Ecosistemas y servicios ecosistemicoselti.fesprojects.net/2013...

Ecosistemas y servicios ecosistémicos Desarrollo de una visión holística

Patrick LAVELLE Universite P. et M. Curie

Paris 6 Universidad Nacional

1. Earth a living planet

Ecological Research: Seminars and Workshops

The GAIA hypothesis

Jim Lovelock

Earth is a super organism able to develop Homeostasis

The temperature and composition of the Earth's atmosphere and surface are actively controlled by life. Biological responses tend to regulate the state of the Earth's environment in their favor.


How can we tell that a planet has life ?

• Atmospheric composition


Atmosphere regulation by GAIA

% VENUS MARS EARTH EARTH with

no life

CO2 96.5 95.0 0.04 98.0

N 3.5 2.7 79.0 1.9

O2 marcas 0.13 21.0 0.0

Ar 70 ppm 1.6 1.0 0.1

CH4 0.0 0.0 1.7ppm 0.0

T° superficie 459 -53 13 240-340

Pression

(bars)

90 0.0064 1.0 60

Stages of changes in the Earth atmosphere

• Cyanobacteria use solar energy and produce Oxygen

• Phytoplancton accumulate CO2 and Ca++ in their skeletons deposit and accumulate at sea bottom

• 02 concentration stays at an equilibrium value of 21%



Thermal cap: The Ozone layer

• A thin pellicle of ozone molecules creates a thermal cap that prevents atmospheric gases to diffuse outside the atmosphere

• Stops the strongest Uvb

• Allows green house effect to develop


Vertical stratification of temperature on Earth


Skeletons of planctonic organisms deposit at sea bottom forming thick accumulations


Sedimentary rocks


The weight of sediments likely triggered the movement of continental plates and created volcanic eruptions that brought new material

rich in nutrients to the surface

TEST: Are you rather Selfish gene or Gaia

• The selfish gene

• The God Delusion

• The Extended phenotype


• The Ages of Gaia

• The Revange of Gaia

Earthworm communities at Lamto (Ivory Coast)

Earthworms in a 50x50m plot at Lamto (Côte d’Ivoire)

EARTHWORM SPATIAL PATTERNS

E a r t h w o r m d i s t r i b u t i o n

Source : Rossi, 2010 Pedobiologia

WHAT DOES THAT MEAN???

Biodiversity Today: >10M species

Ecology • Community : Species richness +

dominance patterns (Shannon index + equitability)

• Population : genetic diversity

• Ecosystem : sum of existing species/genomes

• Landscape : diversity of ecosystems

Economy/Env. Sciences • The living component

All forms of biological diversity, at all scales

What is biodiversity??

genes

species

ecosystems

Functional diversity and regulation of soil structure

MEA: 10 to 12 million species How many genomes??

Biodiversity

still poorly described in soils

N. of identified sp. decreases with size

R2= = 0,41

0

10

20

30

40

50

60

70

80

90

1 m 100 m 10mm 1m

Mean body size

% d

es

cri

be

d

0,0

1

0,1

1

10

100

1000

10000

Bacteria

Fungi

Nematoda

Protozoa

Acari

Collembola

Diplura Symphyla

Enchytraeidae

Isoptera

Formicoidea Diptera

Isopoda

Chilopoda Dermaptera

Blattoidea

Diplopoda

Arachnida

Coleoptera

Mollusca

Pauropoda

Oligochaeta

Caecilian Sqamata

Mammalia

Species number (x 1000)

NE

NE

NE

NE

NE

NE

NE

NE

NE

NE NE

Described species

Undescribed species

Ta

ille

corp

ore

lle d

es t

axons

Decaëns e

t al. (2

009)

Organization and structure of biodiversity

• Community : the Ecological Niche paradigm

• Ecosystem: Biotic interactions

– Foodweb

– Self organization

Source: Tilman, 1992, Science

Ex: Niche separation in earthworm communities

EPIGEIC

ANECIC

ENDOGEICS

Source: Bouché, 1977; Lavelle , 1983; Lavelle et al., 1998

Community level Earthworms at Lamto (Ivory Coast)

Earthworm community in the Lamto savannah (Côte d’Ivoire)

0

10

20

30

40

1. Millsonia lamtoiana (anecic)

2. Dichogaster baeri (epigeic)

3. Dichogaster agilis (epigeic)

4. Millsonia anomala(mesohumic)

5. Chuniodrilus zielae 6. Stuhlmannia porifera (polyhumic)

7. Dichogaster terrae nigrae (oligohumic

8. Millsonia ghanensis (oligohumic

9. Agastrodrilus opisthogynus (carnivorous)

10. A. multivesiculatus (carnivorous)

1 2 3 4 5-6 7 8 9 10

Niche separation according to: • distribution in depth • size • seasonal variations • feeding regime

Demonstrated foodweb controls Ecosystem level:

foodweb regulations Nicely demonstrated inwater systems

Sea Otters prevent overgrazing of sea grasses by urchins C sequestration

Algal blooms due to decrease In fish communities

Source: Chapin et al., Nature, 2000

Not applicable to most soil environments!!! Ignores Mutualism and Ecosystem engineering

Source FAO, 2003 after Hunt et al., 1987

Nutrient cycling

The power of ecosystem engineers

Several hundred T bio structures created /ha /year

create habitats

Regulate environment conditions for smallerorganisms

Drive their energy from mutualist digestion with Microorganisms

Adaptive strategies of soil organisms

1. Moving in a compact environment

2. Low quality Feeding resources

3. Unstable amphibiotic Environment

Phenol protein

Three major constraints

Microflora and ecosystem engineers: The Sleeping Beauty Paradox

source: Lavelle, 1997

Very large microbial populations in soils

Large potential for multiplication (generation time = 20h in the lab)

BUT

Turnover time of microbial biomass Is 6 to 18 meses

En el suelo las bacterias estan inactivas La mayoria del tiempo

Esperando quien las transporta a un

nuevo substrato alimenticio

Las Raices y los invertebrados son los « Principes Azules »

Sleeping Beauty paradoxe

Inactive Bacteria

Poly saccharids

clay

Mucus

Earthworm

Ecosystem Engineer

Bacteria

Source : Barois and Lavelle, 1986

Mixture of water (1v) and Mucus (5-18%)

Activation of a selected microflora that digests OM in the earthworm guts

Engineers and Workers

Earthworm builds, organizes and regulates

Microorganisms digest everything

Ecosystem Engineers build Functional Domains in soil

Source : Lavelle, 1984, 2002

Primary forest in Madagascar HIGEST SENSITIVITY OF SOILS TO EROSION

Ex. Earthworms as Hydraulic Engineers

in Madagascar

Upper humic horizon with high root density (1km

per m²)

