Mirjam Pulleman: Biodiversity and climate resilience (presentation from Adaptation session at CCAFS Science Workshop, December 2010)

1. Biodiversity and Climate Resilience
in Agricultural Landscapes
Mirjam Pulleman
agroBIODIVERSITY International Project Office,
DIVERSITAS
Biodiversity and Climate Resilience in
Agricultural Landscapes
1. agroBIODIVERSITY research for sustainable
agricultural landscapes and rural livelihoods
2. Joint meeting CCAFS/DIVERSITAS/CRP6 (26-
28 November 2010, Chiapas)
– Filter and buffer functions provided by
(agro)biodiversity & vulnerability/adaptation to
climate change
– Identification of synergies and potential research
topics for collaboration
1

2. agroBIODIVERSITY
• The challenge for agriculture will be to increase
productivity of agriculture, while addressing risk
and variability
• Such focus should address the critical human
and economic dimensions, and environmental
outputs, e.g. GHG emissions, other ecosystem
services and biodiversity loss.
• Eco-efficiency / ecological intensification =>
addresses synergies and trade-offs among a
host of production, conservation, economic, and
social values at landscape scale (e.g., Groot et
al., 2007). Keating et al. 2010
agroBIODIVERSITY
Who are we? What binds us?
– The drivers of biodiversity conservation in
agricultural landscapes and trade-
offs/synergies with sustainable agricultural
production
– The role of AGBD for sustainability/resilience/
adaptation of agriculture and rural livelihoods,
in different social/ecological domains
– How to engage local stakeholders in
sustainable landscape management?
2

3. agroBIODIVERSITY
• Wild and agricultural biodiversity within the landscape
mosaic interact in affecting ecosystem goods and
services at multiple scales (plot to landscape level)
Synergies (and trade-offs) across multiple scales
Courtesy Claire Kremen
3

4. agroBIODIVERSITY
Agrobiodiversity; Management of local resources in a
global /regional context
A key aim of analysis is to identify enabling policies that can create a greater
space for local innovation response and strengthen local communities
influence at higher scales (Giller et al. 2008).
agroBIODIVERSITY
Planning for future uncertainty – sustainagility
Keep options open – trade-offs in time?
Jackson et al., 2010
4

5. agroBIODIVERSITY
• Ecosystems potentially show nonlinear
responses to land-use intensification that would
open management options with limited
ecological losses but satisfying economic gains
(Dewenter et al 2007)
• Climate change and scarcity of resources can
change/have changed these dynamics
• Need for interdisciplinary studies to quantify
ecological and socioeconomic tradeoffs (in
space and time) under different levels of
agricultural intensification and trajectories
Current Biodiversity-based
dominant trend alternative pathway
High
Natural forest Agroforest
domain
environmental services
Biodiversity &
Adapted from Brussaard et al., 2010
Low external
input agro-
ecosystems
Intensive
agroecosys-
tem domain
Degrading
Degraded, aban- agricultural
doned land landscapes
Low
Low High
Agricultural production
5

6. agroBIODIVERSITY
•Eight research sites, 6 biodiversity hotspots
AGROFOREST FRAGILE, INTESIVE AG
NATURAL DEGRADING
FOREST LANSCAPE
Indonesia
India Mexico
Forest Cover
Brazil California
Burkina Faso Netherlands
Degradation Recovering
agroBIODIVERSITY
- 200-500 km-2
landscapes
positioned along a
biodiversity-production
gradient in a wide range
socio-economic
conditions
- Builds upon local
research teams and
participatory
experimentation with
diversified production
Jackson et al., in prep.
systems/landscapes
6

7. Native forest
Agroforestry
Sun-coffee
Participatory agroforestry
research
Zona da Mata, BR
(de Sousa et al., in prep)
Zona da Mata, BR
Tree species
NFV2
NFV1 (de Sousa et al., in prep)
NFA9
NFA8
AFD1 • Multiple ecosystem services
AFA7
AFA3
AFA6
• Livelihoods / food security
AFA5
AFA2 • Trade-offs
AFA4
AFA1
0.04 0.2 0.36 0.52 0.68 0.84 1
• Adaptation to climate change
Sorensen's Coefficient
Tree families
NFV2
NFV1
NFA9
NFA8
AFA6
AFA4
AFA2
AFA7
AFA5
AFD1
AFA3
AFA1
0.4 0.5 0.6 0.7 0.8 0.9 1
SØorensen's Coefficient
7

