microbial respiration quotient (QR) was calculated as the ratio

between values of soil basal respiration and SIR.

Soil samples for DNA analysis were sieved to < 2 mm and stored fresh at -20

ºC. DNA was extracted from soil samples (0.25 g soil) using Power SoilTM DNA

Isolation Kit (MO BIO Laboratories, California, USA) according to the

manufacturer’s specifications. Prior to DNA extraction, soil samples were washed

twice in 120 mM K2HPO4 (pH 8.0) to wash away extracellular DNA from soil

without loss of intact cells (Kowalchuk et al., 1997). In this way, most of the

extracted DNA comes from live bacterial cells (nonetheless, a small fraction of the

extracted DNA might be associated with unlysed dead cells or extracellular DNA

not completely washed from the soil samples) (Kowalchuk et al., 1997).


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For real-time PCR measurements of gene copy abundance, the primers and

amplification regimes used to assess (i) 16S rRNA gene fragments for total bacteria,

(ii) ammonia monooxygenase gene (amoA) for ammonia-oxidizing bacteria and (iii)

group A bacterial chitinases for chitin-degrading bacteria are summarized in Table

6.1. Each 25 μl reaction contained 5 μl of template, 12.5 μl of ABsolute QPCR

SYBR green 2x reaction mix (AbGene, Epsom, UK), 2.5 μl of each primer at a

concentration of 10 μM (0.25 μl at 30 μM in the case of total bacteria), 2.5 μl bovine

serum albumin (BSA; 40 mg ml-1), and 4.5 μl of water in the case of total bacteria.

Known template standards were made from whole genomes extracted from pure

bacterial isolates as described in Yergeau et al. (2007a). All mixes were made using a

CAS-1200 pipetting robot (Corbett Research, Sydney, Australia) to reduce variation

caused by pipetting errors. PCR conditions were as follows: 95 ºC for 15 min; 94 ºC

for 60 s (30 s in the case of total bacteria); specified annealing (Table 1); 72 ºC for

60 s; optional reading (Table 1; 40 cycles); and melt curve from 55 ºC (65 ºC in the

case of total bacteria) to 98 ºC. PCR amplification and product quantification were

performed using the Rotor-Gene 3000 (Corbett Research). Gene copies were

quantified against the standard curve using ROTOR-GENE 6 software (Corbett

Research, Sydney, Australia).

Table 6.1: Primers and amplification regimes used in the real-time PCR.

Primer 1 Primer 2 Annealing Reading Reference Total bacteria Ba519F Ba907R 52 ºC/30 s - (Lueders et al.,

2004a,b)

AmoA AmoA-1F AmoA-2R-TC 52 ºC/60 s 81 ºC/15 s (Nicolaisen and Ramsing, 2002)

Chitinase group A GA1F GA1R 63 ºC/30 s - (Williamson et al.,

2000)

DGGE (denaturing gradient gel electrophoresis) and Geochip analysis were

done only with four of the studied soils (those representing the most extreme cases):

250 Zn + 0 Cd planted; 250 Zn + 0 Cd unplanted; 1,000 Zn + 250 Cd planted;

1,000 Zn + 250 Cd unplanted. For DGGE, bacterial 16S rRNA was amplified by

using the primer pair F968-GC/R1378 (Heuer et al., 1997). PCRs were carried out

in 25 μl volumes containing 2.5 μl of 10x PCR buffer, 0.5 μl of each primer (30

μM), 2.5 μl of dNTPs mix (2 mM), and 3.5 U μl-1 of Expand high fidelity

polymerase (Roche, Mannheim, Germany). Amplifications were carried out on a


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PTC-200 thermal cycler (MJ-Research, Waltham, MA). PCR conditions were as

follows: initial denaturation at 94 ºC for 2 min; 92 ºC for 30 s; 55 ºC for 1 min; 68

ºC for 45 sec (+1 sec cycle-1; 35 cycles) and extension at 68 ºC for 5 min. A D-Code

Universal Mutation Detection System (Bio-Rad, Hercules, CA) was used. The

denaturating gradient was from 45 to 65% of the denaturant (100% denaturant is

defined as 7 M urea and 40%, v/v, formamide). DGGE was performed using 20 µl

of the PCR product in 0.5x TAE buffer at 60 ºC (1x TAE = 40 mM tri-acetate, 20

mM sodium acetate, 1 mM EDTA, pH 8.0). Gradient gels were topped with 10 ml

of acrylamide containing no denaturant. Electrophoresis was performed at 200 V

for 15 min followed by 70 V for an additional 16 h. Electrophoresis gels were

stained with ethidium bromide and digital images captured using an ImaGo

apparatus (Gentaur, Brussels, Belgium) upon UV transillumination. Banding

patterns were analyzed using the Imagemaster elite program (version 4.20)

(Amersham Bioscience, Rosendaal, The Netherlands). The resulting binary

(presence-absence) matrices were used to calculate Jaccard similarity indexes (CJ =

a/a+b+c; where a, the total number of bands present in both treatments; b, the

number of bands present only in the first treatment; and c, the number of bands

present only in the second treatment) among treatments.

Before GeoChip analysis (see below), a desalting protocol was applied to the

DNA in order to remove contaminants and improve 260/230 ratios. The sample

was precipitated with 2.5x volume of 100% ice cold ethanol and 1:10 volume of

NaOAc (3 M, pH 5.2). After 3 hours of incubation, the DNA was centrifuged

(13,000 x g, 30 min) and the pellet washed with 70% ethanol. Samples were then

centrifuged (13,000 x g, 10 min), decanted, dried at room temperature, and finally

resuspended in 0.1 ml of nuclease-free water.

The rest of the protocol for the Geochip analysis is a modification of the one

described by Yergeau et al. (2007b). As the amount of DNA was small (prior to

Geochip analysis, the amount of DNA in our samples was determined on a ND-

1000 spectrophotometer; data not shown), rolling circle amplification was carried

using the TempliPhi kit (Amersham, Piscataway, NJ) according to the

manufacturer’s specifications. Spermidine (0.1 μg μL-1) and single-stranded DNA

binding protein (~260 ηg μl-1) were added to the reaction mix to facilitate


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amplification. The reactions were incubated at 30 ºC for 6 h and the enzyme was

then inactivated by incubation at 65 ºC for 10 min.

For Geochip analysis, these rolling circle amplification products were used for

DNA labeling with Cystidine-5 (Cy-5) dye: amplification products were denatured

for 5 min at 100 ºC in a solution containing 1x random octamer mix (Invitrogen,

Carlsbad, CA) and immediately chilled on ice. Following denaturation, the following

components were added: 5 mM dATP, dGTP and dCTP, 2.5 mM dTTP, 25 ηM Cy-

5 dye and 80 U of the large Klenow fragment (large fragment of DNA polymerase I;

Invitrogen). Reaction mixtures were then incubated at 37 ºC for 6 h. Labeled target

DNA was purified with a QIAquick PCR kit (Qiagen, Valencia, CA) according to

the manufacturer´s instructions, measured on a ND-1000 spectrophotometer, and

dried in a speed-vac at 45ºC for 45 min. Prior to hybridization, dried labeled DNA

was re-suspended in a solution containing 50% formamide, 3x SSC, 0.3% SDS, 0.7

μg μL-1 herring sperm DNA and 0.8 ηM dithiothreitol (DTT). This solution was

incubated at 98 ºC for 3 min and kept at 65 ºC until hybridization. Hybridizations

were performed using a HS4800 Hybridization Station (TECAN US, Durham, NC)

at 42 ºC for 10 h.

Microarrays were scanned using a ProScanArray microarray scanner (Perkin

Elmer, Boston, MA). The emitted fluorescent signal was detected by a

photomultiplier tube (PMT) at 633 ηm using a laser power of 95% and a PMT gain

of 64%. Images were then transferred to ImaGene 6.0 (BioDiscovery, El Segundo,

CA) where a grid of individual circles defining the location of each DNA spot on

the array was superimposed on the image, in order to designate each fluorescent

spot to be quantified. Hybridization spots with a signal-noise ratio SNR < 2 (He and

Zhou, 2008) were removed for further analysis. Normalization among slides was

done based on all spots mean signals (Wu et al., 2008). Replicate outliers (>2

standard deviation) were removed, and gene detection considered positive when a

positive hybridization signal was obtained from 33% of spots targeting the gene of

all replicates.


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T. caerulescens plants were harvested at the end of the experiment, i.e. 4 months

after transplant. Fluorescence measurements were done in dark-adapted leaves after

12 h at room temperature to reduce the effects of diurnal variations in pigments and

provide comparable conditions, “artificial predawn conditions”, as described in

García-Plazaola et al. (2000) and Tausz et al. (2003). Maximal photochemical

efficiency of PSII (Fv/Fm) was determined using a portable modulated fluorimeter

(OS 5-FL, Optisciences, Tyngsboro, USA). Initial (F0) and maximal (Fm)

fluorescence were measured with a saturating pulse of 0.8 s. This measurement

represents the maximal photochemical efficiency of PSII after a period of dark

recovery and thus it can be considered as proportional to the degree of “chronic

photoinhibition” (Werner et al., 2002). Then, approximately 0.02 g FW leaf was

collected, frozen in liquid nitrogen and stored at -80º C until biochemical analysis.

Lipophilic antioxidants (carotenoids and tocopherols) and photosynthetic pigments

[a and b chlorophylls (Chl), carotenoids (Carot), violaxanthin (V), antheraxanthin

(A), zeaxanthin (Z), γ- and α-tocopherols (Toc)] were extracted and measured by

reverse-phase HPLC following the method of García-Plazaola and Becerril (1999),

with the modifications described in García-Plazaola and Becerril (2001). Shoots and

roots were then harvested separately and their fresh weights (FW) recorded.

For metal analysis, shoots and roots were washed thoroughly with deionized

water to remove soil particles. For metal desorption, roots were also washed with

1% HNO3. Subsequently, shoots and roots were oven-dried at 70 ºC for 48 h and

their dry weights recorded. Subsamples of dried plant tissue were digested with a

mixture of HNO3/HClO4 (Zhao et al., 1994) and, subsequently, Zn and Cd in the

digest were determined using AAS.


Significant differences (P<0.05) between treatments were analyzed by two-way

ANOVAs using Microsoft Stat View software (SAS Institute). Tukey Kramer-test

was used to establish the significance (P<0.05) of the differences among means for:

(i) treatments grouped according to their soil Zn (250 versus 500 versus 1,000) or Cd

(0 versus 50 versus 250) concentration (when, according to two-way ANOVA, no


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interaction was found between soil Zn and Cd); and (ii) all 9 metal combinations,

(when, according to two-way ANOVA, an interaction was found between soil Zn

and Cd). Relationships between soil microbial and physicochemical parameters were

explored by means of principal component analysis (PCA) applied on the

correlation matrix of these variables. In this way, PCA not only revealed the

multivariate relationships between data, but was also used as a dimension reduction

technique.

To choose between linear and unimodal models of response in DGGE binary

matrices and Geochip data, a detrended correspondence analysis (DCA) was

applied: the length of the first and the remaining axes of this DCA were short (λ <

2.5 SD), what evidenced a short beta diversity in our data along ordination axes;

therefore, a linear response model was selected. Then, a redundancy analysis (RDA)

was applied to explain DGGE and GeoChip data as a function of linear

combinations of two variables: T. caerulescens shoot biomass and soil metal

concentration (ter Braak, 1994). To explore the individual and shared effects of

shoot biomass versus soil metal concentration to the revealed patterns in DGGE and

GeoChip data, variation partitioning procedures were employed (Leps and Šmilauer,

2003). RDAs were also performed to identify the physicochemical and microbial soil

parameters with the most significant influence on DGGE and Geochip data. All

multivariate analyses were done by running Canoco for Windows 4.5 (ter Braak and

Šmilauer 2002). Pearson’s correlations were calculated between real-time PCR and

Geochip results using SPSS Programme (SPSS).

6.4 Results

6.4.1 Plant physiological parameters and metal concentrations Table 6.2 shows the values of shoot biomass achieved by T. caerulescens plants

at the end of the phytoextraction experiment. A two-way ANOVA indicated a

significant interaction between both soil metals (Cd, Zn) for shoot biomass values.

Values of shoot biomass were significantly higher in treatment 250-250 than in

treatments 250-0, 500-250 and 1,000-50 (Table 6.2).

Regarding plant physiological parameters, a significant interaction was found

between both soil metals for values of all physiological parameters determined here.


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No significant differences were observed between treatments (data not shown). The

following values (mean ± SE) were found: 0.78 ± 0.00 Fv/Fm; 402 ± 10 μmol Chl

(a+b) m2; 329 ± 2 mmol Carot mol-1 Chl (a+b); 51 ± 1 mmol VAZ mol-1 Chl (a+b); 119 ± 8 mmol A+Z mol-1 VAZ; and 109 ± 7 mmol Toc mol-1 Chl (a+b).

Concerning shoot and root metal concentrations, no interaction was found

between both soil metals for values of (i) Zn root concentration and (ii) Cd shoot

and root concentrations: in these three cases, increasing soil metal concentrations

led to significantly higher values of their respective metal tissue concentrations

(Figure 6.1). However, according to two-way ANOVA, there was a significant

interaction between both soil metals for values of shoot Zn concentration. In soils

polluted with 250 and 500 mg Zn kg-1 DW, shoot Zn concentration was

significantly highest in the presence of 250 mg Cd kg-1 DW (Figure 6.1). Highest

values of shoot Zn and Cd concentration were obtained in treatment 500-250 (i.e., 8,211 and 1,763 mg kg-1 DW shoot for Zn and Cd, respectively). Finally, metal

concentrations were much higher in shoots than in roots (Figure 6.1).


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Figure 6.1: Shoot and root metal concentrations in T. caerulescens plants, subjected to different Zn (first value) and Cd (second value) soil concentrations (mg kg-1 DW), at the end of the

phytoextraction experiment. Bars with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil metals). Mean values (n = 4) ± standard errors.

Regarding translocation factors (TF = shoot metal concentration/root metal

concentration) (Table 6.2), a significant interaction was observed between both soil

metals. Highest TF values for Zn were found in treatment 250-250 (TF = 11.1). By

contrast, highest TF values for Cd were found in treatment 1,000-250 (TF = 3.8).

As far as total amount of metal phytoextracted from soil is concerned (shoot

biomass x shoot metal concentration) (Table 6.2), a significant interaction was

found between both soil metals for values of phytoextracted Zn and Cd. Highest

values of Zn phytoextracted from soil were observed in treatment 1,000-250 (43.4

mg). Highest values of Cd phytoextracted from soil were found in treatment 250-


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250 (10.6 mg). This treatment 250-250 achieved highest values of T. caerulescens shoot biomass.

Table 6.2: Shoot biomass (g DW tissue), translocation factors (TF), amount of metal

phytoextracted from soil (μg), and bioconcentration factors (BF) in T. caerulescens plants, subjected to different Zn (first value) and Cd (second value) soil concentrations (mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different

(P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 4) ± standard errors.

TF Metal phytoextracted BF

Shoot biomass Zn Cd Zn Cd Zn Cd

250-0 3.61 ± 0.21a 4.2 ± 0.3a - 9310 ± 705a 4 ± 0a 8.4 ± 0.6abc -

250-50 5.59 ± 0.42ab 5.1 ± 1.0abc 0.9 ± 0.1a 16204 ± 2610ab 1236 ± 148a 9.8 ± 0.9ab 5.5 ± 0.4a

250-250 7.62 ± 0.88b 11.1 ± 0.6d 1.6 ± 0.1ab 38972 ± 5774cd 10572 ± 1456b 17.4 ± 0.8d 8.0 ± 0.4a

500-0 5.89 ± 0.95ab 3.5 ± 0.2a - 18281 ± 2964ab 13 ± 3a 6 ± 0.5ac -

500-50 5.69 ± 0.54ab 7.4 ± 0.9bc 2.4 ± 0.2ab 27011 ± 2895bcd 1610 ± 114ac 10.1 ± 1.1b 7.2 ± 0.3a

500-250 3.63 ± 0.23a 7.9 ± 0.4b 1.9 ± 0.2ab 28030 ± 2531bcd 4935 ± 734cd 15.2 ± 0.7d 7.1 ± 0.8a

1,000-0 4.83 ± 0.28ab 3.5 ± 0.2a - 25903 ± 1031abc 6 ± 1a 5.4 ± 0.3c -

1,000-50 4.57 ± 0.18a 4.9 ± 0.5abc 1.3 ± 0.1ab 31777 ± 3422bcd 1368 ± 109ac 7.8 ± 0.8abc 7.5 ± 0.6a

1,000-250 6.35 ± 0.48ab 4.5 ± 0.6ac 3.8 ± 1.3b 43387 ± 3197d 8560 ± 1133bd 8.3 ± 0.2abc 8.0 ± 0.9a

CaCl2-extractable metal concentrations in soil are shown in Table 6.3. A

significant interaction between both soil metals was observed for values of CaCl2-

extractable Zn and Cd soil concentration. CaCl2-extractable Zn concentrations

tended to decrease in treatment 1000-250, as compared to treatments 1000-0 and

1000-50 (Table 6.3). Instead, CaCl2-extractable Cd concentrations were significantly

higher in the presence of 500 or 1,000 mg Zn kg-1 DW soil (in planted pots, only

with 500 mg Zn kg-1 DW soil). In many treatments, planted soils showed

significantly lower values of CaCl2-extractable metal concentrations than

corresponding unplanted soils (Table 6.3): a 18 and 24% reduction (planted versus unplanted) in CaCl2-extractable Cd was observed in the presence of 50 and 250 mg

Cd kg-1 DW soil, respectively; a 9, 22 and 17% reduction (planted versus unplanted)

in CaCl2-extractable Zn was observed in the presence of 250, 500 and 1,000 mg Zn

kg-1 DW soil, respectively. A reduction, though less pronounced, between planted


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and unplanted pots was also observed regarding total soil metal concentrations at

the end of the phytoextraction experiment (data not shown): a 3 and 18% reduction

(planted versus unplanted) in total Cd was observed in the presence of 50 and 250

mg Cd kg-1 DW soil, respectively; a 4, 9 and 14% reduction (planted versus unplanted) in total Zn was observed in the presence of 250, 500 and 1,000 mg Zn

kg-1 DW soil, respectively.

Table 6.3: CaCl2-extractable metal (Zn and Cd) concentrations in soils polluted with different Zn (first value) and Cd (second value) concentrations (mg kg-1 DW) at the end of the phytoextraction

experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (lower case letters: among unplanted treatments; upper case letters: among planted treatments). Asterisks represent significant differences (P<0.05 or lower) between

planted and unplanted soils. Mean values (n = 4) ± standard errors.

Zn Cd

(mg kg-1 DW soil)

250-0 116 ± 2a* 0 ± 0a

250-50 111 ± 2a* 19 ± 0ab*

250-250 99 ± 4a* 77 ± 3c*

500-0 201 ± 1b* 0 ± 0a*

500-50 212 ± 8b* 20 ± 0b*

500-250 189 ± 1b 106 ± 1d

1,000-0 395 ± 3c 1 ± 0a*

1,000-50 405 ± 9c* 22 ± 0b*

Unp

lant

ed

1,000-250 353 ± 17d* 122 ± 10d*

250-0 95 ± 2AB 0 ± 0A

250-50 79 ± 2A 16 ± 0B

250-250 79 ± 3A 61 ± 1C

500-0 167 ± 3BC 0 ± 0A

500-50 162 ± 4ABC 17 ± 0B

500-250 224 ± 43C 96 ± 5D

1,000-0 390 ± 11D 0 ± 0A

1,000-50 329 ± 10D 17 ± 1B

Plan

ted

1,000-250 232 ± 10C 76 ± 6C


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With regard to bioconcentration factors (BF = shoot metal concentration/soil

metal concentration) (Table 6.2), there was a significant interaction between both

soil metals for BF values of Zn and Cd. BF values for Zn tended to decrease with

increasing soil Zn concentrations and decreasing soil Cd concentrations (Table 6.2).

Highest BF values for Zn were found in treatment 250-250 (BF = 17.4). No

significant differences between treatments were found concerning BF values for Cd

(Table 6.2).

6.4.2 Soil physicochemical and microbial parameters

Table 6.4 shows the values of soil basal respiration, SIR and QR at the end of

the phytoextraction experiment. For both planted and unplanted pots, a two-way

ANOVA indicated a significant interaction between both soil metals for values of

basal respiration, SIR and QR, except for basal respiration in unplanted pots. In

these unplanted pots, basal respiration decreased significantly with increasing soil

Zn concentrations (mean values ± SE were: 1.26 ± 0.05, 0.90 ± 0.01 and 0.50 ±

0.03 μg C g-1 h-1 for soils with 250, 500 and 1,000 mg Zn kg-1 DW, respectively),

while soil Cd concentrations did not have any effect on such parameter. In planted

pots, in general, values of basal respiration tended to decrease with increasing soil

metal concentrations. Values of basal respiration were, in general, higher in planted

than unplanted soils.

In unplanted pots, treatments 250-50 and 250-250 showed highest values of

SIR (Table 6.4). On the contrary, in planted pots, no significant differences were

found between treatments regarding SIR. Values of SIR were always higher in

planted than unplanted soils, though differences were rarely statistically significant.

In respect to QR (Table 6.4), highest values were found in unplanted pots

under treatment 250-0 (lowest values were found in unplanted pots under

treatments 1,000-0 and 1,000-250). In planted pots, values of QR were significantly

highest under treatment 250-0.


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Table 6.4: Soil basal respiration, substrate-induced respiration (SIR) and microbial respiration quotient (QR) in soils polluted with different Zn (first value) and Cd (second value) concentrations (mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil

metals). Lower case letters: among unplanted treatments; upper case letters: among planted treatments. Asterisks represent significant differences (P<0.05 or lower) between planted and

unplanted soils. Mean values (n = 4) ± standard errors.

Basal respiration SIR QR (μg C g-1 DW soil h-1)

250-0 1.33 ± 0.07 3.38 ± 0.31a 0.41 ± 0.06a

250-50 1.19 ± 0.08 6.78 ± 0.17b* 0.18 ± 0.01bc

250-250 1.27 ± 0.11 6.03 ± 0.32bc* 0.21 ± 0.01bc*

500-0 0.88 ± 0.03 2.96 ± 0.49a 0.34 ± 0.07ab

500-50 0.87 ± 0.01* 3.78 ± 0.68ac 0.26 ± 0.05abc

500-250 0.95 ± 0.01 4.93 ± 0.26abc 0.19 ± 0.01bc

1,000-0 0.55 ± 0.07* 4.79 ± 0.08abc 0.12 ± 0.01c

1,000-50 0.55 ± 0.04* 4.32 ± 0.76ac 0.14 ± 0.02bc

Unp

lant

ed

1,000-250 0.40 ± 0.02* 3.75 ± 0.39ac* 0.11 ± 0.02c

250-0 1.51 ± 0.08A 4.18 ± 0.44A 0.39 ± 0.07A

250-50 1.21 ± 0.03B 8.46 ± 0.47A 0.15 ± 0.01B

250-250 0.97 ± 0.01CD 8.08 ± 0.08A 0.12 ± 0.00B

500-0 0.95 ± 0.02CD 6.85 ± 1.40A 0.16 ± 0.03B

500-50 1.23 ± 0.03B 6.55 ± 1.22A 0.21 ± 0.03B

500-250 0.81 ± 0.06DE 5.94 ± 0.67A 0.14 ± 0.02B

1,000-0 1.06 ± 0.03BC 5.92 ± 0.68A 0.19 ± 0.03B

1,000-50 0.85 ± 0.02CE 5.47 ± 0.17A 0.16 ± 0.01B

Plan

ted

1,000-250 0.69 ± 0.05E 7.62 ± 0.92A 0.10 ± 0.01B

With regard to gene copy quantification from real-time PCR (Table 6.5), a

significant interaction was observed between both soil metals in unplanted pots. In

unplanted pots, abundance of total bacteria gene fragments was highest under

treatment 250-50 and lowest under treatment 500-0. In planted pots, soil Zn

concentration did not have any significant effect on gene abundance of total

bacteria. On the contrary, in these planted pots, the presence of 50 and 250 mg Cd

kg-1 DW soil led to significantly lower values of total bacteria gene abundance as


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compared to soils lacking Cd: 132,514 ± 24,641 x 103 copies g-1 for soils non-

polluted with Cd versus 71,370 ± 8,031 copies g-1 for soils polluted with Cd (mean

value of soils polluted with 50 and 250 mg kg-1 DW). For chitin-degrading bacteria,

in unplanted pots, treatment 250-50 showed highest values of gene copies

(treatments 500-0 and 1,000-0 showed lowest values). In planted pots, no significant

differences were observed regarding abundance of chitin-degrading gene copies

between metal treatments. Finally, concerning abundance of ammonia-oxidizing

gene copies, in unplanted pots, again treatment 250-50 showed highest values

(treatment 1,000-250 showed lowest values). In planted pots, at 1,000 mg Zn kg-1

DW soil, ammonia-oxidizing gene copies decreased compared to that observed at

250 mg Zn kg-1 DW (8.9 ± 2.4 versus 17.2 ± 2.1 x 103 copies g-1). Similarly, in these

planted pots, at 250 mg Cd kg-1 DW soil, ammonia-oxidizing gene fragment

abundance decreased compared to that observed in the absence of Cd (10.8 ± 1.7

versus 18.8 ± 2.5 x 103 copies g-1). In respect to differences between planted and

unplanted soils regarding bacterial gene abundances, no clear patterns were

observed (Table 6.5). However, as a whole, planted soils showed a 58% higher total

bacterial gene abundance than unplanted soils.

Concerning the experiment on the capacity of the phytoremediated soil to

support M. sativa growth at the end of the phytoextraction study, it was found that

alfalfa growth was highly inhibited by the presence of both heavy metals: actually,

M. sativa growth was only observed in treatments 250-0, 250-50 and 500-0. In

previously unplanted soils, the following values of alfalfa shoot biomass were found

for treatment 250-0, 250-50 and 500-0, respectively: 1.80 ± 0.33, 0.14 ± 0.04 and

0.16 ± 0.05 g DW shoot. Instead, in previously planted (with T. caerulescens) soils, the

following values of alfalfa shoot biomass were found for treatments 250-0, 250-50

and 500-0, respectively: 0.88 ± 0.21, 0.18 ± 0.06 and 0.21 ± 0.10 g DW shoot.

Under treatment 250-0, values of alfalfa shoot biomass were 49% lower in soils

previously planted with T. caerulescens versus previously unplanted pots (on the

contrary, under treatment 250-50 and 500-0, values of alfalfa shoot biomass were 26

and 34% higher, respectively, in previously planted versus unplanted).


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Table 6.5: Total bacteria, group A bacterial chitinases and ammonia monooxygenase gene abundance in soils polluted with different Zn (first value) and Cd (second value) concentrations

(mg kg-1 DW) at the end of the phytoextraction experiment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test (statistics are shown only when, according to two-way ANOVA, a significant interaction was found between both soil

metals). Asterisks represent significant differences (P<0.05 or lower) between planted and unplanted soils. Mean values (n = 4) ± standard errors.

Total bacteria Chitinase group A AmoA (103 copies g-1 DW soil)

250-0 124360 ± 33241ab 135 ± 23a 19.0 ± 0.8ab

250-50 137622 ± 54455a 253 ± 7b* 36.9 ± 1.3c*

250-250 22795 ± 6225ab 157 ± 26ab 16.7 ± 2.4ab

500-0 10247 ± 448b* 112 ± 25a 13.6 ± 0.8abd

500-50 64639 ± 18855ab 147 ± 20ab 16.9 ± 1.8ab

500-250 38897 ± 6734ab 156 ± 19ab 19.1 ± 1.1ab

1,000-0 31138 ± 5089ab* 110 ± 9a* 23.3 ± 4.8a

1,000-50 33488 ± 564ab 160 ± 22ab 8.2 ± 1.5bd

Unp

lant

ed

1,000-250 59259 ± 9644ab 212 ± 12ab* 3.1 ± 0.8d

250-0 205862 ± 49911 179 ± 14 19.4 ± 4.4

250-50 63122 ± 7632 118 ± 29 18.4 ± 3.3

250-250 66442 ± 20075 161 ± 24 13.7 ± 2.1

500-0 102297 ± 29487 151 ± 30 23.8 ± 4.5

500-50 49229 ± 6125 180 ± 13 13.3 ± 1.3

500-250 44446 ± 13238 102 ± 27 11.6 ± 3.9

1,000-0 89383 ± 8123 158 ± 8 15.6 ± 5.5

1,000-50 102339 ± 25350 166 ± 32 4.1 ± 0.5

Plan

ted

1,000-250 102643 ± 13926 156 ± 11 7.0 ± 1.2

The application of PCA to all soil physicochemical and microbial parameters

determined here (Figure 6.2) separated soils subjected to different levels of Zn

pollution along axis 1, which accounted for 29% of the variance. Soils treated with

250 mg Zn kg-1 DW showed higher values of nitrates content, alfalfa growth,

ammonia monooxygenase gene abundance, extractable P content and basal

respiration. These five parameters were positively correlated with each other, and

negatively with values of soil pH. No clear pattern was observed regarding the

possible correlation between soil Cd concentration and physicochemical or


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microbial parameters. On the other hand, planted and unplanted pots also appeared

separated (Figure 6.2). Planted pots showed higher values of SIR and total bacterial

gene fragments and group A bacterial chitinase gene abundances, and lower values

of total N and K+ content.

Figure 6.2: Principal component analysis of soil physicochemical and microbial properties in planted (P) and unplanted (UP) soils, polluted with different Zn (first value) and Cd (second value) concentrations, at the end of the phytoextraction experiment. Axis 1 and Axis 2 account for 29 and

17% of the variance, respectively. SIR: substrate-induced respiration; Chit: group a bacterial chitinase gene abundance; Bac: total bacteria gene abundance; OM: organic matter content; BR:

basal respiration; P: extractable phosphorus content; Amo: ammonia monooxygenase gene abundance; Ms: Medicago sativa growth; NO3: nitrates content; N: total N content; K: potassium

content.


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Regarding DGGE results, out of all treatment pairs, the pairs 250-0-

unplanted/250-0-planted and 1,000-250-unplanted/1,000-250-planted showed the

highest values of the Jaccard index (CJ = 0.64 and CJ = 0.66, respectively). The

remaining values of the Jaccard index ranged between 0.40 and 0.46. According to

the RDA, soil heavy metal concentration and T. caerulescens shoot biomass explained

41% of the total inertia present in the DGGE data. After partialling out the

influence of selected sets of co-variables, most of the explained variation in DGGE

data was attributable to changes in soil metal concentration (31.7%), and just 7.0%

could be attributed to changes in T. caerulescens shoot biomass. In addition, another

RDA was performed to identify the soil physicochemical and microbial properties

that had the most significant influence on bacterial community structure. The soil

properties that yielded P<0.05 after forward selection were: basal respiration

(P<0.001) and pH (P<0.008), which positively influenced non-polluted (250-0) and

metal polluted (1,000-250) soils, respectively.

Table 6.6: Genes detected in the Geochip functional genes array, together with the variation partitioning obtained by RDA, in planted (P) and unplanted (UP) soils polluted with different Zn (first value) and Cd (second value) concentrations, at the end of the phytoextraction experiment.

Numbers shown below ‘Explaining factors’ quantify the effects of each set of explaining factors (T. caerulescens shoot biomass and soil metal concentration), after partialling out the effect of the other

variables, expressed as a percent contribution to the total inertia in the response variable.

N-cycle C-cycle Sulphate Heavy metals

Organic compounds TOTAL

250-0-UP 19 18 5 22 44 108

250-0-P 31 41 9 54 75 210

1,000-250-UP 63 74 17 94 160 408

1,000-250-P 85 105 26 118 198 532

% Explained 54.6 63.3 55.8 60.9 59.3

% Unexplained 45.4 36.7 44.2 39.1 40.7

Explaining factors

Shoot biomass 15.4 15.4 16.1 14.7 14.7 Soil metal

concentration 39.9 44.0 35.2 46.7 41.6

Interaction 0.0 3.9 4.5 0.0 3.0

Finally, Table 6.6 shows a summary of the genes detected in the Geochip for

each treatment. In every gene category, more genes were detected in polluted

(1,000-250) than non-polluted (250-0) soils. Besides, gene detection was higher in


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planted versus unplanted soils. The RDA explained a high percentage (above 54%) of

the total inertia present in the Geochip data. After partialling out the influence of

selected covariables (i.e., T. caerulescens shoot biomass and metal concentration), most

of the explained variation was due to changes in soil metal concentration. Indeed,

for every gene category, soil metal concentration explained from 35.2 to 46.7% of

data variation, while T. caerulescens shoot biomass explained from 14.7 to 16.1%.

Out of the twelve Zn and/or Cd resistance genes detected, three belonged to

Staphylococcus sp. All of them were present in metal-polluted (1,000-250) planted soils,

while only seven of them were found in metal-polluted (1,000-250) unplanted soils

(five of them were present in 250-0 planted soils, and just one in these non-polluted

unplanted soils).

Using binary presence-absence data, the number of different gene variants

detected were studied to gain insight into possible functional redundancy. The gene

families that were well-represented (with a minimum of 5 gene variants) and that

showed a significant (P<0.05) difference between treatments according to ANOVA

are shown in Figure 6.3. As a general pattern, both metal polluted (1,000-250) and

planted soils showed a larger number of gene variants than non-polluted and

unplanted soils, respectively.


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Figure 6.3: Number of gene variants detected in the Geochip functional gene array in planted (P) and unplanted (UP) soils, polluted with different Zn (first value) and Cd (second value)

concentrations, at the end of the phytoextraction experiment. Only those gene variants well-represented (with a minimum of 5 gene variants) and showing significant differences (P <0.05)

among treatments, according to ANOVA, are presented.


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RDAs were performed for each gene category in order to identify the soil

physicochemical and microbial properties that had the most significant influence on

functional genes. The soil properties that yielded P<0.05 after forward selection

were SIR and K+ content for the C-cycle, sulphate reduction and organic

contaminant degradation gene categories, which positively influenced 1,000-250

planted and unplanted soils, respectively. On the other hand, SIR and nitrates

content yielded P< 0.05 after forward selection for the N-cycle and metal reduction

and resistance gene categories, and positively influenced 1,000-250 planted and 250-

0 planted/unplanted soils, respectively. Finally, no significant correlations were

found between abundandes of ammonia monooxygenase gene and group A

bacterial chitinases estimated through real-time PCR and their respective

abundances obtained in the Geochip microarray.

6.5 Discussion

6.5.1 Metal phytoextraction

Our T. caerulescens Lanestosa ecotype proved to have a great capacity for Zn

and Cd hyperaccumulation. In fact, shoot Cd concentrations reached values above

the hyperacumulation threshold of 100 mg Cd kg-1 DW (Baker et al., 2000). These

results are in accordance with those previously reported by us for this very same

ecotype (Epelde et al., 2008a). Besides, as reflected by the values of the plant

physiological parameters studied here, T. caerulescens plants did not show any

phytoxicity symptoms in the presence of high levels of metals. Indeed, our results

indicate that T. caerulescens Lanestosa ecotype has an elevated tolerance to Cd, a

heavy metal for which few hyperaccumulator species are known (Baker et al., 2000).

Interestingly, at a soil Zn concentration of 250 and 500 mg kg-1 DW, the presence

of 250 mg Cd kg-1 DW soil significantly stimulated Zn shoot accumulation (and also

Zn translocation at 250 mg Zn kg-1 DW).

Translocation factors for both metals were >1, as it is usually the case with

hyperaccumulators (McGrath et al., 2002). On the other hand, according to Zhao et

al. (2003), for metal phytoextraction, bioconcentration factors are more important

than shoot metal concentrations. In the present study, T. caerulescens plants showed


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most promising bioconcentration factors for Cd (up to 8.0) and Zn (up to 17.4),

taking into account that 10 is the threshold value reported for a phytoextraction

process to be considered feasible (McGrath et al., 2006).

6.5.2 Impact of metal pollution on soil properties

In this study, it was found that the lower the soil Zn concentration, the higher

the values of alfalfa growth (i.e., capacity of the phytoremediated soil to support

plant growth), soil basal respiration and abundance of ammonia-oxidizer genes

(Figure 6.2). On the other hand, these three parameters were negatively correlated

with soil pH. By contrast, in a study by Wang et al. (2006), a positive correlation

between soil biological activities and pH was found. Likewise, in our study, the

abundance of ammonia-oxidizer genes was positively correlated with soil nitrates

content. The amoA gene codes the α subunit of ammonia monooxygenase (AMO),

the key enzyme of all aerobic ammonia-oxidizing bacteria: this enzyme catalyzes the

rate limiting process of nitrification, i.e. the oxidation of ammonia to hydroxylamine

(Yuan et al., 2005).

Biological parameters, especially those related to the activity, size and diversity

of soil microbial communities, are becoming increasingly used to assess the impact

of pollutants on soil functioning due to their sensitivity, rapid response and capacity

to provide information that integrates many environmental factors (Hernández-

Allica et al., 2006a; Epelde et al., 2008a, b). Soil basal respiration, an indicator of the

overall activity of microorganisms involved in OM decomposition (Anderson,

1982), has been shown to be negatively affected by the presence of heavy metals

(Duxbury, 1985; Kandeler et al., 1996). In our study, Zn pollution led to decreased

levels of both soil basal respiration and SIR values (an indicator of potentially active

microbial biomass). Also, under some treatments, a metal-induced reduction in total

bacterial gene abundance was also observed: Cd pollution (50 and 250 mg Cd kg-1

DW soil) negatively affected the abundance of total bacterial genes in planted pots;

highest levels of metal pollution (1,000 mg Zn kg-1 DW and 250 mg Cd kg-1 DW)

led to lower values of abundance of ammonia-oxidizer genes. Similarly, Mertens et

al. (2006) reported that ammonia-oxidizer populations were sensitive to increasing

Zn concentrations in artificially contaminated soils. This metal-induced inhibition is


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also reflected in the values of QR, a parameter frequently used to assess the effect of

disturbances on the soil ecosystem (Anderson and Domsch, 1985; Insam and

Domsh, 1988).

In soils polluted with high levels of metals (treatment 1,000-250), both Cd

and Zn had a clear effect on the structural genetic diversity of soil bacteria. This is in

accordance with other studies which also detected metal-induced shifts in the soil

bacterial community using DGGE and other molecular techniques (Gremion et al.,

2004; Sandaa et al., 1999a).

Functional diversity, as determined by the GeoChip, was also most affected by

the presence of heavy metals. Unlike soil properties related to microbial activity or

biomass, functional diversity (number of genes detected), regardless of gene

category, increased as a result of metal pollution. Similarly, functional redundancy

appeared higher as a response to metal pollution.

No correlations were found between real-time PCR data and the respective

values of gene abundance detected by the Geochip. This could be due to the rolling

circle amplification carried out before labeling and hybridization steps. Most

important, any quantitative interpretation of microarray studies requiring an

intermediate PCR amplification should be treated with caution, as results are

susceptible to the same biases associated with any end-point PCR protocol

(Reysenbach et al., 1992; Smith and Osborn, 2009). In addition, in our study, real-

time PCR assays rely on different priming sites than those used for probing on the

array. Furthermore, probe signals were a summation of signals derived from

multiple specific signals within a gene family, whereas real-time PCR results were

generated by gene-family specific primers. Another explanation is that both

methods rely on extant sequence data for primer and probe design and may either

miss some members of the target gene families or overlap with related gene families

(Yergeau et al., 2007b).

Finally, regarding the M. sativa productivity experiment carried out to

determine the capacity of the phytoremediated soil to support plant growth at the

end of the phytoextraction experiment, it was found that Zn and Cd levels were still

very toxic for this plant species (alfalfa growth was only observed under treatments

250-0, 250-50 and 500-0; much higher growth was found under 250-0 as compared


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to the other two treatments). Though plant bioassays are certainly a most useful tool

to assess soil toxicity, its response depends on a variety of factors such as the

species used, type and levels of contamination, edaphic and environmental factors

of the assay, etc.

6.5.3 Effect of T. caerulescens growth and metal phytoextraction on soil properties

T. caerulescens growth and metal phytoextraction increased the values of soil

basal respiration, SIR and total bacterial gene abundance. As compared to bare soil,

vegetated soils commonly have higher rates of microbial biomass and activity as a

result of the improvement in soil conditions due to the presence of greater

quantities of organic compounds and surfaces for microbial colonization (Grayston

et al., 1997). In similar phytoextraction experiments with T. caerulescens plants, we

previoulsy found higher values of microbial activity in rhizosphere versus non-

rhizosphere soil (Hernández-Allica et al., 2006a; Epelde et al., 2008a).

Regarding the M. sativa productivity experiment, under treatment 250-0, M. sativa growth was lower in previously planted soils, probably due to the reduction in

soil nutrient levels caused by T. caerulescens growth. However, under treatments 250-

50 and 500-0, M. sativa growth was higher in previously planted soils, most likely

owing to a positive effect derived from the reduction in soil metal concentrations

caused by T. caerulescens metal uptake, which compensates the negative effect

produced from decreased nutrient levels.

Interestingly, the PCA separated planted and unplanted treatments: planted

treatments showed higher values of microbial biomass data which were all positively

correlated among each other despite targeting different portions of the soil

microbial community (e.g., SIR, an indicator of potentially active microbial biomass,

was positively correlated with total bacteria gene abundance calculated by real-time

PCR). The lower values of total N and extractable K+ observed in planted versus unplanted soils are most likely due to plant uptake.

As far as structural genetic bacterial diversity, no major differences were found

between planted and unplanted soils. Similarly, in a phytoremediation experiment


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with poplars, Frey et al. (2008) reported that DGGE patterns of Pseudomonas populations of unplanted and planted treatments were similar. On the contrary,

Wang et al. (2008) found differences in bacterial community composition (measured

also with DGGE) between Elsholtzia splendens and Trifolium repens planted and

unplanted Cu polluted soils. On the other hand, although the presence of plants

explained a low percentage of the variability of the Geochip data, the number of

genes detected and the functional redundancy in planted soils were higher for every

gene category, as compared to unplanted soils.

The abundance of Zn and/or Cd resistance genes detected was higher in T. caerulescens planted versus unplanted soils, even in the absence of metals. There are

quite a few reports on the effects of metals on microbial communities in bulk soils

(Brim et al., 1999; Sandaa et al., 1999b), but the information on the microbial

community present in the rhizosphere of heavy metal-accumulating plants is still

scarce. In particular, it is unclear if heavy metal-accumulating plants selectively affect

bacterial community composition in heavy metal-contaminated soils, showing

communities in the root-zone (Kozdrój and van Elsas, 2001) that may not be

dominant or active in unplanted bulk soil. In this respect, Gremion et al. (2003)

studied a T. caerulescens rhizosphere soil library derived from rRNA, finding out that

Actinobacteria (and more specifically Rubrobacteria) might be a dominating part of the

metabolically active bacteria in the rhizosphere of this hyperaccumulator.

6.6 Conclusions

The Lanestosa ecotype of T. caerulescens confirmed its great potential for Zn

and Cd phytoextraction: highest values of Zn (43.4 mg) and Cd (10.6 mg)

phytoextracted from soil were observed under treatment 1,000-250 and 250-250,

respectively. Translocation factors for both metals were >1. T. caerulescens plants

showed most promising bioconcentration factors: up to 17.4 for Zn and 8.0 for Cd.

Zn pollution led to decreased levels of both soil basal respiration and SIR.

Also, under some treatments, a metal-induced reduction in total bacterial gene

abundance was observed. In soils polluted with high levels of metals, both Cd and

Zn had a clear effect on the structural genetic diversity of soil bacteria. Functional


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diversity (number of genes detected) and redundancy, regardless of gene category,

increased as a result of metal pollution. T. caerulescens growth and metal

phytoextraction increased the values of soil basal respiration, SIR and total bacterial

gene abundance. As far as structural genetic diversity of soil bacteria is concerned,

no major differences were found between planted and unplanted soils. On the other

hand, although the presence of plants explained a low percentage of the variability

of the Geochip data, the number of genes detected and the functional redundancy

in planted soils were higher for every gene category, as compared to unplanted soils.

The abundance of Zn and/or Cd resistance genes detected was higher in T. caerulescens planted versus unplanted soils, even in the absence of metals. Certainly,

more efforts are needed to deepen into the still poorly understood plant-microbe

interactions that occur in metal polluted soils.

7. soil microbial community as bioindicator of the recovery of soil functioninG derived from metal phytoextraction with sorGhum

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7. SOIL MICROBIAL COMMUNITY AS BIOINDICATOR OF THE RECOVERY OF SOIL FUNCTIONING DERIVED FROM METAL

PHYTOEXTRACTION WITH SORGHUM

Epelde et al., published in Soil Biology and Biochemistry (in press, doi:10.1016/j.soilbio.2008.04.001)

7.1 Abstract

A three-month microcosm study was carried out in order to evaluate: (i) the

capacity of sorghum plants to phytoextract Cd (50 mg kg-1) and Zn (1000 mg kg-1)

from artificially polluted soil; and (ii) the possibility of biomonitoring the efficiency

of phytoremediation using parameters related to the size, activity and functional

diversity of the soil microbial community. Apart from plant and soil (total and

bioavailable) metal concentrations, the following parameters were determined: soil

physicochemical properties (pH, OM content, electrical conductivity, total N,

extractable P and K+), dehydrogenase activity, basal and substrate-induced

respiration (with glucose and a model rhizodeposit solution, both adjusted to 800

mg C kg-1 DW soil and 45.2 mg N kg-1 DW soil), microbial respiration quotient,

functional diversity through community level physiological profiles and, finally, seed

germination toxicity tests with Lepidium sativum. Sorghum plants were highly tolerant

to metal pollution and capable of reaching high biomass values in the presence of

metals. In the first two harvests, values of shoot Cd concentrations were higher

than 100 mg Cd kg-1 DW, the threshold value for hyperaccumulators. Nonetheless,

in the third harvest, the bioconcentration factor was 1.34 and 0.35 for Cd and Zn,

respectively, well below the threshold value of 10 considered for a phytoextraction

process to be feasible. In general, microbial parameters showed lower values in

metal polluted than in control non-polluted soils, and higher values in planted than

in control unplanted pots. As a result of the phytoextraction process, which includes

both plant growth and metal phytoextraction, the functioning of the

phytoremediated soil, as reflected by the values of the different microbial

parameters here determined, was restored. Most importantly, although the


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phytoextracted soil recovered its functionally, it was still more phytotoxic than the

control non-polluted soil.