Absorbs 20-100 mm rain

Made by Diptera larvae

In the A1 horizon, giant worms build networks of galleries

that allow drainage

Erosion

Deforestation and removal of surface horizons trigger a catastrophic process of erosion

Water flow

B prismatic horizon

Soil destruction after removal of the surface protecting cover

Massive erosion after deforestation (Lavakas) Soil collapses from

The road

Earthworms in a 50x50m plot at Lamto (Côte d’Ivoire)

EARTHWORM SPATIAL PATTERNS

E a r t h w o r m d i s t r i b u t i o n

Source : Rossi, 2010 Pedobiologia

WHAT DOES THAT MEAN??? Competitive exclusion Response to local conditions Mini successional process

Self Organising Systems are groups of organisms that

• develop networks of interactions

• at discrete spatial scales within boundaries

• with positive or negative feedbacks on external constraints

Self organised systems

Source: Perry, 1995. TREE

Microorganisms

Microbial

aggregates

Microfoodwebs

Intermediate

aggregates

Ecosystem

engineer

Biogenic

structures

Ecosystem services

Organisms

Structures

Created

Soil catenas

Ecosystem

Community

of Ecos. Eng.

Soil horizon

after Lavelle et al., 2004, in Wall (ed).

Soil Self Organization model

after Lavelle et al., 2004, in D.Wall (ed)

Lavelle et al., 2006 Eur.J Soil Biol..

Estructura Fisica del suelo

Activacion Seleccion

Infiltracion Almacenamiento

Agua

Dinamica de la MO

Rec. nutrientes Reg. Clima

Pop

Comm

SERV. ECOS.

Energia

All elementary SOS go through successional processes and associate in a Panarchy

• Adaptive cycle of a Self Organized System

• SOS of different natures form a Panarchy

Soil Eco

nomy Institu tions

Source : Gunderson and Holling, 2001

Fresh Biogenic structures have specific compositions

and SOM quality

Contribution to SE: C sequestration Plant Production Water cycling Plant protection Erosion and flood control

Ecosystem process : Primary production Earthworm contribution :5 mechanisms (cg. Brown et al., 1999) Indicator : soil morphology; soil microbial communities; abundance and diversity of pests; plant gene expression

(Blanchart, 1990)

Stimulation of Plant growth Plant Protection

Nematodos

Nematodos+ Lombrices

Lombrices

Control

Bixa orellana

No worms

Brown, G. et al. in Lavelle, P., Brussaard, L. & Hendrix, P. 87-148 (CAB International, Wallingford, UK, 1999). Scheu, S. Pedobiologia 47, 846-856 (2003). Blouin, M., Barot, S. & Lavelle, P.. Soil Biol. Biochem. 38, 2063-2068 (2006). Blouin, M. Zuily-Fodil, Y.,Pham-Thi, A.T.,Laffray, D., Reversat, G., Pando, A., Tondoh, J., Lavelle, P. Ecol Lett 8, , 8 (202-208). (2005).

Se daño una rueda: Pontoscolex corethrurus en pastizales amazonicos

Number of morphospecies

0

40

80

120

160

Fo P4 P8 Pes Pro Pah J I J II HI LI

Other Species

Forest Species

PasturesFallows

Agroforestry

Source: Barros, 1999

Forest

Soil Macrofauna Richness

The invasive Pontoscolex corethrurus colonizes

High density of Pontoscolex corethrurus

Other decompacting species

Largely disappeared

High activity In the upper 10 cm of soil

A continuous crust of compact casts of

P. Corethrurus seals the soil

Chauvel et al., 1999; Nature

• Spatial modeling predicts a distribution in alternated patches at equilibrium

• Succession process at small scale


Test 2 Porque en el experimento hecho en condiciones

naturales el resultado no esta tan bonito??

Tilman et al., 1997 Hector et al., 1999

0 1 2 4 8 16 32 0

500

1000

1500

Greece Sweden Portugal

UK Ireland

Switzerland

Germany

Species Richness

H: Biological control maintains ecological functions in a disturbed situation

2.

Ecosystem degradation: The Millennium Ecosystem Assessment

MAweb.org

Then a new species came and started to create problems….

• Homo sapiens???

A bull in a China shop

U.S

. Bu

rea

u o

f the

Ce

nsu

s

Millennium Ecosystem Assessment The largest evaluation of ecosystems

ever done

•Experts and Revision process

–Prepared by 1360 experts from 95 countries

–Editorial committee of 80 persons

–Revised by 850 experts with gov. representatives

–33 sub global evaluations

Focus: Ecosystem Services The benefits people obtain from ecosystems

Loss of species threatens the provision of

Ecosystem services

• 60% ES are soil based

• Primary Production

• Nutrient Cycling

• Water cycling

• Soil formation and retention

• Erosion control

• Climate regulation

Etc…..

For this reason Agriculture is responsible for 60% of Global Change

Focus: Consequences of Ecosystem Change for Human Well-being

• 1. Ecosystem Changes in Last 50 Years

• 2. Gains and Losses from Ecosystem Change Three major problems may decrease long-term benefits

– Degradation of Ecosystem Services

– Increased Likelihood of Nonlinear Changes

– Exacerbation of Poverty for Some People

• 3. Ecosystem Prospects for Next 50 Years

• 4. Reversing Ecosystem Degradation

MA Findings - Outline

Temperate Grasslands & Woodlands

Temperate Broadleaf Forest

Tropical Dry Forest

Tropical Grasslands

Tropical Coniferous Forest

Bosque Mediterraneo

Tropical Moist Forest

0 50 100

Percent of habitat (biome) remaining

Habitat Loss to 1990

Source: Millennium Ecosystem Assessment

•More land was converted to cropland in the 30 years after 1950 than in the 150 years between 1700 and 1850.

