Exploring causes, risks, and consequences for ecosystem services

of tipping points in Latin American forests - the role of biodiversity

Jana Verboom; Bart Kruijt; Marta Perez Soba; Hans Baveco ; Michiel Van Eupen; Marielos Pena Claros - Alterra and Wageningen University, Wageningen UR, The Netherlands Celso Von Randow - Instituto Nacional de Pesquisas Espaciais, Ccst, Sao Jose dos Campos, SP, Brazil; Terry Parr; Laurence Jones; Dario Masante; Beth Purse; Chris Huntingford; Eleanor Blyth; Iwona Cisowska - NERC Centre for Ecology & Hydrology, United Kingdom Kirsten Thonicke; Boris Sakschewski; Alice Boit - Potsdam Institute for Climate Impact Research (PIK), Earth system analysis, Potsdam, Germany Patty Balvanera, Sandra Quijas - Instituto de Investigaciones en Ecosistemas, Universidad Nacional Autónoma de México, Mexico

Euridice Leyequien Abarca - Centro de Investigación Científica de Yucatán, Mérida, Mexico Lucieta Martorano - Embrapa, Belem, Brazil

Marisol Toledo - Instituto Boliviano de Investigación Forestal, Santa Cruz de la Sierra, Bolivia

Role Of Biodiversity In climate change

mitigatioN

‘Raising the alert on critical transitions

in the Amazon’

Vulnerability of the Amazon ecosystem services to climate change and deforestation

DRIVERS GLOBAL/NATIONAL/LOCAL Demographic changes Economic development Policy Technologies

DISTURBANCE REGIME Land use change Climate Change

BIODIVERSITY

ECOSYSTEM STRUCTURE

CLIMATE CHANGE MITIGATION

Carbon sequestration Change in carbon stocks

+ OTHER ECOSYSTEM SERVICES

Provision Regulation Support Cultural

HUMAN OUTCOMES Livelihoods Income Human health

SOCIETAL BEHAVIOUR

New policy options and incentives Governance and institutions Management options

ECOLOGICAL SYSTEM

ECOSYSTEM SERVICES

SOCIAL-ECONOMIC SYSTEM

The ROBIN framework

Climate change: Warming Drying Extreme events

Land use change: Deforestation Logging Land use intensification Overgrazing

Degraded state: low biomass, low biodiversity, low water cycling, low carbon content

Pristine State: high biomass, high biodiversity, high water cycling, high carbon content

CLIMATE CHANGE MITIGATION

Carbon sequestration Change in carbon stocks

+ OTHER ECOSYSTEM SERVICES

Provision Regulation Support Cultural

HUMAN OUTCOMES Livelihoods Income Human health

Possible pathway of degradation: a complex system

caught in a negative spiral due to feedback loops

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Degraded state: low biomass, low biodiversity, low water cycling, low carbon content

Pristine State: high biomass, high biodiversity, high water cycling, high carbon content

Species extinction, biodiversity loss

Fire hazard

Erosion

Reduced evapotranspiration

Degradation of the forest

Climate change: Warming Drying Extreme events

Land use change: Deforestation Logging LU intensification Overgrazing

Feedback!

Tree cover – fire & precipitation feedbacks

ROBIN example 1: Future changes in functional diversity and tree density

as predicted by LPJmL-FIT (a DGVM, research by Potsdam Institute for

Climate Impact Research)

Functional diversity in 2100

Driven by HadGEM2-ES RCP8.5 (no land use change, no feedback)

Tree density difference 2000 vs. 2100

Sakschewski et al. (2015) Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model. Global change biology (21) pp. 2711–2725.

Functional diversity in 2000

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Driven by RCP2.6, 8.5 and A1B (no land use change, no tree mortality, no fire)

AMAZALERT example 1: Future changes in amazon forest predicted by HadCM3C model,

conclusion is that the probability of dieback is very low

ROBIN example 2: Future changes in land use as predicted by CLUE(a land use change simulation model developed by Alterra/Wageningen University)

No climate change Only land use change, no feedbacks

Staal, A., Dekker, S. C., Hirota, M., & van Nes, E. H. (2015). Synergistic

effects of drought and deforestation on the resilience of the south-

eastern Amazon rainforest. Ecological Complexity, 22, 65-75.

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Simple model with climate change (precipitation reduction) and land use change:

combined effect is much larger then effect of precipitation reduction or deforestation alone

Intensity class

Description CLUE land use classes

1 Natural Forest, shrubland, grassland, sparse vegetation, bare or desert, flooded/wetland forest

2 Low intensity Grazed shrubland, grazed sparse vegetation

3 Moderate intensity Grazed grassland, Abandoned agricultural land

4 High intensity Cropland food perennial, cropland energy

5 Very high intensity Cropland food feed fibre, Urban

0 Not considered Water, wetland, ice & snow

ROBIN example 3: Provisioning of ES and correlations with land use intensity. Services are normalized between zero and one for ease of comparison.

No climate change Only land use, correlative study

Pro

visi

on

ing

of

ES

• Green = Good jaguar habitat

• Orange = High Human

Development Index

• Blue = Good for both

Managing land use for win-wins Identifying the conditions which support maximum co-benefits

Take home messages

Feedback loops can cause cascading effects where drying, forest degradation, biodiversity loss and fire hazard reinforce each other in a downward spiral

Deforestation and climate change together are a deadly cocktail for tropical forest degradation and could cause tipping points (e.g. Amazon dieback)

Therefore, the resilience of tropical forests depends on their conservation - It’s easier to protect the forest than it is to manage the climate

Early warning signals may or may not occur, e.g. increasing return time (to closed canopy) after logging

Time lags between deterioration of conditions and actual large scale ecosystem response buy us time to undertake adaptation/mitigation measures

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