7.2 Introduction

Phytoextraction, or the utilization of plants to transport and concentrate

metals from the soil into the harvestable parts of roots and above-ground shoots

(Kumar et al., 1995), appears a promising, cost-effective technology for the

remediation of metal polluted soils. Although hyperaccumulators (i.e., plants that

have the capacity to accumulate in their aerial tissues large quantities of metals from

the surrounding soil) have been extensively studied for metal phytoextraction, their

deployment for the phytoremediation of metal polluted soils presents certain

constraints, namely that hyperaccumulating plants are, in general, relatively small,

have slow rates of biomass production, and lack any established cultivation, pest

management or harvesting practices (Wenzel et al., 1999). Consequently, nowadays,

fast-growing, high biomass crop plant species that accumulate moderate levels of

metals in their shoots are actively being tested for phytoextraction (Hernández-

Allica et al., 2007). After all, in some cases, a greater shoot biomass has been

reported to more than compensate for a lower shoot metal concentration (Ebbs and

Kochian, 1997, 1998).

To avoid the inconvenience of having to sow again the phytoextracting plant

after each harvest, an interesting approach is to use perennial plant species, such as

sorghum, able to regrow in the polluted soil after harvesting, thus allowing for

repeated cuttings. Sorghum plants have been reported to accumulate high amounts

of metals in their shoots when grown hydroponically (Hernández-Allica et al., 2007).

Interestingly, cropping of sorghum has been predicted to increase under climate

change due to its drought and heat tolerance (Tuck et al., 2006). In addition,

sorghum plants are multipurpose cereals of potential interests for several non-food

uses, especially as energy crops for the production of bioethanol (Barbanti et al.,

2006). In order to circumvent the recent food versus biofuel debate, it would be

practical to use polluted soils, not suitable for food crops, for energy biomass

production. Furthermore, obtaining products with economic value from plants used


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in the cleanup of polluted soils would be an additional benefit to phytoremediation,

which could indeed help sustain its long-term use (Bañuelos, 2006).

The ultimate goal of any soil remediation process must be not only to remove

the contaminant(s) from the polluted site but, most importantly, to restore the

capacity of the soil to perform or function according to its potential (i.e., its health)

(Hernández-Allica et al., 2006a). Regarding the recovery of soil health/functioning

derived from the phytoextraction process, an ideal target should be to return to the

conditions of a valid control soil (i.e., a vegetated, unpolluted soil of similar

physicochemical properties and subjected to the same edaphoclimatic conditions).

Hence, indicators of soil health are needed to properly assess the efficiency of

a phytoextraction process. Biological indicators of soil health, especially those

related to the size, activity and diversity of soil microbial communities, are becoming

increasingly used due to their sensitivity and capacity to provide information that

integrates many environmental factors (Alkorta et al., 2003b).

Dehydrogenase activity, an intracellular process that occurs in every viable

microbial cell, is used to determine overall microbiological activity of soil

(Nannipieri et al., 2002). Soil microbial activity can also be measured through the

determination of soil basal respiration (ISO 16072 Norm). In turn, soil microbial

functional diversity can be determined through the utilization of community level

physiological profiles (CLPPs) which reflect the potential of the cultivable portion

of the heterotrophic microbial community to respond to carbon substrates (Bending

et al., 2004). Substrate (glucose)-induced respiration (SIR) is a suitable indicator of

potentially active microbial biomass (ISO 17155 Norm). The addition of carbon

sources, other than glucose, commonly reported as constituents of root exudates

might convert SIR into an ecologically more relevant parameter for testing

rhizospheric microbial communities (Dedourge et al., 2004). The microbial

respiration quotient (QR = basal soil respiration to SIR ratio) has been used to assess

the effects of various perturbations in soil ecosystems (Insam and Domsh, 1988).

The aim of the current work was to evaluate the feasibility of using sorghum

plants for Cd and Zn phytoextraction. We hypothesized that bioindicators of soil

health might be valid monitoring tools to assess (i) the effect of metals on soil

functioning and (ii) the efficiency of the phytoextraction process (i.e., its capacity to


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restore soil functioning as a result of the phytoextraction process, which includes

both plant growth and metal phytoextraction).


7.3.1 Soil characterization and experimental design

A three-month microcosm study was carried out with soil collected from the

top layer (0-30 cm) of a natural polyphita grassland located in Derio (Basque

Country, northern Spain). Immediately after collection, the soil was sieved to <4

mm, air-dried at 30 ºC, and subjected to physicochemical characterization according

to standard methods (MAPA, 1994). The soil was a clay loam, with a pH of 7.2, an

organic matter (OM) content of 4.92 %, a total nitrogen (N) content of 0.26 %, a

C/N ratio of 11, a phosphorus (P) content of 57.1 mg kg-1, and an electrical

conductivity (EC) of 0.18 dS m-1.

Subsequently, the soil was artificially contaminated with 50 mg Cd kg-1 dry

weight (DW) soil as CdCl2 and 1000 mg Zn kg-1 DW soil as ZnCl2. Metal polluted

and control non-polluted soils were stored in the dark for 1 month at 20 %

humidity and 20 ºC.

Afterwards, 10 kg of soil (on a DW basis) were placed in pots and fertilized

with 120 mg kg-1 of N, P and K+ before planting. For both metal polluted and

control soils, half of the pots were planted with 200 seeds of Sorghum bicolor x sudanense. Four different treatments (i.e., NM-UP: no metal, unplanted; NM-P: no

metal, planted; M-UP: metal, unplanted; M-P: metal, planted) were conducted in

quadruplicate. The plants were then allowed to grow for three months in a soft

polyethylene-covered greenhouse (Venlo-type) located in Derio at a latitude of 43º

17’ N, a longitude of 2º 52’ W, and an altitude of 65 m above sea-level. The climate

in this region is Atlantic temperate. Minimal temperature set points controlling air-

heating were 14/18 ºC night/day, and maximal temperature set points were 18/20

ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the

experiment, average temperature was 19/31 ºC night/day, average relative humidity

41/76 % night/day, and average photosynthetically active radiation 476 μmol

photon m-2 s-1. At the end of each month, sorghum plants were harvested by means


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of cutting at 2-3 cm of the soil surface. Throughout the experimental period, plants

were bottom watered periodically as needed.


Shoots were harvested three times (at the end of each month). In turn, roots

were harvested only once, i.e. at the end of the experiment. After harvesting, fresh

weights (FW) of shoots and roots were recorded. Shoot and roots were washed

thoroughly with deionized water to remove soil particles. Subsequently, shoots and

roots were oven-dried at 70 ºC for 48 h and their dry weights recorded. Subsamples

(0.4 g) of dried plant tissue were digested with a mixture of HNO3/HClO4 (Zhao et

al., 1994) and Cd and Zn in the digest were determined using inductively coupled

plasma atomic emission spectrometry (ICP-AES, Varian).

7.3.3 Soil parameters

Soil was also sampled at the end of each month. For the first two harvests, a

soil core sampler (1 cm diameter; 20 cm height; 4 cores per pot which were then

pooled) was used. In the first two harvests, only three parameters were determined

in the soil samples: bioavailable metal fraction, dehydrogenase activity and CLPPs.

In the third harvest, all parameters described below were analysed. The selection of

the microbial parameters here determined was carried out following the

recommendations by Bloem et al. (2006).

For analysis of biological parameters, soils were sieved to <2 mm, and stored

at 4 ºC until analysis. Dehydrogenase activity was determined according to Taylor et

al. (2002). The analysis of CLPPs was carried out following Rodríguez-Loinaz et al.

(2007). The plates corresponding to an incubation time of 40 h were chosen for

calculations (at approximately this time, the highest rate of microbial growth was

observed in the Biolog EcoPlatesTM). Jaccard similarity index (CJ = a/a+b+c; where

a, the total number of substrates used in both treatments; b, the number of

substrates used only in the first treatment; and c, the number of substrates used only

in the second treatment) was calculated for each pair of treatments.


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Soil basal microbiological respiration was determined according to ISO 16072

Norm. SIR was determined with glucose following ISO 17155 Norm. Likewise, SIR

was measured using a model rhizodeposit solution as substrate (Griffiths et al.,

1999). For this model rhizodeposit solution, a stock solution of 50 mM fructose, 50

mM glucose, 50 mM sucrose, 25 mM succinic acid, 25 mM malic acid, 12.5 mM

arginine, 12.5 mM serine and 12.5 mM cysteine was prepared. The working solution

was obtained by diluting the stock solution with distilled water to give a rate of 800

mg C kg-1 DW soil and 45.2 mg N kg-1 DW soil. Equivalent rates of C and N were

added in the form of glucose and diammonium sulphate in the glucose-induced

respiration. The addition of these solutions to the soil brought the final soil

moisture content up to 80 % WHC. QR was calculated as the ratio between soil

basal respiration and glucose-induced respiration. For the calculation of QR, the

values of soil basal respiration obtained after 35 days of incubation were chosen to

avoid the priming effect due to sieving, humidification and incubation of soil

samples, processes that frequently speed up the mineralization of the most labile C

fractions. The values of SIR observed after 6 h of incubation were chosen so that a

valid estimate of the potentially active microbial biomass was obtained (i.e., a short

incubation time is used to register the respiration reaction of the initial microbial

population without invoking microbial growth) (Lin and Brookes, 1999).

Soil collected at the third harvest was used to carry out a germination test (to

assess soil phytotoxicity) with Lepidium sativum seeds following Zucconi et al. (1985).

Seed germination and root length in each plate were measured after 48 h. The

germination index (GI) after exposure to the soil extracts was calculated as follows

(Hoekstra et al., 2002):

GI (%) = 100 (SD/SB) (LD/LB)

where SD, SB = number of germinated seeds for sample and blank,

respectively, and LD, LB = average root length of seeds for sample and blank,

respectively.

For analysis of chemical parameters, soils were air-dried at 30 ºC for 48 h,

sieved to <2 mm, and stored at 4 ºC until analysis. Soil pH, OM content, total N,

electrical conductivity, and extractable P and K+ were measured according to

MAPA (1994). Total metal concentrations were determined using ICP-AES


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following aqua regia digestion (McGrath and Cunliffe, 1985). For the determination

of the bioavailable fraction of metals, pore water metal was extracted using 0.01 M

CaCl2 (Houba et al., 2000) and analyzed by ICP-AES.


Differences between treatments were analyzed (i.e., one-way ANOVAs) using

Microsoft Stat View Software (SAS Institute). Fisher´s PLSD-test was used to

establish the significance of the differences among means. Simple regression

analyses were performed to study the relationship between soil metal concentrations

and plant metal accumulation or soil biological parameters. Biolog EcoPlatesTM data

were used to perform a principal component analysis (PCA) treating each of the

substrates as a variable.

7.4 Results

7.4.1 Metal phytoextraction by sorghum plants

In the first two harvests, values of shoot biomass remained practically

constant for both metal polluted and control pots (Table 7.1). However, in the third

harvest, values of shoot biomass decreased by ca. 18 and 24 % in metal polluted and

control pots, respectively. Values of shoot biomass were always lower (on average,

ca. 22 % lower) in metal polluted than in control pots. In turn, root biomass was

halved as a result of metal pollution (Table 7.1). Nonetheless, plants did not show

any visual toxicity symptoms throughout the experiment.

In the first two harvests, values of shoot Cd concentration in metal polluted

pots were higher than 100 mg Cd kg-1 DW (Table 7.1). Shoot Zn concentrations

were 729.2 ± 111.5 and 635.8 ± 87.9 mg kg-1 DW in the first and second harvest,

respectively. In the third harvest, shoot metal concentrations in metal polluted pots

were significantly lower (as compared to the first two harvests) for both metals, with

low translocation factors (TF = shoot metal concentration/root metal

concentration) for both Cd (0.29) and Zn (0.06). At the end of the experiment,

considering the three harvests, sorghum plants had extracted, and subsequently


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traslocated, 12.9 mg of Cd and 74.4 mg of Zn from the soil to the aboveground

tissues.

Table 7.1: Shoot and root biomass (g DW tissue) and metal concentrations (mg kg-1 DW tissue) of sorghum plants in metal polluted and control non-polluted soils. For each metal and biomass value, numbers followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (lower case letters: among harvests; upper case letters: among polluted and non-polluted pots). Mean values (n = 4) ± standard errors.

Shoot

1st harvest Shoot

2nd harvest Shoot

3rd harvest

Root 3rd harvest

Polluted 46.7 ± 2.8aA 45.7 ± 4.2aA 37.9 ± 3.3aA 6.8 ± 1.7A Biomass

Non-polluted 61.1 ± 2.0aB 61.1 ± 0.7aB 46.2 ± 2.4bA 13.7 ± 0.4B

Polluted 122.4 ± 8.5aA 113.7 ± 5.0aA 52.5 ± 3.3bA 183.5 ± 6.2A Cd concentration Non-polluted 6.5 ± 0.5aB 10.9 ± 1.0aB 7.6 ± 0.6aB

10.7 ± 1.0B

Polluted 729.2 ± 111.5aA 635.8 ± 87.9aA 299.3 ± 53.1bA 4659.4 ± 605.3A Zn concentration

Non-polluted 49.7 ± 2.1aB 73.0 ± 2.4aB 44.5 ± 1.0aB

161.2 ± 13.0B

In metal polluted pots, a 6.6 and 6.8 % reduction in total Cd and Zn,

respectively, was observed in planted versus unplanted pots (Table 7.2). In these

metal polluted pots, concentrations of bioavailable Cd and Zn were significantly

lower in planted versus unplanted pots (a 46.7 and 50.7 % reduction in bioavailable

Cd and Zn, respectively). In control non-polluted soils, no significant differences in

total or bioavailable metal concentrations were found between planted and

unplanted pots. In metal polluted soils, shoot Cd and Zn concentrations were

correlated to soil metal bioavailable fractions (R2 = 0.52 for Cd and 0.77 for Zn; P =

0.008 and <0.001 for Cd and Zn, respectively) but not to soil total concentrations

(R2 = 0.07 for Cd and 0.10 for Zn; P = 0.736 and 0.684 for Cd and Zn,

respectively).

In the third harvest, the bioconcentration factor in metal polluted pots (BF =

shoot metal concentration/soil metal concentration) was 1.34 and 0.35 for Cd and

Zn, respectively.


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Table 7.2: Total (aqua regia digested) and bioavailable (CaCl2 extractable) metal concentrations (mg kg-1 DW soil) in soil samples at the end of the phytoextraction experiment. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (letters refer to differences among treatments). Mean values (n = 4) ± standard errors.

Cd Zn Total Bioavailable Total Bioavailable

NM-UP 0.90 ± 0.06a 0.04 ± 0.01a 84.08 ± 3.44a 0.38 ± 0.19a

NM-P 0.83 ± 0.02a 0.06 ± 0.00a 66.05 ± 1.77a 0.68 ± 0.07a

M-UP 42.08 ± 2.19b 8.31 ± 0.50b 923.00 ± 36.53b 149.92 ± 11.11b

M-P 39.30 ± 1.70b 4.43 ± 0.94c 860.50 ± 32.32b 73.88 ± 19.82c

7.4.2 Effect of metal pollution and phytoextraction on soil parameters

In metal polluted pots, in the third harvest, the presence of sorghum led to a

statistically significant 412.4 % increase in dehydrogenase activity (Table 7.3). In

metal polluted soils, dehydrogenase activity was correlated to soil metal bioavailable

fractions (R2 = 0.45 for Cd and 0.52 for Zn; P <0.001 for both Cd and Zn) but not

to soil total metal concentrations (R2 = 0.02 for Cd and 0.06 for Zn; P = 0.713 and

0.577 for Cd and Zn, respectively). Table 7.3: Values of dehydrogenase activity (mg INTF kg-1 20 h-1). NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Values followed with different letters are significantly different (P <0.05 or lower) according to Fisher´s PLSD-test (lower case letters: among harvests; upper case letters: among treatments). Mean values (n = 4) ± standard errors.

NM-UP NM-P M-UP M-P

1st harvest 165.4 ± 59.9aA 168.8 ± 15.5aA 97.9 ± 4.3aA 146.2 ± 22.1aA

2nd harvest 144.9 ± 48.9aA 183.5 ± 6.5aA 100.4 ± 10.6aA 160.8 ± 6.5aA

3rd harvest 116.6 ± 38.8aAB 124.7 ± 6.4aAB 45.0 ± 16.8aA 185.6 ± 27.6aB

Figure 7.1 shows the average well colour development (AWCD) values

corresponding to the third harvest. In both the absence and presence of metals,

planted pots showed significantly higher values of AWCD than unplanted pots.


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Figure 7.1: Average well colour development (AWCD) curves in the third harvest. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Lower case letters refer to significant differences (P <0.05 or lower) among treatments, according to Fisher´s PLSD-test, at 40 h of incubation.

In the third harvest, a PCA revealed clear differences among treatments

(Figure 7.2). Along PC1, the PCA significantly (P <0.05) separated planted from

unplanted pots. The substrates responsible to a greater extent for this separation

were L-asparagine, L-phenylalanine, L-serine, D-cellobiose, D-xylose, N-acetyl-D-

glucosamine, D-galactonic acid lactone, 4-hydroxy benzoic acid and glucose-1-

phosphate. The PCA significantly (P <0.05) separated metal polluted from control

pots along PC2 (but PC2 accounted for only 12 % of the variance). The main

substrate responsible for this separation was γ-hydroxybutyric acid.

Out of all treatment pairs, the pair NM-P/M-P showed the highest value of

the Jaccard index (CJ = 0.82). The lowest values of the Jaccard index were found for

the pairs M-UP/NM-P (CJ = 0.43) and M-UP/NM-UP (CJ = 0.48).


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Figure 7.2: Principal component analysis from absorbance values obtained in the third harvest with the Biolog EcoPlatesTM at an incubation time of 40 h. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. PC1 and PC2 account for 76 and 12 % of the variance, respectively.

Cumulative respiration curves corresponding to the third harvest (Figure 7.3)

show that, in both control and metal polluted soils, the presence of sorghum led to

significantly higher values of soil basal respiration. In unplanted pots, metal addition

resulted in significantly lower values of soil basal respiration.

With regard to SIR with glucose (data not shown), after 6 h of incubation, M-

UP pots showed significantly (P <0.05) lower values (mean SIR = 59.8 μg CO2-C g-

1 DW soil) than all the other pots [mean SIR ranged from 80.1 (NM-UP) to 92.8

(M-P) μg CO2-C g-1 DW soil]. After 48 h of incubation (by this time, cell division

has most likely occurred), metal polluted planted and unplanted pots showed

significantly higher values of SIR-glucose (755.3 and 690.9 μg CO2-C g-1 DW soil,

respectively) than their corresponding non-metal polluted planted and unplanted

controls (726.4 and 634.9 μg CO2-C g-1 DW soil, respectively). In addition, SIR-

glucose for planted pots (both metal and non-metal polluted) was significantly

higher than in their corresponding unplanted controls.


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Figure 7.3: Values of cumulative basal respiration at different incubation times obtained in the third harvest. NM-UP: no metal, unplanted; NM-P: no metal, planted; M-UP: metal, unplanted; M-P: metal, planted. Lower case letters refer to significant differences (P <0.05 or lower) among treatments, according to Fisher´s PLSD-test, at 35 days of incubation.

In relation to SIR with the model rhizodeposit solution (data not shown), after

6 h of incubation, planted and unplanted metal polluted soils showed significantly

lower values (17.7 and 10.5 μg CO2-C g-1 DW soil, respectively) than corresponding

planted and unplanted non-polluted controls (21.6 and 17.5 μg CO2-C g-1 DW soil,

respectively), and metal and non-metal planted pots showed significantly higher

values than the respective unplanted controls. Similar results were observed after 48

h of incubation. Thus, unlike SIR-glucose, lower values of SIR-rhizodeposit were

always found in metal polluted than control non-polluted pots.

When comparing SIR values between both substrates (glucose versus rhizodeposit), after 6 h of incubation, values of SIR-glucose were significantly

higher than SIR-rhizodeposit values. By contrast, after 48 h, SIR-rhizodeposit values

were always higher than those obtained with glucose (in some cases the differences

were not statistically significant).


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Although the differences were not statistically significant, values of QR were

higher in planted than unplanted pots and lower in metal polluted than control soils

(QR for NM-UP, NM-P, M-UP and M-P were 19.7 ± 3.0, 23.2 ± 1.0, 15.2 ± 1.7 and

20.8 ± 2.3, respectively).

Values of extractable K+ were significantly lower in planted than unplanted

pots and significantly higher in metal polluted than control soils (values for NM-UP,

NM-P, M-UP and M-P were 280.8, 111.3, 328.5 and 178.3 mg kg-1, respectively).

Values of extractable P were significantly lower in planted than unplanted pots and

in metal polluted than control soils (values for NM-UP, NM-P, M-UP and M-P pots

were 98.0, 80.8, 75.5 and 67.3 mg kg-1, respectively). Values of EC were significantly

higher in planted than unplanted pots (on average, values of EC for planted and

unplanted pots were 2566 and 2308 µS cm-1, respectively). No differences among

treatments were found for the remaining soil physicochemical parameters here

determined (pH, OM, total N, C/N).

At the end of the experiment, the phytoremediated soils were still significantly

more phytotoxic than control non-polluted soils (values of GI for NM-UP, NM-P,

M-UP and M-P pots were 96.8 ± 4.3, 95.3 ± 5.4, 78.5 ± 3.8 and 78.1 ± 1.5,

respectively). Indeed, metal polluted soils were significantly (P <0.005) more

phytotoxic than control non-polluted soils (no significant differences were found

between planted and unplanted pots).

7.5 Discussion

7.5.1 Metal phytoextraction by sorghum plants

Our sorghum plants proved to be highly tolerant to metal pollution and

capable of reaching high biomass values in the presence of metals. In the first two

harvests, values of shoot Cd concentrations in metal polluted pots were higher than

100 mg Cd kg-1 DW, the threshold value for hyperaccumulators indicated by Baker

et al. (2000). However, in the third harvest, the bioconcentration factors in metal

polluted pots were well below the threshold value of 10 considered for a

phytoextraction process to be feasible (McGrath et al., 2006). For both metals, the

shoot-to-root metal concentration ratio was well below 1 (by contrast,


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hyperaccumulator plants are characterized by a shoot-to-root metal concentration

ratio >1) (Baker, 1981). In the literature, there are not many reports on the metal

tolerance and phytoextraction potential of sorghum. In a previous study, we found

sorghum plants to accumulate high amounts of metals in their shoots when grown

hydroponically (Hernández-Allica et al., 2008). By contrast, in a field trial, Marchiol

et al. (2007) found sorghum plants to have a poor capacity for metal

phytoextraction.

If one assumes that metal pollution is restricted to the active rooting zone of

sorghum (i.e., top 90-cm soil layer) (Mbuya et al., 2001), which would give a total

soil mass to remediate of 11,700 t ha-1 (considering a soil bulk density of 1.3 t m-3),

some theoretical calculations can be performed. Thus, if we consider that in, for

instance, Spain, sorghum plants have been reported to reach a mean biomass yield

of 29 t ha-1 (Fernández, 1998), according to our metal concentration data, 0.61% of

the total amount of Cd present in a soil polluted with 50 mg Cd kg-1 DW soil would

be removed in the first harvest. If we hypothesize that sorghum plants are able to

extract the same amount of Cd in consecutive crops, independently of the soil Cd

concentration, then it would take 154 consecutive crops to reduce the initial soil Cd

concentration used in our experiment to 3 mg kg-1 (the target end-point

concentration used by Lombi et al., 2001). In our region, an average of 3 cuttings of

sorghum per year might be feasible, leading to an estimated remediation time of 51

years. As Cd concentration in shoots might decrease with decreasing Cd content in

soil, this calculation represents only a theoretical abstraction and a clear

overestimate of the reality. Indeed, as metals are removed from the soil by

successful croppings, the available metal concentration is expected to decrease (Van

Nevel et al., 2007). Although this change may occasionally be linear, in most cases a

logarithmic decay upon succesive croppings could occur (Robinson et al., 1999).

Eriksson and Ledin (1999) reported a 30-40 % decrease in plant-available Cd as a

result of long-term cropping of Salix. In any case, this reduction of the bioavailable

metal pool is still a matter of debate since other authors (Keller and Hammer, 2004;

Fischerová et al., 2006) have described a replenishment of the bioavailable pool. In

our experiment, the bioavailable CaCl2-extractable metal pool appears to be the

phytoavailable fraction of metals. Most likely, the lower shoot metal concentrations


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found in the third harvest, as compared to the first two harvests (Table 7.1), are due

to the decrease in the bioavailable pool of Cd and Zn observed in M-P pots.

7.5.2 Effect of metal pollution and phytoextraction on soil parameters

In general, microbial parameters (i.e., dehydrogenase activity, AWCD, basal

respiration, SIR-glucose, SIR-rhizodeposits, QR) show lower values in metal

polluted than control non-polluted soils. Actually, one of the lowest values of the

Jaccard index corresponded to the pair M-UP/NM-UP, indicating that, in the

absence of plants, metal pollution had a strong impact on the soil functional

diversity. Metals have frequently been reported to have a negative effect on soil

functioning and soil biological parameters (Giller et al., 1998; Kelly and Tate, 1998).

After all, metals are known to affect growth, morphology and metabolism of soil

microorganisms through functional disturbance, protein denaturation and

destruction of cell membrane integrity (Leita et al., 1995). Interestingly,

dehydrogenase activity was correlated to soil metal bioavailable fractions but not to

soil total metal concentrations, suggesting that the inhibitory effect of metals on

dehydrogenase activity was dependent on the bioavailable metal pool. Similar results

were reported by Hattori (1992) in sewage sludge amended soils. Inhibition of

enzyme activities in metal polluted soils reflects metal bioavailability because the

mechanisms that protect soil enzymes from inhibition by metals are likely to be the

same mechanisms limiting metal uptake by plants and soil organisms (Speir and

Ross, 2002). Then, the increase in dehydrogenase activity observed for M-P pots, as

compared to M-UP pots, in the third harvest (Table 7.3), may well be due to the

decrease in bioavailable metal concentration found in such pots (Table 7.2), together

with the stimulatory effect of plants on soil microbes (see below). Except for a few

enzymes like dehydrogenase, most soil enzymes have a significant portion of the

enzymatic activity associated with abiontic enzymes (Dick, 1997; Nannipieri et al.,

2002). By contrast, dehydrogenase requires the organization of the living

intracellular environment to express its activity and then it is a measure of the

activity of physiologically active microorganisms (Speir and Ross, 2002). That is why

the most widely studied enzyme indicator of soil biological activity is dehydrogenase

(because it exists only in viable cells) (Dick, 1997). Nonetheless, measured


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dehydrogenase activity does not correlate consistently with other parameters of

microbial activity such as respiration, due to, for instance, extracellular phenol

oxidases and some common anions in soil, such as nitrate, acting as alternative

hydrogen acceptors (Dick, 1997; Speir and Ross, 2002). Another problem with the

dehydrogenase enzyme assay is that copper (Cu) can interfere with the analytical

procedure so that soils high in soil solution Cu show artificially low dehydrogenase

activity levels (Chander and Brookes, 1991). In our case, in metal polluted soils,

dehydrogenase, basal respiration, SIR-glucose and SIR-rhizodeposit showed similar

trends with higher values in planted than unplanted pots (see below).

Although further research is still needed to explain the higher values of SIR-

glucose found in metal polluted pots after 48 h of incubation, soil microorganisms

under stress have been reported to divert energy from growth to cell maintenance

function, leading to higher values of CO2 evolution (Killham, 1985). Unlike SIR-

glucose, lower values of SIR-rhizodeposit were always found in metal polluted than

control non-polluted pots and, in this respect, it is important to point out that SIR-

rhizodeposit is an ecologically more relevant parameter for testing rhizospheric

microbial communities than SIR-glucose (Dedourge et al., 2004). After 6 h of

incubation, values of SIR-glucose were significantly higher than SIR-rhizodeposit

values. It has been previously reported that soil microorganisms utilize glucose

rapidly and efficiently because of its being a simple, soluble, low molecular weight

substrate which diffuses quite readily within the soil matrix (Chowdhury et al.,

2000). In any case, an understanding of the mechanisms by which rhizodeposits

affect soil community structure is beyond the intention of this study.

Likewise, it has been observed that all microbial parameters measured (i.e.,

dehydrogenase activity, AWCD, basal respiration, SIR-glucose, SIR-rhizodeposits,

QR) show higher values in planted than unplanted pots. As compared to bare soil,

vegetated soils are commonly described as having higher rates of microbial activity

and biomass, due to the presence of easily metabolizable root exudates (e.g., sugars,

amino compounds, organic acids, fatty acids, growth factors, nucleotides) and

surfaces for microbial colonization (Curl and Truelove, 1986; Grayston et al., 1997).

In similar phytoextraction experiments with T. caerulescens plants, higher values of


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biological activity were also found in rhizosphere versus non-rhizosphere soil

(Hernández-Allica et al., 2006a; Wang et al., 2006).

The values of AWCD, basal respiration and SIR-glucose obtained in M-P soils

at the end of the experiment were similar to those found in NM-P pots.

Furthermore, out of all treatment pairs, when applied to Biolog EcoPlatesTM data,

the highest value of the Jaccard index corresponded to the pair NM-P/M-P. Then,

it can be concluded that, as a result of the phytoextraction process, which includes

both plant growth and metal phytoextraction, the functioning of the

phytoremediated soil has been restored. Indeed, as abovementioned, regarding the

recovery of soil functioning derived from a phytoextraction process, an ideal target

should be to return to the conditions of a valid control soil (i.e., a vegetated,

unpolluted soil of similar physicochemical properties and subjected to the same

edaphoclimatic conditions). However, at the end of the experiment, according to

the germination test, the phytoremediated soils were still significantly more

phytotoxic than control non-polluted soils. This discrepancy between data obtained

with the germination test versus those obtained through the determination of soil

microbial parameters is not surprising because the former reflect only the effect of

metal pollution on the germination of a specific plant species while the latter reflect

the status of the soil microbial community, not necessarily behaving in a similar way.

Although CLPPs analysis by Biolog EcoPlatesTM has been criticised because of

its being prone to the biases inherent to methods measuring diversity under culture

conditions (Preston-Mafham et al., 2002), here it proved to be a very useful tool,

capable of clearly differentiating between treatments. Differences between

treatments were observed for substrates that belonged to different classes (e.g.,

amino acid, organic acid), but not regarding patterns of substrate class utilization.

Interestingly, five of the substrates that defined the plant treatment (L-asparagine, L-

phenylalanine, L-serine, D-xylose and 4-hydroxy benzoic acid) corresponded to C

sources reported as constituents of root exudates (Campbell et al., 1997).

Finally, regarding physicochemical parameters, it was concluded that they are

not as sensitive as biological indicators for the assessment of the effect of metal

pollution on soil functioning, as previously suggested by Mijangos et al. (2006).


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7.6 Conclusions

To avoid the inconvenience of having to sow again the phytoextracting plant

after each harvest, an interesting approach, worthy of in-depth study, is to use

perennial plant species able to regrow in the polluted soil after harvesting. In this

work, sorghum plants were able to accumulate high levels of Cd in their shoots

while maintaining a high biomass yield.

In terms of the values obtained for many of the soil microbial parameters here

determined, phytoremediated and control (vegetated) soils were very similar at the

end of the experiment and, then, it was concluded that, as a result of the

phytoextraction process, which includes both plant growth and metal

phytoextraction, the functioning of the phytoremediated soil was restored.

However, most importantly, although the phytoextracted soil recovered its

functionally, it was still more phytotoxic than the control non-polluted soil.

8. effects of chelates on plants and soil microbial community: comparison of edta and edds for lead phytoextraction

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8. EFFECTS OF CHELATES ON PLANTS AND SOIL MICROBIAL COMMUNITY: COMPARISON OF EDTA AND EDDS FOR LEAD

PHYTOEXTRACTION

Epelde et al. (2008), published in Science of the Total Environment 401, 21-28

8.1 Abstract

Most studies on chelate-induced phytoextraction have focused on EDTA-

mediated Pb phytoextraction. But EDTA and the formed EDTA-Pb complexes

have low biodegradability and high solubility in soil, resulting in an elevated risk of

adverse environmental effects. EDDS is an easily biodegradable chelating agent that

has recently been proposed as an environmentally sound alternative to EDTA.

Consequently, a greenhouse experiment, using a completely randomized factorial

design with four replications, was carried out to compare the potential of EDTA

and EDDS for chelate-induced Pb phytoextraction with Cynara cardunculus, as well as

to investigate the toxicity of these two chelates to both cardoon plants and soil

microorganisms. The effects of chelate addition on soil microbial communities were

studied through the determination of a variety of biological indicators of soil quality

such as soil enzyme activities, basal and substrate-induced respiration, potentially

mineralizable nitrogen, and community level physiological profiles. EDTA was

much more efficient than EDDS for the enhancement of root Pb uptake and root-

to-shoot Pb translocation. In a soil polluted with 5000 mg Pb kg-1, as a result of the

addition of 1 g EDTA kg-1 soil, a value of 1332 mg Pb kg-1 DW shoot was obtained.

EDDS application resulted in a shoot Pb accumulation of only 310 mg kg-1 DW.

Plants treated with EDDS showed lower values of biomass than those treated with

EDTA. EDDS proved to be rapidly degraded, and less toxic to the soil microbial

community in control non-polluted soils. Pb-polluted EDDS-treated soils showed

significantly higher values of basal and substrate-induced respiration than those

treated with EDTA. Although EDDS had a lower capacity to enhance Pb

phytoextraction than EDTA, it has the advantage of rapid biodegradation.


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8.2 Introduction

The application of chelating agents to the soil has been reported to increase

plant metal uptake and translocation, thus opening a wide range of possibilities for

metal phytoextraction (Blaylock et al., 1997; Garbisu and Alkorta, 2001; Garbisu et

al., 2002; Alkorta et al., 2004d). For chelate-induced phytoextraction, plants should

be fast-growing, tolerant to grow in polluted soils, easily cultivated using well-known

agricultural practices, and produce a large biomass (McGrath et al., 2002). Cardoon

(Cynara cardunculus L.) plants fulfil most of these requirements and, in addition, are

well adapted to a wide range of soils and tolerant to adverse climatic conditions,

making them interesting candidates for chelate-induced phytoextraction

(Hernández-Allica et al., 2007).

Most studies on chelate-induced phytoextraction have focused on EDTA

(ethylene diamine tetracetic acid)-mediated lead (Pb) phytoextraction (McGrath et

al., 2002). Nevertheless, EDTA and the formed EDTA-Pb complexes have low

biodegradability and high solubility in soil, resulting in an elevated risk of adverse

environmental effects due to metal mobilization and long persistence (Alkorta et al.,

2004b, d). In this respect, the amount of Pb taken up by plants has been reported to

be much smaller than the amount of Pb mobilized from the soil during EDTA-

induced Pb phytoextraction (Chen et al., 2004). EDDS (ethylene diamine

disuccinate) was proposed as an alternative for chelate-induced metal

phytoextraction (Grčman et al., 2003). EDDS has been shown to be easily

biodegradable (Jaworska et al., 1999), to form strong complexes with transition

metals and radionuclides (Jones and Williams, 2001), to cause a much smaller

leaching of Pb down the soil profile than EDTA (Grčman et al., 2003), and to be

less toxic to soil microorganisms (Grčman et al., 2003).

Contradictory results can be found in the literature regarding the capacity of

EDTA and EDDS to induce plant Pb accumulation. Grčman et al. (2003) found

that EDDS and EDTA were equally efficient for the induction of Pb accumulation

in Chinese cabbage shoots. By contrast, under similar experimental conditions, Kos

and Leštan (2003) reported that EDTA was almost twice as efficient as EDDS for

the induction of Pb accumulation in Chinese cabbage shoots. Likewise, conflicting

data can be found in the literature regarding the phytotoxicity of these chelates and


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the formed metal-chelate complexes. Grčman et al. (2003) observed a significant

phytotoxic effect with EDTA but not with EDDS on Brassica rapa. Conversely, Luo

et al. (2005) observed a greater plant growth inhibition in EDDS-treated plants, as

compared to those treated with EDTA. Meers et al. (2005) did not observe any

visual toxicity symptoms or growth inhibition in plants treated with EDDS or

EDTA.

Finally, the ultimate goal of any soil (phyto)remediation process must be not

only to remove the contaminant(s) from the polluted site but to restore soil quality,

i.e. the continued capacity of soil to perform or function according to its potential

(Hernández-Allica et al., 2006a). Although to date much more emphasis has been

placed on physicochemical indicators of soil quality (Mijangos et al., 2006),

biological indicators (e.g., enzyme activities, microbial biomass, basal and substrate-

induced respiration, mineralizable N, structural and functional biodiversity, and so

on) are becoming increasingly used due to their being more sensitive to changes in

the soil as well as to their capacity to provide information that integrates many

environmental factors (Alkorta et al., 2003a, b). We hypothesized that biological

indicators of soil quality are useful monitoring tools (i) to assess the efficiency of a

chelate-induced phytoextraction process and (ii) to determine the chelate-induced

toxic effect on the soil microbial community.

The objectives of this study were (i) to compare the capacity of EDTA and

EDDS to solubilize Pb from an artificially polluted soil and induce Pb accumulation

in cardoon plants, and (ii) to investigate the toxicity of these two chelates to both

cardoon plants and soil microorganisms [in this latter case, through the

determination of a variety of biological indicators of soil quality, such as enzyme

activities, basal and substrate induced respiration, mineralizable N, and community

level physiological profiles (CLPPs)].


8.3.1 Greenhouse experiment

Soil was collected from the upper 20 cm of a natural grassland located in

Larrauri (Basque Country, northern Spain). The physicochemical properties of this


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soil (Table 8.1) were determined according to standard methods (MAPA, 1994).

Immediately after collection, the soil was air-dried for 24 h to allow sieving through

a 5 mm mesh and then stored at 4 ºC.

Table 8.1: Selected physicochemical parameters of the soil used in this study.

Parameter Value

pH 6.9

Organic matter (%) 14.4

C/N 13

WHC* (%) 35.5

Coarse sand (%) 15.7

Fine sand (%) 36.3

Loam (%) 24.4

Clay (%) 23.7

Pb (mg kg-1) 46.5

*WHC: water holding capacity at 33 kPa

Soil portions equivalent to 250 g of dried soil were individually contaminated

(by mechanical mixing in plastic bags) with two different concentrations of Pb (2500

and 5000 mg Pb kg-1 DW soil) as Pb(NO3)2 dissolved in water, and then placed in

350 cm3 plastic pots. Control, non-polluted soil portions were similarly amended

with KNO3 to compensate for the amount of nitrate added to the polluted soil.

Control and polluted soil portions were allowed to settle for 2 weeks (at 25 ºC and

70% water holding capacity-WHC) in the plastic pots.

The experiment was carried out in a greenhouse under controlled conditions

with pots arranged in a completely randomized factorial design with four

replications. Temperature (15-30 ºC) and humidity (50-95% relative humidity) were

electronically monitored and controlled by means of an automatic ventilating and

heating system. Initially, seeds of cardoon plants were germinated in trays on John

Innes No. 2 compost. One week later, cardoon seedlings (one emerging seedling per

pot) were transplanted to the pots and left to grow for four months. Throughout

the experimental period, plants were bottom-watered using deionized water, so that

soils were kept at 60-70% of their WHC at 33 kPa. Four months after transplanting,


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the following chelate treatments were applied: (i) a single dose of 1 g EDTA kg-1

DW soil (as reported by Lombi et al., 2001) and (ii) a single dose of 1 g EDDS kg-1

DW soil. Four control, untreated pots were also included in the experiment.

8.3.2 Plant metal accumulation

Seven days after chelate treatment, cardoon plants were harvested by cutting

the shoots exactly at the swelling formed in the root to shoot junction. Roots and

shoots were washed thoroughly with deionized water to remove soil particles,

blotted with tissue paper, and their fresh weights recorded. Plant material was dried

in an oven at 70 ºC for 48 h and dry weights recorded. Then, shoots and roots were

prepared for acid digestion by milling in a ball-mill (Restch) (2 mm mesh).

Subsamples (0.2 g) of dried plant tissue were digested with a mixture of

HNO3/HClO4 (Zhao et al., 1994) and Pb in the digest was determined using an

atomic absorption spectrometer (Spectra AA-250 plus, Varian, Australia) equipped

with an automatic sampler (Sps-5, Varian, Australia). The reliability of the digestion

and analytical procedure was tested including blanks and standards of plant leaves

(IPE 150 and IPE 160, 2nd semester 2004, Wageningen University, Holland) with

every batch of sample digest. Percentage recoveries were between 95 and 105%.

8.3.3 Soil solution analysis

In order to study the effect of chelates on Pb concentration in the soil

solution, 2500 mg kg-1 Pb-polluted pots were fitted with MOM-type Rhizons

(Eijkelkamp Agrisearch Equipment, The Netherlands). MOM-type Rhizons are

porous plastic samplers frequently used for the extraction of soil solution free of

microbial and colloidal contamination (Knight et al., 1998). One and 7 days after

chelate addition, soil solution was extracted from the pots and analyzed for Pb using

an atomic absorption spectrometer. Reagent blanks and at least two replicates of all

samples were used to ensure accuracy and precision in the analysis. The rate of

EDDS degradation was assessed, for three weeks, in the 2500 mg kg-1 Pb-polluted

pots according to Vandevivere et al. (2001). In this assay, filtered water extracts were

diluted to less than 2 mM EDDS and acidified to pH 2.1 with HNO3. Following


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addition of CuSO4 to 3 mM and 30 min incubation, absorbance was measured at

670 nm. In the current study, the rate of EDTA degradation in soil was not

determined. However, EDTA has previously been reported to degrade very slowly

in soil, i.e. 5 months after EDTA application, EDTA-metal complexes were still

present in the soil pore water (Lombi et al., 2001).

8.3.4 Soil biological indicators

Biological parameters were determined in control (non-polluted) and 2500 mg

kg-1 Pb-polluted soils. Soils were sieved to <2 mm and stored in fresh at 4 ºC.

Enzyme activities (i.e., dehydrogenase, acid phosphatase, β-glucosidase, and

arylsulphatase) were determined according to Dick et al. (1996) and Taylor et al.

(2002). Dehydrogenase (EC 1.1) activity is an intracellular process that occurs in

every viable microbial cell and is measured to determine overall microbiological

activity of soil (Nannipieri et al., 2002). Acid phosphatase (EC 3.1.3.2) is an

important enzyme in the P cycle because it provides P for plant uptake by releasing

phosphate from organic P (Eivazi and Tabatabai, 1977). β-glucosidase (EC 3.2.1.21),

a glycosidase important in the C cycle, hydrolyses carbohydrates with a β-D-

glycoside bond by splitting off the terminal β-D-glucose (Schinner et al., 1996) and

then plays a central role in the hydrolysis of polymers of plant residues, such as the

disaccharide cellobiose, releasing glucose as an important energy source for soil

heterotrophic organisms. Arylsulphatase (EC 3.1.6.1) is the enzyme that catalyses

the hydrolysis of organic sulphate ester releasing sulphate, the plant available form

of S (Rodríguez-Loinaz et al., 2008).

Potentially mineralizable N, an indicator of biologically active soil N, was

measured as described by Powers (1980). For soil basal microbiological respiration

(an indicator of overall microbiological activity), soil samples were placed in airtight

jars and moistened to 60 % WHC. The soils were incubated for three days at 30ºC

together with vials containing 0.2 M NaOH. The CO2 evolved during the incubation

period was determined by titration with 0.1 N HCl (ISO 16072 Norm). Substrate-

induced respiration, a measure of potentially active microbial biomass, was

determined by adding 10000 mg C kg-1 DW soil as glucose and then measuring the

respiration rate after 6 hours of incubation (ISO 17155 Norm). Finally, metabolic


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quotients (qCO2) were calculated as the ratio between values of basal respiration and

substrate-induced respiration.

For the analysis of CLPPs, Biolog EcoPlatesTM were used. Soil samples were

extracted by agitating in an orbital shaker (125 rev min-1) 1 g DW soil with 10 mL of

autoclaved Mili-Q ultra pure water for 1 h. After shaking, samples were left to settle

down and then a 1:100 dilution (1 mL soil suspension:100 mL autoclaved Mili-Q

ultra pure water) was inoculated onto the Biolog EcoPlatesTM. The plates were

incubated at 30 ºC and colour development was read at 595 nm using a micro plate

reader (Anthos Zenyth 3100). For each reading time, raw absorbance data were

corrected by subtracting the zero hour reading point and the absorbance value given

by the control well. Average well colour development (AWCD) was determined by

calculating the mean of every well’s absorbance value at each reading time. The

plates corresponding to an incubation time of 48 h were chosen for further

calculations (at approximately this incubation time, the highest rate of microbial

growth was observed in the Biolog EcoPlatesTM). The number of utilized substrates

(i.e., the number of substrates with an absorbance value > 0.25; this value marked

the beginning of the exponential phase in the Biolog EcoPlatesTM), equivalent to

species richness, S, was calculated at this 48 h incubation time. Similarly, Shannon´s

diversity (H’=-∑pilog2pi) and evenness (J’=H’/Hmax=H’/log2S) indexes (Magurran,

2004) were calculated, considering absorbance values at each well as equivalent to

species abundance.


Statistical analyses were performed using StatView software (SAS Institute

Inc.). Differences among treatments were analyzed by analyses of variance

(ANOVA) using Stat View software. Fisher´s PLSD-test was used to establish the

significance of the differences among means.


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8.4 Results

8.4.1 Chelate effects on soil Pb mobilization Much higher values of Pb concentration in soil solution were found in EDTA-

treated pots than in those treated with EDDS. Twenty-four hours after chelate

addition, values of Pb concentration in soil solution were 2.5-fold higher in EDTA-

treated pots (340 mg Pb L-1), as compared to EDDS-treated pots (139 mg Pb L-1).

At harvest (7 days after chelate addition), values of Pb concentration in soil solution

were 29.8-fold higher in EDTA-treated pots (264 mg Pb L-1), as compared to

EDDS-treated pots (9 mg Pb L-1).

Figure 8.1 shows the rate of EDDS degradation in the 2500 mg kg-1 Pb-

polluted soil, fitted with an exponential decay equation. As seen in this Figure 8.1,

EDDS showed a half-life in this polluted soil of 24 h.