Cultivated Systems in 2000 cover 25% of Earth’s terrestrial surface

Significant and largely irreversible changes to species diversity

– Species extinction rate X 1,000

–10–30% of vetrebrate species are threatened with extinction

• 1. Ecosystem Changes in Last 50 Years

• 2. Gains and Losses from Ecosystem Change Three major problems may decrease long-term benefits

– Degradation of Ecosystem Services

– Increased Likelihood of Nonlinear Changes

– Exacerbation of Poverty for Some People

• 3. Ecosystem Prospects for Next 50 Years

• 4. Reversing Ecosystem Degradation

MA Findings - Outline

Changes to ecosystems have provided substantial benefits

– Food production has more than doubled since 1960

– Food production per capita has grown

– Food price has fallen

At expenses of other ecosystem goods and services

The Balance Sheet

Crops Livestock Aquaculture Carbon sequestration

Capture fisheries Wild foods Wood fuel Genetic resources Biochemicals Fresh Water Air quality regulation Regional & local climate

regulation Erosion regulation Water purification Pest regulation Pollination Natural Hazard regulation Spiritual & religious Aesthetic values

Timber Fiber Water regulation Disease regulation Recreation & ecotourism

Enhanced Degraded Mixed

Bottom Line: 60% of Ecosystem Services are Degraded

0

1

2

3

4

5

6

7

8

9

Sources Sinks

Land Use

Fossil Fuel Atmosphere

Oceans

Terrestrial

Gigatons carbon per year

Sources and Sinks of Carbon in 1990s


Climate Regulation (Global) Enhanced

For how long ????

Eutrophication : the global P cycle

Source: Lavelle et al., MEA 2005

Phosphate rocks 4 x 10 9 Tg

Mineable resource: 1x10 4 Tg

Soil: 2 x 10 5 Tg [2000y]

Increasing by 10.5 - 15.5/y

Soil: 2 x 10 5 Tg [2000y]

Increasing by 10.5 - 15.5/y

Plankton & fish: 140 [0.13y] Surface ocean water: 2700 [2.6y]

Deep ocean: 8.7 x 10 4 Tg

Rivers,lakes & coast

Plants 3000 Tg

[47 y] Atmospheric dust

0.028 Tg [0.006y]

Ocean sediments: 4 x 10 9 Tg [2 million y]

60 Tg/y Dust 4.2 Tg/y

Dust 3.2 Tg/y

Dust 1 Tg/y

Was: 7 - 9

River transport Was: 7 - 9 Tg/y

-

Animals

15 Tg/y

Weathering Was:10 Tg/y

-

17-32 Tg

Mined

19.8Tg

Fertiliser 17 Tg/y

Industrial 0.8 Tg/y

Animal feed 2.0 Tg/y

Now:15 30Tg/y

Return in geological time

Percent Increase in Nitrogen Flows in Rivers


Stream contamination

•Freshwater Status: Degraded

15–35% of Irrigation Withdrawals

Unsustainable

(low to medium certainty)

Zonas muertas en el mar Gulf of Mexico Dead Zone

Source: NOAA

Year of Peak Fish Harvest Harvest peak

Pre-peak

Post-peak

Source: Millennium Ecosystem Assessment and Sea Around Us project

Fish stocks are progressively exhausted

Value (per hectare)

0

$2000

$4000

Mangrove Shrimp Farm

Coastal Protection (~$3,840)

Timber and Non-timber products ($90)

Fishery nursery ($70)

Net: $2,000 (Gross $17,900 less costs of $15,900)

Pollution Costs (-$230)

Less subsidies (-$1,700)

Restoration (-$8,240)

Mangrove Conversion

Private Net Present Value per hectare

Mangrove: $91

Shrimp Farm: $2000

1987 1999 Public Net Present Value per hectare

Mangrove: $1,000 to $3,600

Shrimp Farm: $-5,400 to $200

Source: Millennium Ecosystem Assessment; Sathirathai and Barbier 2001

Source: UNEP

QUIEN SE APROVECHA DEL CRIMEN ?

Fiber

Food

Spiritual & religious

Freshwater

Genetic Resources

Climate regulation

Water purification

Disease regulation

Flood/Fire regulation

Recreation & tourism

Aesthetic

Economic Value ($)

Economic Valuation

Difficult or impossible

Easy

Private Benefit Capture

Difficult

Easy

?

?

?

?

?

?

?

?

?

?

?

Many services are public goods

Degradation of ecosystem services often causes significant harm to human well-being

– The total economic value associated with managing ecosystems more sustainably is often higher than the value associated with conversion

– Conversion may still occur because private economic benefits are often greater for the converted system

The threat of nonlinear changes The case of Atlantic cod

What will happen ? What can we do?

Direct drivers growing in intensity

•Most direct drivers of degradation in ecosystem services remain constant or are growing in intensity in most ecosystems

Order from Strength

Adapting Mosaic

Global Orchestration

TechnoGarden

Globalization Regionalization

World Development En

viro

nm

en

tal M

anag

em

en

t

Pro

acti

ve

Rea

ctiv

e

MA Scenarios

Scenario Storylines

Global Orchestration Globally connected

society ; global trade and economic liberalization

reactive approach

strong steps to reduce poverty and inequality and to

invest in public goods such as infrastructure and education.

Order from Strength Regionalized and

fragmented world,

concerned with security and protection,

regional markets,

little attention to public goods,

reactive approach to ecosystem problems.

Scenario Storylines

Adapting Mosaic Regional watershed-scale

focus of political and economic activity.

Local institutions are strengthened and local ecosystem management strategies are common;

strongly proactive approach to the management of ecosystems.

TechnoGarden Globally connected world

relying strongly on environmentally sound technology,

using highly managed, often engineered, ecosystems to deliver ecosystem services,

proactive approach to the management of ecosystems in an effort to avoid problems.

Temperate Broadleaf Forest

Tropical Dry Forest

Tropical Grasslands

Tropical Coniferous Forest

Mediterranean Forests

Tropical Moist Forest

0 50 100

Percent of habitat (biome) remaining

Habitat Loss to 1990 Habitat Loss to 2050 under MA Scenarios


Temperate Grasslands & Woodlands

Improvements in services can be achieved by 2050

•Significant changes in policy can improve ecosystem services

•The changes required are large and not currently under way

Ejemplos de cambios en las políticas y prácticas que arrojan resultados positivos

• Orquestación Global

– Mayores inversiones en bienes públicos (e.g., educación, infraestructura) y reducción de la pobreza

– Eliminación de barreras comerciales y subsidios distorsivos

• Mosaico Adaptativo

– Uso extendido del manejo adaptativo activo

– Inversión en educación (los países gastan el 13% del PBI en educación, comparado con el 3.5% en la actualidad)

• Tecnogarden

– Inversión significativa en el desarrollo de tecnologías para aumentar el uso eficiente de los servicios de los ecosistemas

– Uso extendido de PSA y desarrollo de mecanismos de mercado

Creditos

Ecoefficient Landscapes to Prevent Degradation of Agroecosystems in

Deforested Amazonia

Patrick LAVELLE S. Dolédec, B. Ramirez, I. Veiga, X. Arnauld de Sartre, T. Decaëns, V. Gond, M. Grimaldi, J. Oszwald, B. Hubert, S. de Souza,

W. S. de Assis, F. Michelotti , M. Martins, A. Feijoo, E. Castañeda, P. Chacon, T. Desjardins, S. Fonte, E. Gordillo, E. Guevara , M. P. Hurtado, P. Lena, T. Lima, R. Marichal, D. Mitja, I. Miranda, L. E. Moreno , J. T. Otero, C. Praxedes, P. de

Robert, G. Rodriguez, C. Sanabria, S. Tselouiko, A. Velasquez, J. Velasquez, E. Velasquez

Tropical Soils TSBF-LAC Institut de Recherche pour le Développement

Cali, Colombia

CHALLENGE: To propose a sustainable management for Visible and invisible elements

Visibles and invisible accounts

Water flow, Erosion

Polination, Biological control Soil Conservation Plant Vigor, Landscape

COUNTRY

$

REGION

PLANET

Climate heatingo Seasons

$?