8. 40
oC
SC MAX
30
AF MAX
NF MAX Climate
20
SC MIN
change
resilience
AF MIN
10
NF MIN
+3oC
0
Loss: 69
JAN FEB MAR APR MAY JUN JUL AGO SEP OCT NOV DEC MONTH
%
1.0
NF*D1
Cmic
Total N
TOC
Silt
CO2
qMic Nmin
Mg
CEC NF*A1 Al sat
CaK Al
NF*A2 H+Al
pH
AF*D1
P
Sand
Base Sat AF*A2
Soil fertility Also: Coffee productivity
SC*D1 SC*A1
SC*A2 AF*A1 and soil C Economics incl. labour
Clay
qMet
Zona da Mata, BR
-1.0
0-10
cm
(de Sousa et al, in prep)
-1.0 1.0
La Sepultura Reserve and buffer zone,
Chiapas
DRIVERS: IMPACT:
Landscape-level Field-based assessment of
forest cover analysis riparian woody plant
using Landsat data diversity and soil quality
from different yrs
(Jackson et al, in prep)
La Sepultura, MX
8

9. Participatory
modeling and
consensus
building
Multi-agent
modiling
And: Participatory
implementation of fodder trees
for climate change adaptation
and forest conservation
agroBIODIVERSITY
Work in progress: Integration across 8 sites – connect
global and local learning:
 Collection of a minimum common data set from all sites
 Synthesis of results across sites to show agricultural
production-biodiversity relationships, and potential for
resilience/adaptation to (climate) change based on
assets (N, F, S, H, P capital)
 Identifying biodiversity-based adaptation pathways in a
given landscape domain
 Testing of hypotheses in field sites
9

10. Biodiversity and Climate Resilience in
Agricultural Landscapes
1. agroBIODIVERSITY research for sustainable
agricultural landscapes and rural livelihoods
2. Joint meeting CCAFS/DIVERSITAS/CRP6 (26-
28 November 2010, Chiapas)
– Filter and buffer functions provided by
(agro)biodiversity & vulnerability/adaptation to
climate change
– Identification of synergies and potential research
topics for collaboration
26‐28 November 2010
DIVERSITAS (ESSP) CCAFS (CGIAR/ESSP) // CRP7
Agrobiodiversity network Climate change agriculture and
food systems
8-site global comparison
3- focal regions, interest
of consequences of
in broader scope; Linking
agricultural intensification
adaptation, mitigation &
poverty agenda’s
Chiapas site hosts (ECOSUR)
Exploring shared
agenda’s for
research, November
Friday Synergies in site
27 & 28
November networks, Joint
funding Exploring a
26 visit to Forest, Tree, Agroforestry // CRP6 joint
‘learning CIFOR, ICRAF, Bioversity, CIAT
research
landscape’ Sentinel landscapes
agenda
across forest/tree cover
transition, focus on
‘ecosystem services’
10

11. Joint meeting
CCAFS/DIVERSITAS/CRP6
Goals of the project
• Enhance knowledge on the way filter and buffer
functions provided by agrobiodiversity reduce
human vulnerability to climate change across a
wide range of settings
• Support current development efforts to reduce
human vulnerability through identification of
current ‘best practice’ and promote the use of
such approaches
Variability of Variability of Human vulnerability to
climate water flows floods & droughts
Vulnerability
Resiliency
Tolerated range
range
range
Landscape
filter & buffer
functions
Currently Currently Focus of ‘adapta-
increasing decreasing tion stragegies’?
Preventable increase
in exposure
M. Van Noordwijk
11