Figure 8.1: Rate of EDDS degradation in the 2500 mg kg-1 Pb-polluted soil, fitted with an exponential decay equation.

8.4.2 Pb accumulation in cardoon plants

For all treatments, increasing values of soil Pb concentration led to increasing

values of root and shoot Pb concentration (Table 8.2). In control pots (no chelate


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added), root Pb concentrations were much higher than shoot Pb concentrations.

The root-to-shoot translocation (shoot metal concentration/root metal

concentration) induced by EDTA (and not EDDS; Table 8.2) resulted in relatively

high values of shoot Pb concentration (1332 mg Pb kg-1 DW tissue) in the 5000 mg

kg-1 Pb-polluted pots.

As expected, chelate addition (both EDTA and EDDS) led to higher values of

root and shoot Pb concentration, as compared to control pots. EDTA was much

more effective than EDDS for the enhancement of both root Pb uptake and root-

to-shoot Pb translocation (Table 8.2). Higher values of shoot Pb concentration were

observed in EDTA-treated pots than in those treated with EDDS (i.e., 8.6- and 4.3-

fold higher for the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively). This

effect was less apparent in roots, i.e. in the 5000 mg kg-1 Pb-polluted soils, the

addition of EDTA led to 1.6-fold higher values of root Pb concentration than the

addition of EDDS.

Table 8.2: Effect of EDTA and EDDS on plant Pb accumulation (mg Pb kg-1 DW tissue) and translocation factor (TF) in cardoon plants subjected to different levels of Pb pollution in soil. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test (lower case: among chelate treatments for shoots, roots or TF; upper case:

among Pb concentrations for shoots, roots or TF). Mean values (n = 4) ± standard errors.

46.5 2500 5000

mg Pb kg-1 DW soil

Control 0.1 ± 0.1aA 14.9 ± 2.3aA 43.2 ± 3.1aA

EDTA 46.2 ± 20.3aA 666.8 ± 229.9bB 1332.0 ± 244.3bC Shoot

EDDS 0.9 ± 0.0aA 77.2 ± 17.9aA 310.2 ± 100.7aA

Control 8.3 ± 1.5aA 675.6 ± 16.8aA 1961.1 ± 96.8aB

EDTA 91.1 ± 44.3bA 1450.7 ± 67.3bB 6695.2 ± 711.2bC Root

EDDS 12.2 ± 2.9aA 1412.2 ± 132.1bB 4165.8 ± 607.9cC

Control 0.015 ± 0.011aA 0.022 ± 0.003aA 0.022 ± 0.002aA

EDTA 0.518 ± 0.100bA 0.461 ± 0.138bA 0.203 ± 0.036aB TF

EDDS 0.086 ± 0.018aA 0.053 ± 0.008aA 0.076 ± 0.024aA


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Furthermore, in EDDS-treated pots, the bioconcentration factor (BF = shoot

metal concentration/soil metal concentration) was 0.03 and 0.06 for the 2500 and

5000 mg kg-1 Pb-polluted pots, respectively. In EDTA-treated pots, the BF was 0.27

for both the 2500 and 5000 mg kg-1 Pb-polluted pots.

8.4.3 Plant biomass Table 8.3: Effect of EDTA and EDDS on shoot, root and total (shoot + root) dry weight (in

grams) of cardoon plants subjected to different levels of Pb pollution in soil. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test (lower case: among chelate treatments for shoots, roots or total; upper case: among Pb concentrations for

shoots, roots or total). Mean values (n = 4) ± standard errors.

46.5 2500 5000

mg Pb kg-1 DW soil

Control 3.5 ± 0.1aA 4.1 ± 0.4aA 2.7 ± 0.1aB

EDTA 2.6 ± 0.2bA 3.3 ± 0.3abB 2.1 ± 0.1bA Shoot

EDDS 2.6 ± 0.2bA 2.6 ± 0.2bA 2.0 ± 0.3bA

Control 2.2 ± 0.1aA 2.0 ± 0.1aA 1.4 ± 0.2aB

EDTA 1.6 ± 0.2bA 1.5 ± 0.1bAB 1.1 ± 0.1abB Root

EDDS 1.3 ± 0.2bA 0.9 ± 0.1cAB 0.8 ± 0.1bB

Control 5.7 ± 0.1aA 6.1 ± 0.3aA 4.0 ± 0.3aB

EDTA 4.1 ± 0.2bA 4.8 ± 0.3bA 3.2 ± 0.1abB Total

EDDS 3.8 ± 0.2bA 3.5 ± 0.2cAB 2.8 ± 0.3bB

For all treatments, lower values of shoot, root and total (shoot + root)

biomass were obtained at 5000 mg kg-1 Pb-polluted pots, as compared to 2500 mg

kg-1 Pb-polluted pots (Table 8.3). In non-polluted pots, chelate addition led to lower

values of shoot, root and total biomass, as compared to control plants (no chelate

added). In Pb-polluted soils, EDDS induced a greater reduction in shoot, root and

total biomass than EDTA. As compared to control plants, EDTA treatment

resulted in 20 and 22% lower values of shoot biomass in the 2500 and 5000 mg kg-1

Pb-polluted pots, respectively. On the other hand, as compared to control plants,

EDDS treatment resulted in 37 and 26% lower values of shoot biomass in the 2500

and 5000 mg kg-1 Pb-polluted pots, respectively. This effect was more marked for

root biomass: as compared to control plants, EDTA-treatment led to 25 and 21%


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lower values in the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively; EDDS-

treatment led to 55 and 43% lower values in the 2500 and 5000 mg kg-1 Pb-polluted

pots, respectively. Finally, regarding total biomass, EDTA-treatment led to 21 and

20% lower values in the 2500 and 5000 mg kg-1 Pb-polluted pots, respectively;

EDDS-treatment led to 43 and 30% lower values in the 2500 and 5000 mg kg-1 Pb-

polluted pots, respectively.

8.4.4 Soil biological indicators The effect of chelate addition on soil biological properties was determined for

non-polluted and 2500 mg kg-1 Pb-polluted pots. In non-polluted pots, the addition

of EDTA, but not of EDDS, significantly inhibited dehydrogenase activity (Table

8.4). In 2500 mg kg-1 Pb-polluted pots, the addition of EDDS, but not of EDTA,

led to significantly higher values of β-glucosidase (Table 8.4). In both non-polluted

and 2500 mg kg-1 Pb-polluted pots, no significant differences were found for

arylsulphatase, acid phosphatase and potentially mineralizable N between controls

(no chelate added) and chelate-treated pots. Finally, in the absence of chelates, the

presence of 2500 mg Pb kg-1 did not have any inhibitory effect on soil enzymes and

potentially mineralizable N (as compared to those values obtained in non-polluted

pots) (Table 8.4). Table 8.4: Effect of EDTA and EDDS on soil enzyme activities and potentially mineralizable nitrogen in non-polluted and 2500 mg kg-1 Pb-polluted soils. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors.

Dehydrogenase Arylsulphatase β-glucosidase Acid phosphatase Potentially mineralizable N

mg INTF kg-1

DW soil h-1 mg PN kg-1 DW soil h-1 mg N-NH4 kg-1 DW soil

Control 448.3 ± 20.1a 202.3 ± 16.8ab 227.8 ± 6.0a 1070.0 ± 52.6a 8.1 ± 0.3a

EDTA 294.5 ± 15.2b 182.2 ± 10.8a 241.4 ± 5.2ab 1159.4 ± 58.5a 9.3 ± 1.1a 46.5

EDDS 420.1 ± 56.8ab 204.5 ± 11.7ab 242.1 ± 3.5ab 1168.8 ± 64.1a 9.0 ± 1.2a

Control 440.4 ± 36.9a 233.7 ± 4.4b 233.4 ± 5.3a 1038.3 ± 116.1a 10.0 ± 0.8a

EDTA 325.9 ± 22.0ab 211.2 ± 6.5ab 245.1 ± 5.7ab 1233.6 ± 39.2a 8.5 ± 0.6a 2500

mg

Pb k

g-1 D

W so

il

EDDS 441.9 ± 69.9a 219.1 ± 8.3b 252.5 ± 4.9b 1236.5 ± 45.6a 7.8 ± 0.1a


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Figure 8.2: Effect of EDTA and EDDS on (a) soil basal respiration, (b) substrate-induced respiration and (c) microbial metabolic quotient (qCO2) in control non-polluted and 2500 mg kg-1 Pb-polluted pots. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors.


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Concerning soil respiration parameters (Fig. 8.2), EDTA addition led to

significantly lower values of basal respiration in both non-polluted and 2500 mg kg-1

Pb-polluted soil (Fig. 8.2a). The addition of EDDS also resulted in a significant but

lower inhibition of soil basal respiration in the non-polluted soil. With regard to

SIR, it was observed that EDTA treatment caused a significant reduction in this

parameter only in the 2500 mg kg-1 Pb-polluted pots (Fig. 8.2b). By contrast, EDDS

addition had no significant effect on SIR. Finally, the microbial metabolic quotient

(i.e., qCO2 = basal respiration/SIR) significantly decreased as a result of both

EDTA and EDDS treatment (Fig. 8.2c). In any case, EDTA addition resulted in

significantly lower values of qCO2, as compared to EDDS. In the absence of

chelates (control plants), similar values of these three respiratory parameters were

found in both non-polluted and 2500 mg kg-1 Pb-polluted pots (Fig. 8.2).

Data on soil microbial functional diversity obtained from the CLPPs are

summarized in Table 8.5. EDDS, but not EDTA, caused a significant increase in

species richness (S) and Shannon´s diversity (H’) in both non-polluted and 2500 mg

kg-1 Pb-polluted pots (Table 8.5). By contrast, no significant differences were

observed among treatments regarding AWCD and Shannon´s evenness (J’). In the

absence of chelates, the presence of 2500 mg Pb kg-1 led to significantly higher

values of S and H’.

Table 8.5: Effect of EDTA and EDDS on the AWCD and diversity indexes calculated from Biolog EcoPlatesTM absorbance data at an incubation time of 48 h. Values followed with different letters are significantly different (P<0.05 or lower) according to Fisher´s PLSD-test. Mean values (n = 4) ± standard errors. AWCD: average well colour development; S = richness; H’ = Shannon´s diversity index; J’ = Shannon´s evenness index.

AWCD S H’ J’

Control 0.49 ± 0.08a 15.67 ± 1.20a 2.64 ± 0.07a 0.67 ± 0.00a

EDTA 0.55 ± 0.10a 15.33 ± 0.88a 2.59 ± 0.05a 0.66 ± 0.00a 46.5

EDDS 0.62 ± 0.08a 19.67 ± 1.20bc 2.85 ± 0.06bc 0.66 ± 0.00a

Control 0.51 ± 0.03a 18.33 ± 0.33b 2.77 ± 0.01b 0.66 ± 0.00a

EDTA 0.57 ± 0.03a 18.67 ± 0.33b 2.80 ± 0.01b 0.66 ± 0.00a 2500

m

g Pb

kg-

1 DW

soil

EDDS 0.80 ± 0.06b 21.33 ± 0.33c 2.93 ± 0.02c 0.66 ± 0.00a


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8.5 Discussion

8.5.1 Chelate effects on soil Pb mobilization

In the current study, we investigated the potential of EDTA and EDDS for

chelate-induced Pb phytoextraction using cardoon plants and taking into account,

most importantly, the possible detrimental effect of chelate addition on soil

microbial communities. After all, microorganisms depend directly on the soil

solution for uptake of nutrients and water, and thus chelate-elevated metal

concentrations could lead to toxic effects for soil microorganisms which are

critically important for soil functioning (Kos and Leštan, 2004).

In our study, EDDS was less effective than EDTA for the enhancement of

soil Pb solubilization. This is not an unexpected result because EDTA has been

reported to have a stronger affinity for Pb (log Ks = 17.88) than EDDS (log Ks =

12.70) (Luo et al., 2005). The fast rate of EDDS biodegradation might also be an

important factor determining the differences in Pb solubilization efficiency. In our

soil, we obtained a degradation half-life of 24 h for EDDS. Jaworska et al. (1999)

reported a calculated half-life of 2.5 d for EDDS in sludge amended soil. Although

we did not determine the rate of EDTA degradation in soil, this chelate has

previously been reported to degrade very slowly, i.e. 5 months after EDTA

application; EDTA-metal complexes were still present in the soil pore water (Lombi

et al., 2001). Twenty-four hours after chelate addition, in the presence of 2500 mg

Pb kg-1, the concentration of Pb in the soil solution of our EDDS-treated pots was

approximately 40% of that found in EDTA-treated pots. Then, if we consider that,

at that time, approximately 50% of the EDDS was already degraded in our soil, it

could be speculated that, while present, EDDS showed a similar capacity to

solubilise Pb than EDTA. Most likely, the differences between EDTA and EDDS

regarding their capacity to solubilize Pb would be smaller at lower Pb

concentrations with a Pb:chelate ratio close to 1. In this case, the capacity of

chelates to solubilize Pb is strongly dependent on soil pH and the presence of other

ions such as Ca2+ and Fe2+. Tandy et al. (2006) indicated that at a soil pH of 7 and a

Pb:chelate ratio of 1, EDDS was as efficient as EDTA for metal solubilization.

Finally, in a previous study with a natural soil polluted with Cd, Zn and Pb (Santos


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et al., 2006), we also found EDTA to be much more effective in soil Pb

solubilization than EDDS.

8.5.2 Pb accumulation in cardoon plants

Regarding shoot Pb accumulation, EDTA appeared much more efficient than

EDDS (Table 8.2). Although shoot Pb concentrations observed as a result of

EDTA addition did not reach the 10000 mg kg-1 threshold proposed by several

authors (Blaylock et al., 1997; Salt et al., 1998) for a feasible phytoextraction in the

field, they were relatively high (1332 mg kg-1 in the 5000 mg kg-1 Pb-polluted soil).

In agreement with our results, Luo et al. (2005) found that Pb translocation from

roots to shoots of corn and bean plants was higher in the presence of EDTA than

EDDS, and concluded that it was due to the stronger chemical affinity of EDTA

for Pb. Apart from EDDS´s weaker affinity for Pb and its lower capacity to

solubilize Pb, due to its high degradation rate, EDDS-mediated uptake was probably

restricted to the first 2-3 days after treatment which could explain, at least partly, the

observed lower efficiency of EDDS to induce Pb accumulation under our

experimental conditions. Conversely, in a previous study with Brachiaria decumbens plants growing in a natural polluted soil (Santos et al., 2006), we found EDDS to be

more efficient inducing Pb accumulation in shoots than EDTA (and also more

efficient than EDTA in stimulating the translocation of Pb from roots to shoots).

Differences in experimental conditions (e.g., plant species, presence of other metals,

type of soil, time of exposure and harvest, etc.) can explain some of the conflicting

results among chelate-induced Pb phytoextraction experiments. Finally, it has been

reported that both chelates are taken up and translocated to the shoots through the

same apoplastic and non-selective absorption pathways (Tandy et al., 2006;

Hernández-Allica et al., 2007).

8.5.3 Plant biomass

The phytotoxicity of both chelates was similar in control non-polluted pots (a

reduction in shoot biomass of around 25% was observed for both chelates) (Table

8.3). However, the lower values of Pb accumulation induced by EDDS, as


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compared to EDTA, could also be due to the higher phytotoxicity caused by this

chelate when applied to the Pb-polluted soil (Tables 8.3). In agreement with our

data, Luo et al. (2005) found a significant reduction in shoot DW as a result of

EDDS addition. On the contrary, in a biotest with red clover (Trifolium pratense L.),

Grčman et al. (2003) found a greater phytotoxic effect with EDTA than EDDS. In

all treatments where 10 mmol kg-1 EDTA or EDDS was applied, Kos and Leštan

(2003) observed visual symptoms (necrotic lesions on the leaves of Chinese

cabbage) of chelator toxicity (the effect was much less pronounced at lower chelate

concentrations). In a previous study with cardoon plants grown hydroponically

(Hernandez-Allica et al., 2007), we found EDTA to negatively affect plant

physiological parameters related to plant water transpiration. Both in the absence

and presence of metals, Tandy et al. (2006) did not find a significant EDDS-induced

(500 μM) phytotoxicity in hydroponically grown sunflower plants. This EDDS-

imposed phytotoxicity is an important factor to be considered for the practical

aspects of chelate application in the field. Since EDDS degrades quite fast, it should

be possible to schedule several gradual applications of small doses of this chelate

during the growing period, in an attempt to maximize shoot metal uptake and

reduce the risk of metal movement into groundwater (Alkorta et al., 2004d).

Unfortunately, this strategy would be impeded if the chelate had a high

phytotoxicity.

8.5.4 Soil biological indicators

The adverse effects of heavy metal contamination on soil microbial

communities have been widely demonstrated in numerous field and laboratory

studies (Giller et al., 1998; Kelly et al., 1999). However, Pb is a poorly bioavailable

metal and consequently might not have such a strong negative impact on soil

microbes. As a matter of fact, in our work, Pb pollution did not have a significant

effect on some bioindicators known to reflect the activity of soil microbial

communities (i.e., dehydrogenase activity, potentially mineralizable N, basal

respiration, and SIR) (Table 8.4, Fig. 8.2). By contrast, the presence of Pb did have a

positive impact on the capacity of the culturable portion of the microbial

community to respond to substrates, as indicated by the significantly higher values


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of S and H’ obtained in the 2500 mg kg-1 Pb-polluted soils, as compared to non-

polluted pots (Table 8.5). Then, we could speculate that the presence of Pb might

have induced the appearance of Pb-tolerant, culturable, fast growing, r-selected

microbial populations.

On the contrary, the effects of chelate addition on soil microbes in metal

contaminated soils have rarely been investigated (Grčman et al., 2003; Bouwman et

al., 2005; Ultra et al., 2005). Particularly, very little is known about the effects of

chelator amendment on soil microbial activity and community composition during

metal chelate-assisted phytoremediation (Chen et al., 2006). In non-polluted soils,

EDTA had a strong negative impact on the activity of the soil microbial population,

as indicated by its effects on soil respiration and dehydrogenase activity (Fig. 8.2,

Table 8.4). In non-polluted soils, EDDS also caused a significant inhibition of soil

basal respiration, but less pronounced than that observed with EDTA (Fig. 8.2).

Interestingly, in non-polluted pots, SIR, an indicator of potentially active microbial

biomass, was not significantly affected by any of these chelates (Fig. 8.2). Kos and

Leštan (2004) observed that 5 mmol kg-1 of EDDS increased SIR perhaps because it

increased the bioavailability of trace metals essential for microbial growth (in their

study, higher EDDS concentrations caused no increase in SIR). In a previous study,

they found lower values of SIR in soils treated with EDTA, as compared to those

treated with EDDS (Kos and Leštan, 2003). The lower values of qCO2 here

obtained in the presence of chelates, as compared to control soils (Fig. 2), could

indicate an increased metabolic efficiency in the conversion of substrates into

biomass, as suggested by Pirt (1975). EDDS is a naturally occurring substance in soil

where it is readily decomposed into benign degradation products (Grčman et al.,

2003), which could explain its lower toxicity for soil microbes, as compared to

EDTA. In fact, EDDS has previously been reported to cause less stress to soil

microorganisms, as indicated by the trans to cis phospholipid fatty acid ratio

(Grčman et al., 2003).

The higher values of AWCD, S and H’ found in Pb-polluted EDDS-treated

pots, as compared to Pb-polluted EDTA-treated pots, could also confirm the lower

toxicity of EDDS to soil microorganisms. However, in the case of these Pb-polluted

soils, the lower values of AWCD, S and H’ found in EDTA-treated versus EDDS-


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treated pots are most likely also due to the higher concentrations of Pb in soil

solution found in EDTA-treated pots.

Finally, it is important to emphasize that, since many chelates are toxic for

both plants and soil microorganisms and pose a considerable environmental

problem due to their leaching towards groundwater, environmentally safe methods

of chelate-induced phytoextraction must clearly be developed before steps towards

further development and commercialization of this phytoremediation technology

are taken (Alkorta et al., 2004d).

8.6 Conclusions

EDTA was much more efficient than EDDS for Pb phytoextraction with C. cardunculus. EDDS had a half-life in soil of 24 h and, when applied to a Pb-polluted

soil, caused more toxicity to cardoon plants than EDTA. On the other hand, in

control non-polluted soils, EDDS proved to be less toxic to the soil microbial

community than EDTA. Then, it was concluded that although EDDS had a lower

capacity to enhance Pb phytoextraction in cardoon plants than EDTA, it has the

advantage of rapid biodegradation.

9. evaluation of the efficiency of a phytostabilization process with bioloGical indicators of soil health

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9. EVALUATION OF THE EFFICIENCY OF A PHYTOSTABILIZATION PROCESS WITH BIOLOGICAL

INDICATORS OF SOIL HEALTH

Epelde et al., published in Journal of Environmental Quality (accepted)

9.1 Abstract A phytostabilization process which combined the addition of a synthetic

(CalcinitTM + urea + PK14% + calcium carbonate) or organic (cow slurry)

amendment with Lolium perenne L. growth was used to remediate a mine soil

moderately contaminated with Zn, Pb and Cd. The reduced toxicity caused by both

amendments allowed the establishment of a healthy L. perenne vegetation cover

which had a positive influence on soil properties, increasing the biomass, activity

and functional diversity of the soil microbial community. Beneficial effects of

phytostabilization on soil properties were more accentuated in organically amended

than in synthetically amended soils. Root-to-shoot translocation factors were smaller

in amended versus control plants indicating a reduction in the risk of metals entering

the food chain through phytostabilization. The sensitivity, rapid response, and

integrative character of biological indicators of soil health make them valuable tools

for the assessment of the efficiency of metal phytostabilization processes.

9.2 Introduction

The enormous costs associated with the remediation of contaminated soils by

means of traditional physicochemical methods have stimulated the development of

innovative biological technologies which could economically clean-up these soils

(Hernández-Allica et al., 2007). Phytoremediation, the use of green plants to remove

pollutants from the environment or to render them harmless (Cunningham et al.,

1995), has great potential for the remediation of contaminated soils. Within the

phytoremediation field, “phytostabilization”, a process wherein plants are

established and function primarily to accumulate metals into root tissue or aid in

their precipitation in the root zone (Cunningham et al., 1995; Salt et al., 1995), is

being encouraged for the revegetation and remediation of soils contaminated with


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high levels of metals, e.g. mine soils. Ideally, plants for phytostabilization should

develop an extensive root system and produce a large amount of biomass in the

presence of high concentrations of metals, while keeping root-to-shoot metal

translocation as small as possible (Wong, 2003). Nevertheless, mine soils are

frequently unfavourable environments for plants due to the presence of many

growth limiting factors, such as high levels of available metals, soil acidity, lack of

organic matter (OM) and its associated nutrients, and poor substrate structure

(Tordoff et al., 2000; Wong, 2003). Then, the use of organic amendments is a

common practice in phytostabilization procedures as organic residues are able to

improve soil properties by raising pH, increasing OM content, adding essential

nutrients for plant growth, increasing water holding capacity, and

modifying/reducing metal bioavailability (Alvarenga et al., 2009a, b). If revegetation

is performed in combination with amendments, it can then be termed as “aided

phytostabilization” (Alvarenga et al., 2009a, b) or “chemophytostabilization” (Knox

et al., 2000). The utilization of amendments, in the absence of plants, for the

remediation of mine soils has a number of limitations such as the need for regular

inspections, a lack of proven durability, and its failure to enhance the sometimes

unsightly nature of abandoned mine sites (Tordoff et al., 2000). On the contrary,

revegetation is an aesthetically pleasing technology which prevents water and wind

erosion as well as runoff and leaching of metals by rhizosphere-induced adsorption

and precipitation processes (Arienzo et al., 2004).

In any case, the ultimate goal of any soil metal remediation process must be

not only to remove the metals from the contaminated site or to render them

harmless (immobile, non-bioavailable) but to restore soil health/functioning. To

date, considerable emphasis has been placed on soil physicochemical properties as

indicators of soil health. However, soil biological properties, particularly those

related to the size, activity and diversity of soil microbial communities, are becoming

increasingly used as bioindicators of soil health owing to, among other advantages,

their rapid response, sensitive and capacity to provide information that integrates

many environmental factors (Mijangos et al., 2006).

The objective of this work was to evaluate the suitability of soil

microbiological indicators for the short-term assessment of the efficiency of

phytostabilization processes. For that purpose, a short-term phytostabilization


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microcosm study was carried out using Lolium perenne, combined with the addition

of a synthetic versus an organic amendment, to remediate a mine soil moderately

contaminated with Zn, Pb and Cd.

9.3 Materials and methods 9.3.1 Experimental design

A soil moderately contaminated with metals (total Zn, Pb and Cd in mg kg-1:

1000, 340 and 2.6, respectively; CaCl2-extractable Zn, Pb and Cd in mg kg-1: 417, 4.0

and 1.1, respectively) was collected with a shovel (upper 0-20 cm) from an

abandoned mine located in Lanestosa, Bizkaia, northern Spain (latitude 43°13´,

longitude 3°26´). This metal contaminated site occupies several hectares in the

middle of an area of predominantly rural use, providing an excellent opportunity for

the application of phytoremediation procedures. In previous studies (Barrutia et al.,

2009; Hernández-Allica et al., 2006a, 2008; Santos et al., 2006), we observed that

metal distribution in the Lanestosa mine was highly heterogeneous. For the current

study, soil was collected from an area known to contain moderate total

concentrations of metals. Immediately after collection, the soil was sieved to <4

mm, taken to the laboratory and subjected to characterization (see methods below).

The soil was a sandy-loam with the following physicochemical properties: pH = 4.8;

OM (%) = 4.75; total N (%) = 0.18; C/N = 15.3; extractable P (mg kg-1) = 6;

extractable K+ (mg kg-1) = 30; electrical conductivity (μS cm-1) = 2,400; and cation

exchange capacity (mEq 100 mL-1) = 2.89.

After characterization, one third of the soil was treated with cow slurry (pH =

8.2; OM (%) = 57.3; total N (%) = 0.36; total P (%) = 0.59; total K+ (%) = 3.03; all

values on a fresh weight basis) to reach a final concentration of major

macronutrients of: 0.39 mg N kg-1 dry weight (DW) soil, 0.25 mg P2O5 kg-1 DW

soil, 0.43 mg K2O kg-1 DW soil and 0.20 mg Ca2+ kg-1 DW soil. Another third was

treated with a mixture of synthetic amendments (CalcinitTM + urea + PK14% +

calcium carbonate) to reach the same macronutrient (N, P, K+ and Ca2+)

concentrations. In both cases, the amount of amendment added to the soil was <

1.5% the amount of soil (on a DW basis). A cement mixer was used to properly

homogenize the amendment-soil mixtures. The last third corresponded to non-

amended control soil (control soil samples were also homogenized in the cement


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180

mixer). All soils were allowed to stabilize in the dark for 6 months at 30% humidity

and 20 ºC. After this stabilization period, composite soil samples from each

treatment (SA: synthetic amendment; OA: organic amendment with cow slurry; C:

controls) were taken for the phytostabilization experiment.

Prior to the study, a two-week experiment (data not shown) was carried out

with four gramineous plant species, i.e. Agrostis tenuis Sibth (cv. Highland), Festuca arundinacea Schreber (cv. Villageoise), Lolium perenne L. (cv. Concerto) and Festuca rubra L. (cv. Pernille), to find out the most suitable species in terms of growth and

tolerance in the studied mine contaminated soil. L. perenne showed the best

germination rate and growth in the mine soil and, consequently, we selected this

species for our study. L. perenne has been reported (Alvarenga et al., 2008; Arienzo et

al., 2004) as a suitable species for revegetation of metalliferous sites, producing high

dry matter yields and accumulating moderate to high levels of metals in its biomass.

Pots were filled with 250 g DW of soil (SA, OA or C) moistened with distilled

water to 80% of the field capacity and sowed with L. perenne seeds at 0.4 g seed pot-1

(P: planted). Parallel to this one, another complete set remained unplanted (UP:

unplanted). All treatments were conducted in quadruplicate. Plants were then

allowed to grow for one month in a soft polyethylene-covered greenhouse (Venlo-

type) located in Derio (Bizkaia) at a latitude of 43º 17’ N, a longitude of 2º 52’ W

and an altitude of 65 m above sea-level. The climate in this region is Atlantic

temperate. Minimal temperature set points controlling air-heating were 14/18 ºC

night/day, and maximal temperature set points were 18/20 ºC night/day. Vent

opening temperatures were 20/25 ºC night/day. During the experiment, average

temperature was 15/24 ºC night/day, average relative humidity 45.7%, and average

photosynthetically active radiation 472 μmol photon m-2 s-1. After this month,

plants were harvested and washed thoroughly with deionized water to remove soil

particles. Fresh weights of shoots and roots were recorded and samples of leaves

(0.1 g) were collected from each pot to determine photosynthetic pigments

(chlorophyll a, chlorophyll b and carotenoids) content according to Wellburn

(1994). For the analysis of plant metal concentrations, shoots and roots were oven-

dried at 70 ºC for 48 h and their DWs recorded. Subsamples (0.4 g) of dried plant

tissue were digested with a mixture of HNO3/HClO4 (Zhao et al., 1994) and metals

in the digest were determined using inductively coupled plasma atomic emission


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181

spectrometry (ICP-AES; Varian, Palo Alto, CA). The reliability of the digestion and

analytical procedure was tested including blanks and standards of plant leaves (IPE,

Wageningen University, The Netherlands) with every batch of sample digest.

Finally, soil was sampled, by gently shaking off the rhizosphere soil that adhered to

roots, sieved to <2 mm and subjected to physicochemical and biological

characterization.

9.3.2 Soil physicochemical and biological characterization For soil physicochemical analysis, the soil was air-dried at 30 ºC for 48 h,

sieved to <2 mm, and stored at room temperature. Soil pH, cation exchange

capacity (CEC), electrical conductivity (EC), particle size distribution, and contents

of soil OM, total N and extractable P and K+ were determined following standard

methods (MAPA, 1994). Total metal concentrations in soil were determined using

ICP-AES following aqua regia digestion (McGrath and Cunliffe, 1985). The

reliability of the digestion and analytical procedure was tested including blanks and

standards of soil (ISE, Wageningen University, The Netherlands) with every batch

of sample digest. The soluble/available fraction of metals was extracted using 0.01

M CaCl2, as described by Houba et al. (2000), and Cd, Pb and Zn concentrations in

each extract were analyzed by flame atomic absorption spectrometry (SpectrAA-250

plus; Varian, Palo Alto, CA).

Regarding soil biological parameters, soils were sieved to <2 mm and stored

fresh at 4 ºC until analysis. Microbial biomass carbon (Cmic) was measured by the

fumigation-extraction method (Vance et al., 1987).

β-glucosidase, acid phosphatase and arylsulphatase activities were determined

according to a modification of Tabatabai (1994). One gram of soil (DW) was mixed

with 1.6 mL of buffer (20 mM modified universal buffer-MUB, pH 6.0, for β-

glucosidase; 20 mM MUB, pH 6.5, for acid phosphatase; 500 mM acetate buffer, pH

5.8, for arylsulphatase) and 0.4 mL of substrate [4-nitrophenyl-β-D-glucopyranoside

(1.5% w/v) for β-glucosidase; 4-nitrophenyl phosphate disodium salt (1.85% w/v)

for acid phosphatase; potassium 4-nitrophenyl sulphate (1.3% w/v) for

arylsulphatase]. The mixture was incubated at 37 oC for 45 min and the reaction

stopped with 0.4 mL of 500 mM CaCl2 and 1.6 mL of 500 mM NaOH for

arylsulphatase and acid phosphatase, and with 0.4 mL of 500 mM CaCl2 and 1.6 mL


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of 100 mM Tris (hydroxymethyl) aminomethane buffer-THAM, pH 12, for β-

glucosidase. After centrifugation (1250 x g, 5 min), the absorbance value of the

samples was read at 410 nm. Dehydrogenase activity was determined following a

modification of Von Mersi and Schiner (1991). One gram of soil (wet weight) was

mixed with 0.4 mL of 100 mM THAM, pH 7.0, and 0.4 mL of iodonitrotetrazolium

chloride-INT (0.5% w/v). The mixture was then incubated at 25 oC for 4 h and the

reaction stopped with 8 mL of methanol. After centrifugation (1250 x g, 5 min), the

absorbance value of the samples was read at 490 nm. Specific enzyme activity was

calculated as the value of each enzyme activity divided by the mg of Cmic kg-1 DW

soil.

Potentially mineralizable nitrogen, Nmin, an indicator of the capacity of the soil

to supply plant-available N, was measured as described by Powers (1980). Specific

Nmin (Nmin in μg N-NH4+ kg-1 DW soil divided by Cmic in mg of C kg-1 DW soil) was

also calculated.

For the analysis of community level physiological profiles (CLPPs), Biolog

EcoPlatesTM were used according to Epelde et al. (2008a, b). For each reading time,

average well colour development (AWCD) was determined. The plates

corresponding to an incubation time of 50 h were chosen for further calculations (at

approximately this incubation time, the highest rate of microbial growth was

observed in the EcoPlatesTM). The number of utilized substrates (i.e., the number of

substrates with an absorbance value >0.25; this value marked the beginning of the

exponential phase in the EcoPlatesTM), equivalent to species richness, S, was

calculated at this 50 h incubation time. Similarly, Shannon’s diversity index (H’=-

∑pilog2pi) and Simpson’s diversity index (1-D; D=∑pi2) were calculated considering

absorbance values at each well as equivalent to abundance of individuals in each

species.

9.3.3 Statistical analysis Differences between treatments were analyzed with one-way ANOVA using

Microsoft Stat View Software (SAS Institute, 1998). Fisher’s PLSD-test was used to

establish the significance of the differences among means. Results from

physicochemical (pH, EC, OM, total N, C/N, extractable P and K+, CaCl2-

extractable Cd, Pb and Zn concentrations) and biological (Cmic, β-glucosidase, acid

phosphatase, arylsulphatase, dehydrogenase, Nmin, AWCD, S and H’ from Biolog


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183

EcoplatesTM) determinations were used to perform a principal component analysis

(PCA) with Canoco 4.5 for Windows. Pearson’s correlations were calculated

between soil physicochemical and biological parameters, as well as soil metal

concentrations and plant metal accumulation using SPSS Programme (SPSS, 1989).

9.4 Results 9.4.1 CaCl2-extractable metal concentrations in soil

In unplanted pots, amendments (SA and OA) led to significantly lower values

of CaCl2-extractable metal concentrations, as compared to controls (Table 9.1).

Indeed, SA-treatment reduced the CaCl2-extractable concentration of Cd, Pb and

Zn by 11, 53 and 13%, respectively. The addition of cow slurry led to a 37, 55, 32%

reduction of CaCl2-extractable Cd, Pb and Zn, respectively. Most important, within

the three treatments studied here (OA, SA, control), significantly lower values of

CaCl2-extractable metal concentrations were found in planted versus unplanted pots

(Table 9.1). Table 9.1: CaCl2-extractable metal concentrations in soil samples at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.

Cd Pb Zn

(mg kg-1 DW soil)

C-UP 1.15 ± 0.01a 4.44 ± 0.02a 450.7 ± 4.2a

C-P 1.06 ± 0.00b 3.92 ± 0.06b 421.7 ± 11.2b

SA-UP 1.02 ± 0.01b 2.09 ± 0.03c 393.0 ± 2.9c

SA-P 0.81 ± 0.01c 1.28 ± 0.02d 304.3 ± 4.3d

OA-UP 0.73 ± 0.03d 2.00 ± 0.13c 308.5 ± 5.4d

OA-P 0.62 ± 0.01e 1.23 ± 0.06d 265.8 ± 4.4e


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184


SA- and OA-treated plants had significantly higher values of shoot and root

biomass than unamended controls (shoot biomass in SA and OA-plants was 111

and 90% higher than in control plants, respectively; root biomass in SA and OA-

plants was 105 and 284% higher than in control plants, respectively) (Table 9.2).

Throughout the experiment, control (unamended) plants showed clear visual

symptoms of chlorosis as reflected by their significantly lower values of

photosynthetic pigments content as compared to SA and OA-treated plants (Table

9.2). Table 9.2: Shoot and root biomass and photosynthetic pigments contents of Lolium perenne plants at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.

Shoot Root Chlorophyll a+b Carotenoids

(g DW pot-1) (µg g-1 DW tissue)

C 0.70 ± 0.09b 0.19 ± 0.00c 1092 ± 81b 212 ± 13b

SA 1.48 ± 0.04a 0.39 ± 0.03b 2898 ± 107a 477 ± 19a

OA 1.33 ± 0.08a 0.73 ± 0.07a 2224 ± 301a 375 ± 51a

Regarding metal concentrations in L. perenne plants (Table 9.3), significantly

higher values of shoot metal concentrations were found in control than amended

plants. Furthermore, significantly lower values of shoot Cd and Zn concentration

were found in OA- than in SA-treated plants (no significant differences were found

between SA- and OA-treated shoots for Pb). On the other hand, Cd was

accumulated to a significantly greater extent in amended roots (SA and OA) than

control roots (values of root Cd concentration were 158 and 26% higher in SA and

OA-treated plants, respectively, as compared to controls). On the contrary, Pb was

accumulated to a significantly lower extent in amended (SA and OA) than in control

roots (values of root Pb concentration were 24 and 28% lower in SA and OA-

treated plants, respectively, as compared to controls). Finally, significantly highest


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185

and lowest values of root Zn concentration were found for synthetically amended

and organically amended plants, respectively.

Translocation factors (TF = shoot metal concentration / root metal

concentration) decreased in both SA- and OA-treated pots (Table 9.3). Lowest and

highest translocation factors were found for Pb and Zn, respectively (Table 9.3).

In terms of total amount of metal (Cd + Pb + Zn) phytostabilized in L. perenne roots, highest values were found in organically amended pots (i.e., OA-pots: 416.95

μg pot-1; SA-pots: 380.02 μg pot-1; control pots: 146.45 μg pot-1). Most of this metal

corresponded to Zn, i.e. the amount of Zn phytostabilized in roots was (in μg pot-1)

366.46, 351.39 and 128.63 in OA, SA and controls, respectively.


186

18

7

Tab

le 9

.3:

Shoo

t an

d ro

ot m

etal

conc

entra

tions

and

tra

nslo

catio

n fa

ctor

s of

Loli

um p

erenn

e pl

ants

at

the

end

of t

he e

xper

imen

t. C:

una

men

ded

cont

rols;

SA

: sy

nthe

tic a

men

dmen

t; O

A: o

rgan

ic am

endm

ent;

UP:

unp

lante

d; P

: plan

ted.

Valu

es fo

llow

ed w

ith d

iffer

ent l

ette

rs a

re s

igni

fican

tly d

iffer

ent (

P<0.

05) a

ccor

ding

to

Fish

er’s

PLSD

-test

. Mea

n va

lues

(n =

4) ±

stan

dard

err

ors.

Sh

oots

R

oots

T

rans

loca

tion

fact

or

C

d Pb

Zn

C

d Pb

Zn

C

d Pb

Zn

(mg

kg-1 D

W ti

ssue

)

C

0.74

± 0

.02a

10

.5 ±

1.8

a 61

3 ±

24a

1.

24 ±

0.0

1c

92.5

± 0

.0a

677

± 0

b 0.

59 ±

0.0

2a

0.11

± 0

.02a

0.

91 ±

0.0

4a

SA

0.60

± 0

.04b

2.

8 ±

0.6

b 32

2 ±

15b

3.

20 ±

0.0

1a

70.2

± 3

.2b

901

± 0

a 0.

19 ±

0.0

1b

0.04

± 0

.01b

0.

36 ±

0.0

2b

OA

0.25

± 0

.01c

2.

7 ±

0.8

b 15

9 ±

5c

1.56

± 0

.08b

67

.6 ±

4.8

b 50

2 ±

57c

0.

17 ±

0.0

1b

0.04

± 0

.01b

0.

33 ±

0.0

3b

Tab

le 9

.4:

Soil

phys

icoch

emica

l pa

ram

eter

s at

the

end

of

the

expe

rimen

t. C:

una

men

ded

cont

rols;

SA

: syn

thet

ic am

endm

ent;

OA

: org

anic

amen

dmen

t; U

P:

unpl

ante

d; P

: plan

ted.

Valu

es f

ollo

wed

with

diff

eren

t let

ters

are

sig

nific

antly

diff

eren

t (P<

0.05

) acc

ordi

ng to

Fish

er’s

PLSD

-test

. Mea

n va

lues

(n =

4) ±

sta

ndar

d er

rors

.

pH

C

EC

E

C

OM

N

C

/N

Ext

. P

Ext

. K+

(mE

q 10

0 m

L-1 )

(µS

cm-1)

(%)

(m

g l-1

)

C-U

P 4.

63 ±

0.0

2e

3.36

± 0

.08c

24

30 ±

15c

4.

66 ±

0.0

4cd

0.17

± 0

.00c

15

.9 ±

0.1

cd

6.67

± 0

.20d

43

.3 ±

1.3

d

C-P

4.

77 ±

0.0

2d

3.05

± 0

.02c

24

33 ±

7c

4.80

± 0

.04c

0.

17 ±

0.0

0c

16.4

± 0

.4bc

7.

67 ±

0.2

0c

44.7

± 0

.4d

SA-U

P 4.

93 ±

0.0

2c

6.27

± 0

.12a

26

60 ±

19b

4.

44 ±

0.0

1e

0.17

± 0

.00c

15

.2 ±

0.1

d 14

.50

± 0

.25a

14

8.3

± 2

.5b

SA-P

5.

28 ±

0.0

2b

6.18

± 0

.11a

22

08 ±

27d

4.

63 ±

0.0

3d

0.16

± 0

.00d

17

.1 ±

0.3

ab

13.5

0 ±

0.2

5b

50.0

± 2

.4d

OA-

UP

5.30

± 0

.00b

5.

13 ±

0.1

0b

2723

± 1

1a

5.18

± 0

.04b

0.

19 ±

0.0

0a

15.9

± 0

.1cd

14

.00

± 0

.35a

b 25

3.5

± 3

.2a

OA-

P 5.

70 ±

0.0

4a

ND

† 22

13 ±

16d

5.

42 ±

0.0

9a

0.18

± 0

.00b

17

.3 ±

0.1

a 13

.25

± 0

.41b

12

1.0

± 4

.5c

† Non

-det

erm

ined


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188

9.4.3 Soil physicochemical and biological parameters

Table 9.4 shows the values of soil physicochemical parameters at the end of

the phytostabilization experiment. In unplanted pots, the addition of synthetic

amendment led to significantly higher values of soil pH, CEC, EC, extractable P and

extractable K+, and significantly lower values of OM content, as compared to

controls. In unplanted pots, OA-treated soils showed significant higher values of all

physicochemical parameters, as compared to controls. The presence of plants under

both amendments (SA, OA) resulted in significantly higher values of soil pH and

OM content, and significantly lower EC, total N and extractable K+ (Table 9.4).

Figure 9.1: Microbial biomass C at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.

Regarding Cmic (Figure 9.1), in unplanted pots, synthetic amendment

significantly reduced this parameter while, on the contrary, the addition of cow

slurry led to significantly higher values. Under SA (not under OA), planted pots

showed significantly higher values of Cmic than unplanted pots. Values of Nmin

followed a similar trend (Figure 9.2), although, in this case, organically amended

planted pots had significantly higher values of this parameter than OA-treated

unplanted pots. In unplanted pots, specific rates of Nmin (μg N-NH4+ mg-1 Cmic)


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189

were significantly lower in OA (3.43 ± 0.18) than in SA (7.66 ± 0.57) or control

soils (6.50 ± 0.47). In addition, in organically amended soils, the presence of plants

resulted in higher values of this parameter (6.37 ± 0.30). No significant differences

were found between planted and unplanted soils in SA- or control pots regarding

specific Nmin (Figure 9.2).

Figure 9.2: Potential mineralizable N at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Bars with different letters are significantly different (P<0.05 or lower) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.


189

189

In unplanted pots, both amendments (SA and OA) significantly increased and

decreased β-glucosidase and acid phosphatase activity, respectively, as compared to

controls (Table 9.5). Under organic amendments, planted pots had significantly

higher values of dehydrogenase and arylsulphatase activity than unplanted pots.

Similarly, under synthetic amendment, planted pots had significantly higher values

of dehydrogenase, β-glucosidase and acid phosphatase activity than unplanted pots.

In control unamended pots, the presence of plants led to significantly higher values

of β-glucosidase and acid phosphatase activity. Table 9.5: Soil enzyme activities and their respective specific activities (enzyme activity / Cmic) at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.

Dehydrogenase β-glucosidase Arylsulphatase Acid phosphatase

(mg INTF kg-1 20 h-1) (mg ρ-Nitrophenol kg-1 h-1)

C-UP 33.3 ± 0.6c 46.4 ± 0.9e 37.8 ± 3.6bc 454.8 ± 5.6b

C-P 37.3 ± 3.0c 56.1 ± 2.3d 39.8 ± 2.1b 509.5 ± 10.5a

SA-UP 48.3 ± 2.0c 65.1 ± 1.3c 31.4 ± 0.8c 392.6 ± 3.7c

SA-P 151.1 ± 9.7b 79.7 ± 1.5b 33.4 ± 0.5bc 454.8 ± 12.6b

OA-UP 145.8 ± 2.7b 120.9 ± 3.8a 39.6 ± 2.0b 406.0 ± 6.5c

OA-P 257.8 ± 5.7a 117.2 ± 0.9a 51.1 ± 3.2a 424.8 ± 16.3bc

SPECIFIC ACTIVITIES

C-UP 0.40 ± 0.03c 0.55 ± 0.03b 0.46 ± 0.07b -

C-P 0.45 ± 0.05c 0.67 ± 0.03b 0.48 ± 0.05b -

SA-UP 0.81 ± 0.08b 1.08 ± 0.07a 0.52 ± 0.04b -

SA-P 1.33 ± 0.18a 0.69 ± 0.06b 0.29 ± 0.02a -

OA-UP 0.69 ± 0.02bc 0.57 ± 0.03b 0.19 ± 0.01a -

OA-P 1.29 ± 0.05a 0.59 ± 0.02b 0.26 ± 0.02a -

Except acid phosphatase, enzyme activities studied here were positively

correlated with Cmic (R = 0.805, P<0.001 for dehydrogenase; R = 0.917, P<0.001


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for β-glucosidase; R = 0.491, P<0.015 for arylsulphatase) and then specific enzyme

activities (enzyme activity / Cmic) were calculated for these three enzymes (Table

9.5). Organic amendment in unplanted pots did not significantly affect

dehydrogenase and β-glucosidase specific activities, as compared to controls. On the

contrary, synthetic amendment in unplanted pots resulted in significantly higher

values of these two specific enzyme activities (dehydrogenase, β-glucosidase).