$?

$?

“Boom and bust” development after deforestation

DEFORESTATION (YEARS)

Human development Standard of living

20 40 60 80 0

20 40 60 80 0

20 40 60 80 0

Source: Rodrigues et al., 2009. Science 324,

• H1: “Bust” is due to environmental degradation • How to build sustainable farming systems (Social-, economic- and environmentally)?

The AMAZ project: 2006-2010 Agence Nationale pour la Recherche

France

Socio economic conditions, Ecosystem goods and services and Biodiversity, in Amazonian

landscapes

16 Institutions 30 Scientist 100 Students 1000 Inhabitants

The AMAZ team

• 16 institutions from 3 countries

• 4 disciplinary fields

• 30 researchers

• > 200 students

• ~ 1000 inhabitants of deforested Amazonian areas

A nested sampling from regions (2) to lanscapes (6), farms(54) and

sampling points (270) in AMAZONIA

ON FARM APPROACH SMALL HOLDERS

Palmares Maçaran

duba Pacaja Tradicional

Silvo pastoril

Agrosilvo pastoril

PL1 PL2 PL3 M1 M2 M3 Pa1 Pa3 T1 T2 T3 S1 S2 S3 A1 A2 A3 Pa2

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

17

3

153 farms 153 farms

27 farms 5 sampling points

27 farms 5 sampling points

BRASIL Pará

COLOMBIA Caqueta

3 landscape windows 3 landscape windows

3 sub windows

SOCIOECO LANDSCAPE

BIODIVERSITY Productions Soil Ecosystem Services

A stratified sampling protocole

Conceptual Model

M MA

MULTI AGENT MODELING

SOCIOECO Lives, formation, housings

Crédits

LANDSCAPES Composition, structure

BIODIVERSITY Plants, Birds, Moths,

Drosophilidae, Earthwors, Ants Soil Macrofauna

ECOSYSTEM SERVICES Soil Fertility, Water Infiltration and storage, C sequestration,

Chemical Fertility

PRODUCTIONS Live stock, Agriculture

Extractivism,

EXCHANGE of KNOWLEDGE

Ef logEp Bd Qs

ECOEFFICIENCY

= * *

1. The social context

Migrating farmers

Studies Urban life

BRASIL 15-20 años

COLOMBIA 60-80 años

A gradient from pure rural, little formed to semi urban highly trained farmers

2. Production systems

F2: 7,9 %

Perennial crops

Intermediate incomes

C3

C1

C2

C4 C6 C5

C7

Diversified Meet Annual cropss

Small

Low incomes

Large Extensive cat. breeding Altos ingresos

C1 C2 C3

C4 C5 C6 C7

7 types • Size of the farm • Non agricult. revenues • Man power • Production types • Total revenues

AGRO FORESTRY

EXTENSIVE CATTLE BREEDING

PIONEER FRONTS

Productions

Front pionnier10 ans

Paysage agroforestier60 ans

Elevage extensif60 ans

LANDSTRUCTURE

LANDUSE

DYN. LAND

STRUCTURE

DYN. LAND

USE

LAND

STRUCTURE

DYN. LANDSTRUCTURE

LAND

STRUCTURE

LANDUSE

DYN. LANDSTRUCTURE

DYN. LAND

USE

EWM

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLmedPLinf

ANTS

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLmedPLinf

ANTS

PLmed

EWM

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLinf

ANTS

SC010

SC1030INFIL

TW050

AW050 FCHIM

SC010

SC1030INFIL

TW050

AW050 FCHIM

SC010

SC1030INFIL

TW050

AW050 FCHIM

PAYSAGES

BIODIVERSITÉ

SERVICES ECOSYSTÉMIQUES

Viande

LaitC. Annuelles

P. Elev. Extrac.

1 2 4 53

C. Pérennes

C3PRODUCTIONSPRODUCCIONES Annuals

Perenials

Milk

Meat

Extractivism Small animals

Pioneer Fronts 10 years

Agroforestry 60 years

Extensive cattle breeding 60 years

Incomes

1 2 3 4 5 6 7

1.0

3.2

10

32

320

100

Recent Pioneer fronts

Agroforestry

Diverse

Milk on larg e areas

10 3 € /an

1 2 3 4 5 6 7 5

10

15

20

25

30

35 PAYSAGE

SERVICES

ECOSYSTÉMIQUES

Extensive cattle breeding

1 2 3 4 5 6 7

0.2

0.4

0.6

0.8

1.0

2 1 3 4 5 6 7

0.3

0.4

0.5

0.6

0.7 BIODIVERSITÉ

P < 0.01 P = 0.08

P<0.01

Figure 2 : Variations en fonction des types socio économiques échelonnés suivant les valeurs du facteur 1 de la figure 2) de (a) - Revenus des fermes (valeurs en 10 3 Euros ; (b) - Indicateur d’usure du paysage; (c) - Biodiversité (indicateur synthétique); (d) - serviesc

écosystémiques (indicateur synthétique), (d) - Eco efficience: Indicateur Ef voir texte.

P = 0.08

1 2 3 4 5 6 7

0.3

0.4

0.5

0.6

0.7

0.8

0.9

ECO - EFFICIENCE 4

Figure 4 : V ariations en fonction des t ypes socio - économiques classés suivant leurs valeurs du facteur 1 de la figure 2, de (a) - revenus des fermes (en 10 3 € ); (b) – Indicateur d’intégrité

du p aysage ; (c) - Biodiversité ( indicateur synthétique ); (d) - services Écosystémiques ( indicateur synthétique ); (d) - éco - efficience : indicateur Ef ( voir texte ).