12. Adaptation
options
M. Van Noordwijk
Social stressors originating within
Persistence and among community/ies
Shielding Economic stressors
Climatic stressors: networks due to market
means, variability fluctuations & policy
and change Market shifts
Landscape access &
buffers & insurance
filters Pover
M. Van Noordwijk -ty?
Resource
Innovation
accessibility
support
Access to under- Access to new
utilized resources for markets, satisfying new
innovative use types of demand
Change M. Van Noordwijk
12

13. Multidimensional Buffer-Filters create “Shields” that can differ among local groups
with different coping/adapting conditions.
Physical/Financial
Wealth
Before BUFFER-FILTERING After BUFFER-FILTERING
Land Tenure
Time series of percieved
Eco-Tecnology Norms and Laws
Climate Variable “A”
Big Coffee producers
low
Time series of have a shield based on
m
Climate Variable “A”
Wealth and Market institutions
diu
me
Tree Cover
h
hig
Local Cooperative
Institutions
Physical/Financial
Wealth Small Coffee producers
have a shield based on
high medium low
local cooperation and
Time series of agroforestry technology
Climate Variable “A”
Land Tenure Time series of percieved
Norms and Laws Climate Variable “A”
Eco-Tecnology
L. Garcia Barrios
San Cristóbal Meeting Nov 26-28
Local Cooperative Tree Cover
Institutions
26 November: Field trip
13

14. Where would you like
to see more trees?
27 Nov: Conceptual frameworks,
hypotheses and methods
28 Nov: Modalities for cooperation,
sites and research priorities
14

15. Boundary research / adaptive research
A.Communicate
Current understanding of buffers ‘ready to use’ Global
& filters as intermediate between science governance
external drivers (incl. climate, of the climate
social, economic) and local change
livelihood options & vulnerability challenge
B. Facilitate multi-
C.Priority issues
scale mitigadap-
for new science
tation approaches
Site level multistakeholder complexity of
‘driving forces’ and ‘intervention points’ 
relevance of ‘negotiation support’
A. Science ready to be communicated
• Conserving and utilizing AB at different scales is necessary for
sustaining livelihoods of poor farmers by increasing the flow of
provisioning services and the stability of such flows, hence leading to
food security, especially in the face of enviro/economic stressors.
• Institutional issues related to secure access/control of natural capital
(incl land tenure) are key for climate change mitigation and adaptation
through the use of AB. Ecological buffers have the potential to benefit
both adaptation and mitigation.
• Strong social capital is a key social filter/buffer by poor farmer
communities to enhance the capacity of adaptation through improved
coping strategies (& change beyond coping)
• Any measure to be taken has to be accompanied by consideration of
potential social, economic and environmental trade-offs in a multi-
stakeholder landscape and global linkages between them (e.g. in the
case of biofuel production on land suitable for food production).
15

16. C. Priority research
• Forecasting
– How can forecast models be made more relevant to the
society in specific local contexts, by integrating societal
needs, critical drivers, thresholds, and emerging properties
at the appropriate temporal and spatial scales?
• Observing
– How do people’s situation, knowledge and behavior affect
ecosystems and their services and vice versa, in a context of
adaptation?
• Confining
– How will the spatial and temporal configuration of ecological
and social buffers and filters increase the sustainability and
efficiency of adaptation policies and projects?
• Responding
– What are the governance and institutional mechanisms for
enhancing buffers and filters, depending on the context, and
what their cost, benefit and distributional effects?
• Innovating
– Where is innovation needed for enhancing buffers and filters
and how can these buffers and filters act as incentives for
further innovation?
16

17. Innovating
Forecasting Observing
Research sites
• Represent different climate risks (rainfall variability, drought,
storms, flooding)
• Agroecological conditions (regions)
• Different institutional settings (countries)
• Social norms (communities)
• Endowment (farm)
Analogue sites? =>
does it work for landscapes?
17

18. Acknowledgements
• Meine van Noordwijk and all participants
• The agroBIODIVERSITY network
Louise Jackson, Lijbert Brussaard, Kamal Bawa, Irene Cardoso, Luis Garcia
Barrios, George Brown,Elisée Ouedraogo, Unai Pascual, Peter de Ruiter,
Teja Tscharntke, Meine van Noordwijk
Thank you!
agroBIODIVERSITY site – the Netherlands – intensive ag
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