Comparing planted and unplanted pots, under synthetic amendment the presence of

plants significantly reduced the values of β-glucosidase and arylsulphatase specific

activity, while this inhibitory effect was not observed under OA. Under both

amendments, the presence of plants significantly increased values of dehydrogenase

specific activity.

Table 9.6 presents the values of the different parameters (AWCD, S, H’ and 1-

D) calculated from EcoplatesTM. In unplanted pots, SA led to significantly lower

values of all those parameters as compared to controls. On the contrary, in both the

absence and presence of plants, OA significantly increased AWCD, S and H’.

Significant differences between planted and unplanted pots were found in

synthetically amended soils (higher values of AWCD, S, H’ and 1-D in planted pots)

but not in OA-treated soils.

Table 9.6: Average well colour development (AWCD) and diversity indexes (S = richness; H’ = Shannon’s diversity; 1-D = Simpson’s diversity) calculated from EcoPlatesTM absorbance data (50 h incubation time) at the end of the experiment. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. Values followed with different letters are significantly different (P<0.05) according to Fisher’s PLSD-test. Mean values (n = 4) ± standard errors.

AWCD S H’ 1-D

C-UP 0.39 ± 0.02d 14.33 ± 0.20c 2.54 ± 0.00c 0.91 ± 0.00a

C-P 0.55 ± 0.03c 17.00 ± 0.35bc 2.73 ± 0.02bc 0.93 ± 0.00a

SA-UP 0.06 ± 0.01e 1.67 ± 0.20d 0.45 ± 0.14d 0.32 ± 0.10b

SA-P 0.65 ± 0.02bc 18.33 ± 0.89b 2.78 ± 0.05b 0.93 ± 0.00a

OA-UP 0.72 ± 0.01ab 22.00 ± 0.00a 2.97 ± 0.00ab 0.94 ± 0.00a

OA-P 0.85 ± 0.13a 24.67 ± 1.74a 3.07 ± 0.08a 0.95 ± 0.00a


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Finally, the application of a PCA to all soil physicochemical and biological

parameters (Figure 9.3) separated controls from amended pots (SA and OA) along

PC2 which accounted for 20% of the variance. Along PC2, SA-unplanted pots were

separated from all the other treatments. PC1, which accounted for 54% of the

variance, separated planted controls from SA and OA-treated planted pots. As

suggested in Figure 9.3, apart from acid phosphatase activity which was negatively

correlated with extractable P (R= -0.663, P<0.001; these two parameters extended

along the negative and positive axis of the PC2, respectively), most of the biological

parameters clumped together (along the positive axis of the PC1) and were

positively correlated with soil pH and OM content and negatively with CaCl2-

extractable metals (which extended along the negative axis of PC1). A negative

correlation between CaCl2-extractable metals and soil pH (R = -0.971, P<0.001 for

Zn; R = -0.972, P<0.001 for Cd) was found.

Figure 9.3: Principal component analysis of soil physicochemical and biological parameters. C: unamended controls; SA: synthetic amendment; OA: organic amendment; UP: unplanted; P: planted. PC1 and PC2 account for 54 and 20% of the variance, respectively. Only those parameters showing a fit range >40% have been included. GLU: β-glucosidase; DH: dehydrogenase; Cmic: microbial biomass C; Nmin: potentially mineralizable N; OM: organic matter content; SUL: arylsulphatase; PHO: phosphatase; Zn, Cd, Pb: CaCl2-extractable metal concentrations; AWCD, S and H’ from Biolog EcoplatesTM.


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9.5 Discussion

Metal contaminated soils represent a threat to soil ecosystems, hampering

plant growth and reducing soil functionality (Kumpiene et al., 2009) by (i) reducing

the soil microbial biomass and activity as a result of selection of metal tolerant

organisms that are less metabolically efficient (Giller et al., 1998) and (ii) inhibiting

the activity of hydrolase enzymes that are important in nutrient cycling (Tyler et al.,

1989). Then, demonstration of recovery of soil functionality and increasing

complexity of microbial communities in phytostabilized soils might be a key issue

for the acceptance of such a remediation option (Kumpiene et al., 2009). In other

words, ecological restoration of mine degraded soils, achieved by the application of

amendments and phytostabilization, must be assessed based not only on soil

chemical properties and metal availability, but also on assays that measure soil

microbial activity or community structure and enzyme actitivies related to the

biocycles of nutrients (Alvarenga et al., 2008; Hinojosa et al., 2004; Zhang et al.,

2006). Liao et al. (2005) reported that soil microbiological parameters have great

potential as early sensitive, effective and reliable indicators of stresses or

perturbations in soils affected by mine wastes.

The mine soil studied here was only moderately contaminated in terms of

total metal concentrations, but the levels of CaCl2-extractable metals were relatively

high, possibly due to its sandy-loam nature and low pH. Soils of these characteristics

usually present a high risk of metals leaching to groundwater and an elevated

toxicity to soil biota, making them good candidates for phytostabilization

experiments.

Regarding CaCl2-extractable metal concentrations, although both amendments

led to lower values, this reduction was more accentuated in OA-treated soils. Metal

bioavailability in soil can be reduced through the addition of OM so that insoluble

metal-organic complexes with humic acids are formed, thereby lessening the risk of

metal toxicity to plants and microbes (Kirkham, 1977). Much work has been carried

out on the utilization of manure (Rotkittikhun et al., 2007), compost (Gomez et al.,

2006) and sewage sludge (Chiu et al., 2006) for this purpose. Importantly, we

observed a further reduction in CaCl2-extractable metal concentrations in planted

versus unplanted soils, indicating a superior remediation efficiency in the presence of


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plants. It has been reported that a vegetation cover further improves the chemical

and biological characteristics of the contaminated soil by increasing OM content,

nutrient levels, CEC and biological activity, allowing the creation of a self-sustaining

ecosystem (Pérez de Mora et al., 2005, 2006).

The synthetic and organic amendments led to the development of a healthy L. perenne cover as opposed to control plants that showed clear visual symptoms of

phytotoxicity throughout the experiment as reflected by their lower values of

biomass and photosynthetic pigments content. Similarly, in a previous study

(Barrutia et al., 2009), we found that synthetic fertilization overcame phytotoxicity

symptoms in non-tolerant Rumex acetosa populations. Some amendments are known

to be effective at lowering soil metal toxicity while providing a release of valuable

nutrients for plant growth (Chiu et al., 2006). Vangronsveld et al. (1995) treated a

Zn-polluted soil with beringite and compost quickly stimulating the growth of a

healthy vegetation cover. In a field phytostabilization experiment (Li et al., 2000),

compost addition lowered soluble Zn and Cd concentrations resulting in lower

phytotoxicity. Indeed, the presence of healthier plants in highly contaminated

mining sites following organic amendments was the result of the amendments’

ability to reduce phytoavailable soil metal concentrations (Mench et al., 2003) as well

as the improvement of soil nutritional conditions. The reduction in CaCl2-

extractable metal concentrations observed in the soil of planted pots was mainly due

to modification of the rhizosphere characteristics, not to plant metal uptake.

Regarding metal concentrations in L. perenne shoots, the lower values of amended

versus control plants might be the consequence of such reduction in CaCl2-

extractable metal concentrations. The fact that translocation factors were lower in

amended than in control plants is of considerable importance, as it indicates that

our phytostabilization process reduced the risk of metals entering the food chain.

Finally, although shoot Zn concentrations were high in control and amended pots,

both OA- and SA-treatments managed to lower them below phytotoxic threshold

levels (>500 mg Zn kg-1) (Chaney, 1993). In any case, the addition of cow slurry

resulted in all metal concentrations in plant shoots being below toxic levels for

herbivore consumption (Chaney, 1989).


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The addition of synthetic and organic amendments increased crucial soil

physicochemical properties (pH, OM and CEC) which could explain the observed

low values of CaCl2-extractable metals. This effect was enhanced in planted pots.

Under both amendments, L. perenne growth increased soil pH, a noteworthy

improvement in acid mine soils such as ours, and OM content which, again,

indicates a superior remediation efficiency in the presence of plants. In both planted

and unplanted soils, synthetic amendment decreased the content of soil OM (and of

total N in the case of planted soils) which could be explained by a more rapid

turnover/oxidation of OM under SA-treatment. The significantly lower values of

total N and extractable K+ found in planted versus unplanted pots under both

amendments might be due to plant uptake of inorganic forms of these essential

nutrients.

Our experiment was carried out for a short period of time to investigate the

potential of microbiological indicators of soil health to detect early changes in soil

properties derived from phytostabilization, in an attempt to highlight their

sensitivity and rapid response. The addition of nutrients and OM to the soil usually

increases the biomass and activity of the soil microbial community and,

simultaneously, affects the impact of contaminants, like metals, on biological

parameters such as enzyme activities. In this respect, soil enzymes are highly

sensitive to metals and, therefore, have been recommended as standard biochemical

indicators to assess quality of metal contaminated soils (Hinojosa et al., 2004, 2008).

Tejada et al. (2008) reported an increase in enzyme activities in metal-contaminated

soils as a result of the addition of organic amendments. Similarly, in our study, the

addition of cow slurry led to an increase in dehydrogenase activity (dehydrogenase is

an oxidoreductase enzyme which has been used as a measurement of overall

microbial activity, since it is an intracellular enzyme related to the oxidative

phosphorylation process; Tabatabai, 1994) and β-glucosidase activity (it reflects the

state of the soil OM and the mineralization and humification processes) in both

planted and unplanted soils, suggesting an stimulation of the C cycle as a response

to the application of labile OM. Soil hydrolases, such as β-glucosidase, urease and

phosphatase, are sensitive indicators of management-induced changes due to their

strong relationship with soil OM content and quality (Tejada et al., 2006). In planted

pots, synthetic amendment also led to an increase in dehydrogenase and β-


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glucosidase activity, in this case probably due to the addition of essential nutrients to

a mine soil characterized by low levels of such nutrients and to the positive effects

of plant growth. On the other hand, significantly higher values of dehydrogenase

and β-glucosidase specific activities found in SA-treated unplanted soils, as

compared to controls (cow slurry did not significantly affect these two specific

enzyme activities in unplanted pots), suggests a stress response of the soil microbial

community to the addition of our synthetic amendment. Lastly, under both

amendments, L. perenne growth increased dehydrogenase activity (as compared to

amended unplanted pots), one more time highlighting the positive effect of plants

on soil microbial activity.

Acid phosphatase activity (an indicator of organic P mineralization) decreased

as a response to both amendments in planted and unplanted soils, which can be

attributed to feedback inhibition of the enzyme activity by available-P (acid

phosphatase activity was negatively correlated with the content of soil extractable P).

The increase in acid phosphatase and β-glucosidase activity found in control and

SA-soils (not in OA-treated soils) as a result of L. perenne growth might be explained

by an stimulatory effect caused by root exudates. Several studies reported increased

soil hydrolase activities following the revegetation of metal-contaminated soils

(Izquierdo et al., 2005; Pérez de Mora et al., 2005, 2006; Zhang et al., 2006).

Not surprisingly, most biological parameters were positively correlated with

soil pH and OM content, emphasizing the beneficial effects of an increase in these

parameters in acid mine soils. Wang et al. (2006) also found a correlation between

soil biological activities and pH which was well characterized by linear or quadratic

regression models.

Microbial biomass parameters have been widely used for assessing soil quality

and the degree of restoration in degraded and/or contaminated soils (Clemente et

al., 2006, 2007; Pérez de Mora et al., 2005). The lower values of Cmic in SA-treated

unplanted soils as compared to controls may be caused by amendment-induced

toxicity. Previous studies have reported a negative effect of synthetic amendment

addition on total microbial biomass (Sarathchandra et al., 2001) and bacterial

populations (Biederbeck et al., 1996). Killham (1985) suggested that soil

microorganisms under stress divert energy from growth to cell maintenance


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functions which may be a plausible explanation for these lower Cmic values. The

presence of L. perenne reverted this toxic effect, possibly due to overall beneficial

effects of plants on soil microbial communities. We have previously reported the

positive effects of revegetation on microbial communities in metal-contaminated

soils (Epelde et al., 2008a, b; Hernández-Allica et al., 2006a). As compared to bare

soil, vegetated soils frequently have a higher microbial biomass and activity, owing

to the presence of additional surfaces for microbial colonization and root exudation

of organic compounds (Delorme et al., 2001). In agreement with our data, Clemente

et al. (2006) reported a positive effect of organic amendments on Cmic. The only

difference between data of Cmic and Nmin (OA planted pots had higher values of

Nmin than OA unplanted pots while regarding Cmic no significant differences were

observed between OA-treated planted and unplanted pots) again suggests that the

presence of plants activates soil microbial activity.

Regarding CLLPs, in general, synthetic amendment had a negative or no effect

on all parameters while the addition of cow slurry increased overall activity (AWCD)

and functional diversity (S, H’) of the heterotrophic cultivable soil microbial

community. Sarathchandra et al. (2001), in a urea fertilization trial, also found higher

values of H’ and AWCD in unfertilized than in fertilized soils. In OA-treated soils,

the easily mineralizable OM might have favoured the development of the soil

microbial activity, together with its microbial biomass and functional diversity.

These results are in agreement with other studies (Gomez et al., 2006) where OM

incorporation resulted in significant increases of AWCD, S and H’.

9.6 Conclusions

The addition of amendments, especially cow slurry, improved the properties

of the contaminated mine soil and reduced metal toxicity and bioavailability. This

reduced toxicity, together with the benefits provided by the addition of nutrients,

allowed the establishment of a healthy L. perenne vegetation cover in the mine soil

which, through the modification of crucial soil physicochemical properties (pH, OM

content), further enhanced soil biological parameters, increasing the biomass,

activity and functional diversity of the microbial community. The beneficial effects

of phytostabilization were more accentuated in organically amended than in


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synthetically amended soils. Our phytostabilization procedure reduced the risk of

metals entering the food chain, with the addition of cow slurry resulting in shoot

metal concentrations below toxic levels for herbivore consumption. In this study, L. perenne has been used as a model species under greenhouse controlled conditions but

now further research is needed to verify the beneficial effects of phytostabilization

under long-term field conditions with native metallophytes. Use of native plants is

certainly desirable as they are usually tolerant to local environmental conditions and,

most important, provide a foundation for natural ecological succession.

Phytostabilization is an aesthetically pleasing, useful technology that might help

restore degraded mine soils to some acceptable condition for revegetation by

decreasing soil metal bioavailability and overcoming nutrient deficiency in such soils.

The sensitivity, rapid response and integrative character of biological indicators of

soil health make them valuable tools for the short-term assessment of the efficiency

of phytostabilization processes.

10. links between pseudometallophytes and rhizosphere microbial communities in a metalliferous soil

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10. LINKS BETWEEN PSEUDOMETALLOPHYTES AND RHIZOSPHERE MICROBIAL COMMUNITIES IN A

METALLIFEROUS SOIL

Epelde et al., in preparation for publication

10.1 Abstract

The objective of this work was to study, in a slightly polluted metalliferous soil, the

short-term interactions between pseudometallophytes and rhizosphere microbial

communities as reflected by the values of soil microbial properties with potential as

bioindicators of soil health, in an attempt to quantify improvements in soil health derived

from pseudometallophyte growth and metal phytoextraction and phytostabilization under

different pseudometallophytes compositions. To this aim, plant consortia consisting of 1-

3 pseudometallophytes with different metal-tolerance strategies (hyperaccumulator:

Thlaspi caerulescens; accumulator: Rumex acetosa; excluder: Festuca rubra) were grown for two

months in a mine soil. At the end of the experiment, the following soil microbial

properties were determined: enzyme activities, biomass C, functional and structural

diversity, and bacterial and fungal abundance. Growing together with T. caerulescens proved

stimulatory for the other two pseudometallophytes, probably due to T. caerulescens metal

phytoextraction. R. acetosa, in combination with T. caerulescens, extracted the highest

amounts of Zn from our metalliferous soil. Lowest values of microbial functional

diversity were found in soils planted only with R. acetosa. Except for β-glucosidase, in

general, a negative correlation was found between enzyme activities and number of

pseudometallophytes present in the study pots. Highest values of microbial biomass C

were observed in the presence of the three pseudometallophytes. A methodology to link

the concept of soil health to that of ecosystem health is here proposed, assigning soil

microbial properties to attributes of ecosystem health (vigor, organization and stability).


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10.2 Introduction

It is increasingly recognized that aboveground and belowground components of

terrestrial ecosystems are closely related (Rodríguez-Loinaz et al., 2008). Plant diversity

and composition can alter rhizosphere microbial communities due to, among other

factors, differences in the quantity and quality of root exudates and plant litter, leading to

increased heterogeneity of organic substrates with its concomitant effects on the soil

decomposer community (Broughton and Gross, 2000; Stephan et al., 2000). In turn,

belowground microbial communities are known to decompose soil organic matter (OM),

stabilize soil structure and release nutrients for plant growth (Porazinska et al., 2003), thus

affecting vegetation structure.

On the other hand, soil microbial properties, especially those related to the biomass,

activity and diversity of the soil microbial communities, are becoming more and more

used as biological indicators of soil health (i.e., the soil´s continued capacity to sustain plant

growth and maintain its functions) (Coleman et al., 1998), due to their rapid response,

sensitivity and capacity to provide information that integrates many environmental factors

(Hernández-Allica et al., 2006a). In any event, whatever occurs in the soil has a profound

effect not only on soil health but also on ecosystem health. The concept of ecosystem health

has been elaborated as a comprehensive, multiscale, dynamic, hierarchical measure of

system´s (i) vigor, which may be quantified in terms of productivity, throughput of material

and energy in the system, etc.; (ii) organization, which may be assessed in terms of both

diversity of components and their degree of mutual dependence; and (ii) resilience/stability, which may be determined in terms of the system´s ability to maintain its structure and

pattern of behaviour in the presence of stress (Rapport, 1998; Alkorta et al., 2004a).

Many of the Earth’s fragile ecosystems such as metalliferous mining sites can be

considered ‘unhealthy’ in the sense that, in them, toxic metals often adversely affect the

number, activity and diversity of soil organisms, and restrict the growth of all but the

most tolerant plants (Wong, 2003). However, metalliferous soils are frequently home to

an endemic plant diversity that offers huge potential for the development of

environmental technologies such as, for instance, the phytoremediation and revegetation

of metal-enriched environments (Barrutia et al., 2008). Metallophytes are plant species

that have evolved biological mechanisms to resist, tolerate, or thrive in metalliferous soils

(Whiting et al., 2004). Similarly, pseudometallophytes are plants that colonize both


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metalliferous and non-metalliferous environments. The combination of

(pseudo)metallophytes with different physiological strategies (exclusion, accumulation,

hyperaccumulation) to deal with the toxic levels of heavy metals present in metalliferous

soils appears a most promising approach for phytoextraction (the utilization of

hyperaccumulating plants that have the capacity to accumulate, translocate and tolerate

high amounts of metals) and/or phytostabilization (the utilization of excluder plants to

convert metal pollutants into inert, immobile forms) (Epelde et al., 2009a). After all, the

limitations of one species might be overcome by the advantages of another.

Regrettably, so far, only a few studies have addressed the interactions between

aboveground and belowground communities in polluted environments (Phillips et al.,

2008; Yang et al., 2007). Then, the main objective of this work was to study, in a slightly

polluted metalliferous soil, the short-term interactions between pseudometallophytes and

rhizosphere microbial communities as reflected by the values of soil microbial properties

with potential as bioindicators of soil health, in an attempt to quantify improvements in

soil health derived from pseudometallophyte growth and metal phytoextraction and

phytostabilization under different pseudometallophytes compositions. The utilization of

pseudometallophytes for phytoextraction and phytostabilization was also discussed. Most

interestingly, and to our knowledge in a pioneering way, a methodology to link the

concept of soil health to that of ecosystem health is here proposed.


10.3.1 Soil characterization and experimental design

A short-term microcosm pot study was carried out with soil collected from the top

layer (0-30 cm) of the Pb/Zn “Txomin” mine area located in the province of Biscay

(northern Spain). Immediately after collection, the soil was sieved to <2 mm, air-dried at

30 ºC for 48 h, and subjected to physicochemical characterization according to standard

methods (MAPA, 1994). The soil was sandy loam, with a pH of 4.4, an OM content of

6.3%, a total nitrogen (N) content of 0.25%, a C/N ratio of 17.1, a phosphorus (P)

content of 2.7 mg kg-1 DW soil, and a potassium (K+) content of 41 mg kg-1 DW soil.

Total concentrations of heavy metals in soil were determined using flame atomic

absorption spectrometry (AAS, Varian) following digestion with a mixture of


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HNO3/HClO4 (Zhao et al., 1994). The following values of total metal concentration were

found (mg kg-1 DW soil): 0.93, 325.3 and 320.8 for Cd, Pb and Zn, respectively. For the

determination of soil metal fractions, the sequential extraction procedure of Berna et al.

(2000) was employed. This procedure subdivides metals into 5 operationally defined

fractions: (i) MgCl2-extractable fraction (soluble/exchangeable); (ii) NaOAc-extractable

fraction (carbonates), which is assumed to recover metals associated with carbonates; (iii)

NH2OH·HCl+HCl-extractable fraction (FeMnOxides), which contains metals associated

with the reducible Fe oxides and Mn oxides; (iv) H2O2-extractable fraction (OM), which

retains metals complexed by OM; and (v) HF+HCl-extractable fraction (residual) in

which crystalline minerals are dissolved and metals constituting the lattices solubilised. In

our soil, Cd was mainly bound to OM (37%) and Fe/MnOxides (29%); 62% of Pb was in

the Fe/MnOxides fraction; 45% of Zn was bound to carbonates (Figure 1). On average,

higher percentage values were found in the soluble/exchangeable (26%) than in the

residual fraction (14%).

Figure 10.1 : Soil metal (Cd, Pb and Zn) fractions according to sequential extraction: MgCl2-extractable (SOLUBLE/EXCHANGEABLE); NaOAc-extractable (CARBONATES); NH2OH·HCl+HCl-

extractable (FeMnOxides); H2O2-extractable (OM); and HF+HCl-extractable (RESIDUAL).

For this study, plant consortia consisting of 1-3 pseudometallophytes with

different metal-tolerance strategies (hyperaccumulator: Thlaspi caerulescence; accumulator:

Rumex acetosa; excluder: Festuca rubra) were used. T. caerulescens J. & C. Presl. and R. acetosa

L. seeds of the local Lanestosa ecotypes were collected from the “Txomin” mine and then


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germinated for two and one months, respectively, on a mixture of perlite and vermiculite

(2:3 v/v, moistened with deionized water) in a growth chamber under the following

conditions: 20/16 ºC day/night temperature, 70% relative humidity, and a photosynthetic

photon flux density of 300 µmol photon m-2 s-1 by supplementing natural illumination

with white cold lamps. Subsequently, seedlings (see treatments below) were transferred to

study pots (14 cm diameter x 10 cm height) containing 800 g FW (20% humidity) of the

mine soil. F. rubra L. was seeded (0.05 g of seeds for each T. caerulescens or R. acetosa

seedling; seeds were obtained from “Zulueta Corporación para la Naturaleza”, Spain)

directly in the study pots. In a preliminary experiment carried out under the same

greenhouse conditions described below, it was found that, after two months of growth,

the addition of 0.05 g of F. rubra seeds to our soil resulted in a similar biomass to that

obtained for each T. caerulescens or R. acetosa seedling at the end of the greenhouse

experiment (see below). This was done to compensate for the different growth rates

presented by the three pseudometallophytes, in an attempt to achieve a similar biomass of

each pseudometallophyte at the end of the experiment.

Eight treatments were conducted in triplicate: (1) T: T. caerulescens alone (six

seedlings); (2) R: R. acetosa alone (six seedlings); (3) F: F. rubra alone (0.30 g of seeds); (4)

T+R: 50% T. caerulescens (three seedlings) + 50% R. acetosa (three seedlings); (5) T+F:

50% T. caerulescens (three seedlings) + 50% F. rubra (0.15 g of seeds); (6) R+F: 50% R. acetosa (three seedlings) + 50% F. rubra (0.15 g of seeds); (7) T+R+F: one third T. caerulescens (two seedlings) + one third R. acetosa (two seedlings) + one third F. rubra (0.10

g of seeds); and (8) C: control unplanted pots. Plants were then allowed to grow for two

months in a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Biscay)

at a latitude of 43º 17’ N, a longitude of 2º 52’ W and an altitude of 65 m above sea-level.

The climate in this region is Atlantic temperate. Minimal temperature set points

controlling air-heating were 14/18 ºC night/day and maximal temperature set points were

18/20 ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the

experiment, average temperature was 17/29 ºC night/day, average relative humidity 55%,

and average photosynthetically active radiation 454 µmol photon m-2 s-1. Throughout the

experimental period, plants were bottom watered periodically as needed.



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After two months of growth, shoots were harvested separately for each species and

washed thoroughly with deionized water. Shoot fresh weights (FW) were recorded and,

subsequently, plant material was oven-dried at 70 ºC for 48 h to determine dry weights

(DW). Subsamples (0.4 g) of dried shoot tissue were digested with a mixture of

HNO3/HClO4 (Zhao et al., 1994) and Cd, Pb and Zn in the digest were determined using

AAS.

10.3.3 Soil physicochemical and microbial properties

For analysis of physicochemical parameters, rhizosphere soil was collected (by

gently shaking off the soil that adhered to roots), air-dried at 30 ºC for 48 h, sieved to <2

mm, and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v, soil:water) was measured

following standard methods (MAPA, 1994). Water-soluble organic carbon (WSOC) was

extracted by shaking soil (horizontal shaker at 175 rpm) with distilled water (1:5 w/v) for

1 h. Then, 3.5 ml of chromium reagent [chromium (VI) oxide (0.06% w/v); sulfuric acid

(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min. Organic C

concentration was determined colorimetrically at 445 nm. Total concentrations of heavy

metals in soil were determined as above. For the estimation of metal bioavailability, CaCl2-

extractable (0.01 M) metal fractions in soil were determined following Houba et al. (2000)


For analysis of microbial parameters, rhizosphere soil was sieved to <2 mm and

stored fresh at 4 ºC until analysis. Regarding enzyme activities (they can be used as

indicators of the functional status or condition of the soil environment) (Naseby and

Lynch, 2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.

(2002). β-glucosidase (EC 3.2.1.21), arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC

3.1.3.2) activities were determined according to Dick et al. (1996) and Taylor et al. (2002),

as described in Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined

according to Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).

Microbial biomass C was measured by the fumigation-extraction method (Vance et

al., 1987) assuming an extractability of 0.38 (Wu et al. 1990).

Microbial functional diversity was determined through community level

physiological profiles (CLPPs) with Biolog EcoplatesTM, which reflect the potential of the

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After two months of growth, shoots were harvested separately for each species and

washed thoroughly with deionized water. Shoot fresh weights (FW) were recorded and,

subsequently, plant material was oven-dried at 70 ºC for 48 h to determine dry weights

(DW). Subsamples (0.4 g) of dried shoot tissue were digested with a mixture of

HNO3/HClO4 (Zhao et al., 1994) and Cd, Pb and Zn in the digest were determined using

AAS.

10.3.3 Soil physicochemical and microbial properties

For analysis of physicochemical parameters, rhizosphere soil was collected (by

gently shaking off the soil that adhered to roots), air-dried at 30 ºC for 48 h, sieved to <2

mm, and stored at 4 ºC until analysis. Soil pH (1:2.5 w/v, soil:water) was measured

following standard methods (MAPA, 1994). Water-soluble organic carbon (WSOC) was

extracted by shaking soil (horizontal shaker at 175 rpm) with distilled water (1:5 w/v) for

1 h. Then, 3.5 ml of chromium reagent [chromium (VI) oxide (0.06% w/v); sulfuric acid

(65% v/v)] were added to 2 ml of extract and incubated at 150 ºC for 60 min. Organic C

concentration was determined colorimetrically at 445 nm. Total concentrations of heavy

metals in soil were determined as above. For the estimation of metal bioavailability, CaCl2-

extractable (0.01 M) metal fractions in soil were determined following Houba et al. (2000)


For analysis of microbial parameters, rhizosphere soil was sieved to <2 mm and

stored fresh at 4 ºC until analysis. Regarding enzyme activities (they can be used as

indicators of the functional status or condition of the soil environment) (Naseby and

Lynch, 2002), dehydrogenase activity (EC 1.1) was determined according to Taylor et al.

(2002). β-glucosidase (EC 3.2.1.21), arylsulphatase (EC 3.1.6.1) and acid phosphatase (EC

3.1.3.2) activities were determined according to Dick et al. (1996) and Taylor et al. (2002),

as described in Epelde et al. (2008a). Urease (EC 3.5.1.5) activity was determined

according to Kandeler and Gerber (1988), as described in Rodríguez-Loinaz et al. (2008).

Microbial biomass C was measured by the fumigation-extraction method (Vance et

al., 1987) assuming an extractability of 0.38 (Wu et al. 1990).

Microbial functional diversity was determined through community level

physiological profiles (CLPPs) with Biolog EcoplatesTM, which reflect the potential of the

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germinated for two and one months, respectively, on a mixture of perlite and vermiculite

(2:3 v/v, moistened with deionized water) in a growth chamber under the following

conditions: 20/16 ºC day/night temperature, 70% relative humidity, and a photosynthetic

photon flux density of 300 µmol photon m-2 s-1 by supplementing natural illumination

with white cold lamps. Subsequently, seedlings (see treatments below) were transferred to

study pots (14 cm diameter x 10 cm height) containing 800 g FW (20% humidity) of the

mine soil. F. rubra L. was seeded (0.05 g of seeds for each T. caerulescens or R. acetosa

seedling; seeds were obtained from “Zulueta Corporación para la Naturaleza”, Spain)

directly in the study pots. In a preliminary experiment carried out under the same

greenhouse conditions described below, it was found that, after two months of growth,

the addition of 0.05 g of F. rubra seeds to our soil resulted in a similar biomass to that

obtained for each T. caerulescens or R. acetosa seedling at the end of the greenhouse

experiment (see below). This was done to compensate for the different growth rates

presented by the three pseudometallophytes, in an attempt to achieve a similar biomass of

each pseudometallophyte at the end of the experiment.

Eight treatments were conducted in triplicate: (1) T: T. caerulescens alone (six

seedlings); (2) R: R. acetosa alone (six seedlings); (3) F: F. rubra alone (0.30 g of seeds); (4)

T+R: 50% T. caerulescens (three seedlings) + 50% R. acetosa (three seedlings); (5) T+F:

50% T. caerulescens (three seedlings) + 50% F. rubra (0.15 g of seeds); (6) R+F: 50% R. acetosa (three seedlings) + 50% F. rubra (0.15 g of seeds); (7) T+R+F: one third T. caerulescens (two seedlings) + one third R. acetosa (two seedlings) + one third F. rubra (0.10

g of seeds); and (8) C: control unplanted pots. Plants were then allowed to grow for two

months in a soft polyethylene-covered greenhouse (Venlo-type) located in Derio (Biscay)

at a latitude of 43º 17’ N, a longitude of 2º 52’ W and an altitude of 65 m above sea-level.

The climate in this region is Atlantic temperate. Minimal temperature set points

controlling air-heating were 14/18 ºC night/day and maximal temperature set points were

18/20 ºC night/day. Vent opening temperatures were 20/25 ºC night/day. During the

experiment, average temperature was 17/29 ºC night/day, average relative humidity 55%,

and average photosynthetically active radiation 454 µmol photon m-2 s-1. Throughout the

experimental period, plants were bottom watered periodically as needed.



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culturable portion of the heterotrophic microbial community to respond to C substrates

(Bending et al., 2004), following Epelde et al. (2008a). Average well colour development

(AWCD) was calculated at a 44 h incubation time (at approximately this incubation time,

the highest rate of microbial growth was observed in the Biolog EcoPlatesTM).

Soil samples for DNA analysis were sieved to < 2 mm and stored fresh at -20 ºC.

DNA was extracted from soil samples (0.25 g FW) using Power SoilTM DNA Isolation

Kit (MO BIO Laboratories, California) according to manufacturer’s specifications. Prior

to DNA extraction, soil samples were washed twice in 120 mM K2HPO4 (pH 8.0) to

wash away extracellular DNA from soil without loss of intact cells (Kowalchuk et al.,

1997). In this way, most of the extracted DNA comes from live bacterial cells

(nonetheless, a small fraction of the extracted DNA might be associated with unlysed

dead cells or extracellular DNA not completely washed from the soil samples)

(Kowalchuk et al., 1997). With this extracted DNA, real-time PCR and PCR-DGGE were

carried out.

Real-time PCR was done to quantify rhizosphere bacterial and fungal biomass. For

amplification of rRNA gene fragments, Ba519f/Ba907r and Fung5f/FF390r primers

(Lueders et al., 2004a, b) were used for bacteria and fungi, respectively. Each 25 μl

reaction contained 5 μl of template, 12.5 μl of ABsolute QPCR SYBR green 2 x reaction

mix (AbGene, Epsom, UK), 0.25 μl of each primer (30 μM), 2.5 μl bovine serum albumin

(BSA, 40 mg ml-1) and 4.5 μl of water. Standards were made from full-length PCR-

amplified 16S rRNA or 18S rRNA genes from pure bacterial and fungal isolates,

respectively, following Yergeau et al. (2007a). All mixes were made using a CAS-1200

pipetting robot (Corbett Research, Sydney) to reduce variation caused by pipetting errors.

PCR conditions were: 95 ºC for 15 min; 94 ºC for 30 s; 52 ºC (48 ºC for fungi) for 30 s;

72 ºC for 60 s (40 cycles); and melt curve from 65 to 98 ºC. PCR amplification and

product quantification were performed using the Rotor-Gene 3000 (Corbett Research).

rRNA gene copies were quantified against the standard curve using ROTOR-GENE 6.

For the determination of microbial structural diversity, PCR-DGGE (denaturing

gradient gel electrophoresis) was carried out. Bacterial and fungal rDNA was amplified by

using F968-GC/R1378 (Heuer et al., 1997) and FR1-GC/FF390 (Vainio and Hantula,

2000) primer pairs, respectively. All PCRs were carried out in 25 μl volumes containing

2.5 μl of 10 x PCR buffer, 0.5 μl of each primer (30 μM), 2.5 μl of dNTPs mix (2 mM)


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and 3.5 U μl-1 of Expand high fidelity polymerase (Roche, Mannheim). Amplifications

were carried out on a PTC-200 thermal cycler (MJ-Research, Waltham). PCR conditions

for bacteria were: initial denaturation at 94 ºC for 2 min; 92 ºC for 30 s; 55 ºC for 1 min;

68 ºC for 45 sec (+1 sec cycle-1; 35 cycles) and extension at 68 ºC for 5 min. Conditions

for fungi were: initial denaturation at 94 ºC for 4 min; 92 ºC for 30 s; touchdown 55 ºC to

47 ºC for 1 min; 68 ºC for 45 sec (+1 sec cycle-1; 40 cycles) and extension at 68 ºC for 10

min. All DGGE analyses were done with a D-Code Universal Mutation Detection System

(Bio-Rad, Hercules) with a denaturating gradient of 45 to 65% for bacteria and 40 to 55%

for fungi (100% denaturant is defined as 7 M urea and 40% v/v formamide). DGGE was

performed using 20 µl of the PCR product in 0.5 x TAE buffer at 60 ºC (1 x TAE = 40

mM Tri-acetate, 20 mM sodium acetate, 1 mM EDTA, pH 8.0). Gradient gels were

topped with 10 ml of acrylamide containing no denaturant. Electrophoresis was

performed at 200 V for 15 min followed by 70 V for an additional 16 h. Electrophoresis

gels were stained with ethidium bromide and digital images captured using an ImaGo

apparatus (Gentaur, Brussels) upon UV transillumination. Banding patterns were

normalized with respect to standards of known composition and dendrogram

construction was performed using Imagemaster elite program 4.20 (Amersham

Bioscience, Rosendaal).

Richness (S) and Shannon’s diversity (H’) (Magurran, 2004) were calculated from

data on enzyme activities, CLPPs (S = number of substrates with an absorbance value

>0.25 at a 44 h incubation time) and DGGE (S = band number; abundance values were

obtained from band intensity) according to Mijangos et al. (2006, 2009). Areas under

AWCD curves (see below) were calculated following a trapezoidal approximation

(Guckert et al., 1996).

10.3.4 Soil ecosystem health

A methodology to link the concept of soil health to that of ecosystem health is here

proposed. To this aim, values of soil microbial properties were assigned to the three

attributes of ecosystem health abovementioned: vigor, organization, and

resilience/stability. We propose the following soil microbial properties for: (i) VIGOR:

overall enzyme activity (OEA), as indicator of the soil´s overall catalytic capacity (it was

calculated from the values of β-glucosidase, acid phosphatase, arylsulphatase and urease,


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as follows: the highest value for each enzyme activity was considered as 100; the other

values were transformed accordingly; finally, the average of all four enzyme activities was

calculated); area under AWCD curve, as indicator of the soil´s overall functional-catabolic

capacity; microbial biomass C, as indicator of the soil´s capacity to support microbial growth;

productivity of sorghum, as indicator of the soil´s capacity to support plant growth (see

below); (ii) ORGANIZATION: S and H’ from enzyme activities, as indicator of functional-

catalytic diversity; S and H’ from CLPPs, as indicator of functional-catabolic diversity; S and H’ from bacterial and fungal PCR-DGGE, as indicator of structural-genotypic diversity; and

(iii) STABILITY: resistance and resilience indexes calculated (see below), after transient heating

at 40 oC or copper (Cu) amendment, from data on soil basal respiration and nitrification potential rate (NPR).

Values of all these soil properties were scaled from 1 to 10 (1 = lowest value; 10 =

highest value). Within each attribute, mean values of the proposed soil properties were

calculated. Overall ecosystem health was determined as the mean of the three attributes.

For the essay on sorghum productivity, at the end of the experiment, rhizosphere

soil was collected from the pots. Twenty-five seeds of Sorghum bicolor x sudanense were

directly seeded in pots (9 cm diameter x 7 cm height) containing 200 g FW of this soil and

incubated under the same greenhouse conditions described above. In a preliminary

experiment, sorghum plants proved capable of growing in our metalliferous soil. Ten days

after seeding, germination rate was determined. Twenty days later, sorghum shoots were

harvested and their FW recorded. Shoots were then oven-dried at 70 ºC for 48 h to

calculate DW.

Similarly, at the end of the experiment, rhizosphere soil was collected from the

pots to carry out a soil stability experiment following a modification of Griffiths et al.

(2000): 6 replicates of fresh soil (each equivalent to 50 g DW) from each treatment were

incubated under dark in airtight jars at 30 ºC and a water holding capacity (WHC) of 60%,

for preconditioning purposes, during 1 week. Subsequently, two of the replicates were

heat-stressed at 40 ºC for 18 hours and then left unwatered (disturbance: “heat wave +

drought”); another two replicates were amended with 600 mg Cu kg-1 DW soil as CuCl2

(the addition of the water-dissolved CuCl2 increased the WHC up to 80%) (disturbance:

“Cu-amendment”); the remaining two replicates were left untreated as controls (for

comparison purposes, water was added to the soil to adjust the WHC to 80%). Twenty


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days later, WHC was adjusted to 80% in one of the two heat-stressed replicates

(disturbance: “heat wave”). Thus, three different types of disturbance were studied: (1)

Cu-amendment (persistent disturbance); heat wave + drought (persistent disturbance),

and heat wave (transient disturbance). Soil basal respiration and NPR were determined in

all 6 jars according to ISO 16072 Norm and ISO 15685 Norm, respectively, at 20 and 60

days of incubation. From the values of soil basal respiration and NPR, resistance (RS) and

resiliency (RL) indexes were calculated (Orwin and Wardle, 2004):

where D0 is the difference between control (C0) and disturbed at 20 days, while Dx is

the difference between control and disturbed at 60 days of incubation. These indexes are

bounded by -1 and +1, a value of +1 meaning maximal resistance or resilience.

In Cu-amended soils, the bioavailable fraction of Cu was determined (0.01 M CaCl2

as extractant) by AAS throughout the incubation time, as a possible decrease in

bioavailable Cu concentration could modify data interpretation (however, bioavailable Cu

concentration did not vary throughout the experimental period and then data are not

shown). Likewise, WSOC was measured at the end of the incubation (60 days), to

determine its possible effect on values of soil basal respiration and NPR.


Differences among treatments were analyzed by one-way ANOVA using Microsoft

Stat View Software (SAS Institute). Tukey Kramer-test was used to establish the

significance of the differences among means. Pearson’s correlations were calculated using

SPSS Programme (Inso Corporation).

10.4 Results

10.4.1 Plant parameters and soil properties

At the end of the experiment, T. caerulescens biomass was significantly higher in T+F

than in T or T+R pots (Table 10.1). Similarly, significantly highest values of F. rubra

biomass were observed in T+F pots. Although differences were not statistically

( ) 12

)(0

0 −+

=x

x DDD

tRL( )00

00

21)(

DCD

tRS+

−=


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significant, highest values of R. acetosa biomass were found in T+R pots (on average, 19

leaves per R. acetosa plant were observed in T+R pots versus 12 in R pots). Regarding plant

height, F. rubra plants reached a mean value of 24 cm in T+R pots versus only 13 cm in F

pots and 10 cm in both R+F and T+R+F pots.

Table 10.1. Shoot biomass and Zn concentration achieved by each pseudometallophyte in the different treatments at the end of the experiment. Values followed with different letters are significantly different

(P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 3) ± standard errors.

T. caerulescens R. acetosa F. rubra

Shoot biomass (g DW plant-1)

T 0.27 ± 0.07a

R 0.57 ± 0.03a

F 0.12 ± 0.01a

T+R 0.26 ± 0.02a 0.93 ± 0.02a

T+F 0.54 ± 0.04b 0.52 ± 0.03b

R+F 0.81 ± 0.11a 0.11 ± 0.01a

T+R+F 0.42 ± 0.01ab 0.77 ± 0.05a 0.14 ± 0.01a

Shoot Zn concentration (mg Zn kg-1 DW)

T 364 ± 37a

R 374 ± 32a

F 154 ± 12a

T+R 417 ± 48a 428 ± 10a

T+F 399 ± 18a 149 ± 8a

R+F 339 ± 33a 145 ± 9a

T+R+F 541 ± 38a 404 ± 64a 158 ± 5a

With regard to plant metal accumulation, negligible values of Cd and Pb shoot

concentration were found in the three pseudometallophytes. As far as Zn is concerned

(Table 10.1), significantly higher values of Zn shoot concentration in T. caerulescens were

observed in T+R+F (541 mg Zn kg-1 DW) than in T pots (364 mg Zn kg-1 DW). By

contrast, no significant differences were observed among treatments regarding Zn shoot

concentration in R. acetosa and F. rubra (on average, R. acetosa accumulated 386 mg Zn kg-1

DW shoot while F. rubra accumulated 152 mg Zn kg-1 DW shoot). Concerning the total


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amount of Zn phytoextracted from the soil (shoot metal concentration x shoot biomass)

(Figure 10.2), highest values were found in T+R pots (1.51 mg), closely followed by R

(1.26 mg) and T+R+F (1.10 mg) pots. On the contrary, only 0.11 mg of Zn were

phytoextracted in F pots.

Figure 10.2: Amount of Zn extracted under each treatment. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test.

On the other hand, no significant differences were observed among treatments

regarding soil total or bioavailable metal concentrations (data not shown).

Regarding correlations between pseudometallophytes composition and soil

physicochemical properties, soil pH was significantly lower (P<0.001) when R. acetosa was

present in the pots (pH = 4.6 and 5.1 in the presence and absence of R. acetosa,

respectively). A positive correlation was found between soil pH and biomass of T. caerulescens (R = 0.657, P<0.020) and R. acetosa (R = 0.677, P<0.016). A positive

correlation was observed between soil pH and WSOC (R = 0.467, P<0.021).


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T

able

10.2

: Valu

es o

f enz

yme

activ

ities

in th

e di

ffer

ent t

reat

men

ts a

t the

end

of t

he e

xper

imen

t. O

vera

ll E

nzym

e A

ctiv

ity (O

EA

) was

calc

ulat

ed fr

om th

e va

lues

of

β-gl

ucos

idas

e, ac

id p

hosp

hata

se, a

rylsu

lpha

tase

and

ure

ase,

as fo

llow

s: th

e hi

ghes

t valu

e fo

r eac

h en

zym

e ac

tivity

was

con

sider

ed a

s 100

; the

oth

er v

alues

wer

e tra

nsfo

rmed

acc

ordi

ngly;

fina

lly, t

he m

ean

of a

ll fo

ur e

nzym

e act

iviti

es w

as c

alcul

ated

. Valu

es fo

llow

ed w

ith d

iffer

ent l

ette

rs a

re si

gnifi

cant

ly di

ffere

nt (P

<0.

05 o

r lo

wer

) acc

ordi

ng to

Tuk

ey K

ram

er-te

st. M

ean

valu

es (n

= 3

) ± st

anda

rd e

rror

s.

D

ehyd

roge

nase

β-

Glu

cosi

dase

Ar

ylsu

lpha

tase

Ac

id p

hosp

hata

se

Ure

ase

(m

g IN

TF

kg-1 2

0 h-

1 ) (m

g ρ-

Nitr

ophe

nol k

g-1 h

-1)

(mg

N-N

H4+

kg-

1 h-

1 ) O

EA

Con

trol

41.3

± 0

.00*

81

.7 ±

1.2

9a

1.90

± 0

.07a

18

85 ±

122

.1ab

13

9 ±

3.7

2a

86 ±

3ab

T

42.2

± 0

.00*

82

.7 ±

2.3

6a

2.01

± 0

.07a

18

90 ±

37.

3a

134

± 4

.73a

b 87

± 2

a

R

42.6

± 0

.00*

98

.2 ±

6.8

4a

1.51

± 0

.09b

19

12 ±

141

.5a

120

± 7

.96a

bcd

83 ±

3ab

c

F <

40

82.0

± 8

.72a

1.

65 ±

0.0

5ab

1794

± 1

28.0

ab

131

± 2

.06a

bc

81 ±

4ab

c

T+R

<

40

94.4

± 7

.11a

1.