Production Systems

Transamazonian Highway Travessão Km 338 S

LID TYPE CA PLAND PD ED AREA_AM SHAPE_AM PARA_AM ENN_AM LNUM

CAF11901 paturage avec arbres disperses 3,9475 23,0208 139,9621 250,4738 0,724 2,0077 1248,8917 27,4033 4

CAF11901 NoData 4,5675 26,6365 116,6351 225,1057 0,882 1,8483 1026,8199 25,0461 0

CAF11901 paturage propre 0,02 0,1166 5,8318 2,3327 0,02 1,1667 3500 0 1

CAF11901 friche jeune 0,34 1,9828 34,9905 29,7419 0,0688 1,0564 1794,1176 66,8178 12

CAF11901 paturage avec ligneux arbustifs 0,7525 4,3884 69,981 68,8147 0,1032 1,1468 1674,4186 53,0699 3

CAF11901 friche vielle 4,1925 24,4496 75,8128 259,8046 0,5906 2,0517 1190,2206 26,0503 13

CAF11901 plantation agro forestiere d hevea 2,6275 15,3229 81,6446 149,0013 0,5368 1,5062 1080,8754 33,6068 10

CAF11901 plantation de palme africaine 0,7 4,0822 52,4858 63,2745 0,1011 1,2432 1728,5714 52,8242 9

CAF12001 paturage propre 0,07 0,7421 21,2033 10,6016 0,0352 1,25 2857,1429 210,238 1





CAF12001 NoData 1,0075 10,6812 116,6181 138,8815 0,2319 1,4491 1548,3871 31,8433 0

CAF12001 plantation de palme africaine 0,04 0,4241 10,6016 8,4813 0,04 1 2000 0 9


CAF12101 NoData 4,965 26,2074 105,5688 176,8277 0,989 1,6987 926,4854 24,0106 0





CAF12101 friche jeune 0,28 1,478 36,9491 26,92 0,0488 1,0235 2071,4286 47,2563 12





CAF22201 NoData 2,1525 12,4494 98,3227 132,1573 0,3016 1,314 1212,5436 33,5834 0



CAF22201 plantation de palme africaine 0,125 0,723 17,3511 10,1215 0,0517 1,0233 2080 207,3966 9




CAF22301 NoData 1,775 18,1354 153,2567 206,3857 0,2554 1,3597 1335,2113 45,1014 0


CAF22301 plantation agro forestiere d hevea 2,7 27,5862 20,4342 119,5402 2,6212 2,3882 618,5185 25 10


CAF22301 friche jeune 0,08 0,8174 20,4342 16,3474 0,04 1 2000 205,061 12

CAF22401 NoData 0,9525 8,5292 89,5456 115,9615 0,1447 1,3469 1574,8031 35,0253 0




CAF22401 plantation de palme africaine 0,0975 0,8731 35,8182 17,9091 0,0347 1 2461,5385 118,2912 9

CAF22401 friche jeune 0,1525 1,3656 17,9091 19,2523 0,0935 1,1054 1573,7705 96,1769 12

CAF22401 paturage avec ligneux arbustifs 0,415 3,7161 62,6819 64,9205 0,0646 1,199 2000 34,8838 3

CAF22401 paturage propre 0,04 0,3582 8,9546 6,2682 0,04 1 2000 0 1





CAF32501 NoData 6,91 16,2321 86,9157 177,9422 1,5126 2,6863 1214,1823 27,3871 0



CAF32501 friche jeune 0,12 0,2819 4,6981 5,2854 0,0667 1,2222 2000 25,4951 12

CAF32601 NoData 4,15 13,5433 58,7419 119,9315 1,7351 2,1345 990,3614 37,4858 0





CAF32601 friche jeune 0,04 0,1305 3,2634 2,6108 0,04 1 2000 0 12



CAF32701 NoData 15,175 39,0078 56,5516 193,9464 7,9739 3,0342 618,1219 15,7179 0







CSP11001 plantation agro forestiere d hevea 1,305 1,7317 15,9241 19,8388 0,1472 1,1053 1287,3563 127,6472 10

CSP11001 verger 12,58 16,6938 49,0993 122,5492 2,7163 2,1722 775,8347 28,5167 6

CSP11001 plantation d'arbustes fouragers 19,4325 25,7871 35,8292 165,1461 3,2944 2,6304 688,0226 36,4995 11

CSP11001 paturage propre 15,005 19,9118 50,4263 143,9804 1,3418 1,877 805,065 42,2705 1

CSP11001 NoData 11,0875 14,7132 31,8482 100,3881 2,0434 2,1513 789,177 37,6087 0

CSP11001 friche vielle 13,5325 17,9577 7,962 59,45 12,3068 3,0976 399,0393 17,4865 13

CSP11001 friche jeune 1,2625 1,6753 13,2701 17,8483 0,1927 1,0873 1164,3564 52,5515 12

CSP11001 paturage avec ligneux arbustifs 1,1525 1,5294 2,654 10,417 0,8733 1,4793 720,1735 395,2847 3



CSP11101 NoData 12,0775 48,339 20,012 133,0798 11,7019 2,9916 374,2496 34,8415 0



CSP11101 verger 1,055 4,2225 32,0192 48,6292 0,1656 1,2168 1279,6209 70,0341 6

CSP11101 friche jeune 0,4775 1,9111 20,012 22,6136 0,0971 1,018 1319,3717 98,722 12

CSP11101 paturage avec ligneux arbustifs 0,0575 0,2301 8,0048 3,2019 0,0484 1 2260,8696 57,0088 3

CSP11201 NoData 8,825 58,5406 19,9005 149,9171 8,2317 2,7679 418,1303 35,0036 0


CSP11201 verger 0,7975 5,2902 39,801 47,0978 0,3084 1,2748 1115,9875 76,4759 6


CSP11201 plantation agro forestiere d hevea 0,125 0,8292 13,267 9,9502 0,1201 1,56 1920 545 10

CSP11201 friche jeune 0,02 0,1327 6,6335 2,3217 0,02 1,1667 3500 0 12

CSP11201 paturage avec arbres disperses 0,09 0,597 6,6335 7,9602 0,09 1 1333,3333 0 4

CSP11201 friche vielle 0,045 0,2985 6,6335 3,9801 0,045 1 2000 0 13




CSP21301 friche jeune 1,2775 2,126 9,985 25,0458 0,3673 1,8167 1299,4129 114,6239 12

CSP21301 NoData 9,895 16,467 28,2909 76,9679 2,7843 1,4755 584,1334 46,2198 0

CSP21301 verger 13,88 23,0987 39,9401 147,7783 2,0243 1,8574 709,6542 37,479 6


CSP21301 paturage avec ligneux arbustifs 0,08 0,1331 1,6642 1,4145 0,08 1 1500 0 3

