Pulleman - Biodiversity and climate resilience


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

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Pulleman - Biodiversity and climate resilience

  1. 1. Biodiversity and Climate Resilience in Agricultural Landscapes Mirjam Pulleman agroBIODIVERSITY International Project Office, DIVERSITAS Biodiversity and Climate Resilience in Agricultural Landscapes1. agroBIODIVERSITY research for sustainable agricultural landscapes and rural livelihoods2. 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. 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 agroBIODIVERSITYWho 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. 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. 4. agroBIODIVERSITY Agrobiodiversity; Management of local resources in a global /regional contextA 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. 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 HighNatural forest Agroforest domain environmental services Biodiversity & Adapted from Brussaard et al., 2010 Low external input agro- ecosystems Intensive agroecosys- tem domain DegradingDegraded, aban- agriculturaldoned land landscapes Low Low High Agricultural production 5
  6. 6. agroBIODIVERSITY•Eight research sites, 6 biodiversity hotspots AGROFOREST FRAGILE,  INTESIVE AG NATURAL  DEGRADING  FOREST LANSCAPE Indonesia India MexicoForest Cover Brazil California Burkina Faso Netherlands Degradation Recovering agroBIODIVERSITY- 200-500 km-2landscapespositioned along abiodiversity-productiongradient in a wide rangesocio-economicconditions- Builds upon localresearch teams andparticipatoryexperimentation withdiversified production Jackson et al., in prep.systems/landscapes 6
  7. 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 AFA10.04 0.2 0.36 0.52 0.68 0.84 1 • Adaptation to climate change Sorensens Coefficient Tree families NFV2 NFV1 NFA9 NFA8 AFA6 AFA4 AFA2 AFA7 AFA5 AFD1 AFA3 AFA10.4 0.5 0.6 0.7 0.8 0.9 1 SØorensens Coefficient 7
  8. 8. 40oC 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. 9. Participatorymodeling andconsensusbuildingMulti-agentmodiling 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. 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 2010DIVERSITAS (ESSP) CCAFS (CGIAR/ESSP) // CRP7Agrobiodiversity 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’sChiapas 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. 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 approachesVariability of Variability of Human vulnerability toclimate water flows floods & droughts Vulnerability Resiliency Tolerated range range range Landscape filter & buffer functionsCurrently Currently Focus of ‘adapta-increasing decreasing tion stragegies’? Preventable increase in exposure M. Van Noordwijk 11
  12. 12. Adaptation options M. Van Noordwijk Social stressors originating withinPersistence 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 PoverM. Van Noordwijk -ty? Resource  Innovation  accessibility support Access to under- Access to new utilized resources for markets, satisfying new innovative use types of demandChange M. Van Noordwijk 12
  13. 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 lowTime series of have a shield based on mClimate 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. 14. Where would you like  to see more trees? 27 Nov: Conceptual frameworks, hypotheses and methods28 Nov: Modalities for cooperation, sites and research priorities 14
  15. 15. Boundary research / adaptive research A.CommunicateCurrent understanding of buffers ‘ready to use’ Global& filters as intermediate between science governanceexternal drivers (incl. climate, of the climatesocial, economic) and local changelivelihood 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. 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. 17. InnovatingForecasting 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. 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 18