40 ±

0.0

4b

1473

± 1

7.6a

b 10

8 ±

1.4

6bcd

73

± 1

abc

T+F

52

.6 ±

6.6

5a

81.3

± 2

.74a

1.

41 ±

0.0

5b

1635

± 3

4.0a

b 10

6 ±

2.0

4cd

72 ±

2bc

R+F

58

.2 ±

4.1

4a

82.0

± 6

.63a

1.

43 ±

0.0

6b

1377

± 1

7.1b

10

4 ±

5.0

0cd

69 ±

2c

T+R

+F

<40

91

.7 ±

7.3

8a

1.33

± 0

.06b

14

76 ±

24.

8ab

102

± 5

.54d

71

± 1

c *O

nly

one

of th

e re

plica

tes w

as a

bove

det

ectio

n lim

it


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212

212

With regard to enzyme activities (Table 10.2), values for dehydrogenase were below

detection limit in F, T+R and T+R+F pots. β-glucosidase values showed no significant

differences among treatments (this activity was positively correlated with soil bioavailable

Zn concentration; R = 0.499, P<0.013). Control and T pots showed significantly higher

values of arylsulphatase than all the other pots. T and R pots had significantly higher

values of acid phosphatase than R+F pots (Table 10.2). Lastly, control pots showed

significantly higher values of urease than T+R+F pots. Three enzyme activities were

negatively correlated with the number of pseumetallophytes present in the pots: acid

phosphatase (R = -0.659, P<0.001), arylsulphatase (R = -0.731, P<0.001) and urease (R =

-0.800, P<0.001). These three enzyme activities showed a positive correlation with soil

pH (R = 0.415, P<0.044 for acid phosphatase; R = 0.581, P<0.003 for arylsulphatase; R

= 0.533, P<0.007 for urease) and WSOC (R = 0.765, P<0.001 for acid phosphatase; R =

0.452, P<0.027 for arylsulphatase; R = 0.586, P<0.003 for urease). Values of OEA were

higher in control pots and in those with only one pseudometallophyte, as compared to

those with 2-3 pseudometallophytes.

Table 10.3: Values of microbial biomass carbon (MBC), and fungal and bacterial abundance as

determined by real-time PCR. F:B ratio: ratio of fungal to bacterial abundance. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test. Mean values

(n = 3) ± standard errors.

MBC Fungi Bacteria F:B ratio

(mg C kg-1 DW soil) (107 copies g-1 DW soil)

Control 226 ± 15.4a 1.26 ± 0.58a 46.41 ± 15.87a 0.024 ± 0.003a

T 240 ± 0.7ab 1.00 ± 0.27a 42.72 ± 11.52a 0.024 ± 0.004a

R 264 ± 38.4ab 1.97 ± 1.01a 14.03 ± 1.33a 0.126 ± 0.055a

F 316 ± 15.5ab 1.43 ± 0.77a 70.34 ± 42.87a 0.029 ± 0.007a

T+R 251 ± 16.0ab 1.20 ± 0.58a 42.45 ± 27.92a 0.058 ± 0.019a

T+F 262 ± 8.2ab 0.97 ± 0.34a 47.31 ± 25.84a 0.032 ± 0.009a

R+F 285 ± 13.9ab 1.76 ± 0.13a 55.34 ± 3.77a 0.032 ± 0.001a

T+R+F 340 ± 8.5b 2.74 ± 1.41a 131.09 ± 79.26a 0.026 ± 0.003a

T+R+F pots had significantly higher values of microbial biomass C than control

pots (Table 10.3). No significant differences were found among treatments regarding


213

213

213

bacterial and fungal abundances calculated from real-time PCR (Table 10.3). Although

differences were not statistically significant, highest values of fungal and bacterial

abundances were observed in T+R+F soils. Bacterial and fungal abundances were

positively correlated among each other (R = 0.820, P<0.001) and followed similar trends,

except for R pots. In R pots, lowest values of bacterial abundance and concomitant

highest values of F:B (fungal abundance: bacterial abundance) ratio were observed

(differences were not statistically significant).

Figure 10.3 shows the AWCD curves obtained from Biolog EcoplatesTM. At 44 h of

incubation, values of AWCD in T+F and T pots were significantly higher than in C and R

pots. A positive correlation was found between values of AWCD and biomass of T. caerulescens (R = 0.694, P<0.012) and F. rubra (R = 0.712, P<0.009). On the contrary, no

significant differences were found among treatments regarding values of area under the

AWCD curves (data not shown). A positive correlation was found between area under

AWCD curves and biomass of T. caerulescens (R = 0.658, P<0.020) and F. rubra (R = 0.653,

P<0.021). Values of area under AWCD curves and AWCD at 44 h incubation were

positively correlated with soil pH (R = 0.477, P<0.019 for area under AWCD curves; R =

0.591, P<0.002 for AWCD at 44 h).

Figure 10.3: Average well colour development (AWCD) curves for each treatment. Mean values (n = 3).


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214

Regarding S and H’ calculated from enzyme activities, no significant differences

among treatments were observed (Table 10.4). Values of S and H’ from enzyme activities

were negatively correlated with soil bioavailable Zn concentration (R = -0.568, P<0.004

for S; R = -0.569, P<0.004 for H’). In contrast, S and H’ from CLPPs (Table 10.4) did

show some significant differences among treatments: highest and lowest values of S and

H’ were found in T+F and R pots, respectively. Concerning S and H’ calculated from

PCR-DGGE for bacteria and fungi (Table 10.4), no significant differences among

treatments were observed.

Table 10.4: Richness (S) and Shannon´s diversity (H’) indexes calculated from enzyme activities, CLPPs

and DGGE (both bacterial and fungal) data. Values followed with different letters are significantly different (P<0.05 or lower) according to Tukey Kramer-test. Mean values (n = 3) ± standard errors.

Enzymes CLPPs DGGE

S H’ S H’ S-Bact H’-Bact S-Fungi H’-Fungi

Control 4.33 ± 0.27a 2.09 ± 0.09a 19.33 ± 0.54abc 4.09 ± 0.04abcd 19.00 ± 0.47a 4.17 ± 0.03a 13.00 ± 0.82a 3.50 ± 0.10a

T 4.33 ± 0.27a 2.10 ± 0.09a 24.33 ± 1.52bab 4.39 ± 0.07ab 17.00 ± 1.89a 3.94 ± 0.15a 11.67 ± 1.09a 3.34 ± 0.13a

R 4.33 ± 0.27a 2.09 ± 0.08a 14.33 ± 1.09c 3.67 ± 0.06c 14.33 ± 1.19ª 3.75 ± 0.12a 10.00 ± 1.25a 3.10 ± 0.20a

F 4.00 ± 0.00a 1.99 ± 0.01a 21.33 ± 2.60abc 4.18 ± 0.16abd 13.00 ± 1.63a 3.58 ± 0.17a 12.33 ± 0.54a 3.43 ± 0.04a

T+R 4.00 ± 0.00a 1.99 ± 0.00a 19.00 ± 0.47bc 4.04 ± 0.05abcd 15.67 ± 0.98a 3.88 ± 0.09a 11.33 ± 0.27a 3.39 ± 0.02a

T+F 4.67 ± 0.27a 2.20 ± 0.09a 26.67 ± 0.27a 4.50 ± 0.02a 14.67 ± 0.72a 3.79 ± 0.07a 12.00 ± 0.82a 3.35 ± 0.10a

R+F 4.67 ± 0.27a 2.20 ± 0.09a 18.33 ± 1.09bc 4.01 ± 0.07bcd 14.67 ± 1.66a 3.78 ± 0.16a 12.00 ± 0.47a 3.40 ± 0.03a

T+R+F 4.00 ± 0.00a 1.99 ± 0.01a 17.00 ± 0.82bc 3.83 ± 0.06cd 16.67 ± 0.98a 3.97 ± 0.08a 13.00 ± 1.25a 3.43 ± 0.12a

10.4.2 Soil ecosytem health

10.4.2.1 Sorghum productivity essay

The rate of sorghum germination was significantly higher in control and R pots (6.9-

and 5.5-fold higher, respectively), as compared to all the other pots. Similarly, productivity

values were significantly higher in control (7.7-fold) and R (7.6-fold) pots, as compared to

all the other pots.


215

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215

T

able

10.5

: Valu

es o

f soi

l res

istan

ce a

nd re

silien

cy in

dexe

s, ca

lculat

ed fr

om re

spira

tion

and

NPR

dat

a, in

all t

reat

men

ts at

the

end

of th

e exp

erim

ent,

whe

n su

bjec

ted

to th

ree

diffe

rent

type

s of d

istur

banc

e: (i)

Cu-

amen

dmen

t; (ii

) hea

t wav

e-dr

ough

t; an

d (ii

i) he

at w

ave

(see

text

). V

alues

follo

wed

with

diff

eren

t let

ters

are

signi

fican

tly

diffe

rent

(P<

0.05

or l

ower

) acc

ordi

ng to

Tuk

ey K

ram

er-te

st (l

ower

cas

e let

ters

: am

ong

treat

men

ts; u

pper

cas

e let

ters

: am

ong

dist

urba

nces

). So

il re

spira

tion

valu

es

follo

wed

with

an

aste

risk

are

signi

fican

tly d

iffer

ent (

P<0.

05 o

r low

er) a

ccor

ding

to T

ukey

Kra

mer

-test

as c

ompa

red

to th

eir c

orre

spon

ding

NPR

valu

es. M

ean

valu

es

(n =

2) ±

stan

dard

err

ors.

R

ESI

STAN

CE

R

ESI

LIE

NC

Y

C

u-am

endm

ent

Hea

t wav

e-dr

ough

t &

H

eat w

ave

Cu-

amen

dmen

t H

eat w

ave-

drou

ght

Hea

t wav

e

R

esp.

N

PR

Res

p.

NPR

R

esp.

N

PR

Res

p.

NPR

R

esp.

N

PR

Con

trol

0.75

± 0

.01a

A*

0.53

± 0

.02a

A

0.39

± 0

.05a

B 0.

38 ±

0.0

9aA

0.04

± 0

.00a

A*

-0.4

7 ±

0.0

3aA

0.04

A

-0.4

8A

0.99

B -0

.26A

T

0.89

± 0

.03a

A

0.57

± 0

.06a

A

0.35

± 0

.06a

B 0.

29 ±

0.0

7aA

-0.3

1 ±

0.1

1aA

-0.5

5 ±

0.0

9aA

-0.1

0A

-0.1

5A

0.88

A

-0.1

0A

R

0.93

± 0

.01a

A*

0.38

± 0

.01a

bA

0.46

± 0

.04a

B 0.

33 ±

0.0

6aA

-0.6

9 ±

0.0

3aA*

0.26

± 0

.05a

A

-0.1

9A

0.17

A

0.31

A

0.00

A

F 0.

86 ±

0.0

3aA*

0.26

± 0

.03b

A

0.25

± 0

.02a

B 0.

23 ±

0.0

5aA

-0.3

7 ±

0.0

6aA

0.20

± 0

.23a

A

0.12

A

0.06

A

0.82

A

0.39

A

T+R

0.

91 ±

0.0

5aA*

0.40

± 0

.03a

bA

0.22

± 0

.02a

B 0.

21 ±

0.0

2aA

0.07

± 0

.34a

A

-0.0

7 ±

0.1

1aA

0.06

A

0.51

A

0.98

A

0.71

A

T+F

0.

75 ±

0.0

0aA*

0.32

± 0

.04a

bA

0.42

± 0

.05a

B 0.

43 ±

0.1

7aA

-0.2

8 ±

0.0

0aA*

0.09

± 0

.01a

A

-0.1

3B

0.47

B 0.

99C

0.28

AB

R+F

0.

83 ±

0.1

0aA*

0.22

± 0

.02b

A

0.19

± 0

.01a

B 0.

32 ±

0.0

4aA

-0.2

0 ±

0.0

1aA

-0.2

0 ±

0.0

5aA

0.11

B -0

.15A

0.

84C

-0.2

5A

T+R

+F

0.81

± 0

.00a

A*

0.26

± 0

.01b

A

0.23

± 0

.02a

B 0.

57 ±

0.0

6aA

-0.3

5 ±

0.0

7aA

0.01

± 0

.07a

A

0.01

A

0.05

A

0.72

A

0.55

A


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216

216

10.4.2.2 Soil stability

Resistance and resilience indexes calculated from basal respiration and NPR data are

presented in Table 10.5. Regarding RS calculated from respiration data in Cu-amended

and heat-treated soils, no significant differences were observed among treatments.

Significantly lower values of RS calculated from respiration were found in heat-treated

versus Cu-amended soils (probably due to the 41% increase in WSOC observed in Cu-

amended soils).

As far as RS from NPR in Cu-amended soils is concerned, C and T soils showed

significantly higher values of RS than F, R+F and T+R+F soils. By contrast, no

significant differences in RS from NRP were found among treatments in heat-treated

soils. No significant differences in RS from NPR were observed between Cu-amended

and heat-treated soils.

Concerning RL (Table 10.5), in Cu-amended soils, no differences were found

among treatments. In “heat wave-drought” soils, highest values of RL were observed in F

soils when calculated from respiration data and in T+R soils when calculated from NPR

data. In “heat wave” soils, highest values of RL were observed in T and T+F soils when

calculated from respiration data and in T+R soils when calculated from NPR data. In

T+F and R+F soils, significantly higher values of RL were observed in “heat wave-

drought” and “heat wave” soils than in Cu-amended soils when RL was calculated from

respiration data. Likewise, RL calculated from soil respiration data were higher in “heat

wave” soils than in “heat wave-drought” soils (differences were statistically significant in

C, T+F and R+F). The addition of water to the “heat wave” soils led to a 30% increase in

WSOC (this parameter remained constant in “heat wave-drought” soils), resulting in a

stimulated soil microbial community.

10.4.2.3 Attributes of ecosystem health and overall ecosystem health

Control, T, R and F soils showed higher values of vigor than those soils where 2-3

pseudometallophytes were present (Table 10.6). Lowest and highest values of

organization were found in R and T+F soils, respectively. Lowest values of stability were

found in T and R soils. Highest values of stability were found in T+R soils. Finally, lowest

values of overall ecosystem health were found in R soils. Highest values of overall

ecosystem health were found in F and T+F soils.


217

217

217

Table 10.6: Soil vigor, organization, resiliency and overall health in the different treatments at the end of the experiment. Values were scaled from 1 to 10 (1 = lowest; 10 = highest).

Vigor Organization Resiliency Health

Control 5 6 5 5

T 5 6 4 5

R 5 3 4 4

F 6 4 7 6

T+R 3 4 8 5

T+F 4 7 7 6

R+F 4 6 5 5

T+R+F 4 4 6 5

10.5 Discussion

10.5.1 Soil and plant parameters

Although our metalliferous soil was only slightly polluted with metals, it did surpass

the reference critical values reported for the protection of ecosystems in the Basque

Country for soils of these characteristics (i.e., 0.8, 32.8 and 60.1 mg kg-1 for Cd, Pb and

Zn, respectively) (IHOBE, 1998). We selected for this study a metalliferous soil with a

low level of metal polution in order to be able to detect improvements in soil ecosystem

health in a short-term experiment such as ours.

In the “Txomin” mine, soil metal concentrations might be responsible for the

relatively high soil OM content, as OM accumulation in metal polluted soils might occur

due to metals impeding mineralization cycles (Chander and Brookes, 1991). As a

consequence of the scarce mineralization of OM, nutrient contents (N, P and K+) are also

very low in the “Txomin” mine soil. In metalliferous soils, microbial communities are

usually exposed to high levels of available toxic heavy metals (Figure 1), with concomitant

negative consequences for soil ecosystem functioning. In this respect, as reported by van

der Heijden et al. (2008), microbial diversity is likely to have the biggest impact on

ecosystem performance in nutrient poor ecosystems.

As far as plant biomass is concerned, growing together with T. caerulescens proved

stimulatory for the other two pseudometallophytes (Table 10.1). In previous works, we

confirmed the Zn hyperaccumulation capacity of the Lanestosa ecotype of T. caerulescens


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218

218

used in this study (Hernandez-Allica et al., 2006; Epelde et al., 2009b). In the current

work, total Zn concentration in soil was low and, consequently, shoot metal

concentration in T. caerulescens was much lower, not reaching the threshold value of 10,000

mg Zn kg-1 DW indicated by Baker et al. (2000) for Zn hyperacummulators. In any case,

it appears plausible that the stimulatory growth effect caused by T. caerulescens on the other

pseudometallophytes might be due to its metal phytoextraction: T. caerulescens showed

highest values of shoot Zn concentrations, but was closely followed by R. acetosa. We have

recently highlighted the potential of R. acetosa for Zn phytoextraction (Barrutia et al.,

2008). Unfortunately, one of the most important constraints for the utilization of T. caerulescens for metal phytoextraction is its low biomass production and slow rate of

growth. Actually, regarding total metal phytoextracted from soil, the greater shoot

biomass of R. acetosa, as compared to that of T. caerulescens, compensated for its lower

shoot metal concentration (Figure 10.2): R. acetosa, mainly in combination with T. caerulescens, phytoextracted the highest amounts of Zn from our soil (T+R was the best

option for phytoextraction).

F. rubra phytoextracted by far the lowest amount of Zn. This species might be a

good candidate for metal phytostabilization. Certainly, for phytostabilization, low values

of shoot Zn concentration are desired, as the risk of metals entering the food chain

decreases. The simultaneous utilization of both approaches (phytoextraction and

phytostabilization) for the phytoremediation of metal polluted sites appears an interesting

option, as metal uptake by phytoextracting plants does not seem to be diminished by the

presence of phytostabilizating plants.

Values of soil pH increased with increasing values of T. caerulescens and R. acetosa

biomass. In agreement with other works (Luo et al., 2000; Epelde et al., 2008a), metal

accumulation in T. caerulescens appears not to be achieved through soil acidification.

Regarding soil microbial properties, enzyme activities control the rates of soil

nutrient cycling and provide a unique integrative biological assessment of soil function,

especially those catalyzing a wide range of biological processes, such as dehydrogenase,

urease, phosphatase, etc. (Nannipieri et al., 2002). In our study, values of dehydrogenase

activity were most of the times below detection limits which indicates a very low level of

overall microbial activity in our soil. Except for β-glucosidase, in general, a negative

correlation was found between enzyme activities (and OEA) and number of


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219

pseudometallophytes present in the pots (Table 10.2). On the contrary, Yang et al. (2007)

found urease to be higher in two and four species mixtures compared to monoculture,

while no significant effects of species mixtures on acid and alkaline phosphatases or

dehydrogenase were observed.

Regarding CLPPs (Figure 10.3), no differences among treatments were found

regarding area under AWCD curves (nevertheless, T and T+F pots showed significantly

higher values of AWCD at 44 h). The area calculation procedure has the advantage of

collapsing the absorbance versus time curves down to a single value that integrates

information from the entire incubation period (it incorporates the lag phase, the rate of

development and the extent of dye development for each well) (Guckert et al., 1996). In a

study by Loranger-Merciris et al. (2006), three and four species mixtures had higher

culturable bacterial activity than monocultures and two species mixtures.

Remarkably, a positive correlation was observed between soil pH and many

microbial parameters (acid phosphatase, arylsulphatase, urease, OEA, AWCD, area under

AWCD curve). Similar results were reported by Wang et al. (2006), confirming the

character of master variable for soil pH.

Highest values of microbial biomass C were observed in T+R+F pots (Table 10.3).

Although differences were not statistically significantly, highest values of bacterial and

fungal abundances were also found in T+R+F pots (the three parameters, i.e. microbial

biomass C and bacterial and fungal abundances, followed similar patterns). Zak et al.

(2003) reported that plant communities influence soil microbial biomass mainly through

plant litter and root exudates rather than through plant diversity per se. In a study by Yang

et al. (2007), plant mixtures did not affect microbial biomass C.

Highest values of F:B ratio were found in R pots, suggesting a high fungal

abundance in the R. acetosa rhizosphere. The relative abundance of bacteria and fungi in

ecosystems receives a large amount of attention, but little is known about its functional

significance (van der Heijden et al., 2008). In general terms, bacteria-dominated food

webs might enhance rates of nutrient mineralization and availability of nutrients to plants,

whereas fungal-dominated food webs promote slow and highly conservative cycling of

nutrients (Wardle et al., 2004).


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From an ecological perspective, in the soil ecosystem, functional diversity, as

opposed to structural diversity, provides more relevant information (Torsvik and Øvreås,

2007). There are different methods to determine functional diversity of soil microbial

communities such as, for instance, enzyme activities (Larson et al., 2002) and CLPPs

(Preston-Mafham et al., 2002). In our study, enzyme activities responded negatively to soil

bioavailable Zn concentration. This negative correlation was not observed for total Zn

concentration, emphsizing the higher toxicity caused by bioavailable metals (as compared

to non-bioavailable metals). Concerning CLPPs, lowest values of S and H’ were found in

R soils, which could well be related to the high F:B ratios observed for this treatment.

Meanwhile, in agreement with AWCD data, highest values of S and H’ were observed in

T+F soils. In the work by Yang et al. (2007), soil microbial functional diversity was higher

under two and four species mixtures than under monocultures. The lack of correlation

between data on enzyme activities and CLPPs here found in not surprising, as Biolog

EcoPlatesTM reflect the potential of only the culturable portion of the heterotrophic

microbial community to respond to C substrates, while enzyme analyses reflect the status

of the whole microbial community.

The use of cultivation-independent methods, such as PCR-DGGE, removes the

bias imposed by techniques based on culturing organisms (Ellis et al., 2003). Indeed,

culture-independent methods take into account a greater complexity than that

traditionally studied with culture-dependent methods (Yang et al., 2001), although the

relevance of this fact in terms of ecosystem function is rarely discussed (McCaig et al.,

2001). In our study, no differences were found among treatments regarding bacterial or

fungal structural genotypic diversity (Table 10.4). In contrast, various studies have shown

that composition of soil microbial communities may vary markedly depending on

aboveground vegetation (Bardgett et al., 1998; Wardle et al., 1999), mainly through

development of beneficial rhizobacteria by the release of specific sugars and amino acids

into the rhizosphere (Kowalchuk et al., 2002).

10.5.2 Soil ecosystem health

Most interestingly, and to our knowledge in a pioneering way, a methodology to link

the concept of soil health to that of ecosystem health is here described. To this aim, we

propose to interpret the values of biological indicators of soil health (particularly, those


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related to the biomass, activity and diversity of the soil microbial communities) from the

point of view of the attributes measured when assessing ecosystem health: vigor,

organization and stability (Rapport, 1998), in an attempt to integrate many different soil

parameters within a single concept, i.e. overall ecosystem health. Although these types of

integrative approaches often entail loss of valuable information and an oversimplification

of the frequently overwhelming complexity of ecosystems, they are of great value for, and

mostly needed by, soil managers, legislators, conservation decision-takers and so on. Data

on ecosystem health must be analyzed from a environmental manager´s point of view,

more than from an ecologist´s perspective.

We propose vigor to be measured from values of OEA (enzyme activities provide a

unique integrative biological assessment of soil function), area under AWCD curves,

microbial biomass C and sorghum productivity (sorghum was chosen for productivity

essays in metalliferous soils due to its metal tolerance). Interestingly, soils with only one

pseudometallophyte showed higher values of vigor than those where 2-3

pseudometallophytes were present.

Organization refers to ecosystem complexity and is affected by both diversity of

species and number of pathways of material exchange between each component

(Costanza et al., 1998). Consequently, we propose organization to be measured from

values of S and H’ from enzyme activities, CLPPs and PCR-DGGE. Highest values of

organization were found in T+F soils, which also had highest values of overall ecosystem

health.

The concept of stability comprises both resilience, the property of the system to

recover after disturbance, and resistance, the inherent capacity of the system to withstand

disturbance (Lazzaro et al., 2006). There is a lot of confusion regarding the terminology

used in ecological stability studies, with a variety of terms, such as constancy, resilience,

persistance, resistance, elasticity, etc. used differently and often interchangeably in the

literature, but it is not within the scope of this manuscript to engage in a comparative

discussion on those terms (for a very interesting discussion on the topic, see Grimm and

Wissel, 1997). We propose stability (possibly the most important attribute of ecosystem

health in soils subjected to pollution) to be assessed through the integration of resistance

and resilience indexes calculated after disturbances (Cu-amendment; heat wave-drought;

heat wave) using soil respiration and NPR data. Interestingly, T+R showed the highest


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and lowest values of stability and vigor, respectively, indicating a lack of correlation

between different attributes of ecosystem health. On the other hand, regarding the

different patterns obtained when calculating RS from respiration versus NPR data, this is

not an unexpected results, since soil respiration is a measure of general activity while NPR

targets a much narrower process in terms of microbial phylogeny. Griffiths et al. (2001)

compared functional stability on paired grassland soils to which different environmental

impacts were applied (different levels of plant biodiversity, polluted versus non-polluted,

etc.). These authors reported that the polluted soil was less resistant to heat stress than

the corresponding non-polluted. On the other hand, there was an apparent delay in the

recovery of the one-species grassland soil, but it showed a greater resilience than the six-

species soil.

Finally, when averaging vigor, organization and stability to obtain a final value of

soil overall ecosystem health, no major differences among treatments were observed

(including control unplanted soils), indicating that the growth of the different

pseudometallophytes did not exert a clear overall beneficial effect on rhizosphere soil

health, which is understandable taking into account the short duration of our experiment.

Much further research is needed to: (i) unravel the links between aboveground

pseudometallophytes and belowground rhizosphere microbial communities in

metalliferous soils and (ii) properly quantify the improvement in soil ecosystem health

caused by pseudometallophytes growth in metalliferous soils.

10.6 Conclusions

As far as plant biomass is concerned, growing together with T. caerulescens proved

stimulatory for the other two pseudometallophytes, probably due to its metal

phytoextraction. R. acetosa, especially in combination with T. caerulescens, phytoextracted

the highest amounts of Zn from our metalliferous soil. Lowest values of microbial

functional diversity (S and H’), as reflected by the values of CLPPs obtained with Biolog

EcoplatesTM, were found in soils planted only with R. acetosa. Except for β-glucosidase, in

general, a negative correlation was found between values of enzyme activities and number

of pseudometallophytes present in the pots. Highest values of microbial biomass C were

observed in the presence of the three pseudometallophytes. Most interestingly, a

methodology to link the concept of soil health to that of ecosystem health is here


223

223

223

proposed, assigning soil microbial properties to attributes of ecosystem health. Although

these types of integrative approaches often entail loss of valuable information and an

oversimplification of the frequently overwhelming complexity of ecosystems, they are of

great value for, and mostly needed by, soil managers, legislators, conservation decision-

takers and so on. When averaging vigor, organization and stability to obtain a final value

of soil overall ecosystem health, no major differences among treatments were observed

(including control unplanted soils), indicating that the growth of the different

pseudometallophytes did not exert a clear overall beneficial effect on rhizosphere soil

health.

11. síntesis

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224

11. SÍNTESIS

La supervivencia de nuestra sociedad está ligada de forma inextricable a la salud del

suelo. Por desgracia, en las últimas décadas, se ha liberado al suelo una gran cantidad de

sustancias químicas contaminantes que están afectando seriamente la funcionalidad y

sostenibilidad de este recurso, convirtiéndose así en un problema medioambiental de

enorme repercusión y trascendencia. Por suerte, existen en la actualidad una serie de

tecnologías de descontaminación de suelos contaminados que presentan un enorme

potencial para paliar/solucionar la preocupante degradación de nuestros suelos derivada

de la acumulación de contaminantes. Dentro de estas tecnologías, en este trabajo se ha

profundizado en la fitorremediación, una fitotecnología que se basa en la capacidad de

algunas especies vegetales (y microorganismos asociados) para tolerar, absorber, acumular

y degradar compuestos contaminantes (Salt et al., 1995).

El marco conceptual en el que se sustenta este trabajo es la convicción de que el

objetivo último de un proceso fitorremediador de suelos contaminados no debe ser

solamente eliminar el contaminante o, en su defecto, reducir su concentración hasta los

límites marcados en la legislación, sino recuperar la salud del suelo (Epelde y cols., 2009a),

entendida ésta como la capacidad de este vital recurso para realizar sus funciones de

forma sostenible (Coleman y cols., 1998), desde una doble perspectiva antropocéntrica-

bio/ecocéntrica. En consecuencia, es indispensable disponer de un conjunto de

indicadores fiables y relevantes que nos permitan evaluar la salud del ecosistema edáfico,

para así poder monitorizar la eficacia de los procesos fitorremediadores de suelos

contaminados (Epelde y cols., 2008c). En este trabajo se ha optado por las propiedades

microbiológicas con potencial indicador de la salud del ecosistema edáfico, frente a las

propiedades físico-químicas tradicionales, en la firme creencia de que dichas propiedades

microbiológicas presentan ciertas ventajas como herramientas monitorizadoras de la

eficacia de procesos fitorremediadores, léase, su rapidez de respuesta, su mayor

sensibilidad, su carácter integrador, y la posibilidad de incorporar en ocasiones el

componente temporal a la evaluación de la funcionalidad del suelo, con el consiguiente

interés para los estudios sobre la sostenibilidad de este recurso (Mijangos y cols., 2009).

Dentro de la extensa casuística de la contaminación de los suelos, este trabajo ha

focalizado, aunque no exclusivamente, su atención a la contaminación por metales en

entornos mineros y a la utilización de especies pseudometalofitas para procesos


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224

fitoextractores y fitoestabilizadores. Las especies nativas pseudometalofitas propias de

entornos mineros presentan una elevada tolerancia a la presencia de concentraciones altas

de metal en suelo y son, asimismo, capaces de crecer en las condiciones adversas

habituales en estos entornos metalíferos (Becerril y cols., 2007). Ciertamente, la utilización

de estas especies nativas pseudometalofitas para fitotecnologías de revegetación y

recuperación de ecosistemas degradados y contaminados con niveles altos de metales es

una alternativa de gran interés (Becerril y cols., 2007).

En el entorno minero de Lanestosa (Bizkaia), a pesar de que los suelos están sin

duda contaminados con niveles muy elevados de Zn, Pb y Cd, se observa una gran

diversidad de flora; no obstante, muchas especies presentan bajas producciones

biomásicas y tasas de crecimiento lentas (Barrutia, 2008), lo cual es esperable en

organismos que han de dedicar gran parte de su maquinaria metabólica y energía a

sobrevivir en condiciones extremas (Salt y cols., 1995). Análogamente, los metales del

suelo afectan a la biomasa, actividad y diversidad de los microorganismos edáficos, si bien

éstos son también capaces de desarrollar mecanismos de tolerancia frente a dichos

compuestos tóxicos (Kelly y cols., 1999). Por otro lado, las plantas y las comunidades

microbianas edáficas están estrechamente relacionadas y el estudio de los vínculos entre

ambos compartimentos biológicos es un tema de indiscutible actualidad (Rodríguez-

Loinaz y cols., 2008). Por desgracia, existen pocos estudios focalizados en la comprensión

de dichos vínculos (“aboveground-belowground links”) que hayan sido realizados en

suelos contaminados (Phillips y cols, 2008; Yang y cols., 2007) y, en este momento, no

tenemos constancia de que alguno haya sido desarrollado en un entorno minero altamente

contaminado por metales (como es el caso de la mina de Lanestosa) en condiciones de

campo.

Por ello, en el Capítulo 4 se estudiaron consorcios de plantas, encontrados de forma

natural en la mina de Lanestosa, compuestos por 1-4 especies pseudometalofitas que

presentan diferentes estrategias de tolerancia a metales: hiperacumuladora: Thlaspi caerulescens; acumuladora: Jasione montana; indicadora: Rumex acetosa; exclusora: Festuca rubra.

Además de analizar la respuesta fisiológica y el potencial fitorremediador de estas

especies, se profundizó en los posibles vínculos entre las especies pseudometalofitas y sus

respectivas comunidades microbianas rizosféricas. Cuando crecía de forma individual (en

ausencia de las otras especies), Thlaspi caerulescens confirmó su capacidad para

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hiperacumular Zn (alcanzó concentraciones de Zn en tallo de hasta un 2.7%) y Pb

(concentración máxima en tallo: 0.14%), corroborando su potencial como especie de gran

interés para estudios/procesos de fitoextracción (McGrath y cols., 2001b; Lombi y cols.,

2002). Por su parte, Jasione montana y Rumex acetosa acumularon también cantidades

considerables de Zn y Pb. Rumex acetosa, especie indicadora según estudios previos

llevados a cabo en este mismo emplazamiento (Barrutia, 2008), no respondió como tal en

este trabajo, posiblemente debido a las elevadas concentraciones de metales presentes en

la zona de estudio. Finalmente, Festuca rubra sí mostró su carácter exclusor, lo cual

confirma su interés para procesos fitoestabilizadores. De acuerdo a los parámetros

fisiológicos cuantificados en este estudio, ninguna de estas cuatro especies

pseudometalofitas mostró síntomas fitotóxicos agudos (ratificando la ausencia de

síntomas visuales de fitotoxicidad que presentaban las plantas en la mina; no obstante,

como se ha mencionado anteriormente, los individuos de estas especies presentaban en

general por una reducida biomasa), lo cual confirma su tolerancia a los metales presentes

en la mina. Procede subrayar que Thlaspi caerulescens mostró algunas características

interesantes relacionadas con la tolerancia al estrés (Collin y cols., 2008), léase, niveles

elevados del ratio A+Z/VAZ y del contenido en tocoferol.

En este estudio (Capítulo 4), no se encontraron correlaciones entre la riqueza de

plantas pseudometalofitas y las propiedades del suelo estudiadas. Sin embargo, la mayoría

de las propiedades microbiológicas del suelo sí estuvieron positivamente correlacionadas

con la biomasa total de las plantas (la suma de las biomasas de todas las especies presentes

en el consorcio). En contraste, a medida que aumentaba la biomasa de Thlaspi caerulescens, se observaba un descenso de los valores de estas propiedades microbiológicas. Es

importante destacar aquí que las propiedades microbiológicas del suelo tuvieron un efecto

mayor sobre la biomasa vegetal que viceversa (35.2% frente a 14.9%). Por otra parte, la

biomasa de Rumex acetosa estuvo positivamente correlacionada con las actividades

enzimáticas del suelo y los valores de S (riqueza) y AWCD (desarrollo de color medio de

los pocillos) obtenidos con las placas Biolog EcoPlatesTM. La biomasa de Jasione montana

estuvo positivamente correlacionada con el carbono de la biomasa microbiana, mientras

que la biomasa de Festuca rubra aumentó en suelos con valores más altos de actividad

fosfatasa ácida, arilsulfatasa y deshidrogenasa. Al contrario, la biomasa de Thlaspi caerulescens aumentó en los suelos con valores más bajos de las propiedades


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microbiológicas estudiadas. Por último, las propiedades físico-químicas y microbiológicas

del suelo mostraron asimismo una fuerte correlación entre ellas.

En relación con la fitoextracción (o utilización de plantas para extraer metales de los

suelos y posteriormente acumularlos en los tejidos aéreos; potencialmente una de las

fitotecnologías de recuperación de suelos contaminados más prometedoras), en este

estudio se investigó asimismo en profundidad la capacidad de una de las especies

pseudometalofitas más interesantes identificadas en la mina de Lanestosa: el ecotipo local

de la especie hiperacumuladora de Zn y Cd Thlaspi caerulescens. De entre las numerosas

(más de 400) especies hiperacumuladoras descritas en la bibliografía (Brooks, 2000),

Thlaspi caerulescens ha sido propuesta como especie modelo para la investigación en

fitoextracción (Assunção y cols., 2003), habiendo sido ampliamente estudiada a este

respecto (Hernández-Allica y cols., 2006a,b; Epelde y cols., 2008a; McGrath y cols., 2006).

Como era esperable debido a su condición de especie hiperacumuladora (las especies

hiperacumuladoras son capaces de tolerar, absorber y acumular en sus tejidos altas

concentraciones de metales, extrayéndolos de forma eficiente del suelo; Assunção y cols.,

2003), el ecotipo Lanestosa de Thlaspi caerulescens demostró su potencial para procesos

fitoextractores de Zn y Cd. A este respecto, en los Capítulos 5 y 6 se muestran dos

estudios de fitoextracción en continuo realizados con este ecotipo. Las plantas de Thlaspi caerulescens demostraron a escala microcosmos su gran tolerancia a niveles elevados de

metales, su capacidad para crecer sin problemas en suelos contaminados por dichos

metales y, sobre todo, su capacidad para hiperacumular Zn y Cd en los tejidos aéreos.

Respecto a la concentración de metales en los suelos vegetados con Thlaspi caerulescens, se observó una disminución de Zn y Cd, tanto total como extractable en

CaCl2, que fue mayor a concentraciones más elevadas. En el Capítulo 5, los valores de

metales totales en suelo sufrieron una disminución más pronunciada que los

correspondientes valores de metal biodisponible (extractable), lo cual puede deberse a las

cinéticas de reposición de las fracciones metálicas disponibles y a la acumulación de metal

en las raíces de Thlaspi caerulescens (Whiting y cols., 2001; Hamer y Keller, 2002).

En el Capítulo 5, la contaminación por metales no causó una clara inhibición de las

actividades enzimáticas del suelo, considerando éstas de forma individual. Por otra parte,

los resultados de diversidad obtenidos a partir de los valores de las actividades enzimáticas

del suelo (diversidad catalítica) y los obtenidos a partir de los perfiles fisiológicos a nivel de

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comunidad (CLPPs; diversidad funcional-catabólica calculada con Biolog EcoPlatesTM) no

fueron concordantes: la presencia de metales en el suelo hizo disminuir significativamente

los valores del índice de diversidad Shannon (H’) obtenidos a partir de los valores de las

actividades enzimáticas y aumentar (aunque no significativamente) los valores de S y H’

obtenidos con las placas Biolog EcoPlatesTM. Sin embargo, éste no es un resultado

sorprendente: las actividades enzimáticas reflejan el estado de la comunidad microbiana

edáfica en su totalidad (en particular, el potencial catalítico de la comunidad microbiana

edáfica en condiciones óptimas de pH, concentración de substrato, temperatura, etc.),

mientras que las placas Biolog EcoPlatesTM reflejan la capacidad (potencial catabólico-

metabólico, funcional) de tan sólo la porción cultivable de la comunidad microbiana

heterótrofa para utilizar las 31 fuentes de carbono (donadores de electrones a la cadena de

transporte respiratoria) incluidas en las Biolog EcoPlatesTM (estos 31 substratos se dividen

en 5 familias químicas: aminas/amidas, aminoácidos, carbohidratos, ácidos carboxílicos y

polímeros). Cabe destacar aquí que la D-celobiosa, el ácido ketobutírico, el ácido D-

málico y la glucosa-1-fosfato fueron utilizados en mayor proporción en los suelos

vegetados con Thlaspi caerulescens y contaminados con metales que en el resto de

tratamientos (no vegetados y/o no contaminados). A este respecto, en plantas

hiperacumuladoras, los niveles de los ácidos cítrico, málico, malónico y oxálico se han

visto correlacionados con la presencia de elevadas concentraciones de Ni o Zn en su

biomasa (Lee y cols., 1978; Tolrá y cols., 1996). En cualquier caso, las plantas de Thlaspi caerulescens muestran constitutivamente concentraciones elevadas de ácido málico/malato

en sus tejidos (Shen y cols., 1997; Boominathan y Doran, 2003).

En el Capítulo 6, se detectó que la presencia de metales en el suelo afectaba a su

funcionamiento: la contaminación por Zn redujo los valores de respiración basal e

inducida por substrato, además de la abundancia de genes oxidadores de amonio (con

1.000 mg Zn kg-1). Análogamente, la presencia de Cd en el suelo hizo disminuir la

abundancia de genes de bacterias totales (con 50 y 250 mg Cd kg-1) y de oxidadores de

amonio (con 250 mg Cd kg-1). Es relevante mencionar que la abundancia de genes

oxidadores de amonio (la oxidación de amonio es el proceso limitante en la tasa de

nitrificación; Yuan y cols., 2005) estuvo positivamente correlacionada con los niveles de

nitrato en suelo. Asimismo, la contaminación por metales (Zn, Cd) afectó a la diversidad

estructural (DGGE) y funcional genética (microarray de genes funcionales Geochip): al

contrario que los parámetros de abundancia de genes y actividad biológica, el número de


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genes detectados en todas las categorías del microarray (léase, ciclo del nitrógeno,

carbono, azufre y fósforo; reducción y resistencia a metales; degradación de

contaminantes orgánicos) aumentaron en los suelos contaminados con metales frente a

los no contaminados. Análogamente, la redundancia funcional o número de variantes

detectados dentro de cada familia de genes estudiados en el Geochip (e.g., actividad

celulasa, resistencia al Zn), pareció aumentar en los suelos contaminados con metales

frente a los no contaminados.

En el Capítulo 5, se observó que como resultado del proceso fitoextractor (que

engloba tanto el crecimiento de Thlaspi caerulescens como la fitoextracción de metales

llevada a cabo por dicha especie hiperacumuladora), la actividad de cinco enzimas del

suelo con funciones clave en los ciclos del C, N, P y S (β-glucosidasa, ureasa, fosfatasa

ácida, fosfatasa alcalina, arilsulfatasa) aumentaba. De hecho, fue la presencia de Thlaspi caerulescens, más que la fitoextracción de metales en sí, la que tuvo mayor influencia en las

propiedades microbiológicas del suelo. En los suelos contaminados con metales, la

presencia de Thlaspi caerulescens hizo aumentar en un 154, 115, 140, 37 y 164% la actividad

β-glucosidasa, arilsulfatasa, fosfatasa ácida, fosfatasa alcalina y ureasa, respectivamente. En

numerosas ocasiones se ha descrito que los suelos vegetados presentan mayores tasas de

actividad microbiana, frente a los no vegetados, debido a la presencia de superficies

adicionales para la colonización microbiana y a los compuestos orgánicos liberados por

las raíces de las plantas (Tate, 1995; Delorme y cols., 2001).

Igualmente, en el Capítulo 6, se describe que la respiración basal e inducida por

substrato, así como la abundancia de genes de bacterias totales y de degradadores de

quitina, aumentaron significativamente en los suelos en los que Thlaspi caerulescens estaba

presente. Aunque la diversidad estructural genética (DGGE) no varió en los suelos

vegetados con Thlaspi caerulescens, el número de genes detectados en el microarray de genes

funcionales así como la redundancia funcional sí se vieron incrementados. La abundancia

de genes de resistencia a Zn y/o Cd fue mayor en presencia de Thlaspi caerulescens. Aunque

ya se pueden encontrar en la bibliografía estudios diversos sobre las comunidades

microbianas propias de los suelos contaminados con metales (Brim y cols., 1999; Sandaa y

cols, 1999b), la información sobre la composición de las comunidades microbianas

rizosféricas de plantas hiperacumuladoras es todavía muy escasa.

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Por desgracia, las plantas hiperacumuladoras como Thlaspi caerulescens tienen

habitualmente un baja producción de biomasa y tasas de crecimiento lentas (igualmente,

por el momento, desconocemos las prácticas agronómicas más adecuadas para optimizar

su crecimiento), lo cual dificulta sobremanera la viabilidad de los procesos de

fitoextracción en continuo. Por consiguiente, y al objeto de solventar asimismo el

inconveniente de tener que sembrar de nuevo la planta fitoextractora después de cada

cosecha, en el Capítulo 7, procedimos a investigar el potencial fitoextractor del sorgo, una

especie de características agronómicas conocidas, elevada biomasa y capaz de rebrotar

después de la cosecha. Así, se estableció un ensayo de fitoextracción en continuo con el

cultivar de gran biomasa y crecimiento rápido Sorghum bicolor x sudanense en un suelo

contaminado con Zn y Cd. Es interesante reseñar que la planta del sorgo tiene además

interés como cultivo energético para la producción de bioetanol, siendo esto una ventaja

que innegablemente debería tenerse en cuenta a la hora de considerar esta especie como

candidata para la fitoextracción: la aceptación y viabilidad de la fitoextracción como

tecnología descontaminadora de suelos contaminados con metales se vería

substancialmente incrementada en el caso de generar algún producto comercializable a

partir de la planta cosechada (de hecho, cualquier aspecto que sirva para aportar valor

añadido al proceso fitorremediador, casi siempre excesivamente dilatado en el tiempo, es

de gran valor a la hora de justificar la viabilidad de esta fitotecnología). Por ello, a ser

posible, las especies de plantas candidatas para la fitorremediación también deberían ser

evaluadas desde el punto de vista de su capacidad para realísticamente generar productos

que pudieran tener un valor económico como, por ejemplo, suplemento alimenticio,

acondicionador de suelo, aditivo energético, etc. (Bañuelos, 2006).

En nuestro estudio, las plantas de sorgo se mostraron altamente tolerantes a la

contaminación por metales, siendo capaces de lograr un buen crecimiento en su

presencia. Además, en las dos primeras cosechas de las tres que se realizaron en este

estudio, los valores de concentración de Cd en tallo excedieron los 100 mg Cd kg-1. En la

tercera cosecha, la acumulación de metal en tallo disminuyó, posiblemente debido a la

reducción observada en los valores de concentración de metal biodisponible en el suelo.

En este caso, al contrario a lo anteriormente mencionado para Thlaspi caerulescens, no se

observó ninguna reposición de las fracciones metálicas biodisponibles desde las fracciones

no biodisponibles.


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Por otra parte, en este ensayo de fitoextracción en continuo con sorgo, se observó

que, en los suelos contaminados con metales, la actividad deshidrogenasa se encontraba

correlacionada con las fracciones biodisponibles de dichos metales, pero no así con las

concentraciones totales correspondientes. En general, las propiedades microbiológicas

determinadas en este estudio (i.e., actividad deshidrogenasa, CLPPs, respiración basal,

respiración inducida por substrato-glucosa, respiración inducida por substrato-solución

modelo rizodepósito, cociente de respiración) mostraron valores más bajos en los suelos

contaminados con metales frente a los no contaminados. A este respecto, se ha descrito a

menudo que los metales influyen negativamente en las propiedades biológicas del suelo y,

por ende, en su funcionalidad (Kandeler y cols., 1996; Giller y cols., 1998; Kelly y Tate,

1998). Después de todo, es bien sabido que los metales pueden afectar negativamente al

crecimiento, morfología y metabolismo de los microorganismos del suelo mediante

perturbaciones de carácter funcional, desnaturalización de proteínas, destrucción de la

integridad membranal, etc. (Leita y cols., 1995).