CSP21301 paturage avec arbres disperses 0,09 0,1498 1,6642 1,997 0,09 1 1333,3333 0 4


CSP21401 NoData 13,63 22,0675 25,9046 102,5662 9,9918 3,3131 556,8599 41,8676 0

CSP21401 verger 6,1725 9,9935 37,2379 91,7996 0,8032 1,7744 976,9137 38,9296 6




CSP21401 friche jeune 0,3025 0,4898 4,8571 5,6666 0,1374 1,0484 1289,2562 117,9174 12

CSP21401 paturage avec arbres disperses 0,18 0,2914 3,2381 3,8857 0,09 1 1333,3333 315,6739 4

CSP21501 NoData 11,21 21,1849 47,2456 102,7119 3,6894 1,5759 601,2489 40,5474 0




CSP21501 verger 4,7975 9,0664 26,4575 72,0968 1,0344 1,6606 815,0078 36,7238 6

CSP21501 plantation agro forestiere d hevea 0,09 0,1701 1,8898 2,2678 0,09 1 1333,3333 0 10

CSP21501 paturage avec arbres disperses 2,17 4,1009 18,8982 36,0956 0,4936 1,4706 995,3917 50,4516 4




CSP31601 friche jeune 0,665 1,4826 11,1477 16,7215 0,177 1,2206 1263,1579 106,7393 12


CSP31601 verger 8,63 19,2408 46,8201 150,7162 1,0951 1,7885 850,5214 37,2463 6

CSP31601 NoData 11,115 24,7812 35,6725 173,5689 2,1182 2,3966 783,6257 35,3155 0

CSP31601 paturage avec ligneux arbustifs 0,09 0,2007 2,2295 2,6754 0,09 1 1333,3333 0 3


CSP31701 NoData 23,9 31,2899 20,9472 129,4145 14,6964 3,7669 483,682 40,4274 0


CSP31701 verger 9,1575 11,989 43,2036 98,2555 0,6176 1,5831 948,9489 47,0563 6



CSP31701 friche jeune 2,5125 3,2894 17,0196 31,7481 0,3342 1,3068 1046,7662 144,8455 12


CSP31801 NoData 12,3225 24,6524 24,0072 132,5398 9,1127 3,4843 565,632 37,8746 0



CSP31801 verger 6,1775 12,3587 36,0108 100,8302 0,6986 1,5465 866,0461 41,8094 6


CSP31801 friche jeune 2,19 4,3813 20,006 47,0141 1,0035 2,6315 1246,5753 52,3863 12



CTR10101 NoData 13,7825 12,3885 49,4371 108,4021 0,6888 1,6402 983,8563 40,2959 0

CTR10101 paturage avec arbres disperses 16,935 15,2221 31,46 98,4697 3,9244 2,0826 692,6484 43,3152 4

CTR10101 friche vielle 21,985 19,7614 34,1565 134,9183 2,3316 2,0632 712,3038 37,8151 13

CTR10101 friche jeune 2,03 1,8247 8,9886 18,2018 0,4563 1,6898 1157,6355 174,1876 12

CTR10101 paturage propre 56,07 50,3989 16,1794 183,5464 37,7834 5,0987 401,1058 29,3624 1

CTR10101 paturage avec ligneux arbustifs 0,45 0,4045 2,6966 4,3145 0,162 1,0471 1066,6667 148,9943 3


CTR10201 NoData 14,445 12,6811 50,0395 109,7358 0,7278 1,5357 936,6563 40,9856 0



CTR10201 friche jeune 1,1475 1,0074 7,0231 11,3247 0,2048 1,3379 1298,4749 130,7602 12

CTR10201 paturage avec ligneux arbustifs 0,18 0,158 1,7558 2,1069 0,09 1 1333,3333 65,192 3



CTR10301 NoData 52,6975 18,2835 39,5524 114,7194 4,6004 2,092 668,1531 39,8075 0


CTR10301 friche jeune 6,6525 2,3081 15,2659 25,2233 0,2661 1,2812 1137,9181 49,16 12




CTR20401 NoData 116,8975 23,6018 31,6986 129,5907 8,5915 2,7608 591,1161 38,7097 0


CTR20401 friche jeune 2,435 0,4916 3,6342 5,1889 0,247 1,282 1190,9651 98,7413 12


CTR20401 verger 2,7975 0,5648 0,8076 3,503 1,2294 1,6583 650,5809 70,3031 6

CTR20401 plantation d'arbustes fouragers 2,9325 0,5921 1,0095 4,563 1,6761 2,2782 825,2344 64,3434 11

CTR20401 plantation agro forestiere d hevea 0,18 0,0363 0,4038 0,4846 0,09 1 1333,3333 275,0455 10

CTR20501 friche jeune 1,5225 1,8802 18,5242 24,1433 0,1385 1,2271 1385,8785 72,5015 12


CTR20501 NoData 19,3075 23,8438 37,0485 162,7045 7,9659 3,8347 743,7524 35,5537 0




CTR20601 NoData 21,595 24,0559 41,2164 140,4144 4,7979 2,2282 636,2584 37,3542 0





CTR20601 friche jeune 1,08 1,2031 3,3419 12,0307 0,465 1,6241 1000 142,5947 12


CTR30701 NoData 6,265 18,9964 51,5464 137,356 0,7119 1,4935 849,162 59,9757 0




CTR30801 friche jeune 2,8575 7,9652 30,662 64,5296 0,7252 1,6569 923,8845 61,1754 12



CTR30801 NoData 8,5425 23,8118 61,324 166,8293 2,1275 2,1365 801,873 29,6756 0




CTR30901 NoData 3,435 6,0462 19,3619 43,3003 0,6403 1,3339 818,0495 65,193 0

CTR30901 friche jeune 6,265 11,0275 36,9637 84,1364 0,8249 1,5439 842,7773 44,5772 12

CTR30901 verger 2,675 4,7085 33,4433 49,901 0,212 1,2125 1192,5234 57,876 6

CTR30901 plantation agro forestiere d hevea 2,7525 4,8449 36,9637 56,0616 0,2476 1,2184 1195,277 48,7719 10

CTR30901 plantation d'arbustes fouragers 8,9275 15,714 36,9637 134,3014 1,4125 2,2598 926,3512 38,2428 11



METRICS (cover, structure)

54 FARMS

3. LANDSCAPES MAPS PLANT COVER

SOIL COVER CATEGORIES

The 4 indicators of landscape

Composicion 2007

Estructura 2007

Dinamica Composicion 1990-2007

Dinamica estructura 1990-2007

Indicator of Landscape intensificacion

Mixed systems Extensive livestock 20-40 years

Pioneer front < 15 years

Degraded pastures 60 years Forest

Source Oszwald et al., BFT, 2011,

Produccion systems and landscape

12 34 56 7

1.0

3.2

10

32

320

100

Fronts pionniersrécents

AgroForesterie

+ divers

Diversifiépauvres

Lait/diversGr. Surf.

Revenus de la ferme

103 EUROS /an

12 34 56 7

510

15

20

25

30

35

PAYSAGE


Elevage BovinsGr. Surf.

12 34 56 7

0.2

0.4

0.6

0.8

1.0

2 1 34 56 7

0.3

0.4

0.5

0.6

0.7

BIODIVERSITÉ

P < 0.01 P = 0.08

P<0.01

Figure 2 : Variations en fonction des types socio économiques échelonnés suivant les valeurs du facteur 1 de la

figure 2) de (a)- Revenus des fermes (valeurs en 10 3 Euros ; (b)- Indicateur d’usure du paysage; (c)- Biodiversité (indicateur synthétique); (d)-serviescécosystémiques (indicateur synthétique), (d)- Eco efficience: Indicateur Ef voir texte.

P = 0.08

12 34 56 7

0.3

0.4

0.5

0.6

0.7

0.8

0.9 ECO-EFFICIENCE

4

Figure 4 : Variations en fonction des types socio-économiques classéssuivant leurs valeurs du facteur 1 de la figure 2, de (a)- revenus des fermes(en 10 3 €); (b) –Indicateur d’intégritédu paysage; (c)- Biodiversité(indicateur synthétique); (d)-servicesÉcosystémiques (indicateursynthétique); (d)- éco-efficience: indicateur Ef (voir texte).

PAISAJE

Landscape integrity

Pioneer Fronts

Agro Forestry

Extensive Cattle Breeding

4. BIODIVERSITY

Plantes

Oiseaux

Fourmis

Vers de terre

Drosophiles

Saturnidae

> 4103 espèces identified in 270 sampling points Indicator varies between 0.1 y 1.0

Termites

Species Richness

Groupe taxonomique

Colombie Brésil Sp nov

Plantes (strate inf) 555 sp 1302 sp Non renseigné

Plantes (strate moy) 320 799 sp Non renseigné

Plantes (strate sup) 123 sp 305 sp Non renseigné

Oiseaux 150 sp 238 sp Non

Saturniidae 36 sp 60 sp Oui (2)

Sphingidae 33 sp 48 sp Non

Drosophiles 40 sp/msp 69 sp/msp Non précisé

Vers de terre 16 sp/msp 11 sp/msp Oui (20)

Fourmis 39 gn 40 gn Non renseigné

1190 Taxa 2872 Taxa

Biodiversity and landscape intensification 12 34 56 7

1.0

3.2

10

32

320

100

Fronts pionniersrécents

AgroForesterie

+ divers

Diversifiépauvres

Lait/diversGr. Surf.

Revenus de la ferme

103 EUROS /an

12 34 56 7

510

15

20

25

30

35

PAYSAGE


Elevage BovinsGr. Surf.

12 34 56 7

0.2

0.4

0.6

0.8

1.0

2 1 34 56 7

0.3

0.4

0.5

0.6

0.7BIODIVERSITÉ

P < 0.01 P = 0.08

P<0.01

Figure 2 : Variations en fonction des types socio économiques échelonnés suivant les valeurs du facteur 1 de la

figure 2) de (a)- Revenus des fermes (valeurs en 10 3 Euros ; (b)- Indicateur d’usure du paysage; (c)- Biodiversité (indicateur synthétique); (d)-serviescécosystémiques (indicateur synthétique), (d)- Eco efficience: Indicateur Ef voir texte.

P = 0.08

12 34 56 7

0.3

0.4

0.5

0.6

0.7

0.8

0.9 ECO-EFFICIENCE

4

Figure 4 : Variations en fonction des types socio-économiques classéssuivant leurs valeurs du facteur 1 de la figure 2, de (a)- revenus des fermes(en 10 3 €); (b) –Indicateur d’intégritédu paysage; (c)- Biodiversité(indicateur synthétique); (d)-servicesÉcosystémiques (indicateursynthétique); (d)- éco-efficience: indicateur Ef (voir texte).

Intensificacion

Bd

Biodiversity

Front pionnier10 ans

Paysage agroforestier60 ans

Elevage extensif60 ans

LANDSTRUCTURE

LANDUSE

DYN. LAND

STRUCTURE

DYN. LAND

USE

LAND

STRUCTURE

DYN. LANDSTRUCTURE

LAND

STRUCTURE

LANDUSE

DYN. LANDSTRUCTURE

DYN. LAND

USE

EWM

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLmedPLinf

ANTS

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLmedPLinf

ANTS

PLmed

EWM

BIRDS

SPHIN

SATUR

DROSO

PLsup

PLinf

ANTS

SC010

SC1030INFIL

TW050

AW050 FCHIM

SC010

SC1030INFIL

TW050

AW050 FCHIM

SC010

SC1030INFIL

TW050

AW050 FCHIM

PAYSAGES

BIODIVERSITÉ


Viande

LaitC. Annuelles

P. Elev. Extrac.

1 2 4 53

C. Pérennes

C3PRODUCTIONS

Pioneer Fronts 10 years

Agroforestry 60 years

Extensive Cattle breeding 60 years

Specific richness and woody cover

A B C D E F

30

40

50

60

70

Wooded area quality index

Ric

hn

ess in

de

x

* (p = 6.4e-06)

A

A B C D E

30

40

50

60

70

Wooded area dominance index

Ric

hn

ess in

de

x* (p = 4.38e-06 )

B

5. Soil Ecosystem Services

• Climate Regulation

– C in soil and biomass

• Regulation of flooding and erosion

– Water Infiltration

– Water storage

– Useful water

• Primary production

– Chemical fertility

– GISQ indic.