Una vez más, en el ensayo de fitoextracción con sorgo, también se apreció un

incremento de los valores de las propiedades microbiológicas del suelo medidas en los

tratamientos vegetados, frente a los no vegetados, tal y como ocurría en los Capítulos 5 y

6. Al final del experimento de fitoextracción, los valores del AWCD y de los índices de

diversidad calculados a partir de datos obtenidos con las placas Biolog EcoPlatesTM, así

como los de respiración basal y respiración inducida por substrato-glucosa, fueron

similares en los suelos vegetados contaminados y en los vegetados no contaminados. Es

más, al aplicar el índice de Jaccard a los datos obtenidos con las placas Biolog

EcoPlatesTM, el valor más alto correspondió a la pareja “suelo vegetado contaminado-

suelo vegetado no contaminado”. En consecuencia, se puede concluir que, como

resultado del proceso de fitoextracción con sorgo, que incluye tanto el crecimiento de la

planta como la fitoextracción del metal propiamente dicha, se consiguió recuperar la

funcionalidad del suelo. En lo concerniente a la recuperación de la funcionalidad del suelo

derivada de cualquier proceso fitoextractor, un objetivo ideal razonable es volver a las

condiciones presente en un suelo control válido (léase, un suelo vegetado, no

contaminado de similares características edafoclimáticas).

Sin embargo, al final del experimento con sorgo, y de acuerdo al índice de

germinación con Lepidium sativum, se percibió que los suelos fitorremediados seguían

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siendo significativamente más fitotóxicos que los suelos control no contaminados. Esta

discrepancia entre los resultados obtenidos con el ensayo de germinación frente a los

obtenidos durante la determinación de las propiedades microbiológicas edáficas no es

sorprendente: al fin y al cabo, el ensayo de germinación refleja exclusivamente el efecto de

la contaminación por metales en una especie de planta específica (en este caso, Lepidium sativum), mientras que las propiedades microbiológicas muestran el estado de la

comunidad microbiana edáfica, por lo que no necesariamente tienen que comportarse de

idéntica forma.

Respecto a las propiedades físico-químicas del suelo estudiadas en este ensayo con

sorgo (pH, conductividad eléctrica, contenido en materia orgánica, nitrógeno total,

fósforo y potasio extraíble), se concluyó que no eran tan sensibles como las propiedades

microbiológicas para la evaluación del efecto de la contaminación sobre la funcionalidad

del suelo y de la eficiencia de los procesos fitoextractores.

Asimismo, algunos metales como el Pb tienen una baja disponibilidad en el suelo, lo

que supone una limitación crucial a la hora de plantear su fitoextracción. El

descubrimiento de que la aplicación de agentes quelantes al suelo aumentaba la toma y

translocación por parte de las plantas de metales como el Pb (Blaylock y cols., 1997) abrió

una nueva vía para la fitoextracción de metales de baja disponibilidad y, en particular, para

la utilización de cultivares de gran biomasa en procesos fitoextractores de suelos

contaminados. Sin embargo, por desgracia, muchos quelantes resultan ser tóxicos tanto

para las plantas como para los microorganismos del suelo, además de suponer un riesgo

medioambiental derivado de la concomitante lixiviación de los metales quelados hacia

aguas subterráneas. Por ello, en los últimos años, se ha investigado profusamente en la

búsqueda de quelantes medioambientalmente respetuosos para su aplicación en procesos

de fitoextracción inducida de metales de baja disponibilidad (Grčman y cols., 2003;

Alkorta y cols., 2004d). En el Capítulo 8 se muestra un estudio en el que se investigó el

potencial del EDTA (ácido etilendiaminotetraacético) y del EDDS

(etilendiaminodisuccinato) para la fitoextracción inducida por quelantes de Pb utilizando

plantas de cardo (Cynara cardunculus). El EDTA es un quelante poco biodegradable y

altamente soluble en suelo, por lo que presenta un alto riesgo de provocar efectos

medioambientales adversos debido a la movilización de metales y a su alta persistencia.

Por otra parte, el EDDS es fácilmente biodegradable, causando una menor lixiviación de


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metales. Finalmente, se estudiaron los posibles efectos que la adición de estos quelantes

pudieran tener sobre la comunidad microbiana edáfica.

El EDTA fue mucho más eficiente que el EDDS para la fitoextracción de Pb con

Cynara cardunculus (el EDTA tiene una mayor afinidad por el Pb). El EDTA se degrada

muy lentamente en el suelo (Lombi et al., 2001), mientras que el EDDS tuvo una vida

media de tan sólo 24 h en nuestro estudio. Al aplicarse a los suelos contaminados con Pb,

el EDDS causó una mayor fitotoxicidad sobre las plantas de cardo que el EDTA. En la

bibliografía se encuentran resultados contradictorios sobre la capacidad del EDDS para

inducir la acumulación de Pb en plantas. Ciertamente, diferencias en las condiciones

experimentales (e.g., especie de planta utilizada, presencia de otros metales, tipo de suelo,

tiempo de exposición y cosecha, etc.) pueden explicar algunos de estos resultados

contradictorios (Grčman y cols., 2003; Kos y Leštan, 2003; Santos y cols., 2006).

Como el Pb es un metal poco biodisponible, no era de esperar que tuviera un efecto

negativo considerable sobre la microbiota del suelo. Efectivamente, la presencia de Pb en

el suelo no tuvo influencia en diversos parámetros indicadores de actividad microbiana

(léase, actividad deshidrogenasa, nitrógeno potencialmente mineralizable, respiración basal

y respiración inducida por substrato). Es más, la presencia de Pb tuvo un efecto positivo

en los valores de S y H’ obtenidos a partir de placas Biolog EcoPlatesTM. Este aumento de

los valores obtenidos a partir de los CLPPs en respuesta a la presencia de metales en el

suelo también se observó en otros estudios del presente trabajo (e.g., Capítulo 5). A este

respecto, se puede especular que la presencia de metales en el suelo induce la aparición de

poblaciones microbianas “estrategas r”, cultivables y de rápido crecimiento.

Por otro lado, el EDDS resultó ser menos tóxico para la comunidad microbiana

edáfica que el EDTA. En los suelos no contaminados con Pb, el EDTA tuvo un impacto

negativo en la actividad de la comunidad microbiana edáfica, como queda reflejado en su

efecto inhibitorio sobre la respiración basal y la actividad deshidrogenasa (el EDDS

también causó una disminución, aunque menor, de la respiración basal). Tanto en los

suelos no contaminados con Pb como en los contaminados, la adición de EDDS produjo

un aumento de los valores S, H’ y AWCD (este último también aumentó al añadir EDTA)

calculados a partir de datos obtenidos con placas Biolog EcoPlatesTM. La menor toxicidad

del EDDS hacia los microorganismos del suelo se podría explicar por el hecho de que el

EDDS es una sustancia natural que se degrada rápidamente en otros compuestos más

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benignos (Grčman y cols., 2003). En conclusión, aunque el EDDS tenga una menor

capacidad que el EDTA para inducir la fitoextracción de Pb en plantas de cardo, presenta

a su vez las importantes ventajas de su rápida biodegradación y menor toxicidad hacia la

comunidad microbiana edáfica.

En cualquier caso, en suelos con muy altas concentraciones de metales como suele

ser el caso de suelos mineros, la fitoextracción no parece en estos momentos una

tecnología viable debido al tiempo excesivamente largo requerido para disminuir la

concentración de dichos metales en el suelo hasta niveles aceptables (generalmente,

décadas). Por ello, en la actualidad, para estos casos se propone la fitoestabilización (o la

utilización de plantas para reducir la disponibilidad de los metales en el suelo y evitar así

su dispersión) como fitotecnología alternativa. Normalmente, la fitoestabilización se

combina con la aplicación de enmiendas orgánicas al objeto de aumentar el pH del suelo,

incrementar su contenido en materia orgánica, reducir la biodisponibilidad de los metales,

añadir nutrientes para las plantas, etc. (Alvarenga y cols., 2009a, b). Este tipo de

fitotecnología se puede asimismo denominar fitoestabilización asistida (Alvarenga y cols.,

2009a, b) o quimiofitoestabilización (Knox y cols., 2000). A este respecto, es importante

considerar el beneficio añadido que conlleva la reutilización de residuos orgánicos a modo

de enmienda. No obstante, no hay que olvidar que la aplicación de estas enmiendas debe

hacerse siempre bajo un control exhaustivo de los posibles efectos adversos que dichas

adiciones (dependiendo sobre todo de la composición de la enmienda orgánica) puedan

causar sobre el funcionamiento del ecosistema edáfico, en general, y de las comunidades

microbianas, en particular. En el Capítulo 9 se muestran los resultados obtenidos en un

ensayo de quimiofitoestabilización llevado a cabo combinando la adición de una

enmienda sintética (CalcinitTM + urea + PK14% + carbonato cálcico) u orgánica (purín

de vacuno) con el crecimiento de la planta Lolium perenne en un suelo minero contaminado

con Zn, Pb y Cd.

La quimiofitoestabilización mejoró las propiedades del suelo y redujo la

biodisponibilidad y toxicidad de los metales presentes en el mismo. La adición de purín de

vacuno aumentó los valores de las actividades deshidrogenasa y β-glucosidasa, el

nitrógeno potencialmente mineralizable, el carbono de la biomasa microbiana y

parámetros obtenidos con las placas Biolog EcoplatesTM, por lo que se concluyó que

había favorecido el desarrollo de la actividad microbiana, junto con su biomasa y


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diversidad funcional. La reducción de la toxicidad, junto con los beneficios provocados

por la adición de nutrientes, permitieron el establecimiento de una cubierta saludable de

Lolium perenne. Por su parte, el desarrollo de la vegetación colaboró en la mejora de

propiedades físico-químicas edáficas clave (léase, pH, contenido en materia orgánica) de la

rizosfera, aumentando aún más los valores de algunas de las propiedades microbiológicas

estudiadas, tales como la biomasa, actividad y diversidad funcional de la comunidad

microbiana rizosférica. En este ensayo, al igual que en muchos otros de los descritos en

este trabajo, se encontraron correlaciones entre las propiedades microbiológicas y físico-

químicas (e.g., pH, contenido en materia orgánica) del suelo. Es de destacar que la

actividad fosfatasa ácida estuvo negativamente correlacionada con el contenido de fósforo

extraíble del suelo, indicando muy probablemente una inhibición por retroalimentación.

En los suelos tratados con la enmienda sintética, se obtuvieron valores más altos de

actividad específica deshidrogenasa y β-glucosidasa, sugiriendo una respuesta de estrés a la

adición de dicha enmienda. A este respecto, Killham (1985) indicó que los

microorganismos del suelo sometidos a estrés pueden derivar la energía inicialmente

destinada al crecimiento hacia funciones de mantenimiento celular, lo que podría explicar

los valores más altos de actividad por unidad de biomasa observados en este estudio. Esta

toxicidad/estrés causado por la enmienda sintética no se observó en los suelos vegetados

con Lolium perenne, posiblemente debido a los conocidos efectos beneficiosos de las

plantas sobre la salud del suelo.

Nuestro procedimiento quimiofitoestabilizador disminuyó el riesgo de

entrada/incorporación de los metales a la cadena trófica, ya que la adición de la enmienda

orgánica condujo a niveles menores de metales en tallo (niveles por debajo de los límites

establecidos para consumo por herbívoros). A partir de los datos encontrados en este

estudio, se concluyó que la quimiofitoestabilización es una alternativa de gran interés para

la remediación de suelos mineros degradados: la mejora en la propiedades del suelo

derivada de la aplicación de enmiendas (e.g., aumento del pH, aporte de nutrientes, etc.)

favorece la implantación de una cubierta vegetal (revegetación) con los beneficios que ello

conlleva.

Curiosamente, la práctica totalidad de los estudios de fitorremediación se llevan a

cabo empleando una única especie de planta fitorremediadora. Sin embargo, la idea de

utilizar consorcios de especies de plantas que presenten distintas estrategias de tolerancia a

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los metales merece sin duda nuestro interés, ya que a priori parece factible que las ventajas

e inconvenientes de cada especie puedan complementarse con las/los de las otras

especies. Entre otros aspectos a considerar, debemos tener en cuenta la posibilidad de

que la diversidad de las comunidades microbianas aumente como resultado del

incremento en la diversidad de especies vegetales (una mayor diversidad vegetal implica

una mayor heterogeneidad de exudados orgánicos, creación de nuevos nichos, etc.)

(Broughton y Gross, 2000; Stephan y cols., 2000). Una mayor biodiversidad se ha

asociado en numerosas ocasiones a una mayor resiliencia (estabilidad) del ecosistema

frente a perturbaciones externas (Sankaran y McNaughton, 1999; Griffiths y cols., 2000).

Basándonos en los datos obtenidos en el Capítulo 4, llevamos a cabo un ensayo (Capítulo

10) de fitorremediación de suelos contaminados con metales empleando consorcios de 1,

2 y 3 especies pseudometalofitas con distintas estrategias de tolerancia a metales

(hiperacumuladora: Thlaspi caerulescens; indicadora: Rumex acetosa; exclusora: Festuca rubra).

Con carácter pionero, en este estudio, se propuso vincular los conceptos de salud del

suelo (en base a propiedades físico-químicas y microbiológicas con potencial indicador) y

salud del ecosistema (en base a sus atributos: vigor, organización y resiliencia). Mientras

que el vigor se puede cuantificar en términos de productividad o rendimiento de materia y

energía en el sistema, la organización se refiere a la complejidad de los ecosistemas. Por

último, el concepto de estabilidad incluye tanto resiliencia (la capacidad del sistema para

recuperarse de una perturbación) como resistencia (la capacidad del sistema para soportar

una perturbación).

El crecimiento de las otras plantas presentes en el consorcio fue superior en

presencia de Thlaspi caerulescens. En lo que se refiere a la acumulación de metales, como era

de esperar, la especie que alcanzó concentraciones superiores de metales en tallo fue

Thlaspi caerulescens. Sin embargo, el mayor crecimiento de Rumex acetosa hizo que esta

especie fuera la que extrajera al final una mayor cantidad de Zn del suelo. Un consorcio

formado por Thlaspi caerulescens y Rumex acetosa parece entonces una opción digna de

estudio en profundidad para mejorar la viabilidad de los procesos actuales de

fitoextracción. Festuca rubra, por su parte, fue la especie que acumuló la menor cantidad de

metales en sus tejidos (es una especie exclusora), con la consiguiente minimización del

riesgo de incorporación de metales a la cadena trófica, por lo que esta especie parece una

opción interesante para procesos fitoestabilizadores. Una combinación de las tres especies

aquí estudiadas también sería interesante, ya que la toma y translocación de metales por


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parte de las plantas fitoextractoras (Thlaspi caerulescens y Rumex acetosa) no se vió disminuida

por la presencia de Festuca rubra.

En relación con las actividades enzimáticas del suelo (controlan los ciclos de

nutrientes y pueden, a su vez, aportar un visión integrada de la funcionalidad del

ecosistema edáfico), en nuestro estudio de utilización de consorcios de plantas

pseudometalofitas para procesos fitorremediadores, la mayoría de las veces la actividad

deshidrogenasa se encontró por debajo del límite de detección, lo que indica una actividad

biológica general del suelo muy baja. Excepto para la actividad β-glucosidasa, se encontró

una correlación negativa entre el número de plantas presentes en el consorcio y los

valores de actividades enzimáticas (también respecto a la actividad enzimática global;

OEA: overall enzyme activity). Por otra parte, en relación con los datos obtenidos con las

placas Biolog EcoplatesTM, no se hallaron diferencias significativas entre tratamientos

respecto al área englobada por las curvas de AWCD. Los valores más altos de carbono de

la biomasa microbiana se hallaron en el tratamiento que combinaba las tres especies de

plantas pseudometalofitas. Los valores más altos del ratio “abundancia

hongos/abundancia bacterias” se encontraron en los tiestos de Rumex acetosa, sugiriendo

una presencia elevada de hongos en la rizosfera de esta especie exclusora.

Desde un punto de vista ecológico, se considera que la diversidad funcional puede

aportar información de mayor relevancia que la diversidad estructural (Torsvik y Øvreås,

2007). En este estudio, la diversidad funcional se determinó a partir de valores de

actividades enzimáticas y datos obtenidos con las placas Biolog EcoplatesTM. En lo

referente a las placas Biolog EcoplatesTM, los valores más bajos de S y H’ se encontraron

en los suelos vegetados con exclusivamente Rumex acetosa, aspecto que podría estar

relacionado con los altos ratios “abundancia hongos/abundancia bacterias” hallados en

este mismo tratamiento. Por el contrario, los valores más altos de S y H’ a partir de placas

Biolog EcoplatesTM se encontraron en los suelos vegetados con Thlaspi caerulescens y Festuca rubra (tanto juntas como por separado). En lo que se refiere a la diversidad estructural, no

se encontraron diferencias entre tratamientos respecto a la diversidad genotípica de

bacterias u hongos.

Como se ha mencionado anteriormente, con carácter pionero, en este trabajo, se ha

propuesto una metodología para vincular el concepto de salud del suelo con el de salud

del ecosistema (en base a sus atributos: vigor, organización y resiliencia). El vigor se

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cuantificó a partir de los valores de: (i) OEA; (ii) área bajo las curvas de AWCD; (iii)

carbono de la biomasa microbiana; y (iv) productividad vegetal (sorgo). Los suelos con

una sola especie presente en el consorcio mostraron valores más altos de vigor. La

organización se midió, en este estudio, a partir de los valores de S y H’ obtenidos con datos

de actividades enzimáticas (diversidad catalítica), placas Biolog EcoplatesTM (diversidad

funcional-catabólica) y DGGE (diversidad estructural-genética). Los niveles más altos de

organización se encontraron en el tratamiento que combinaba Thlaspi caerulescens y Festuca rubra. Por otro lado, se obtuvieron distintos patrones de respuesta al calcular la resistencia a

partir de datos de respiración basal versus datos de tasa de nitrificación potencial, lo cual

no es en absoluto sorpredente pues la respiración del suelo es una medida de actividad

biológica general, mientras que la tasa de nitrificación potencial refleja un proceso

filogenéticamente mucho más estrecho. Los suelos vegetados conjuntamente con Thlaspi caerulescens y Rumex acetosa mostraron los valores más bajos y altos de vigor y estabilidad,

respectivamente, indicando una falta de correlación entre los distintos atributos de salud

del ecosistema. Al calcular la media estadística de los tres atributos de un ecosistema sano

aquí estudiados, al objeto de obtener un valor final integrado de “salud del ecosistema

edáfico”, no se encontraron marcadas diferencias entre tratamientos (incluido el control

no vegetado).

La integración de los bioindicadores de la salud del suelo en el concepto “salud del

ecosistema” supone un intento de salto conceptual hacia la elaboración de una evaluación

del ecosistema edáfico más completa y jerárquica. De todos los parámetros determinados

durante el desarrollo de este trabajo, se podrían considerar como medidas de vigor del

ecosistema edáfico los siguientes: (i) actividad enzimática global del suelo (OEA), (ii) el

nitrógeno potencialmente mineralizable, (iii) la respiración basal e inducida por substrato,

(iv) el AWCD obtenido con las placas Biolog EcoPlatesTM, (v) el carbono de la biomasa

microbiana, (vi) la abundancia de genes obtenida por PCR a tiempo-real y (vii) la

capacidad del suelo para soportar crecimiento de plantas (productividad vegetal).

Asimismo, proponemos que la organización del ecosistema edáfico puede cuantificarse

con los índices de (i) diversidad funcional, obtenidos a partir de actividades enzimáticas,

placas Biolog EcoPlatesTM y microarrays de genes funcionales (Geochip), y (ii) diversidad

estructural, obtenida a partir de datos de PCR-DGGE. Finalmente, en lo que a la

estabilidad del ecosistema edáfico se refiere, se requiere la realización de ensayos de

respuesta a estreses diversos (e.g., contaminación por metales, sequía, golpe de calor, etc.),


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para posteriormente evaluar la respuesta del ecosistema edáfico mediante la

determinación de parámetros biológicos con potencial indicador de la

salud/funcionamiento del ecosistema edáfico. Aunque este tipo de aproximaciones son

indudablemente una clara simplificación de una realidad ecológica mucho más compleja,

son a su vez necesarias y de gran utilidad para gestores, legisladores, etc.

Como se puede observar en los distintos capítulos aquí presentados, a pesar de que

en los ensayos a corto plazo realizados en este trabajo la eliminación de los metales del

suelo derivada de los procesos fitorremediadores no fue considerable, la sola presencia de

la planta fitorremediadora condujo a una estimulación significativa de las propiedades

microbiológicas del suelo, lo cual sugiere una posible mejora de la salud del ecosistema

edáfico. Este hecho enfatiza el beneficio que puede aportar la mera revegetación de los

suelos contaminados con metales con especies tolerantes. Aunque el presente trabajo se

ha centrado en la evaluación de la eficacia de técnicas fitorremediadoras mediante el

empleo de propiedades microbiológicas del suelo (más que en la fitorremediación en sí),

sería deseable en el futuro realizar ensayos de larga duración, para poder así estudiar la

respuesta de las comunidades microbianas edáficas a disminuciones importantes en el

contenido en metales del suelo.

Por otro lado, en el presente trabajo, se han desarrollado ensayos con suelo minero

(contaminación crónica con metales) y con suelo artificialmente contaminado con

metales, con las ventajas y desventajas que ambas alternativas conllevan. Ciertamente, el

suelo minero representa una situación real de contaminación, mientras que en el suelo

artificialmente contaminado los ensayos reflejan el impacto a corto plazo de los metales

sobre las comunidades microbianas edáficas (en cualquier caso, en los ensayos con suelo

artificialmente contaminado, siempre se ha respetado un período de estabilización más o

menos largo entre la adición de los metales al suelo y el establecimiento del ensayo). Sin

embargo, un suelo artificialmente contaminado te permite seleccionar concentraciones y

combinaciones de metales determinadas y, sobre todo, disponer de un suelo control no-

contaminado adecuado (algo, en ocasiones, muy difícil de conseguir en situaciones reales

de suelos contaminados).

A partir de los resultados obtenidos en los estudios incluidos en este trabajo, se

confirma que las propiedades microbiológicas del suelo son herramientas metodológicas

muy sensibles, de rápida respuesta y gran potencial para evaluar/monitorizar la eficacia de

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procesos fitorremediadores de suelos contaminados con metales. Para una correcta

evaluación de la salud del ecosistema edáfico utilizando estas propiedades microbiológicas

con potencial bioindicador es crucial evitar centrarse en un sólo parámetro indicador; se

debe determinar una batería diversa de parámetros en la que, en la medida de lo posible,

estén incluidos indicadores de biomasa, actividad y diversidad microbiana. Asimismo, es

recomendable combinar indicadores del estado general de la comunidad biológica del

suelo (e.g., respiración basal, actividad deshidrogenasa) con aquellos que se centran en

procesos clave específicos (e.g., nitrificación). Por otra parte, tanto las técnicas

consideradas más clásicas (e.g., actividades enzimáticas, carbono de la biomasa microbiana,

respiración basal e inducida por substrato) como otras más punteras (e.g., RT-PCR, PCR-

DGGE, microarrays de genes funcionales) han demostrado su utilidad y

complementariedad.

De la experiencia obtenida aquí durante la utilización de las propiedades

microbiológicas del suelo como bioindicadores potenciales de la salud del ecosistema

edáfico, se pueden extraer una serie de conclusiones de carácter práctico: de entre las

actividades enzimáticas determinadas, la deshidrogenasa presenta la ventaja de ser muy

sensible y presentarse exclusivamente en células viables; desgraciadamente, no es posible

detectar esta actividad en muchos suelos pues los valores están por debajo del límite de

detección. El resto de actividades enzimáticas estudiadas tienen un papel clave en los

principales ciclos biogeoquímicos (ciclos del C, N, P y S), lo cual permite obtener

información sobre el impacto de las perturbaciones (e.g., contaminación con metales,

proceso fitorremediador) en dichos ciclos biogeoquímicos. A la hora de medir la actividad

del suelo también hemos empleado en este trabajo medidas de respiración basal y de

potencial de nitrificación; este último es un proceso clave (keystone) filogenéticamente

mucho más estrecho que la respiración; el estudio de procesos clave facilita la

interpretación en relación con la evaluación del impacto de perturbaciones sobre la salud

del ecosistema edáfico.

En relación con la determinación de la biomasa microbiana, se ha observado una

buena correlación entre los diferentes métodos utilizados en este trabajo para medir este

parámetro, lo cual aporta credibilidad a dichas medidas [este parámetro se he medido en

este trabajo de las siguientes formas: carbono de la biomasa microbiana; respiración

inducida por substrato (biomasa microbiana potencialmente activa); y RT-PCR


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(abundancia de genes)]. Además, se ha medido la abundancia de genes tanto estructurales

(midiendo la cantidad de fragmentos de rRNA de bacterias y hongos) como funcionales

(copias de genes de oxidadores de amonio y degradadores de quitina). Si bien es cierto

que la biomasa estructural y funcional están interrelacionadas y es complicado separarlas

conceptualmente, la utilización de la abundancia de copias de genes con una función

determinada aporta más información a la hora de estudiar el impacto de perturbaciones

sobre la funcionalidad/salud de la comunidad microbiana edáfica y, por ende, del

ecosistema edáfico.

Por otro lado, la utilización de índices ecofisiológicos, e.g. cocientes entre medidas

de actividad biológica y medidas de biomasa (e.g., actividades enzimáticas específicas,

cociente de respiración microbiana) es altamente recomendable pues permite detectar

situaciones de estrés de la comunidad microbiana edáfica.

Las técnicas de estudio de la diversidad microbiana (placas Biolog EcoPlatesTM, PCR-

DGGE, Geochip) generan una enorme cantidad de datos. La aplicación de los índices de

diversidad y uniformidad de Shannon a estos datos, en general, no ha aportado

información de gran relevancia. Por el contrario, el índice de similitud de Jaccard ha

resultado muy útil para ver qué tratamientos se parecían más y cuáles eran más dispares.

Indudablemente, el potencial de los microarrays de genes funcionales (cubre más de 10.000

genes de más de 150 grupos) para medir biodiversidad no es comparable al de las placas

Biolog EcoPlatesTM. Sin embargo, a la hora de comparar/distinguir el efecto de distintos

tratamientos sobre las comunidades mcicrobianas edáficas, los CLPPs se presentan tan

válidos como el Geochip, además de ser más baratos y rápidos de analizar.

Por último, la estadística y, concretamente las técnicas de análisis multivariantes

(análisis de componentes principales, análisis de redundancia), resultan de gran utilidad a la

hora de interpretar los valores de las propiedades microbiológicas del suelo.

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Reflexiones finales

Durante los últimos años hemos profundizado en la posibilidad de utilizar una serie

de parámetros microbiológicos, habitualmente empleados en estudios pertenecientes al

campo de la Ecología Microbiana, como herramientas bioindicadoras/biomonitorizadoras

de la recuperación de la salud del ecosistema edáfico derivada de prácticas de

fitorremediación. Esto nos ha dado la oportunidad de familiarizarnos con una variedad de

técnicas fitorremediadoras enfocadas a la remediación de suelos contaminados con

metales. Aunque, tanto desde el punto de vista de la fitorremediación de suelos

contaminados con metales como en lo concerniente a la validez de los indicadores

microbiológicos para evaluar el impacto de la contaminación y monitorizar la eficacia de

procesos remediadores, los resultados parecen ciertamente prometedores, nos surgen una

serie de reflexiones que se presentan a continuación:

Si bien la fitorremediación es ciertamente una tecnología prometedora,

estéticamente agradable, no intrusiva, socialmente aceptada, ecológica y

medioambientalmente respetuosa y de bajo coste, en su estado actual de desarrollo, sigue

requiriendo plazos de tiempo muy superiores a otras técnicas de remediación con las que

inevitablemente compite y ha de competir en el futuro por su nicho/cuota de mercado

(en particular, el excesivamente largo periodo de tiempo requerido para alcanzar unos

niveles de recuperación aceptables sigue siendo el “talón de Aquiles” de la fitoextracción

de metales). En cualquier caso, parece claro que la casuística propia de cada

emplazamiento, el uso final destinado para el suelo, la naturaleza y el nivel de la

contaminación (tipo de contaminante, presencia simultánea de varios contaminantes,

concentraciones totales y disponibles), etc. tienen un papel determinante en relación con

la selección de la técnica (o técnicas) fitorremediadora a emplear. Posiblemente, de entre

las distintas estrategias de fitorremediación presentes en la actualidad, aquellas que

combinen la fitorremediación propiamente dicha con la obtención de productos que

aporten valor añadido al proceso (por ejemplo, la dendrorremediación con árboles para

luego obtener madera, además de secuestrar carbono; la utilización de plantas de interés

desde el punto de vista de la obtención de biocombustibles) serán las que tengan a largo

plazo mayor proyección comercial. Asimismo, consideramos que la

quimiofitoestabilización es una alternativa de futuro prometedor pues presenta el

interesante atractivo añadido de revalorizar residuos que, amén de disminuir la


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disponibilidad de metales en el suelo, aportan la materia orgánica y los nutrientes que

muchos suelos contaminados (e.g., suelos mineros) necesitan.

Por desgracia, la mayoría de los estudios de fitorremediación (como los aquí

incluidos) han sido realizados a escala microcosmos o a escala piloto en campo.

Innegablemente, llegados a este punto, es imperativo realizar más proyectos en campo a

gran escala para poder avanzar con solidez en el desarrollo de esta fitotecnología.

Uno de los impedimentos claros para el desarrollo de la fitorremediación (de hecho,

para cualquier tecnología de remediación de suelos contaminados) en numerosos países,

incluido el nuestro, es la facilidad que hoy en día existe para deshacerse de los suelos

contaminados en vertederos a bajo coste. En consecuencia, es indispensable que la

legislación limite la entrada de suelos contaminados a los vertederos a exclusivamente

aquellos casos en los que sea inevitable (como, por ejemplo, cuando dichos suelos

provoquen riesgos para la salud humana y/o no exista ninguna tecnología efectiva para su tratamiento).

Al fin y al cabo, el suelo es uno de nuestros recursos (no renovable a nuestra escala

temporal) más preciados y como tal debemos protegerlo frente a las numerosas amenazas

a las que está sometido, e.g. contaminación, erosión, sellado, salinización, etc. y

recuperarlo en la medida de lo posible cuando se encuentre en estado de degradación. No

debemos olvidar que el ecosistema edáfico nos provee de unos servicios (e.g., reciclaje de

nutrientes, descomposición de la materia orgánica, depuración de agua, eliminación de

contaminantes, etc.) de los que depende el bienestar de nuestra sociedad. Sin embargo, el

valor de estos servicios ecosistémicos no está por desgracia reconocido adecuadamente en los mercados económicos y las políticas de gestión medioambiental.

En cualquier caso, la metáfora de la “salud”, bien entendida (a este respecto, es

importante no caer en el error de considerar al suelo como un súper-organismo) y

aplicada, puede aportar una perspectiva de gran valor y utilidad para concienciar a la

sociedad en general y a los gestores de los suelos contaminados en particular, sobre la

imperiosa necesidad de mantener, proteger y recuperar este vital recurso. Como si de una

patología se tratara, y considerando al suelo como un paciente, frente a síntomas y signos

de que el ecosistema edáfico está sufriendo una “enfermedad” (como los que caracterizan

al conocido “síndrome de agotamiento del ecosistema”), el primer paso a seguir es la

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identificación de la etiología del síndrome (la causa de la enfermedad), la cual requiere una

caracterización exhaustiva del estado del paciente. Después, se debe realizar un

diagnóstico (conocer la naturaleza de la “enfermedad” mediante la observación de sus

síntomas y signos) y, a ser posible, una prognosis (conocimiento anticipado del

acaecimiento de la “enfermedad”). A continuación, se debe aplicar una terapia, como

puede ser la fitorremediación, para tratar de “curar la enfermedad” y, asimismo, establecer

un programa de seguimiento/monitorización de la evolución de la “enfermedad”, léase,

de la eficacia del tratamiento (por ejemplo, utilizando propiedades microbiológicas del

suelo como herramienta biomonitorizadora de la eficacia de la terapia fitorremediadora).

Por último, es necesario definir un valor umbral para los parámetros empleados durante la

monitorización de la evolución de la “enfermedad”, a partir del cual se considera que la

terapia ha tenido éxito y es posible interrumpir el tratamiento (por ejemplo, cuando los

parámetros indicadores medidos en el suelo fitorremediado se asemejen a los del suelo

control “sano”; por ejemplo, un suelo vegetado, no contaminado de similares

características edafoclimáticas). En cualquier caso, además de “curar” los suelos

contaminados, al igual que sucede con la salud humana, es vital abordar su prevención, i.e. frenar la preocupante contaminación que padece el suelo como consecuencia de la actividad humana.

Un aspecto crítico que diferencia la remediación y gestión de suelos contaminados

del tratamiento del agua o aire contaminado, es el hecho de que el suelo está generalmente

sujeto a derechos de propiedad (cosa que, por suerte, no ocurre ni con el agua ni con el

aire). En este sentido, un concepto innovador que podría ser de gran utilidad para

promover la conservación del suelo sería la creación de un “Banco de Suelos”, el cual

cuantificaría el valor económico de los servicios ecosistémicos que nos provee de forma

gratuita el suelo, antes y después de cualquier gestión o uso del mismo, y, basándose en un

sistema de préstamos y créditos, crearía un mercado de suelos en el que la moneda de

intercambio sería el valor económico en ese momento de dichos servicios ecosistémicos.

A este respecto, existen experiencias similares para promover la conservación de la

biodiversidad en Australia (“New South Wales BioBanking” y “Victorian Native

Vegetation Management Framework”). Ambos proyectos se centran sobre todo en los

profesionales de la construcción, donde éstos están obligados a proveerse de créditos de


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biodiversidad a través de un mecanismo de mercado para compensar la reducción de

diversidad que conlleva el desmonte de tierras y la construcción de edificios.

Respecto a la utilización de las propiedades microbiológicas del suelo como

bioindicadores de la salud del ecosistema edáfico y, en general, del empleo efectivo en la

práctica del concepto “salud del suelo”, el gran reto (todavía muy lejos de alcanzarse) es

definir con exactitud y precisión qué consideramos un “estado saludable” para un suelo determinado. Indudablemente, esta dificultad se deriva de la enorme heterogeneidad

espacio-temporal y complejidad (a nivel funcional, estructural y de respuesta) del

ecosistema edáfico. No hay que olvidar que las propiedades medibles suelen fluctuar en el

tiempo como resultado de perturbaciones naturales o mecanismos ecológicos internos.

Por otra parte, desde un punto de vista metodológico, la falta de métodos estándares de

análisis es un problema adicional de trascendencia a la hora de interpretar los resultados

de las propiedades microbiológicos aquí estudiadas. Asimismo, en aras de su deseable

incorporación a la metodología de evaluación de análisis de riesgo (herramienta de gran

valor para los gestores de suelos contaminados y en la que se apoya la legislación en esta

materia en muchos países), es imprescindible profundizar en la investigación sobre la

concordancia y coherencia entre datos ecotoxicológicos (obtenidos generalmente con

bioensayos que emplean organismos modelo acordados a este propósito) y ecológicos

(obtenidos, por ejemplo, como en este trabajo, mediante la aplicación de herramientas

metodológicas de la Ecología Microbiana). En este aspecto, es igualmente necesario

estudiar la correlación entre los datos obtenidos a diferentes niveles de organización

biológica (molecular, celular, organismo, población, comunidad, etc.) y con grupos

taxonómicos diversos.

Sea como fuere, los suelos contaminados y la fitorremediación son un escenario

ideal para profundizar en el funcionamiento del ecosistema edáfico, ese gran desconocido,

y en particular en las interacciones y vínculos entre las plantas y los microorganismos del

suelo. De hecho, los sistemas alterados/“enfermos” (e.g., suelos contaminados) son

frecuentemente escenarios idóneos para ahondar en el funcionamiento de los sistemas, tal

y como queda evidente en la aportación de la Medicina al conocimiento de la fisiología del

cuerpo humano.

Los microorganismos son los fundadores de la biosfera en la Tierra y juegan papeles

esenciales en el funcionamiento de los ecosistemas. En relación con el ecosistema edáfico,

11. síntesis

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el conocimiento de la estructura y el funcionamiento de las comunidades microbianas es

crítico para entender el impacto de la contaminación sobre la salud y la sostenibilidad de

este recurso, y para evaluar con fundamento y relevancia ecológica el éxito de procesos

remediadores. Pero la abrumadora complejidad y diversidad de las comunidades

microbianas edáficas, junto con la no cultivabilidad de la mayoría de los microorganismos

del suelo, hace que la detección, caracterización y cuantificación microbiana en suelos sea

actualmente un desafío de grandes proporciones. Al igual que en muchas otras áreas de la

Biología, en los últimos años, la Biología Molecular ha provocado un avance enorme en el

desarrollo de la Ecología Microbiana. Los avances en este campo se suceden a una

velocidad a veces abrumadora: por ejemplo, hasta hace muy poco los microarrays de

DNA/RNA (e.g., Phylochip, Geochip) eran considerados una de las técnicas más

prometedoras para el estudio de la Ecología Microbiana Molecular; sin embargo, en este

momento, ya se empieza a hablar de la tecnología de secuenciación por paralelismo

masivo, capaz de dilucidar la secuencia de nucleótidos exacta de una muestra a una

velocidad vertiginosa (aproximadamente, 200.000 lecturas en 5 horas) como una

herramienta de mayor potencial. Por ello, es importante recordar que la

aplicación/utilización de innovadoras técnicas (moleculares) no debe ser un fin en sí

mismo sino un medio para responder a las cuestiones que nos planteemos durante el

estudio del ecosistema edáfico (en otras palabras, evitar el común error de estar

“movidos” por las nuevas técnicas, en vez de por las preguntas).

Estas nuevas técnicas nos ayudarán sin duda a profundizar en las consecuencias

funcionales que tienen los cambios en la composición y diversidad microbiana

encontrados habitualmente en los suelos contaminados. En presencia de elevadas

concentraciones de contaminantes en el suelo, es ciertamente posible que el supuesto alto

nivel de redundancia funcional propio de las comunidades edáficas no sea suficiente para

evitar una pérdida de funcionalidad, la cual puede acontecer siguiendo un patrón lineal,

exponencial, abrupto, etc. Una vez finalizada la perturbación (en este caso, la

contaminación del suelo), la comunidad edáfica, dependiendo de su resiliencia, puede

recuperarse y retornar al estado previo a la perturbación, derivar hacia otro estado de

equilibrio distinto, o ser incapaz de recuperarse anclándose en un permanente estado de

degradación que puede conducir al colapso irreversible del sistema.


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El establecimiento de Observatorios Microbianos (una red de emplazamientos

seleccionados donde se estudia la naturaleza de las comunidades microbianas y su

variabilidad y respuesta temporal-espacial frente a perturbaciones naturales y antrópicas y

gradientes medioambientales) en suelos “típicos” de ecosistemas diversos de una

determinada región es esencial para comprender mejor el funcionamiento y la dinámica de

las comunidades microbianas edáficas y, por ende, del ecosistema edáfico. Es deseable

que los Observatorios Microbianos incluyan emplazamientos contaminados, pues las

comunidades propias de muchos de estos lugares presentan propiedades singulares

derivadas de su adaptación a la contaminación, que pueden ser de interés, entre otras

cosas, para el desarrollo de tecnologías de remediación. En este contexto, es de gran

interés asimismo disponer de edafotecas completas de suelos (incluyendo suelos

contaminados) en las diferentes regiones, al objeto de beneficiarnos de la propiedad

historiográfica del suelo.

Independientemente de la abrumadora complejidad del ecosistema edáfico y en

particular de la red microcósmica autopoiética de la que depende su funcionalidad y

sostenibilidad, es vital que aquellos que nos dedicamos a su estudio sepamos simplificar,

sin por ello perder la esencia, dicha complejidad para poder trasmitir de forma eficaz a los

gestores del territorio y a la sociedad en general la enorme importancia y trascendencia de

la conservación de uno de nuestros recursos más valioso: EL SUELO.

12. ondorioa naGusiak eta tesia / conclusiones principales y tesis / main conclusions and thesis

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12. ONDORIOAK ETA TESIA

HASIERAKO OHARRA: kapitulu honetan lan honen ondorio nagusiak soilik aipatzen dira. Lan honetan garatutako gai desberdinei buruzko ondorio espezifikoak ikusteko, dagokien kapituluetara jo dezakezu (4-10 Kapituluak).

12.1 Ondorioak

1. Meatze-inguruneetako landare pseudometalofitoak metalen kutsadura jasateko gai dira,

fitoerauzketa eta fitoegonkortze teknologien garaperenako potentzial handia dutelarik.

Garrantzi handikoa da, fitoerauzketa edo fitoegonkortze prozesuan zehar, lurzoruaren

osasunean eragin onuragarrienak izango dituzten landare pseudometalofitoak aukeratzea.

2. Meatze-lurzoruetako propietate mikrobiologikoak lurzoru horietan hazten diren landare

pseudometalofitoen biomasarekin daude koerlazionaturik (eta ez landare

pseudometalofitoen aberastasunarekin). Edozein modutan, garrantzitsua da nabarmentzea

lurzoruko propietate mikrobiologikoek eragin handiagoa izan zutela landare

pseudometalofitoen biomasan, alderantziz baino. Gainera, meatze-lurzoru hauetan,

propietate mikrobiologiko eta fisiko-kimikoak oso koerlazionaturik daude.

3. Hemen aztertutako propietate mikrobiologiko desberdinen balioetatik ondorioztatzen

denez (lurzoruko mikrobio-komunitateen biomasa, aktibitate eta dibertsitatearekin

erlazionaturiko propietateak), metalen kutsadurak eragin nabaria du lurzoruaren

osasunean. Dena dela, geneen erredundantzia eta dibertsitate funtzionala emendatu egiten

dira metalen kutsadura dela eta.

4. Prozesu fitoerremediatzaileen ondorioz (bai metalaren erauzketa/egonkortzea, bai

landareen hazkuntza barne), lurzoru ekosistemaren osasunaren bioadierazle izateko

potentziala duten lurzoruko propietate mikrobiologikoen balioak emendatu egiten dira,

lurzoruaren egoeraren hobekuntza iradokiz.

5. Thlaspi caerulescens-en Lanestosa ekotipoak lurzoruko metal kontzentrazio altuak jasan

eta hauen aurrean egokiro hazteko gaitasuna du. Gainera, ekotipo honek bere aireko

zurtoinetan Zn eta Cd-a metatzeko gaitasun nabaria du, eta baita metal hauentzako

translokazio eta biokontzentrazio faktore oparoak ere. Zn edo/eta Cd-arekiko


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erresistentzia geneen ugaritasuna Thlaspi caerulescens-ekin landatutako lurzoruetan landatu-

gabekoetan baino altuagoa izatea interesgarria da.

6. Basarto landareak, biomasa ekoizpen altuak mantentzeaz batera, Cd kontzentrazio

handiak metatzeko gai dira aireko zurtoinetan. Metalez kutsaturiko lurzoruen

fitoerremediaziorako potentzial handia dute basarto landareek.

7. EDTA EDDSa baino askoz eraginkorragoa da Cynara cardunculus eta kelatzaile bidezko

Pb-aren fitoerauzketarako. Alabaina, EDDSak azkar biodegradatzearen abantaila dauka

eta EDTA baino toxikotasun gutxiago du lurzoruko mikrobio-komunitateentzat (kardu

landareentzat toxikoagoa den arren).

8. Prozesu kimiofitoegonkortzaileetan medeapenen erabilerak, batez ere behi-mindak,

metalez kutsaturiko meatze-lurren propietateak hobetu eta metalen toxikotasun eta

bioeskuragarritasuna jaitsarazten dituzte. Toxikotasunaren jaitsiera honek, elikagaien

gehitzeak dakartzan onurekin batera, Lolium perenne landareen hazkuntza osasuntsua

ahalbidetzen du.

9. Meatze-lurretan Thlaspi caerulescens egoteak/hazteak beste landare pseudometalofitoen

(Rumex acetosa eta Festuca rubra) hazkuntza estimulatzen duela dirudi, metalak fitoerauzteko

duen ahalmenagatik seguruenik. Rumex acetosa-k, Thlaspi caerulescens-ekin batera dagoenean

bereziki, aurkezten ditu erauzitako Zn balio altuenak meatze-lurzoru hauetan.

Orokorrean, kontsortzio batean landare pseudometalofitoen aberastasuna zenbat eta

altuagoa izan, errizosferako lurzoruan orduan eta baxuagoak dira aktibitate entzimatikoen

balioak eta orduan eta altuagoak mikrobio-biomasarenak.

10. Lurzoruaren osasunaren kontzeptua ekosistemaren osasunaren kontzeptuarekin

uztartu daiteke, ekosistemaren osasun-atributu ezpezifikoei propietate mikrobiologikoak

esleituz (indarra, egituraketa, egonkortasuna). Lan honetan epe motzean buruturiko

esperimentuetan ez zen landare pseudometalofitoen hazkuntzaren ondoriozko onurarik

ikusi lurzoru ekosistemaren osasunean (indarra, egituraketa eta egonkortasunaren arabera

estimatua).

11. Beraien sentsibilitate, azkar erantzuteko ahalmen eta izaera bateratzailea dela eta,

lurzoruko propietate mikrobiologikoak balio handiko bioadierazleak dira prozesu

fitoerremediatzaileen efizientzia ebaluatzeko.


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12.2 Tesia

Metalez kutsatutako lurzoruen fitoerremediazio eraginkorralortzeko kasu askotan denboraldi luzeegiak behar izaten diren arren, landare fitoerremediatzaileen hazkuntzak lurzoruaren osasunean ondorioonuragarriak ditu oso epe laburrera, lurzoruko mikriobio-komunitateen aktibitate eta funtzionaltasuna areagotzen baitu, eta hauexek diralurzoruaren funtzionamenduaren erantzule nagusiak. Ondorioz, edozeinprozesu fitoerremediatzaileren gorengo helburua, lurzoruaren osasunaberreskuratzea alegia, lurzorutik kutsadura ezabatu baino lehenagoerdiets daiteke.

Lurzoru ekosistemaren osasunaren adierazle izateko potentzial handia

duten lurzoruaren propietate mikrobiologikoak tresna hobezinak dira metalez

kutsatutako lurzoruen prozesu fitoerremediatzaileen efizientzia ebaluatzeko.


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12. CONCLUSIONES PRINCIPALES Y TESIS

NOTA INTRODUCTORIA: en el presente capítulo se mencionan exclusivamente las conclusiones principales de este trabajo. Para conclusiones más específicas sobre los diferentes temas desarrollados en este trabajo, se remite al lector a los capítulos correspondientes (Capítulos 4-10).

12.1 Conclusiones

1. Las plantas pseudometalofitas de entornos mineros son tolerantes a la contaminación

por metales y muestran un gran potencial para el desarrollo de tecnologías de

fitoextracción y fitoestabilización. Es importante seleccionar aquellas plantas

pseudometalofitas que, durante el proceso fitoextractor o fitoestabilizador, causan un

mayor efecto beneficioso sobre la salud del suelo.

2. Las propiedades microbiológicas en suelos mineros están correlacionadas con la

biomasa de las plantas pseudometalofitas que crecen en dichos suelos (no con la riqueza

de plantas pseudometalofitas). En cualquier caso, es importante destacar que las

propiedades microbiológicas del suelo tuvieron un efecto mayor sobre la biomasa de las

plantas pseudometalofitas que viceversa. Asimismo, en estos suelos mineros, las

propiedades microbiológicas y físico-químicas están muy correlacionadas.

3. La contaminación por metales tiene un claro impacto sobre la salud del suelo, como se

deriva de los valores de las diferentes propiedades microbiológicas del suelo aquí

estudiadas (propiedades relacionadas con la biomasa, actividad y diversidad de las

comunidades microbianas edáficas). No obstante, la redundancia y diversidad funcional

de genes aumentan como resultado de la contaminación por metales.

4. Como consecuencia de los procesos fitorremediadores (que implican tanto la

extracción/estabilización del metal como el crecimiento de las plantas), los valores de las

propiedades microbiológicas del suelo con potencial indicador de la salud del ecosistema

edáfico aumentan, sugiriendo una mejora en el estado del suelo.

5. El ecotipo Lanestosa de Thlaspi caerulescens muestra una alta tolerancia y capacidad de

crecimiento en presencia de elevadas concentraciones de metal en suelo. Asimismo, este

ecotipo muestra una notable capacidad para acumular Zn y Cd en sus tejidos aéreos, así


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como unos factores de traslocación y bioconcentración para estos dos metales muy

prometedores. Es interesante destacar que la abundancia de genes de resistencia al Zn y/o

Cd es mayor en suelos vegetados con Thlaspi caerulescens frente a los no vegetados.

6. Las plantas de sorgo son capaces de acumular altos niveles de Cd en sus tejidos aéreos

a la vez que mantienen una alta producción de biomasa. Las plantas de sorgo presentan

un gran potencial para la fitorremediación de suelos contaminados con metales.

7. El EDTA es mucho más eficiente que el EDDS para la fitoextración de Pb inducida

por quelantes con Cynara cardunculus. No obstante, el EDDS presenta la ventaja de su

rápida biodegradación y es menos tóxico que el EDTA para las comunidades microbianas

edáficas (aunque es más tóxico para las plantas de cardo).

8. La adición de enmiendas en procesos quimiofitoestabilizadores, especialmente purín

vacuno, mejora las propiedades de los suelos mineros contaminados con metales y reduce

la toxicidad y biodisponibilidad de dichos metales. Esta reducción en la toxicidad, junto

con los beneficios derivados del aporte de nutrientes, permite el establecimiento de una

cubierta saludable de plantas de Lolium perenne.

9. La presencia/el crecimiento de Thlaspi caerulescens parece estimular el crecimiento de

otras plantas pseudometalofitas (Rumex acetosa y Festuca rubra) en suelos mineros,

probablemente debido a su capacidad para fitoextraer metales. Rumex acetosa,

especialmente en combinación con Thlaspi caerulescens, presenta los valores más altos de Zn

fitoextraído de estos suelos mineros. En general, a mayor riqueza de plantas

pseudometalofitas presentes en un consorcio, menores valores de actividades enzimáticas

y mayores valores de biomasa microbiana en suelo rizosférico.

10. El concepto de salud del suelo se puede vincular al concepto de salud del ecosistema,

asignando propiedades microbiológicas del suelo a atributos específicos de la salud del

ecosistema (vigor, organización, estabilidad). En los experimentos a corto plazo

desarrollados en este trabajo, no se pudo observar una mejora en la salud del ecosistema

edáfico (estimada en base a vigor, organización y estabilidad) como consecuencia del

crecimiento de plantas pseudometalofitas.

11. Debido a su sensibilidad, rapidez de respuesta y carácter integrador, las propiedades

microbiológicas del suelo son bioindicadores muy valiosos para la evaluación de la eficacia

de procesos fitorremediadores.


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12.2 Tesis

Aunque se necesitan, en muchas ocasiones, periodos de tiempoexcesivamente largos para conseguir una fitorremediación efectiva de sueloscontaminados por metales, el crecimiento de las plantas fitorremediadorasprovoca efectos beneficiosos sobre la salud del suelo al cabo de muy pocotiempo, incrementando la actividad y funcionalidad de las comunidadesmicrobianas edáficas que son las principales responsables delfuncionamiento del suelo. En consecuencia, el objetivo último de cualquierproceso fitorremediador, i.e. recuperar la salud del suelo, puede lograrsemucho antes de haber eliminado el contaminante del suelo.

Las propiedades microbiológicas del suelo con potencial bioindicador de la salud del ecosistema edáfico son herramientas muy válidas para la evaluación de la eficacia de procesos fitorremediadores de suelos contaminados con metales.


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12. MAIN CONCLUSIONS AND THESIS

INTRODUCTORY NOTE: in the current chapter, only the main conclusions from this work are included. For more specific conclusions regarding the different topics dealt with during the development of this work, please refer to the corresponding chapters (Chapters 4-10).

12.1 Conclusions

1. Pseudometallophytes from mining areas are tolerant to metal pollution and offer great

potential for the development of phytoextraction and phytostabilization technologies. It

is important to choose those pseudometallophytes that, during the phytoextraction or

phytostabilization process, cause the most beneficial effects on soil health.

2. Soil microbiological properties in mine soils appear correlated to the biomass of

pseudometallophytes growing on those metal polluted soils (not to pseudometallophytes

richness). In any case, it is important to highlight that the soil microbiological properties

had a stronger effect on the biomass of pseudometallophytes, rather than the other way

around. Likewise, in these mine soils, soil microbiological and physicochemical

properties are highly correlated.

3. Metal pollution has a clear impact on soil health, as indicated by the values of the

different soil microbiological propertiers here determined (properties related to the

biomass, activity and diversity of the soil microbial communities). However, functional

gene diversity and redundancy increase as a result of metal pollution.

4. As a consequence of phytoremediation processes (which involve both metal

extraction/stabilization and plant growth), the values of soil microbiological properties

with potential as bioindicators of soil health increase, suggesting an improvement in the

soil condition.

5. The Lanestosa ecotype of Thlaspi caerulescens shows a high metal tolerance and capacity

to grow at elevated soil metal concentrations. Most importantly, the Lanestosa ecotype

shows a remarkable capacity to accumulate Zn and Cd in its aerial tissues, as well as most

promising translocation and bioconcentration factors for these two metals. Interestingly,


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the abundance of Zn and/or Cd resistance genes is higher in Thlaspi caerulescens planted

versus unplanted soils.

6. Sorghum plants are able to accumulate high levels of Cd in their aerial tissues while

maintaining a high biomass yield. Sorghum plants have great potential for the

phytoremediation of metal polluted soils.

7. EDTA is much more efficient than EDDS for chelate-induced Pb phytoextraction with

Cynara cardunculus. However, EDDS has the advantage of its rapid biodegradation and is

less toxic to the soil microbial communities than EDTA (although it causes more toxicity

to cardoon plants).

8. The addition of amendments in chemophytostabilization processes, especially cow

slurry, improves the properties of metal polluted mine soils and reduces metal toxicity and

bioavailability. This reduced toxicity, together with the benefits provided by the addition

of nutrients, allows the establishment of a healthy Lolium perenne vegetation cover.

9. The presence/growth of Thlaspi caerulescens appears stimulatory for the growth of other

pseudometallophytes (Rumex acetosa and Festuca rubra) in mine soils, probably due to its

metal phytoextraction capacity. Rumex acetosa, especially in combination with Thlaspi caerulescens, phytoextracts the highest amounts of Zn from these mine soils. In general, the

higher the number of pseudometallophytes present in a consortium, the lower the values

of enzyme activities and the highest the values of microbial biomass C observed in the

rhizosphere soil.

10. The concept of soil health can be linked to that of ecosystem health by means of

assigning soil microbiological properties to specific attributes of ecosystem health (vigor,

organization and stability). In the short-term experiments carried out in this work,

pseudometallophytes growth did not exert a clear overall beneficial effect on soil

ecosystem health (according to vigor, organization and stability).

11. The sensitivity, rapid response and integrative character of the soil microbiological

properties make them invaluable bioindicators for the assessment of the efficiency of

phytoremediation processes.


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12.2 Thesis

Although effective soil metal phytoremediation can take, in many cases,unacceptably long periods of time, the growth of the phytoremediating plantscauses beneficial effects on soil health in a very short time, actually enhancingthe activity and functionality of the soil microbial communities which arelargely responsible for soil functioning. In consequence, the ultimate goal of anyphytoremediation process, i.e. the recovery of soil health, can be achieved muchearlier than the removal of the pollutant(s) from the soil.

The soil microbiological properties with potential as bioindicators of soil health are most valid tools for the evaluation of the efficiency of metal phytoremediation processes.

biblioGrafia / biblioGrafía / references

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BIBLIOGRAFIA/BIBLIOGRAFÍA/REFERENCES

Alkorta I, Garbisu C, 2001. Phytoremediation of organic contaminants in soils. Bioresource Technol 79, 273-276.

Alkorta I, Amezaga I, Albizu I, Aizpurua A, Onaindia M, Buchner V, Garbisu C, 2003a. Molecular microbial biodiversity assessment: a biological indicator of soil health. Rev Environ Health 18, 131-151.

Alkorta I, Aizpurua A, Riga P, Albizu I, Amezaga I, Garbisu C, 2003b. Soil enzyme activities as biological indicators of soil health. Rev Environ Health 18, 65-73.

Alkorta I, Albizu I, Amezaga I, Onaindia M, Buchner V, Garbisu C, 2004a. Climbing a ladder: a step-by-step approach to understanding the concept of agroecosystem health. Rev Environ Health 19, 141-159.

Alkorta I, Hernández-Allica J, Becerril JM, Amezaga I, Albizu I, Garbisu C, 2004b. Recent findings on the phytoremediation of soils contaminated with environmentally toxic heavy metals and metalloids such as zinc, cadmium, lead and arsenic. Rev Environ Sci Bio/Technol 3, 71-90.

Alkorta I, Hernández-Allica J, Garbisu C, 2004c. Plants against the global epidemic of arsenic poisoning. Environ Int 30, 949-951.

Alkorta I, Hernández-Allica J, Becerril JM, Amezaga I, Albizu I, Onaindia M, Garbisu C, 2004d. Chelate-enhanced phytoremediation of soils polluted with heavy metals. Rev Environ Sci Bio/Technol 3, 55-70.

Alkorta I, Epelde L, Mijangos I, Amezaga I, Garbisu C, 2006. Bioluminiscent bacterial biosensors for the assessment of metal toxicity and bioavailability in soils. Rev Environ Health 21, 121-134.

Alvarenga P, Gonçalves AP, Fernandes RM, de Varennes A, Vallini G, Duarte E, Cunha-Queda AC, 2008. Evaluation of composts and liming materials in the phytostabilization of a mine soil using perennial ryegrass. Sci Total Environ 406, 43-56.

Alvarenga P, Gonçalves AP, Fernandes RM, de Varennes A, Vallini G, Duarte E, Cunha-Queda AC, 2009a. Organic residues as immobilizing agents in aided

phytostabilization: (I) Effects on soil chemical characteristics. Chemosphere 74, 1292-1300.

Alvarenga P, Palma P, Gonçalves AP, Fernandes RM, de Varennes A, Vallini G, Duarte E, Cunha-Queda AC, 2009b. Organic residues as immobilizing agents in aided phytostabilization: (I) Effects on soil biochemical and ecotoxicological characteristics. Chemosphere 74, 1301-1308.

Anderson JPE, 1982. Soil respiration. In Page AL, Miller RH (ed), Methods of Soil Analysis, Part 2, Chemical and Microbiological Properties. American Society of Agronomy, Madison, pp 831-871.

Anderson JEP, Domsch KH, 1985. Maintenance carbon requirements of actively metabolising microbial populations under in situ situations. Soil Biol Biochem 17, 197-203.

Arienzo M, Adamo P, Cozzolino V, 2004. The potential of Lolium perenne for revegetation of contaminated soils from a metallurgical site. Sci Total Environ 319, 13-15.

Assunção AGL, Schat H, Aarts MGM, 2003. Thlaspi caerulescens, an attractive model species to study heavy metal hyperaccumulation in plants. New Phytol 159, 351-360.

Baker AJM, 1981. Accumulators and excluders – Strategies in the response of plants to heavy metals. Journal Plant Nutr 3, 643-654.

Baker AJM, McGrath SP, Reeves RD, Smith JAC, 2000. Metal hyperaccumulator plants: a review of the ecology and physiology of a biological resource for phytoremediation of metal-polluted soils. In Terry N, Bañuelos G (ed), Phytoremediation of Contaminated Soil and Water. Lewis Publisher, Boca Raton, USA, pp 85-107.

Bañuelos GS, 2006. Phyto-products may be essential for sustainability and implementation of phytoremediation. Environ Pollut 144, 19-23.

Barbanti L, Grandi S, Vecchi A, Venturi G, 2006. Sweet and fibre sorghum (Sorghum bicolor (L.) Moench), energy crops in the frame of environmental protection from excessive nitrogen loads. Eur J Agron 25, 30-39.

Bardgett RD, Wardle DA, Yeates GW, 1998. Linking above-ground and below-ground


260

258

interactions: how plant responses to foliar herbivory influence soil organisms. Soil Biol Biochem 30, 1867-1878.

Barrutia, 2008. Assessment of Zn, Pb and Cd tolerance in native plant species from contaminated soils and its implications for heavy metal phytoextraction. Tesis doctoral, UPV/EHU.

Barrutia O, Epelde L, García-Plazaola JI, Garbisu C, Becerril JM, 2009. Phytoextraction potential of two Rumex acetosa L. accesions collected from metalliferous and non-metalliferous sites: effect of fertilization. Chemosphere 74, 259-264.

Bartelt-Ryser J, Joshi J, Schmid B, Brandl H, Balser T, 2005. Soil feedbacks of plant diversity on soil microbial communities and subsequent plant growth. Perspect Plant Ecol Evol Systemat 7, 27-49.

Becerril JM, Barrutia O, García Plazaola JI, Hernández A, Olano JM, Garbisu C, 2007. Especies nativas de suelos contaminados por metales: aspectos ecofisiológicos y su uso en fitorremediación. Ecosistemas 2007/2, 51-56.

Bending GD, Turner MK, Jones JE, 2002. Interactions between crop residue and soil organic matter quality and the functional diversity of soil microbial communities. Soil Biol Biochem 34, 1073-1082.

Bending GD, Turner MK, Rayns F, Marx MC, Wood M, 2004. Microbial and biochemical soil quality indicators and their potential for differentiating areas under contrasting agricultural management regimes. Soil Biol Biochem 36, 1785-1792.

Berna F, Corti G, Ugolini FC, Agnelli A, 2000. Assessment of the role of rock fragments in the retention of Cadmium and Lead in irrigated arid stony soils. Ann Chim 90, 209-210.

Bezdicek DF, Papendick RI, Lal R, 1996. Introduction: importance of soil quality to health and sustainable land management. In Doran JW, Jones AJ (ed), Methods for assessing soil quality. SSSA Special Publication 49, Soil Science Society of America, Madison, Wisconsin, pp 1-8.

Biederbeck VO, Campbell CA, Ukrainetz H, Curtin D, Bouman OT, 1996. Soil microbial and biochemical properties after ten years of

fertilization with urea and anhydrous ammonia. Can J Soil Sci 76, 7-14.

Blaylock MJ, Salt DE, Dushenkov S, Zakharova O, Gussman C, Kapulnik Y, Ensley BD, Raskin I, 1997. Enhanced accumulation of Pb in Indian mustard by soil-applied chelating agents. Environ Sci Technol 31, 860-865.

Bloem J, Hopkins DW, Benedetti A, 2006. Microbiological Methods for Assessing Soil Quality. CABI Publishing, Cambridge, pp 320.

Bol R, Kandeler E, Amelung W, Glaser B, Marx MC, Preedy N, Lorenz K, 2003. Short-term effects of dairy slurry amendment to carbon sequestration and enzyme activities in a temperate grassland. Soil Biol Biochem 35, 1411-1421.

Boominathan R, Doran PM, 2003. Organic acid complexation, heavy metal distribution and the effect of ATPase inhibition in hairy roots of hyperaccumulator plant species. J Biotechnol 101, 131-146.

Bouwman LA, Bloem J, Römkens PFAM, Japenga J, 2005. EDGA amendment of slightly heavy metal loaded soil affects heavy metal solubility, crop growth and microbivorous nematodes but not bacteria and herbivorous nematodes. Soil Biol Biochem 37, 271-278.

Brim H, Heuer H, Krögerrecklenfort E, Mergeay M, Smalla K, 1999. Characterization of the bacterial community of a zinc-polluted soil. Can J Microbiol 45, 326-338.

Brooks RR, 2000. Plants that Hyperaccumulate Heavy Metals. CAB International, Cambridge, UK, pp 380.

Broughton LC, Gross KL, 2000. Patterns of diversity in plant and soil microbial communities along a productivity gradient in a Michigan old field. Oecologia 125, 420-427.

Burkhardt C, Insam H, Hutchinson TC, Reber HH, 1993. Impact of heavy metals on the degradative capabilities of soil bacterial communities. Biol Fertil Soils 16, 154-156.

Burns RG, Dick RP, 2002. Enzymes in the Environment. Activity, Ecology and Applications. Marcel Dekker, New York, pp 614.

Campbell CD, Grayston SJ, Hirst DJ, 1997. Use of rhizosphere carbon sources in sole carbon


261

259

source tests to discriminate soil microbial communities. J Microbiol Meth 30, 33-41.

Castilla AM, Asensio V, 2007. Biomarcadores y contaminación minera en el País Vasco. Pa´Ciencia 2, 7-9.

Chander K, Brookes PC, 1991. Effects of heavy-metals from past applications of sewage sludge on microbial biomass and organic-matter accumulation in a sandy loam and silty loam UK soil. Soil Biol Biochem 23, 927-932.

Chaney RL, 1989. Toxic element accumulation in soils and crops: protecting soil fertility and agricultural food-chains. In Bar-Yosef B, Barrow NJ, Goldshmid J (ed), Inorganic Contaminants in the Vadose Zone. Springer-Verlag, Berlin, pp 140-158.

Chaney RL, 1993. Zinc phytotoxicity. In Robson AD (ed.), Zinc in Soils and Plants. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp 135-150.

Chaney RL, Malik M, Li YM, Brown SL, Brewer EP, Angle JS, Baker AJM, 1997. Phytoremediation of soil metals. Curr Opin Biotechnol 8, 279-284.

Chaney RL, Angle JS, Baker AJM, Li YM, 1998. Method of phytomining of nickel, cobalt and other metals from soil. Viridian Resources.

Chaney RL, Angle JS, Broadhurst CL, Peters CA, Tappero RV, Donald LS, 2007. Improved understanding of hyperaccumulation yields commercial phytoextraction and phytomining technologies. J Environ Qual 36, 1429-1443.

Chen YH, Li XD, Shen ZG, 2004. Leaching and uptake of heavy metals by ten different species of plants during an EDTA-assisted phytoextraction process. Chemosphere 57, 187-196.

Chen YX, Wang YP, Wu WX, Lin Q, Xue SG, 2006. Impacts of chelate-assisted phytoremediation on microbial community composition in the rhizosphere of a copper accumulator and non-accumulator. Sci Total Environ 356, 247-255.

Chiu KK, Ye ZH, Wong MH, 2006. Growth of Vetiveria zizanioides and Phragmities australis on Pb/Zn and Cu mine tailings amended with manure compost and sewage sludge: a greenhouse study. Bioresource Technol 97, 158-170.

Chowdhury MAH, Kouno K, Ando T, 2000. Critical sulphur concentration and sulphur

requirement of microbial biomass in a glucose and cellulose-amended Regosol. Biol Fert Soils 32, 310-317.

Clemens S, 2001. Molecular mechanisms of plant metal tolerante and homeostasis. Planta 212, 475-486.

Clemente R, Almela C, Bernal MP, 2006. A remediation strategy based on active phytoremediation followed by natural attenuation in a soil contaminated by pyrite waste. Environ Pollut 143, 397-406.

Clemente R., de la Fuente C, Moral R, Bernal MP, 2007. Changes in microbial biomass parameters of a heavy metal-contaminated calcareous soil during a field remediation experiment. J Environ Qual 36, 1137-1144.

Coleman DC, Hendrix PF, Odum EP, 1998. Ecosystem health: an overview. In Huang PM, Adriano DC, Logan TJ, Checkai RT (ed), Soil chemistry and ecosystem health. Soil Science Society of America, Madison, Wisconsin, pp 1-20.

Collin VC, Eymery F, Genty B, Rey P, Havaux M, 2008. Vitamin E is essential for the tolerance of Arabidopsis thaliana to metal-induced oxidative stress. Plant Cell Environ 31, 244-257.

Collins YE, Stotzky G, 1989. Factors affecting the toxicity of heavy metals to microbes. In Beveridge TJ, Doyle RJ (ed), Metal ions and bacteria. John Wiley and Sons, Toronto, pp 31-91.

Costanza R, Norton BG, Haskell BD, 1992. Ecosystem health. New goals for environmental management. Island Press, Washington.

Costanza R, Mageau M, Norton B, Patten BC, 1998. What´s sustainability? In Rapport D, Costanza R, Epstein PR, Gaudet C, Levins R (ed), Ecosystem health. Blackwell Science, Oxford, pp 231-239.

Cunningham S D, Berti WR, 1993. Remediation of contaminated soils with green plants: an overview. In Vitro Cell Dev Biol 29, 207-212.

Cunningham SD, Berti WR, Huang JW, 1995. Phytoremediation of contaminated soils. Trends Biotechnol 13, 393-397.

Curl EA, Truelove B, 1986. The Rhizosphere. Springer-Verlag, Berlin, pp 288.


262

260

Dasappa SM, Loehr RC, 1991. Toxicity reduction in contaminated soil remediation processes. Water Res 25, 1121-1130.

Dedourge O, Vong PC, Lasserre-Joulin F, Benizri E, Guckert A, 2004. Effect of glucose and rhizodeposits (with or without cysteine-S) on immobilized-35S, microbial biomass-35S and arylsulphatase activity in a calcareous and an acid brown soil. Eur J Soil Sci 55, 649-656.

Delorme TA, Gagliardi JV, Angle JS, Chaney RL, 2001. Influence of the zinc hyperaccumulator Thlaspi caerulescens J. & C. Presl. and the nonmetal accumulator Trifolium pratense L. on soil microbial populations. Can J Microbiol 47, 773-776.

Dick RP, 1997. Soil enzyme activities as integrative indicators of soil health. In Pankhurst CE, Doube BM, Gupta VVSR (ed), Biological Indicators of Soil Health. CAB International, Wallingford, UK, pp 121-156.

Dick RP, Breakwell DP, Turco RF, 1996. Soil enzyme activities and biodiversity measurements as integrative microbiological indicators. In Doran JW, Jones AJ (ed), Methods for Assessing Soil Quality. Soil Science Society of America, Madison, WI, pp 247-272.

Do Nascimento CWA, Xing B, 2006. Phytoextraction: a review on enhanced metal availability and plant accumulation. Sci Agr 63, 299-311.

Dobler R, Burri P, Gruiz K, Brandl H, Bachofen R, 2001. Variability in microbial populations in soil highly polluted with heavy metals on the basis of substrate utilization pattern analysis. J Soil Sediment 1, 151-158.

Doran JW, Parkin TB, 1994. Defining and assessing soil quality. In Doran JW, Coleman DC, Bezdiceck DF, Stewart BA (ed), Defining soil quality for a sustainable environment. SSSA Special Publication 35, Soil Science Society of America, Madison, pp 3-21.

Doran JW, Parkin TB, 1996. Quantitative indicators of soil quality: a minimum data set. In Doran JW, Jones AJ (ed), Methods for assessing soil quality. SSSA Special Publication 49, Soil Science Society of America, Madison, pp 25-37.

Doran JW, Safley M, 1997. Defining and assessing soil health and sustainable productivity. In

Pankhurst CE, Doube BM, Gupta VVSR (ed), Biological Indicators of Soil Health. CAB International, Wallingford, UK, pp 1-28.

Duxbury T, 1985. Ecological aspects of heavy metal responses in microorganisms. In Marshall KC (ed), Advances in Microbial Ecology, vol 8. Plenum, New York, pp 185-236.

Ebbs SD, Kochian LV, 1997. Toxicity of zinc and copper to Brassica species: implications for phytoremediation. J Environ Qual 26, 776-781.

Ebbs SD, Kochian LV, 1998. Phytoextraction of zinc by oat (Avena sativa), barley (Hordeum vulgare) and Indian mustard (Brassica juncea). Environ Sci Technol 32, 802-806.

Eivazi F, Tabatabai MA, 1977. Phosphatases in soils. Soil Biol Biochem 9, 167-172.

Ellis RJ, Morgan P, Weightman AJ, Fry JC, 2003. Cultivation-dependent and -independent approaches for determining bacterial diversity in heavy-metal-contaminated soil. Appl Environ Microb 69, 3223-3230.

EPA, 2000. Introduction to phytoremediation. National Risk Management Research Laboratory. Office of Research and Development, US Environmental Protection Agency, Cincinnati.

EPA, 2007. Treatment technologies for site cleanup: annual status report (twelfth edition). EPA-542-R-07-012.

Epelde L, Becerril JM, Hernández-Allica J, Barrutia O, Garbisu C, 2008a. Functional diversity as indicator of the recovery of soil health derived from Thlaspi caerulescens growth and metal phytoextraction. Appl Soil Ecol 39, 299-310.

Epelde L, Hernández-Allica J, Becerril JM, Blanco F, Garbisu C, 2008b. Effects of chelates on plants and soil microbial community: comparison of EDTA and EDDS for lead phytoextraction. Sci Total Environ 401, 21-28.

Epelde L, Mijangos I, Becerril JM, Garbisu C, 2008c. Soil microbial community as bioindicator of the recovery of soil functioning derived from metal phytoextraction with sorghum. Soil Biol Biochem (in press, doi:10.1016/j.soilbio.2008.04.001).


263

261

Epelde L, Becerril JM, Alkorta I, Garbisu C, 2009a. Heavy metal phytoremediation: microbial indicators of soil health for the assessment of remediation efficiency. In Singh A (ed), Advances in Applied Bioremediation. Springer-Verlag, Berlin, (in press, doi: 10.1007/978-3-540-89621-0_16).

Epelde L, Becerril JM, Barrutia O, González-Oreja JA, Garbisu C, 2009b. Interactions between plant and rhizosphere microbial communities in a metalliferous soil. Submitted.

Eriksson J, Ledin S, 1999. Changes in phytoavailability of cadmium in soil after long term Salix cropping. Water Air Soil Pollut 114, 171-184.

Fernández J, 1998. Outlooks of sweet sorghum crop for ethanol production in Spain based on varietal results in multilocal trials. Document ID B10191. European Energy Crops Inter-Network (on line) http://www.eeci.net/ (21 August, 2006).

Fischerová Z, Tlustoš P, Száková J, Šichorová K, 2006. A comparison of phytoremediation capability of selected plant species for given trace elements. Environ Pollut 144, 93-100.

Frey B, Pesaro M, Rüdt A, Widmer F, 2008. Resilience of the rhizosphere Pseudomonas and ammonia-oxidizing bacterial populations during phytoextraction of heavy metal polluted soil with poplar. Environ Microbiol 10, 1433-1449.

Gadd GM, 2004. Microbial influence on metal mobility and application for bioremediation. Geoderma 122, 109-119.

Garbisu C, Alkorta I, 1997. Bioremediation: principles and future. J Clean Technol Environ Toxicol Occup Med , 351-366.

Garbisu C, Alkorta I, 1999. Utilization of genetically engineered microorganisms (GEMs) for bioremediation. J Chem Technol Biotechnol 74, 599-606.

Garbisu C, Alkorta I, 2001. Phytoextraction: a cost-effective plant-based technology for the removal of metals from the environment. Biores Technol 77, 229-236.

Garbisu C, Alkorta I, 2003. Basic concepts on heavy metal soil bioremediation. Eur J Min Proc Environ Protect 3, 58-66.

Garbisu C, Hernández-Allica J, Barrutia O, Alkorta I, Becerril JM, 2002.

Phytoremediation: a technology using green plants to remove contaminants from polluted areas. Rev Environ Health 17, 173-188.

García-Plazaola JI, Becerril JM, 1999. A rapid HPLC method to measure lipophilic antioxidants in stressed plants: simultaneous determination of carotenoids and tocopherols. Phytochem Analysis 10, 307-13.

García-Plazaola JI, Becerril JM, 2001. Seasonal changes in photosynthetic pigments and antioxidants in beech (Fagus sylvatica) in a Mediterranean climate: implications for tree decline diagnosis. Aust J Plant Physiol 28, 225-32.

García-Plazaola JI, Hernández A, Becerril JM, 2000. Photoprotective responses to winter stress in evergreen mediterranean ecosystems. Plant Biology 2, 530-535.

García-Plazaola JI, Hernández A, Olano JM, Becerril JM, 2003. The operation of the lutein epoxide cycle correlates with energy dissipation. Funct Plant Biol 30, 319-324.

Garland JL, 1996. Analytical approaches to the characterisation of sample microbial communities using patterns of potential C source utilisation. Soil Biol Biochem 28, 213-221.

Garland JL, 1997. Analysis and interpretation of community-level physiological profiles in bacterial ecology. FEMS Microbiol Ecol 24, 289-300.

Garland JL, Mills AL, Young JS, 2001. Relative effectiveness of kinetic analysis vs single point readings for classifying environmental samples based on community-level physiological profiles (CLLP). Soil Biol Biochem 33, 1059-1066.

Gérard E, Echevarria G, Sterckeman T, Morel JL, 2000. Cadmium availability to three plant species varying in cadmium accumulation pattern. J Environ Qual 31, 1561-1569.

Giller KE, Witter E, McGrath SP, 1998. Toxicity of heavy metals to microorganisms and microbial processes in agricultural soils: a review. Soil Biol Biochem 30, 1389-1414.

Glass DJ, 1999. US and International Markets for Phytoremediation, 1999-2000. D. Glass Associates, Inc.


264

262

Gómez E, Ferreras L, Toresani S, 2006. Soil bacterial functional diversity as influenced by organic amendment application. Biores Technol 97, 1484-1489.

Goss R, Lepetit B, Wilhelm C, 2006. Evidence for a rebinding of antheraxanthin to the light-harvesting complex during the epoxidation reaction of the violaxanthin cycle. J Plant Physiol 163, 585-590.

Grandia F, Canals A, Cardellach E, Banks E, Banks DA, Perona J, 2003. Origin of ore-forming brines in sediment-hosted Zn-Pb deposits of the Basque-Cantabrian Basin, Northern Spain. Econ Geol 98, 1397-1411.

Grayston SJ, Vaughan D, Jones D, 1997. Rhizosphere carbon flow in trees, in comparison with annual plants: the importance of root exudation and its impact on microbial activity and nutrient availability. Appl Soil Ecol 5, 29-56.

Grčman H, Vodnik D, Velikonja-Bolta S, Leštan D, 2003. Ethylenediaminedisuccinate as a new chelate for environmentally safe enhanced lead phytoextraction. J Environ Qual 32, 500-506.

Gremion F, Chatzinotas A, Harms H, 2003. Comparative 16S rDNA and 16S rRNA sequence analysis indicates that Actinobacteria might be a dominant part of the metabolically active bacteria in heavy metal-contaminated bulk and rhizosphere soil. Environ Microbiol 5, 896-907.

Gremion F, Chatzinotas A, Kaufmann K, Von Sigler W, Harms H, 2004. Impacts of heavy metal contamination and phytoremediation on a microbial community during a twelve-month microcosm experiment. FEMS Microbiol Ecol 48, 273-283.

Griffiths BS, Ritz K, Ebblewhite N, Dobson G, 1999. Soil microbial community structure: effects of substrate loading rates. Soil Biol Biochem 31, 145-153.

Griffiths BS, Ritz K, Bardgett RD, Cook R, Christensen S, Ekelund F, Sorensen SJ, Bååth E, Bloem J, Ruiter PC, Dolfing J, Nicolardot B, 2000. Ecosystem response of pasture soil communities to fumigation-induced microbial diversity reductions: an examination of the biodiversity-ecosystem function relationship. Oikos 90, 279-294.

Griffiths BS, Bonkowski M, Roy J, Ritz K, 2001. Functional stability, substrate utilization and biological indicators of soil following environmental impacts. Applied Soil Ecology 16, 49-61.

Grimm V, Wissel C, 1997. Babel, or the ecological stability discussions: an inventory and analysis of terminology and a guide for avoiding confusion. Oecologia 109, 323-334.

Guckert JB, Carr GJ, Johnson TD, Hamm BG, Davidson DH, Kumagai Y, 1996. Community analysis by Biolog: curve integration for statistical analysis of activated sludge microbial habitats. J Microbiol Meth 27, 183-197.

Guo J, Liu X, Li X, Chen S, Jin Z, Liu G, 2006. Overexpression of VTE1 from Arabidopsis resulting in high vitamin E accumulation and salt stress tolerance increase in tobacco plant. J Appl Environ Biol 12, 468-471.

Haack S, Garchow H, Klug MJ, Forney LJ, 1995. Analysis of factors affecting the accuracy, reproducibility, and interpretation of bacterial community carbon source utilization patterns. Appl Environ Microb 61, 1458-1468.

Hammer D, Keller C, 2002. Changes in the rhizosphere of heavy metal accumulating plants as evidenced by chemical extractants. J Environ Qual 31, 1561-1569.

Hattori H, 1992. Influence of heavy metals on soil microbial activities. Soil Sci Plant Nutr 38, 93-100.

Hauser L, Tandy S, Schuli R, Nowack B, 2005. Column extraction of heavy metals from soils using the biodegradable chelating agent EDDS. Environ Sci Technol 39, 6819-6824.

Havaux M, 1998. Carotenoids as membrane stabilizers in chloroplasts. Trends Plant Sci 3, 147-150.

Havaux H, Niyogi KK, 1999. The violaxanthin cycle protects plants from photooxidative damage by more than one mechanism. Proc Natl Acad Sci USA 96, 8762–8767.

Havaux M, Eymery F, Porfirova S, Rey P, Dörman P, 2005. Vitamin E protects against photoinhibition and photooxidative stress in Arabidopsis thaliana. Plant Cell 17, 3451-3469.

He Z, Zhou J, 2008. Empirical evaluation of a new method for calculating signal-to-noise ratio for microarray data analysis. Appl Environ Microb 74, 2957-2966.


265

263

He Z, Gentry TJ, Schadt CW, Wu L, Liebich J, Chong SC, Huang Z, Wu W, Jardine P, Criddle C, Zhou J, 2007. GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. ISME J 1, 67-77.

Hernández-Allica J, Becerril JM, Zárate O, Garbisu C, 2006a. Assessment of the efficiency of a metal phytoextraction process with biological indicators of soil health. Plant Soil 281, 147-158.

Hernández-Allica J, Garbisu C, Becerril JM, Barrutia O, García-Plazaola JI, Zhao FJ, McGrath SP, 2006b. Synthesis of low molecular weight thiols in response to Cd exposure in Thlaspi caerulescens. Plant Cell Environ 29, 1422-1429.

Hernández-Allica J, Garbisu C, Barrutia O, Becerril JM, 2007. EDTA-induced heavy metal accumulation and phytotoxicity in cardoon plants. Environ Exp Bot 60, 26-32.

Hernández-Allica J, Becerril JM, Garbisu C, 2008. Assessment of the phytoextraction potential of high biomass crop plants. Environ Pollut 152, 32-40.

Heuer H, Krsek M, Baker P, Smalla K, Wellington E, 1997. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel-electrophoretic separation in denaturing gradients. Appl Environ Microb 63, 3233-3241.

Hildén M, Rapport DJ, 1993. Four centuries of cumulative impacts on a Finnish river and its estuary: an ecosystem health-approach. J Aquat Ecosyst Health 2, 261-275.

Hinojosa MB, Carreira JA, García-Ruíz R, Dick RP, 2004. Soil moisture pre-treatment effects on enzyme activities as indicators of heavy metal-contaminated and reclaimed soils. Soil Biol Biochem 36, 1559-1568.

Hinojosa MB, Carreira JA, Rodríguez-Maroto JM, García-Ruíz R, 2008. Effects of pyrite sludge pollution on soil enzyme activities: ecological dose-response model. Sci Total Environ 396, 89-99.

Hiru.com, 2009. Patrimonio industrial en Euskadi (on line), http://www.hiru.com/historia/ondarea (11 June, 2009).

Hoekstra NJ, Bosker T, Lantinga EA, 2002. Effects of cattle dung from farms with different feeding strategies on germination and initial root growth of cress (Lepidium sativum L.). Agriculture Ecosyst Environ 93, 189-196.

Hooper DU, Bignell DE, Brown VK, Brussaard L, Dangerfield JM, Wall DH, Wardle DA, Coleman DC, Giller KE, Lavelle P, Van der Putten WH, De Ruiter PC, Rusek J, Silver WL, Tiedje JM, Wolters V, 2000. Interactions between aboveground and belowground biodiversity in terrestrial ecosystems: patterns, mechanisms, and feedbacks. Bioscience 50, 1049-1061.

Houba VJG, Temminghoff EJM, Gaikhorst GA, van Vark W, 2000. Soil analysis procedures using 0.01 M calcium chloride as extraction reagent. Commun Soil Sci Plan 31, 1299-1396.

Huang PM, Adriano DC, Logan TJ, Checkai RT, 1998. Preface. In Huang PM, Adriano DC, Logan TJ, Checkai RT (ed), Soil chemistry and ecosystem health. Soil Science Society of America, Madison, pp viii.

Hutchinson J, Young S, McGrath SP, West H, Black C, Baker AJM, 2000. Determining uptake of ‘non-labile’ soil cadmium by Thlaspi caerulescens using isotopic dilution techniques. New Phytol 146, 453-460.

IHOBE, 1998. Calidad del suelo. Valores Indicativos de Evaluación (VIE-A, VIE-B, VIE-C). Departamento de Ordenación del Territorio, Vivienda y Medio Ambiente, Gobierno Vasco, pp 272.

Insam H, 1997. A new set of substrates proposed for community characterization in environmental samples. In Insam H, Rangger A (ed), Microbial Communities. Springer-Verlag, Heidelberg, Germany, pp 259-260.

Insam H., Domsch KH, 1988. Relationship between soil organic carbon and microbial biomass on chronosequences of reclamation sites. Microb Ecol 15, 177-188.

ISO 15685 Norm, 2004. Soil Quality – Determination of Potential Nitrification and Inhibition of Nitrification. Rapid Test by Ammonium Oxidation.

ISO 16072 Norm, 2002. Soil Quality ― Laboratory Methods for Determination of Microbial Soil Respiration.


266

264

ISO 17155 Norm, 2002. Soil Quality ― Determination of Abundance and Activity of Soil Microflora Using Respiration Curves.

Izquierdo I, Caravaca F, Alguacil MM, Hernández G, Roldán A, 2005. Use of microbiological indicators for evaluating success in soil restoration after revegetation of a mining area under subtropical conditions. Appl Soil Ecol 30, 3-10.

Jaccard P, 1908. Nouvelles recerches sur la distribution florale. Bulletin de la Societé Vaudoise des Sciences Naturelles 44, 223-270.

Janke RR, Papendick RI, 1994. Preface. In Doran JW, Coleman DC, Bezdiceck DF, Stewart BA (ed), Defining soil quality for a sustainable environment. SSSA Special Publication 35, Soil Science Society of America, Madison, pp ix-xi.

Jarvis MD, Leung DWM, 2001. Chelated Lead transport in Chamaecytisus proliferus (L.f.) link ssp. Proliferus var. palmensis (H. Christ): an Ultrastuctural Study. Plant Sci 161, 433-441.

Jaworska JS, Schowanek D, Feijtel TCJ, 1999. Environmental risk assessment for trisodium [S,S]-ethylene diamine disuccinate, a biodegradable chelator used in detergent applications. Chemosphere 38, 3597-3625.

Jones PW, Williams DR, 2001. Chemical speciation used to assess [S,S']-ethylenediaminedisuccinic acid (EDDS) as a readily-biodegradable replacement for EDTA in radiochemical decontamination formulations. Appl Radiat Isot 54, 587-593.

Kandeler E, 2007. Physiological and biochemical methods for studying soil biota and their function. In Eldor AP (ed), Soil microbiology, ecology and biochemistry. Academic Press, Elsevier, Oxford, pp 53-80.

Kandeler E, Gerber H, 1988. Short-term assay of soil urease activity using colorimetric determination of ammonium. Biol Fert Soils 6, 68-72.

Kandeler E, Kampichler C, Horak O, 1996. Influence of heavy metals on the functional diversity of soil microbial communities. Biol Fert Soils 23, 299-306.

Keller C, Hammer D, 2004. Metal availability and soil toxicity after repeated croppings of Thlaspi caerulescens in metal contaminated soils. Environ Pollut 131, 243-254.

Kelly JJ, Tate RL, 1998. Effects of heavy metal contamination and remediation on soil microbial communities in the vicinity of a zinc smelter. J Environ Qual 27, 609-617.

Kelly JJ, Haggblom M, Tate RL, 1999. Changes in soil microbial communities over time resulting from one time application of zinc: a laboratory microcosm study. Soil Biol Biochem 31, 1455-1465.

Killham K, 1985. A physiological determination of the impact of environmental stress on the activity of microbial biomass. Environ Pollut 38, 283-294.

Kirkham MB, 1977. Organic matter and heavy metal uptake. Compost Sci 18, 18-21.

Knight BP, Chaudri SP, McGrath SP, Killer KE, 1998. Determination of chemical availability of cadmium and zinc using inert soil moisture samplers. Environ Pollut 99, 293-298.

Knox AS, Seaman J, Adriano DC, Pierzynski G, 2000. Chemophytostabilization of metals in contaminated soils. In Wise DL, Trantolo DJ, Cichon EJ, Inyang HI, Stottmeister U (ed), Bioremediation of contaminated soils. Marcel Dekker, New Cork, pp 811-836.

Kos B, Leštan D, 2003. Influence of a biodegradable ([S,S]-EDDS) and nondegradable (EDTA) chelate and hydrogel modified soil water sorption capacity on Pb phytoextraction and leaching. Plant Soil 253, 403-411.

Kos B, Leštan D, 2004. Chelator induced phytoextraction and in situ soil washing of Cu. Environ Pollut 132, 333-339.

Kowalchuk GA, Stephen LR, De Boer W, Prosser JI, Embley TM, Woldendorp JW, 1997. Analysis of β-proteobacteria ammonia-oxidizing bacteria in coastal sand dunes using denaturing gradient gel electrophoresis and sequencing of PCR amplified 16S rDNA fragments. Appl Environ Microb 63, 1489-1497.

Kowalchuk GA, Buma DS, de Boer W, Klinkhamer PGL, van Veen JA, 2002. Effects of above-ground plant species composition and diversity on the diversity of soilborne microorganisms. A Van Leeuw 81, 509-520.

Kozdrój J, van Elsas JD, 2001. Structural diversity of microorganisms in chemically perturbed soil assessed by molecular and cytochemical approaches. J Microbiol Meth 43, 197-212.


267

265

Krieger-Liszkay A, Trebst A, 2006. Tocopherol is the scavenger of singlet oxygen produced by the triplet states of chlorophyll in the PSII reaction centre. J Exp Bot 57, 1677-1684.

Kumar PABAN, Dushenkov V, Motto H, Raskin I, 1995. Phytoextraction: the use of plants to remove heavy metals from soils. Environ Sci Technol 29, 1232-1239.

Kumpiene J, Guerri G, Landi L, Pietramellara G, Nannipieri P, Renella G, 2009. Microbial biomass, respiration and enzyme activities after in situ aided phytostabilization of a Pb- and Cu-contaminated soil. Ecotoxicol Environ Saf 72, 115-119.

Kuperman RG, Carreiro MM, 1997. Soil heavy metal concentrations, microbial biomass and enzyme activities in a contaminated grassland ecosystem. Soil Biol Biochem 29, 179-190.

Larson JL, Zak DR, Sinsabaugh RL, 2002. Extracellular enzyme activity beneath temperate trees growing under elevated carbon dioxide and ozone. Soil Sci Soc Am J 66, 1848-1856.

Lazzaro A, Schulin R, Widmer F, Frey B, 2006. Changes in lead availability affect bacterial community structure but not basal respiration in a microcosm study with forest soil. Sci Total Environ 371, 110-124.

Lee J, Reeves RD, Brooks RR, Jaffré T, 1978. The relation between nickel and citric acid in some nickel-accumulating plants. Phytochemistry 17, 1033-1035.

Leita L, de Nobili M, Muhlbachova G, Mondini C, Marchiol L, Zerbi G, 1995. Bioavailability and effects of heavy metals on soil microbial biomass survival during laboratory incubation. Biol Fert Soils 19, 103-108.

Leps J, Šmilauer P, 2003. Multivariate analysis of ecological data using CANOCO. Cambridge University Press, UK.

Li X, He Z, Zhou J, 2005. Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation. Nucl Acid Res 33, 6114-6123.

Li YM, Chaney RL, Siebielec G, Kerschner BA, 2000. Response of four turfgrass cultivars to limestone and biosolids-compost amendment of a zinc and cadmium contaminated soil at Palmerton, Pennsylvania. J Environ Qual 29, 1440-1447.

Liao M, Chen CL, Huang CY, 2005. Effect of heavy metals on soil microbial activity and diversity in a reclaimed mining wasteland of red soil area. J Environ Sci 17, 832-837.