Synthetic indicators (0,1-1,0) Velasquez et al., 2007, Soil Biology and Biochemistry

C storage

A B C D E F G

10

15

20

25

30

35

40

Landuse dynamics classes

SOIL C 0-10 cmMg ha-1

<20 yr/forest >20 yr/agropastoral

A B C D E F G

20

30

40

50

60

70

80

90


So

il ca

rbo

n s

tock 0

-30

cm

(M

g/h

a)

SOIL C 0-30 cmMg ha-1

LANDSCAPE INTENSIFICATION

ABCDEFG

1.0

1.5

2.0

2.5

3.0

3.5

4.0


WATER INFILTRATIONLog mm/h

ABCDEFG0

24

68

10

12


Water Storage (0-50 cm) cm

STORAGE cm

INFILTRATION mm h-1


Hydrological services

LANDSCAPE INTENSIFICATION

Conceptual Model

M MA

MULTI AGENT MODELING

SOCIOECO Lives, formation, housings

Crédits

LANDSCAPES Composition, structure

BIODIVERSITY Plants, Birds, Moths,

Drosophilidae, Earthwors, Ants Soil Macrofauna

ECOSYSTEM SERVICES Soil Fertility, Water Infiltration and storage, C sequestration,

Chemical Fertility

PRODUCTIONS Live stock, Agriculture

Extractivism,

EXCHANGE of KNOWLEDGE

Ef logEp Bd Qs

ECOEFFICIENCY

= * *

LANDSCAPE

RV coefficients of matrix correlations all p < 0.001

The importance of Landscape

SOCIOECO

0.27

BIODIVERSITY

0.43

0.39

BRASIL

PRODU CTION

0.63

ECOSYSTEM

SERVICES

0.44

0.36 0.43

0.44

0.31 0.61

Landscape use intensification and sub indicators of ecoefficiency

ECONOMICAL

EFFICIENCY

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(a)

Land use intensity

Ef

●

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●

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(b)

Land use intensity

Sb

●

●

●

●

●

●

●

●

●

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0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(c)

Land use intensity

Bd

●

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●

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0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(d)

Land use intensity

Es

●●

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●

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●

A

B

C

D

E

F

G

HUMAN DEVELOPMENT

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(a)

Land use intensity

Ef

●

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0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(b)

Land use intensity

Sb

●

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0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(c)

Land use intensity

Bd

●

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0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(d)

Land use intensity

Es

●●

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B

C

D

E

F

G

BIODIVERSITY

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

(a)

Land use intensity

Ef

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ECOSYSTEM SERVICES

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Improve ecoefficiency of deforested landscapes

FARM

Economy (profitable, competitive)

Social (Development, Well being)

Environment (Biodiversity, ESs)

Ef = f (E, S, A)

Ecoefficiency and landscape intensification

• Tipping point in the relationship

• 50% forest

– 20% pristine

– 30% fallows/tree based sytems

Landscape intensification

Eco

efi

cien

cia

Tree cover and ecoefficiency 0 20 40 60 80 100

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Ecoeffic

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% tree cover % fallow

% original forest % tree crops

Restoration is still possible

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ABCDEFG

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Land use intensityE

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BPCBMBBPRCAFCSPCTR

A: Pioneer front, diversified, low income

B: Pioneering front, diversified, average incomewith external inputsC: Diversified with no extra incomes

D: Predominantly dairy production, low income

E: Livestock and perennials in agroforestry systems, high incomes

F: Extensive dairy and livestock production, high income

G: Extensive dairy and livestock production, highest incomes

Pioneer fronts

Extensive degraded livestock

Sylvo pastoral restoration

Small holder Agroforestry

Mixed systems at different stages

Eco efficiencia en diferentes paisajes en Colombia (Caqueta)

Dia de la Tierra, Riohacha, 22 abril 2010

Indicateur eco efficience prenant en compte le nombre de personnes présentes dans l’EA et les parties

effectivement utilisées des exploitations agricoles

Indicateur eco efficience prenant en compte le nombre de personnes présentes dans l’EA et les parties

effectivement utilisées des exploitations agricoles

AGRO

FORESTRY

SYLVO

PASTORAL CONVENTIONAL

ING: 11200 $ 105 Ha 106 $ ha-1 1.8 persons ES 0.54 Bd: 0.51 EF=27,3

ING: 7500 $ 49 Ha 153 $ ha -1

2.2 persons ES 0.53 Bd : 0.51 EF=30,4

ING: 6600 $ 15 Ha 440 ha -1 2.0 persons ES 0.74 Bd : 0.75 EF=50,0

114

Selling the idea: Landscape as a football team Forest

Morichal

Pantano

Rub

Silvio Pastor

Palm

Frutri

Juka Bin

Soybi Rice

Pasto

Tecnical Staff

Reconstruct ecoefficient landscapes in degraded areas of AMAZONIA

Proyecto AMAZONIA 2030

II

SIMULATION MODEL

11

Social Ind. trajectories

Demogrphy

Education

Health

Landscape Composition

Structure

I DIAGNOSTIC

FARM

13

Economico Ingresos

mercados Incentivos

3 Environmental

Ecos. Serv. . Biodiversity

Climate

10

III FARMSCAPE DESIGN

Bank of Technical options

Public

Policies 12

INITIAL FARM

Ecoeficiency = E1 Ecoeficiency = E1 + δ

FINAL FARML

Conclusions

• In Amazonia Business as usual is a deadly scenario

• Tipping point in landscape/ecoefficiency relationship at 50% woody cover (30% fallows + 20% native forest)

• Recovery is (still) possible

• The need to build ecoefficient landscapes to – Sustain production and development – Conserve Biodiversity and Ecosystem servics – Adapt to + mitigate climate change

Muchas Gracias • Youtube Lavelle1948 Amazonia : A Happy Soil

• http://www.youtube.com/watch?v=lwQ0R-iBK_s

• AMAZ_BD: http://www.youtube.com/watch?v=P-IQ6wLGgP8

• Alix et Gaia: http://www.youtube.com/watch?v=sjSsEYq3R4c

http://www.youtube.com/watch?v=lwQ0R-iBK_s




http://www.youtube.com/watch?v=P-IQ6wLGgP8




http://www.youtube.com/watch?v=sjSsEYq3R4c

What does a farm produce??

$

$

FARM

The Amazonian paradoxe

Legislation does not impede deforestation

People who use the resource in a « mining » way are poor

How could we design applicble policies Is payment for ES an option

Tailandia, Para, Brésil Mars 2008

Pacaja, Para, Brésil Mai 2008

Sampling protocole

2 countries

d

1 2 3

3 « sous - fenêtres »

PR / TR MB / SP PC / AF

01 02

03

04

05 06

07

08 09

10

11 12

13

14

15 16

17

N

01

02

03

04

05

d

1 2 3

3 « - »

PR / TR MB / SP PC / AF

01 02

03

04

05 06

07

08 09

10

11 12

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14

15 16

17

N

01

02

03

04

05

3 windows (51 contiguous farms)

13 sub windows

3 farms

5 points

Ecosistemas y servicios ecosistemicoselti.fesprojects.net/2013...

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