Lin Q, Brookes PC, 1999. An evaluation of the substrate-induced respiration method. Soil Biol Biochem 31, 1969-1983.

Lindstrom JE, Barry RP, Braddock JF, 1998. Microbial community analysis: a kinetic approach to constructing potential C source utilization patterns. Soil Biol Biochem 30, 231-239.

Liu D, Li TQ, Yang XE, Islam XE, Jin XF, Mahmood Q, 2008. Effect of Pb on leaf antioxidant enzyme activities and ultrastructure of two ecotypes of Sedum alfredii Hance. Russ J Plant Physiol 55, 68-76.

Lombi E, Zhao FJ, Dunham SJ, McGrath SP, 2001. Phytoremediation of heavy-metal contaminated soils: natural hyperaccumulation versus chemically enhanced phytoextraction. J Environ Qual 30, 1919-1926.

Lombi E, Tearall KL, Howarth JR, Zhao FJ, Hawkesford MJ, McGrath SP, 2002. Influence of iron status on cadmium and zinc uptake by different ecotypes of the hyperaccumulator Thlaspi caerulescens. Plant Physiol 128, 1359-1367.

Loranger-Merciris G, Barthes L, Gastine A, Leadley P, 2006. Rapid effects of plant species diversity and identity on soil microbial communities in experimental grassland ecosystems. Soil Biol Biochem 38, 2336-2343.

Loreau M, 2000. Biodiversity and ecosystem functioning: recent theoretical advances. Oikos 91, 3-17.

Lueders T, Manefield M, Friedrich MW, 2004a. Enhanced sensitivity of DNA- and rRNA-based stable isotope probing by fractionation and quantitative analysis of isopycnic centrifugation gradients. Environ Microbiol 6, 73-78.

Lueders T, Wagner B, Claus P, Friedrich MW, 2004b. Stable isotope probing of rRNA and DNA reveals a dynamic methylotroph community and trophic interactions with fungi and protozoa in oxic rice field soil. Environ Microbiol 6, 60-72.


268

266

Luo Y, Zhou X, 2006. Preface. In Luo Y, Zhou X (ed) Soil respiration and the environment. Academic Press, Elsevier, Oxford, pp ix-x.

Luo YM, Christie P, Baker AJM, 2000. Soil solution Zn and pH dynamics in non-rhizosphere soil and in the rhizosphere of Thlaspi caerulescens grown in a Zn/Cd-contaminated soil. Chemosphere 41, 161-164.

Luo C, Shen Z, Li X, 2005. Enhanced phytoextraction of Cu, Pb, Zn and Cd with EDTA and EDDS. Chemosphere 59, 1-11.

Mageau MT, Constanza R, Ulanowicz RE, 1995. The development and initial testing of a quantitative assessment of ecosystem health. Ecosyst Health 1, 201-213.

Magurran AE, 2004. Measuring Biological Diversity. Blackwell Publishing, Oxford.

Malik S, Beer M, Megharaj M, Naidu R, 2008. The use of molecular techniques to characterize the microbial communities in contaminated soil and water. Environ Int 34, 265-276.

MAPA, 1994. Métodos Oficiales de Análisis de Suelos y Aguas para Riego. Vol. III. Ministerio de Agricultura, Pesca y Alimentación, Madrid, Spain.

Marchiol L, Fellet G, Perosa D, Zerbi G, 2007. Removal of trace metals by Sorghum bicolor and Helianthus annuus in a site polluted by industrial wastes: a field experience. Plant Physiol Bioch 45, 379-387.

Mbuya OS, Nkedi-Kizza P, Boote KJ, 2001. Fate of atrazine in sandy soil cropped with sorghum. J Environ Qual 30, 71-77.

McCaig AE, Grayston SJ, Prosser JI, Glover LA, 2001. Impact of cultivation on characterisation of species composition of soil bacterial communities. FEMS Microbiol Ecol 35, 37-48.

McGrath SP, 1987. Long-term studies of metal transfers following applications of sewage sludge. In Coughtrey PJ, Martin MH, Unsworth MH (ed), Pollutant transport and fate in ecosystems. Special Publication No. 6 of the British Ecological Society, Blackwell Scientific, Oxford, pp 301-317.

McGrath SP, Cunliffe CH, 1985. A simplified method for the extraction of the metals Fe, Zn, Cu, Ni, Pb, Cr, Co and Mn from soils and sewage sludges. J Sci Food Agr 36, 794-798.

McGrath SP, Zhao FJ, 2003. Phytoextraction of metals and metalloids from contaminated soils. Curr Opin Biotech 14, 277-282.

McGrath SP, Zhao FJ, Lombi E, 2001a. Plant and rhizosphere processes involved in phytoremediation of metal-contaminated soils. Plant and Soil 232, 207-214.

McGrath SP, Lombi E, Zhao FJ, 2001b. What´s new about cadmium hyperaccumulation? New Phytol 149, 2-3.

McGrath SP, Zhao FJ, Lombi E, 2002. Phytoremediation of metals, metalloids, and radionuclides. Adv Agron 75, 1-56.

McGrath SP, Lombi E, Gray CW, Calille N, Dunham SJ, Zhao FJ, 2006. Field evaluation of Cd and Zn phytoextraction potential by the hyperaccumulators Thlaspi caerulescens and Arabidopsis halleri. Environ Pollut 141, 115-125.

Meagher RB, 2000. Phytoremediation of toxic elemental and organic pollutants. Curr Opin Plant Biol 3, 153-162.

Meers E, Ruttens A, Hopgood MJ, Samson D, Tack FMG, 2005. Comparison of EDTA and EDDS as potential soil amendments for enhanced phytoextraction of heavy metals. Chemosphere 58, 1011-1022.

Mench M, Bussière S, Boisson J, Castaing E, Vangronsveld J, Ruttens A, De Koe T, Bleeker P, Assunçao A, Manceau A., 2003. Progress in remediation and revegetation of the barren Jales gold mine spoil after in situ treatments. Plant Soil 249, 187-202.

Mertens J, Springael D, DeTroyer I, Cheyns K, Wattiau P, Smolders E, 2006. Long term exposure to elevated zinc concentrations induced structural changes and zinc tolerance of the nitrifying community in soil. Environ Microbiol 8, 2170-2178.

Mijangos I, Pérez R, Albizu I, Garbisu C, 2006. Effects of fertilization and tillage on soil biological parameters. Enzyme Microb Technol 40, 100-106.

Mijangos I, Becerril JM, Albizu I, Epelde L, Garbisu C, 2009. Effects of glyphosate on rhizosphere soil microbial communities under two different plant compositions by cultivation-dependent and -independent methodologies. Soil Biol Biochem 41, 505-513.


269

267

Munné-Bosch S, Schwartz K, Alegre L, 1999. Enhanced formation of alpha-tocopherol and highly oxidized abietane diterpenes in water-stressed rosemary plants. Plant Physiol 121, 1047-1052.

Naeem S, Hahn DR, Schuurman G, 2000. Producer-decomposer co-dependency influences biodiversity effects. Nature 403, 762-764.

Nannipieri P, Kandeler E, Ruggiero P, 2002. Enzyme activities and microbiological and biochemical processes in soil. In Burns RG, Dick RP (ed), Enzymes in the environment. Marcel Dekker, New York, pp 1-33.

Naseby DC, Lynch JM, 2002. Enzymes and microorganisms in the rhizosphere. In Burns RG, Dick RP (ed), Enzymes in the Environment. Marcel Dekker, New York, pp 109-123.

Nicolaisen MH, Ramsing NB, 2002. Denaturing gradient gel electrophoresis (DGGE) approaches to study the diversity of ammonia-oxidizing bacteria. J Microbiol Meth 50, 186-203.

Odum EP, 1981. The effects of stress on the trajectory of ecological succesion. In Barrett GW, Rosenberg R (ed), Stress effects on natural ecosystems. John Wiley & Sons Ltd, Chichester, pp 43-47.

Orwin KH, Wardle DA, 2004. New indices for quantifying the resistance and resilience of soil biota to exogenous disturbances. Soil Biol Biochem 36, 1907-1912.

Pankhurst CE, Doube BM, Gupta VVSR, 1997. Biological Indicators of Soil Health. CAB International, Wallingford, pp 451.

Pearce F, 2003. Arsenic´s fatal legacy grows. New Sci 179, 4-5.

Peer WA, Baxter IR, Richards EL, Freeman JL, Murphy AS, 2005. Phytoremediation and hyperaccumulator plants. In Tamas M, Martinoia E (ed), Molecular biology of metal homeostasis and detoxification. Topics in Current Genetics, vol. 14. Springer, Berlin, pp 299-340.

Pereira R, Marques SM, Antunes SC, Marques C, Abrantes N, Pestana JLT, Gonçalves F, 2008. Comparison of portuguese soils from different geographical regions using physicochemical, biological and biochemical parameters. J Soil Sediment 8, 106-115.

Pérez de Mora A, Ortega-Calvo JJ, Cabrera F, Madejón E, 2005. Changes in enzyme activities and microbial biomass after “in situ” remediation of heavy metal-contaminated soil. Appl Soil Ecol 28, 125-137.

Pérez de Mora A, Burgos P, Madejón E, Cabrera F, Jaeckel P, Schloter M, 2006. Microbial community structure and function in a soil contaminated by heavy metals: effects of plant growth and different amendments. Soil Biol Biochem 38, 327-341.

Phillips LA, Greer CW, Germida JJ, 2008. Culture-based and culture-independent assessment of the impact of mixed and single plant treatments on rhizosphere microbial communities in hydrocarbon contaminated flare-pit soil. Soil Biol Biochem 38, 2823-2833.

Pilon-Smits E, 2005. Phytoremediation. Annu Rev Plant Biol 56, 15-39.

Pirt SJ, 1975. Principles of Microbe and Cell Cultivation. Blackwell Scientific Publication, Oxford.

Porazinska DL, Bardgett RD, Blaauw MB, Hunt HW, Parsons AN, Seastedt TR, Wall DH, 2003. Relationships at the aboveground–belowground interface: plants, soil biota, and soil processes. Ecol Monogr 73, 377-395.

Powers RF, 1980. Mineralizable soil nitrogen as an index of nitrogen availability to forest trees. Soil Sci Soc Am J 44, 1314–1320.

Prasad MNV, 2007. Phytoremediation in India. In Willey N (ed), Phytoremediation, methods and reviews. Humana Press, New Yersey, pp 435-454.

Preston-Mafham J, Boddy L, Randerson PF, 2002. Analysis of microbial community functional diversity using sole-carbon-source utilisation profiles – a critique. FEMS Microbiol Ecol 42, 1-14.

Ramsey PW, Rillig MC, Feris KP, Gordon NS, Moore JN, Holben WE, Gannon JE, 2005. Relationship between communities and processes; new insights from a field study of a contaminated ecosystem. Ecol Lett 8, 1201-1210.

Rapport D, 1998. Defining ecosystem health. In Rapport D, Costanza R, Epstein PR, Gaudet C, Levins R (ed), Ecosystem health. Blackwell Science, Oxford, pp 18-33.


270

268

Rapport DJ, McCUllum J, Miller MH, 1997. Soil health: its relation to ecosystem health. In Pankhurst CE, Doube BM, Gupta VVSR (ed), Biological indicators of soil health. CAB International, Wallingford, pp 29-47.

Raskin I, Kumar PBAN, Dushenkov S, Salt DE, 1994. Bioconcentration of heavy metals by plants. Curr Opin Biotechnol 5, 285-290.

Raskin I, Smith RD, Salt DE, 1997. Phytoremediation of metals: using plants to remove pollutants from the environment. Curr Opin Biotechnol 8, 221-226.

Reichle DE, 1997. The role of soil invertebrates in nutrient cycling. In Lohm V, Persson T (ed), Soil organisms as components of ecosystems. Swedish Natural Science Research Council, Stockholm, pp 145-156.

Reysenbach AL, Giver LJ, Wickman GS, Pace NR, 1992. Differential amplification of rRNA genes by polymerase chain reaction. Appl Environ Microb 58, 3417-3418.

Rhee S, Liu X, Wu L, Chong S, Wan X, Zhou J, 2004. Detection of genes involved in biodegradation and biotransformation in microbial communities by using 50-mer oligonucleotide microarrays. Appl Environ Microb 70, 4303-4317.

Robinson BH, Brooks RR, Gregg PEH, Kirkham JH, 1999. The nickel phytoextraction potential of some ultramafic soils as determined by sequential extraction. Geoderma 87, 293-304.

Robinson B, Fernández JE, Madejón P, Marañón T, Murillo JM, Green S, Clothier B, 2003. Phytoextraction: an assessment of biogeochemical and economic viability. Plant Soil 249, 117-125.

Rodríguez-Loinaz G, Onaindia M, Amezaga I, Mijangos I, Garbisu C, 2008. Relationship between vegetation diversity and soil functional diversity in native mixed-oak forests. Soil Biol Biochem 40, 49-60.

Römkens P, Bouwman L, Japenga J, Draaisma C, 2002. Potentials and drawbacks of chelate-enhanced phytoremediation of soils. Environ Pollut 116, 109-121.

Rotkittikhun P, Chaiyarat R, Kruatrachue M, Pokethitiyook P, Baker AJM, 2007. Growth and lead accumulation by the grasses Vetiveria zizanioides and Thysanolaena maxima in lead-contaminated soil amended with pig manure

and fertilizer: a glasshouse study. Chemosphere 66, 45-53.

Rough DA, Lee BTO, Morby AP, 1995. Understanding celllular responses to toxic agents: a model for mechanism-choice in bacterial metal resistance. J Ind Microbiol 14, 132-141.

Rozas MA, Alkorta I, Garbisu C, 2006. Phytoextraction and phytofiltration of arsenic. Rev Environ Health 21, 43-56.

Ryan R, Ryan D, Dowling D, 2005. Transferable phenotypes in bacteria as indicators of soil contamination with heavy metals. J Soil Sediment 5, 95-100.

Salt DE, Blaylock M, Kumar NPBA, Dushenkov V, Ensley BD, Chet I, Raskin I, 1995. Phytoremediation: a novel strategy for removal of toxic metals from the environment using plants. Biotechnol 13, 468-474.

Salt DE, Smith RD, Raskin I, 1998. Phytoremediation. Annu Rev Plant Physiol 49, 643-668.

Sandaa RA, Enger O, Torsvik V, 1999a. Abundance and diversity of Archaea in heavy-metal-contaminated soil. Appl Environ Microb 65, 3293-3297.

Sandaa RA, Torsvik V, Enger O, Daae FL, Castberg T, Hahn D, 1999b. Analysis of bacterial communities in heavy metal-contaminated soils at different levels of resolution. FEMS Microbiol Ecol 30, 237-251.

Sankaran M, McNaughton SJ, 1999. Determinants of biodiversity regulate compositional stability of communities. Nature 401, 691–693.

Santos FS, Hernández-Allica J, Becerril JM, Amaral-Sobrinho N, Mazur N, Garbisu C, 2006. Chelate-induced phytoextraction of metal polluted soils with Brachiaria decumbens. Chemosphere 65, 43-50.

Sarathchandra SU, Ghani A, Yeates GW, Burch G, Cox NR, 2001. Effect of nitrogen and phosphate fertilizers on microbial and nematode diversity in pasture soils. Soil Biol Biochem 33, 953-964.

SAS Institute, 1998. Using Statview. SAS Inst., Cary, NC.


271

269

Schinner F, Ohlinger R, Kandeler E, Margesin R, 1996. Methods in Soil Biology. Springer, Berlin.

Schwartz C, Echevarria G, Morel JL, 2003. Phytoextraction of cadmium with Thlaspi caerulescens. Plant Soil 249, 27-35.

Shen ZG, Zhao FJ, McGrath SP, 1997. Uptake and transport of zinc in the hyperaccumulator Thlaspi caerulescens and the non-hyperaccumulator Thlaspi ochroleucum. Plant Cell Environ 20, 898-906.

Silver S, Phung LT, 1996. Bacterial heavy metal resistance: new surprises. Annu Rev Microbiol 50, 753-789.

Smalla K, Wachtendorf U, Heuer H, Liu WT, Forney L, 1998. Analysis of BIOLOG GN substrate utilization patterns by microbial communities. Appl Environ Microb 64, 1220-1225.

Smith CJ, Osborn AM, 2009. Advantages and limitations of quantitative PCR (Q-PCR)-based approaches in microbial ecology. FEMS Microbiol Ecol 67, 6-20.

Sowerby A, Emmett B, Beier C, Tietema A, Peñuelas J, Estiarte M, Van Meeteren MJM, Huges S, Freeman C, 2005. Microbial community changes in heathland soil communities along a geographical gradient: interaction with climate change manipulations. Soil Biol Biochem 37, 1805-1813.

Speir TW, Ross DJ, 2002. Hydrolytic enzyme activities to assess soil degradation and recovery. In Burns RG, Dick RP (ed), Enzymes in the Environment. Marcel Dekker, New York, USA, pp 407-431.

SPSS, 1989. SPSS for Windows. SPSS Inc, Chicago.

Stephan A, Meyer AH, Schmid B, 2000. Plant diversity affects culturable soil bacteria in experimental grassland communities. J Ecol 88, 988-998.

Stevenson FJ, Ardakani MS, 1972. Organic matter reactions involving micronutrients in soils. In Mortvedt JJ, Giordano PM, Lindsay WL (ed), Micronutrients in agriculture. SSSA, Madison, pp 79-114.

Sun B, Zhao FJ, Lombi E, McGrath SP, 2001. Leaching of heavy metals from contaminated soils using EDTA. Environ Pollut 113, 111-120.

Tabatabai MA, 1994. Soil enzymes. In Weaver RW, Angle JS, Bottomley PS (ed), Methods of Soil Analysis. Part 2. Microbiological and Biological Properties. SSSA and ASA, Madison, pp 775-833.

Tandy S, Schulin R, Nowack B, 2006. The influence of EDDS on the uptake of heavy metals in hydroponically grown sunflowers. Chemosphere 62, 1454-1463.

Tang S, 2007. Phytoremediation in China, inorganics. In Willey N (ed), Phytoremediation, methods and reviews. Humana Press, New Yersey, pp 351-379.

Tang YT, Qiu RL, Zeng XW, Ying RR, Yu FM, Zhou XY, 2009. Lead, zinc, cadmium hyperaccumulation and growth stimulation in Arabis paniculata Franch. Environ Exp Bot 66, 126-134.

Tate RL, 1995. Soil Microbiology. John Wiley & Sons Inc., New York, USA.

Tate RL, 2002. Microbiology and enzymology of carbon and nitrogen cycling. In Burns RG, Dick RP (ed), Enzymes in the Environment. Marcel Dekker, New York, USA, pp 227-248.

Tausz M, Wonisch A, Grill D, Morales D, Jiménez MS, 2003. Measuring antioxidants in tree species in the natural environment: from sampling to data evaluation. J Exp Bot 54, 1505-1510.

Taylor JP, Wilson B, Mills MS, 2002. Comparison of microbial numbers and enzymatic activities in surface soils and subsoils using various techniques. Soil Biol Biochem 34, 387-401.

Tejada M, Hernández MT, García C, 2006. Application of two organic amendments on soil restoration: effects on the soil biological properties. J Environ Qual 35, 1010-1017.

Tejada M, Moreno JL, Hernández MT, García C, 2008. Soil amendments with organic wastes reduce the toxicity of nickel to soil enzyme activities. Eur J Soil Biol 44, 129-140.

Ter Braak CJF, 1994. Canonical community ordination. Part I: basic theory and linear methods. Ecoscience 1, 127-140.

Ter Braak CJF, Šmilauer P, 2002. CANOCO Reference Manual and CanoDraw for Windows User´s Guide: Software for Canonical Community Ordination. Ithaca, NY.


272

270

Tolrá RP, Poschenrieder C, Barceló J, 1996. Zync hyperaccumulation in Thlaspi caerulescens. II. Influence on organic acids. J Plant Nutr 19, 1541-1550.

Tordoff GM, Baker AJM, Willis AJ. 2000. Current approaches to the revegetation and reclamation of metalliferous mine wastes. Chemosphere 41, 219-228.

Torsvik V, Øvreås L, 2007. Microbial phylogeny and diversity in soil. In Van Elsas JD, Jansson JK, Trevors JT (ed), Modern soil microbiology. Second Edition. CRC Press, Taylor & Francis Group, Boca Raton, pp 23-54.

Toyota K, Kuninaga S, 2006. Comparison of soil microbial community between soils amended with or without farmyard manure. Appl Soil Ecol 33, 39-48.

Tuck G, Glendining MJ, Smith P House JI, Wattenbach M, 2006. The potential distribution of bioenergy crops in Europe under present and future climate. Biomass Bioenerg 30, 183-197.

Tyler G, Balsberg-Páhlsson AM, Bengtsson G, Bååth E, Tranvik I, 1989. Heavy-metal ecology of terrestrial plants, microorganisms and invertebrates: a review. Water Air Soil Pollut 47, 189-215.

Ultra VU, Yano A, Iwasaki K, Tanaka S, Kang YM, Sakurai K, 2005. Influence of chelating agent addition on copper distribution and microbial activity in soil and copper uptake by brown mustard (Brassica juncea). Soil Sci Plant Nutr 51, 193-202.

Vainio EJ, Hantula J, 2000. Direct analysis of wood-inhabiting fungi using denaturing gradient gel electrophoresis of amplified ribosomal DNA. Mycol Res 104, 927-936.

Van der Heijden MGA, Bardgett RD, van Straalen NM, 2008. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol Lett 11, 296-310.

Van Nevel L, Mertens J, Oorts K, Verheyen K, 2007. Phytoextraction of metals from soils: How far from practice? Environ Pollut 150, 34-40.

Vance ED, Brookes PC, Jenkinson DS, 1987. An extraction method for measuring soil microbial biomass C. Soil Biol Biochem 19, 703-707.

Vandevivere P, Hammes F, Verstraete W, Feijtel T, Schowanek D, 2001. Metal decontamination of soil, sediment, and sewage sludge by means of transition metal chelant [S,S]-EDDS. J Environ Engin ASCE 127, 802-811.

Vangronsveld J, Van Assche F, Clijsters H, 1995. Reclamation of a bare industrial area contaminated by non-ferrous metals: In situ metal inmobilization and revegetation. Environ Pollut 87, 51-59.

Vaughan D, Malcolm RE, 1984. Influence of assay conditions on inversate activity in different Scottish soils. Plant Soil 80, 285-292.

Verschuere L, Fievez V, Van Vooren L, Verstraete W, 1997. The contribution of individual populations to the Biolog pattern of model microbial communities. FEMS Microbiol Ecol 35, 103-115.

Von Mersi W, Schiner F, 1991. An improved and accurate method for determining the dehydrogenase activity of soils with iodonitrotetrazolium chloride. Biol Fert Soils 11, 216-220.

Wang AS, Angle JS, Chaney RL, Delorme TA, McIntosh M, 2006. Changes in soil biological activities under reduced soil pH during Thlaspi caerulescens phytoextraction. Soil Biol Biochem 38, 1451-1461.

Wang YP, Li QB, Shia JY, Lin Q, Chen XC, Wu W, Chen YX, 2008. Assessment of microbial activity and bacterial community composition in the rhizosphere of a copper accumulator and a non-accumulator. Soil Biol Biochem 40, 1167–1177.

Wardle DA, Bonner KI, Barker GM, Yeates GW, Nicholson KS, Bardgett RD, Watson RN, Ghani A, 1999. Plant removals in perennial grassland: vegetation dynamics, decomposers, soil biodiversity, and ecosystem properties. Ecol Monogr 69, 535-568.

Wardle DA, Bardgett RD, Kliromonos JN, Setala H, Van der Putten WH, Wall DH, 2004. Ecological linkages between aboveground and belowground biota. Science 304, 1625-1633.

Watanabe FS, Olsen SR, 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 extracts from soil. Soil Sci Am Soc Proc 29, 677-678.

Wellburn AR, 1994. The spectral determination of Chlorophyll-A and Chlorophhyll-B, as well as


273

271

Total Carotenoids, using various solvents with spectrophotometers of different resolution. J Plant Physiol 144, 307-313.

Welp G, Brümmer GW, 1997. Microbial toxicity of Cd and Hg in different soils related to total and water-soluble contents. Ecotoxicol Environ Saf 38, 200-204.

Wenzel WW, Salt D, Smith R, Adriano DC, 1999. Phytoremediation: a plant-microbe based remediation system. In Adriano DC, Bollag JM, Frankenberger W, Sims R (ed), Bioremediation of contaminated soils. SSSA Special Monograph 37, Madison, pp 457-510.

Werner C, Correia O, Beyschlag W, 2002. Characteristic patterns of chronic and dynamic photoinhibition of different functional groups in a Mediterranean ecosystem. Funct Plant Biol 29, 999-1011.

Whiting SN, Leake JR, McGrath SP, Baker AJM, 2001. Assessment of Zn mobilization in the rhizosphere of Thlaspi caerulescens by bioassay with non-accumulator plants and soil solution. Plant Soil 237, 147-156.

Whiting SN, Reeves RD, Richards D, Johnson MS, Cooke JA, Malaisse F, Paton A, Smith JAC, Angle JS, Chaney RL, Ginocchio R, Jaffré T, Johns R, McIntyre T, Purvis OW, Salt DE, Schat H, Zhao FJ, Baker AJM, 2004. Research priorities for conservation of metallophyte biodiversity and their potential for restoration and site remediation. Restor Ecol 12, 106-116.

Williamson N, Brian P, Wellington EMH, 2000. Molecular detection of bacterial and streptomycete chitinases in the environment. A van Leeuw 78, 315-321.

Wilson KH, Wilson WJ, Radosevich JL, DeSantis TZ, Viswanathan VS, Kuczmarski TA, Andersen GL, 2002. High-density microarray of small-subunit ribosomal DNA probes. Appl Environ Microb 68, 2535-2541.

Wong MH, 2003. Ecological restoration of degraded soils with emphasis on metal contaminated soils. Chemosphere 50, 775-780.

Wu J, Joergensen RG, Pommerening B, Chaussod R, Brookes PC, 1990. Measurement of soil microbial biomass by fumigation-extraction: an automated procedure. Soil Biol Biochem 22, 1167-1169.

Wu L, Kellogg L, Devol AH, Tiedje JM, Zhou J, 2008. Microarray-based characterization of microbial community functional structure and heterogeneity in marine sediments from the Gulf of Mexico. Appl Environ Microb 74, 4516-4529.

Yamaguchi-Shinozaki K, Shinozaki K, 1994. A novel cis-acting element in an Arabidopsis gene is involved in responsiveness to drought, low temperature, or high-salt stress. Plant Cell 6, 251-264.

Yamamoto HY, Bassi R, 1996. Carotenoids: Localization and function. In Ort DR, Yocum CF (ed), Oxygenic Photosynthesis: The Light Reactions. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp 539–563.

Yang CH, Crowley DE, Borneman J, Keen NT, 2001. Microbial phyllosphere populations are more complex than previously realized. Proc Natl Acad Sci USA 98, 3889-3894.

Yang R, Tang J, Chen X, Hu S, 2007. Effects of coexisting plant species on soil microbes and soil enzymes in metal lead contaminated soils. Appl Soil Ecol 37, 240-246.

Yergeau E, Bokhorst S, Huiskes AHL, Boshker HTS, Aerts R, Kowalchuk GA, 2007a. Size and structure of bacterial, fungal and nematode communities along an Antarctic environmental gradient. FEMS Microbiol Ecol 59, 436-451.

Yergeau, E, Kang S, He Z, Zhou J, Kowalchuk GA, 2007b. Functional microarray analysis of nitrogen and carbon cycling genes across an Antarctic latitudinal transect. ISME J 1, 163-179.

Yuan F, Ran W, Shen Q, Wang D, 2005. Characterization of nitrifying bacteria communities of soils from different ecological regions of China by molecular and conventional methods. Biol Fertil Soils 41, 22-27.

Zak JC, Willing MR, Moorhead DL, Wildman HG, 1994. Functional diversity of microbial communities: a quantitative approach. Soil Biol Biochem 26, 1101-1108.

Zak DR, Holmes WE, White DC, Peacock AD, Tilman D, 2003. Plant diversity, soil microbial communities, and ecosystem function: are there any links? Ecology 84, 2042-2050.

Zhang C, Huang I, Luan T, Jin J, Lan C, 2006. Structure and function of microbial communities during the early stages of


274

272

revegetation of barren soils in the vicinity of a Pb/Zn smelter. Geoderma 136, 555-565.

Zhao FJ, McGrath SP, Crosland AR, 1994. Comparison of three wet digestion methods for the determination of plant sulphur by inductively coupled plasma atomic emission spectrometry (ICP-AES). Commun Soil Sci Plan 25, 407-418.

Zhao FJ, Lombi E, McGrath SP, 2003. Assessing the potential for zinc and cadmium phytoremediation with the hyperaccumulator Thlaspi caerulescens. Plant Soil 249, 37-43.

Zhou J, 2003. Microarrays for bacterial detection and microbial community analysis. Curr Opin Microbiol 6, 288-294.

Zhou J, Kang S, Schadt CW, Garten CT, 2008. Spatial scaling of functional gene diversity across various microbial taxa. Proc Natl Acad Sci USA 105, 7768-7773.

Zucconi F, Monaco A, Forte M, de Bertoldi M, 1985. Phytotoxins during the stabilization of organic matter. In Gasser JKR (ed), Composting of Agricultural and Other Wastes. Elsevier, London, pp 73-86.

aGradecimientos / acknowledGements / eskerrak

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273

AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK

Primeramente, quisiera agradecer a mis directores de tesis, el Dr. Carlos Garbisu y la Dra. María Jesús Sevilla por todo su apoyo y por darme la oportunidad de realizar este trabajo.

Asimismo, me gustaría dar las gracias:

Al Instituto Vasco de Investigación y Desarrollo Agrario (NEIKER-Tecnalia) por permitirme el uso de sus instalaciones y por su apoyo.

A la Asociación Laboratorio de Investigación Caleb Brett Ibérica por su apoyo.

To the Centre for Terrestrial Ecology of the Netherlands Institute of Ecology (NIOO-KNAW) and especially to Dr. George A. Kowalchuk for his support during my stay there.

To the Institute for Environmental Genomics (IEG), University of Oklahoma and especially to Dr. Jizhong Zhou for his support during my stay there.

Al Departamento de Industria, Comercio y Turismo del Gobierno Vasco, por su apoyo económico a través de una ayuda del Programa Ikertu.

El primer día, Carlos me dijo que me había escogido como doctoranda porque corría maratones... ¡¡Ahora que esto está terminando, puedo entender el por qué!! Es a Carlos al que quiero mostrar todo mi agradecimiento, por transmitirme su pasión por la ciencia, por su esfuerzo en intentar formarme como investigadora, por sacar tiempo de donde no había para las eternas correcciones… Te debo mucho, tanto profesional como personalmente. Muchas gracias también a Txema Becerril, porque su visión entusiasta desde las plantas nos ha aportado mucho a los del suelo.

Una buena maratón no se puede correr sin “liebres”: mil gracias sobre todo a Javi, tiraste de mí desde el principio; a Oihana, teniente de infantería de las Rumex, de Eibar; y a Iker, siempre con tan buen ánimo y disposición.

273

AGRADECIMIENTOS/ACKNOWLEDGEMENTS/ESKERRAK

Primeramente, quisiera agradecer a mis directores de tesis, el Dr. Carlos Garbisu y la Dra. María Jesús Sevilla por todo su apoyo y por darme la oportunidad de realizar este trabajo.

Asimismo, me gustaría dar las gracias:

Al Instituto Vasco de Investigación y Desarrollo Agrario (NEIKER-Tecnalia) por permitirme el uso de sus instalaciones y por su apoyo.

A la Asociación Laboratorio de Investigación Caleb Brett Ibérica por su apoyo.

To the Centre for Terrestrial Ecology of the Netherlands Institute of Ecology (NIOO-KNAW) and especially to Dr. George A. Kowalchuk for his support during my stay there.

To the Institute for Environmental Genomics (IEG), University of Oklahoma and especially to Dr. Jizhong Zhou for his support during my stay there.

Al Departamento de Industria, Comercio y Turismo del Gobierno Vasco, por su apoyo económico a través de una ayuda del Programa Ikertu.

El primer día, Carlos me dijo que me había escogido como doctoranda porque corría maratones... ¡¡Ahora que esto está terminando, puedo entender el por qué!! Es a Carlos al que quiero mostrar todo mi agradecimiento, por transmitirme su pasión por la ciencia, por su esfuerzo en intentar formarme como investigadora, por sacar tiempo de donde no había para las eternas correcciones… Te debo mucho, tanto profesional como personalmente. Muchas gracias también a Txema Becerril, porque su visión entusiasta desde las plantas nos ha aportado mucho a los del suelo.

Una buena maratón no se puede correr sin “liebres”: mil gracias sobre todo a Javi, tiraste de mí desde el principio; a Oihana, teniente de infantería de las Rumex, de Eibar; y a Iker, siempre con tan buen ánimo y disposición.


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También han contribuido a esta tesis Marta, Onintze, Izas, Olaia, Saioa y más personas que me han ayudado durante estos años. No me puedo olvidar de la gente de los invernaderos de NEIKER-Tecnalia: gracias por cuidar de mis plantitas durante los fines de semana y escapadas varias.

A Fernando, por las soluciones a mil y un problemas en el laboratorio, pero también por las enseñanzas del tipo de que lo importante es el camino y no el llegar a meta. Gracias a Nahia, Haritz, Ainara, Oscar, Goio, Fenxia, Borja, Roberto, Olatz, Patri, Arrate… porque correr bien acompañada es mucho más divertido que hacerlo sola.

Many thanks to the ones that made me feel at home during my stay abroad. Special acknowledgements for the team of Terrestrial Microbial Ecology in Heteren for letting me pick up their knowledge.

Nire eskerrik beroenak familia eta lagunei, Markinar eta Bilbotarrei, bide ertzean animoak ematen izan zaituztedalako, zuengatik ez balitz aspaldi utzia nukeen; Ekozain taldeari, gogo eta asmo onez zein urrun iritsi daitekeen erakutsi didazuelako; biodantzariei, soinu-banda goxo horregatik; pisukideei, egunerokotasunaren zama arintzearren (jada ez daukat etxeko lanak ez egiteko aitzakiarik…).

Eta azkenik etxekoei, gehien jasaten nautenei. Zuek ere hor zaudetela badakit, eguzkia edo kazkabarra izan, eta beti eskertuko dizuet: beste mota bateko ekosistema toxikoak sendatzen ahalegintzen den ama eta zuhaitzak landatzen dituen aita, nonbaitetik atera behar nintzen ni ere! Baita Xabi ere, neba txiki itzel hori. Andoni, bizipoz kutsakor horrekin nire energi-iturria zara. Zein ametsen atzetik joango gara honen ondoren?

TESIS DOCTORALES PUBLICADAS

Nº 1. La raza Latxa: Sistemas de producción y características reproductivas. Eduardo uriartE EgurcEgui

Nº 2. Estudio y puesta a punto de un método simplificado de control lechero cualitativo en la raza ovina Latxa y su inclusión en el plan de selección. gustavo adolfo Maria lEvrino

Nº 3. Implicaciones tecnológicas de la composición química del pescado con especial referencia a los lípidos. rogElio Pozo carro

Nº 4. Estudio de suelos de Vizkaia. Margarita doMingo urartE

Nº 5. El Maedi o neumonía progresiva en el conjunto de las enfermedades respiratorias crónicas del ganado ovino en la Comunidad Autónoma Vasca. lorEnzo gonzálEz angulo

Nº 6. Estudio experimental de las fases iniciales de la paratuberculosis ovina. raMón a. JustE Jordan

Nº 7. Identificación, origen y factores fisicoquímicos que condicionan la contaminación por elementos metálicos de sedimentos de ríos. Estilita ruiz roMEra

Nº 8. Análisis financiero de proyectos de inversión en repoblaciones forestales. álavaro aunos góMEz

Nº 9. Desarrollo y evaluación del sistema integrado de diagnóstico y recomendación (DRIS) para la fertilización de las praderas permanentes. Marta Rodríguez Julia

Nº 10. Estudio de las mieles producidas en la Comunidad Autónoma del País Vasco. María tErEsa sancho ortiz

Nº 11. La biomasa microbiana como agente de las transformaciones de nitrógeno en el suelo tras el ente-rrado de la paja de cereal. JEsús ángEl ocio arMEntia

Nº 12. Análisis jurídico y económico de la implementación de la política agraria comunitaria en la Comunidad Autónoma del País Vasco. BEatriz PérEz dE las hEras

Nº 13. Nemátodos formadores de quistes (Globodera spp.) en patata (Solanum tuberosum L.): caracteri-zación taxonómica, reproducción y actividad de las formas juveniles. azucEna salazar Bayona

Nº 14. Ensayo comparativo de tres métodos de tratamiento antihelmítico estratégico en rebaños de ovejas latxas. ana luisa gracia PérEz

Nº 15. Estudio sobre una encefalitis vírica similar al Louping-ill en el ganado ovino de la Comunidad Autónoma Vasca. daniEl fErnándEz dE luco Martinéz

Nº 16. Análisis de caracteres involucrados en la selección y mejora de Lupinus hispanicus Boiss. et Reuter. vErónica arriEta Pico

Nº 17. Contribución al estudio de fermentaciones artesanales e industriales de Rioja Alavesa. Milagros viñEgra garcía

Nº 18. Estudio del manejo de la alimentación en los rebaños ovinos de raza Latxa y su influencia sobre los resultados reproductivos y de producción de leche. luis Mª. orEgui lizarraldE

Nº 19. El sector pesquero vizcaíno, 1800-1960. Análisis de la interacción de los elementos ambiental, extractivo y comercial en la pesquería. José agustín Maiz alcorta

Nº 20. Epidemiología, diagnóstico y control de la paratuberculosis ovina en la Comunidad Autónoma del País Vasco. J. J. aduriz rEcaldE

Nº 21. Agrupación de poblaciones locales de maíz (Zea mays L.) mediante caracteres morfológicos y parámetros ambientales. José ignacio ruiz dE galarrEta góMEz

Nº 22. Estudio del potencial melífero de Bizkaia. aMElia cErvEllo MartínEz

Nº 23. Influencia de los procesos de salado y ahumado sobre las características fisicoquímicas del queso Idiazabal (compuestos nitrogenados). francisco c. iBañEz Moya

Nº 24. El Euskal Artzain Txakurra (el perro pastor vasco) descripción y tipificación racial. Mariano góMEz fErnándEz

Nº 25. Evaluación de diferentes ciclos de selección recurrente en dos poblaciones sintéticas de maíz. gotzonE garay solachi

Nº 26. Valoración agronómica de la gallinaza: Compostaje. adolfo MEnoyo PuEllEs

Nº 27. Relación clima-vegetación en la Comunidad Autónoma del País Vasco. aMElia ortuBay fuEntEs

Nº 28. Influencia de los procesos de salado y ahumado tradicional sobre las características microbiológi-cas y organolépticas del queso Idiazabal. francisco J. PérEz Elortondo

Nº 29. Mastitis en la oveja Latxa: epidemiología, diagnóstico y control. Juan c. Marco MElEro

Nº 30. Contribución al conocimiento anatomopatológico y diagnóstico de la tuberculosis caprina y ovina por Mycobacterium bovis. M.ª MontsErrat gutiérrEz cancEla

Nº 31. Estudio de factores que pueden influir en la calidad de la pluma de gallos Eusko-oiloa (Variedad Marradune) para la fabricación de moscas artificiales utilizadas en la pesca de la trucha. rosa M.ª Echarri toMé

Nº 32. Estudio de la fracción lipídica durante la maduración del queso Idiazabal. Influencia de los proce-sos tecnológicos del tiempo de permanencia en salmuera y ahumado. ana isaBEl náJEra ortigosa

Nº 33. Influencia del tipo de cuajo y adición de cultivo iniciador sobre los compuestos nitrogenados durante la maduración del queso Idiazabal. M.ª solEdad vicEntE Martín

Nº 34. Estudio de la infección por Borrelia burgdorferi, grupo Ehrlichia phagocytophila y virus de la encefalitis ovina en las poblaciones de ixódidos de la Comunidad Autónoma Vasca. Marta Barral lahidalga

Nº 35. Lipolisis en el queso Idiazabal: efecto de la época de elaboración, del cultivo iniciador, de la pas-teurización y del tipo de cuajo. fElisa chavarri díaz dE cErio

Nº 36. Aspectos inmunopalógicos de la paratuberculosis de los pequeños rumiantes. Respuesta inmune asociada a la vacunación. Juan ManuEl corPa arEnas

Nº 37. Desarrollo y evaluación de nuevas técnicas de diagnóstico del Maedi-Visna. ana BElén ExtraMiana alonso

Nº 38. Estudios sobre Patogenia y Diagnóstico de la Adenomatosis Pulmonar Ovina. María MErcEdEs garcía goti

Nº 39. Análisis de los factores de explotación que afectan a la producción lechera en los rebaños de raza Latxa de la CAPV. roBErto J. ruiz santos

Nº 40. Crecimiento y producción de repoblaciones de Pinus radiata D. Don en el Territorio Histórico de Gipuzkoa (País Vasco). luis Mario chauchard Badano

Nº 41. Puesta a punto de técnicas PCR en heces y de Elisa para el diagnóstico de la Paratuberculosis. Estudio de prevalencia en ganado bovino. JosEBa M. garrido urkullu

Nº 42. Epidemiología y diagnóstico de la leptospirosis y la neosporosis en explotaciones de bovino leche-ro de la CAPV. raquEl achaErandio galdos

Nº 43. Relaciones aire-agua en sustratos de cultivo como base para el control del riego. Metodología de laboratorio y modelización. valEntín tErés tErés

Nº 44. Zonas endémicas de enfermedad de Lyme en la CAPV: estudio del papel de los micromamíferos en el mantenimiento de Borrelia burgdorferi sensu lato en el medio natural. horacio gil gil

Nº 45. Optimización del esquema de mejora de la raza Latxa: análisis del modelo de valoración e intro-ducción de nuevos caractéres en el objetivo de selección. andrés lEgarza alBizu

Nº 46. Influencia de las condiciones de almacenamiento, reimplantación y lluvia ácida en la viabilidad de Pinus radiata D. Don. MirEn aMaia MEna PEtitE

Nº 47. Estudio sobre encefalopatías en peces: patogenicidad del nodavirus causante de la enfermedad y retinopatía vírica (ERV) y transmisión experimental del prión scrapie a peces. raquEl arangurEn ruiz

Nº 48. Enfermedades transmitidas por semilla en judía-grano (Phaseolus vulgaris L.): detección, control sanitario y mejora genética. ana María díEz navaJas

Nº 49. Pastoreo del ganado vacuno en zonas de montaña y su integración en los sistemas de producción de la CAPV. nErEa Mandaluniz astigarraga

Nº 50. Aspectos básicos de la mejora genética de patata (Solanum tuberosum L.) a nivel diploide. lEirE Barandalla urtiaga

nº 51. El cuajo de cordero en pasta: preparación y efecto en los procesos proteolíticos y lipolíticos de la maduración del queso de Idiazabal. Mª. ángElEs BustaMantE gallEgo

Nº 52. Dinámica de la población de atún blanco (Thunnus alalunga Bonnaterre 1788) del Atlántico Norte. Josu santiago Burrutxaga

nº 53. El pino radiata (Pinus radiata D.Don) en la historia forestal de la Comunidad Autónoma de eus-kadi. Análisis de un proceso de forestalismo intensivo. Mario MichEl rodríguEz

nº 54. Balance hídrico y mineral del pimiento de Gernika (Capsicum annuum L., cv Derio) en cultivo hidropónico. Relaciones con la producción. hugo Macía olivEr

nº 55. Desarrollo de métodos moleculares y su aplicación al estudio de la resistencia genética y patogenia molecular del Scrapie. david garcía crEsPo

nº 56. Estudio epidemiológico y experimental de la transmisión y control del virus Maedi-Visna en ovino lechero de raza Latxa del País Vasco. vEga álvarEz MaiztEgui

nº 57. Desarrollo y aplicación de técnicas de diagnóstico serológico para el estudio de la transmisión calostral y horizontal del virus Maedi-Visna (VMV) en ovino. Mara Elisa daltaBuit tEst

nº 58. Integral Study of Calving Ease in Spanish Holstein Population. EvangElina lóPEz dE Maturana lóPEz dE lacallE

nº 59. Caracterización Molecular, Detección y Resistencia de Mycobacterium avium subespecie paratu-berculosis. ikEr sEvilla agirrEgoMoskorta

nº 60. Desarrollo de un sistema de fertilización nitrogenada racional en trigo blando de invierno bajo condiciones de clima mediterráneo húmedo. M.ª arritokiEta ortuzar iragorri

nº 61. Estructura y dinámica de la materia orgánica del suelo en ecosistemas forestales templados: de los particular a lo general. nahia gartzia BEngoEtxEa

nº 62. Análisis sensorial del vino tinto joven de Rioja Alavesa: descripción y evaluación de la calidad. iñaki Etaio alonso

nº 63. Biología del gusano de alambre (Agriotes spp.) en la Llanada Alavesa y desarrollo de estrategias de control integrado en el cultivo de la patata. ana isaBEl ruiz dE azúa Estívariz

nº 64. La sucesión en la ganadería familiar: el ovino de leche en el País Vasco. guadaluPE raMos truchEro

nº 65. Identificación molecular de las especies de piroplasmas en las poblaciones de Inóxidos de la Comunidad Autónoma del País Vasco. Distribución y prevalencia de babesia y theileria en los ungulados domésticos y silvestre. MirEn JosunE garcía

nº 66. Estudio de variables inmunológicas y bacteriológicas en relación con la inmunización frente a paratuberculosis en los rumiantes. María v. gEiJo vázquEz

nº 67. Bacterias lácticas de sidra natural: implicación en alteraciones y potencial probiótico de cepas productoras de (1,3)(1,2)-ß-D-glucanos. gaizka garai iBaBE

nº 68. Influencia de los sistemas de producción ovina en la calidad y las propiedades tecnológicas de la leche y el queso. EunatE aBillEira cillEro

nº 69. Los carnívoros silvestre como reservorios de enfermedades de interés en sanidad animal y salud pública. xEidEr gErrikagoitia sagarna

nº 70. Cattle nutrition as a strategy to mitigate gaseous nitrogen losses from dairy farming. haritz arriaga sasiEta

ISBN: 978-84-457-3092-8

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