This document discusses the implications of climate change on agriculture and small farmers' livelihoods. Crop prediction models are used to estimate the impact of climate change on the suitability of various crops. Results are then translated to analyze the effects on livelihoods using socioeconomic indicators and econometric models. Participatory workshops are recommended to identify best practices and adaptation strategies. While some crops may lose suitability, climate change also brings new opportunities. Adaptation requires site-specific management and preparing for change.

1. The implications of climate change on agriculture and small-farmers livelihoods A. Eitzinger, P. Laderach, A. Jarvis, J.Ramirez CIAT - (International Center of Tropical Agriculture) Presentation in the context of the „World Climate Teach-In Day“

2. OUTLINE Climate change: demanding information for agriculture Estimate the impact using crop prediction models Translate results on livelihoods Upstream supply chain adaptation by participation Conclusions Some questions

3. Climate change: demanding information for agriculture Agriculture is a niche industry - high resolution of IPCC prediction models are needed; Downscaling techniques for 1 - 5 km resolution Climate baseline; www.worldclim.org database (Hijmans et al, 2005). Timeseries of future climate data; monthly data until 2030 (2050) a relevant for making decisions now Certainty of prediction; Measurement of agreement between models Biologically meaningful variables for crop caracterization Modelling geographic distribution; crop-niche modeling

4. Climate baseline WorldClim Data from mayor climate db (more than 47.000) SRTM elevation database as input Interpolated by using thin plate smoothing splines 21 „global climate models“ GCMs based on atmospheric science, chemistry, physics, biology Run from the past through to the present and into the future Use different scenarios for emissions Downscaled by CIAT to 1 km resolution

5. Bioclimatic variables 19 variables derived from monthly temperature and rainfall Represent annual trends Seasonality and extreme or limiting environmental factors Examples: Annual mean temperature, Annual Precipitation, Maximum temperature of warmest month, Precipitation of Driest Month, Mean Temperature of Driest Quarter, Precipitation of Wettest Quarter, …

6. Generation of future climate Current climate from worldclim (1km resolution) Prec, temp min/mean/max, 19 bioclims Future climate Calculate anomaly (future – current) Downscale (spline interpolation) Add to current climate (worldclim) Calculate 19 bioclimatic variables for future climate Current climate + Climate-Change = Future climate

7. Estimate the impact using crop prediction models EcoCrop - developed by the FAO(http://ecocrop.fao.org/ecocrop/srv/en/home) MaxEnt - Maximum Entropy modelling of species geographic distributionhttp://www.cs.princeton.edu/~schapire/maxent/ CaNaSTA – Crop Niche Selection for Tropical Agriculture http://csusap.csu.edu.au/~robrien/canasta/index.htm AquaCrop - Crop Water Productivity Modelhttp://www.fao.org/nr/water/aquacrop.html

8. Suitability of crops: MaxEnt principle Example: Coffea arabica in Nicaragua Input: Crop evidence (5.000 GPS points) 19 bioclimatic variables of current (worldclim) & future climate (18 GCM) Output: Crop suitability (%)

9. Relation between crop-suitability and altitude for current climates, and predicted for 2050

10. Importance of different climatic drivers (of 19 bioclims)by stepwise regression

11. Crop prediction models: Suitability of crops: Ecocrop model Evaluates on monthly basis if there are adequate climatic conditions within a growing season for temperature and precipitation… … and calculates the climatic suitability of the resulting interaction between rainfall and temperature…

12. Example: department of Guatemala Suitability change of 14 mayor crops by the year 2050 Most crops are loosingsuitability between 20-40% Few are gaining

13. Translate results on livelihoods Impact on production, pest and desease of crops in supply chain Definition Systemvulnerability to climate change Exposition of system Sensibility of system on climate Capacity to adapt Searching for socio-economic indicators depending on climate-change by participatory analysis (Focus groups) Use identified indicators for socio-econometric models to transalte results to livelihoods

14. Data collection by surveys Questions based on indicators ofThe Five Capitals Model of sustainable development natural human social financial manufacture

15. Methodology Current and future crop Suitability Socio-economic indicators Economtetric models System Vulnerability econometric models

16. Upstream supply chain adaptation by participation Workshops with case-studies Include local expert-knowledge Sharing experience Best practise examples and adaptation strategies Identify crop/production alternatives

17. Conclusions changes in crop suitability a site-specific because of its own very specific environmental conditions. Solution is site-specific management Climate change will bring not only bad news but also a lot of new potential. The winners will be those who are prepared for change and know how to adapt.

18. Some guiding questions Where will crop grow in the future? Where will crop not grow any more? Where can crop still grow with adapted mgt? What are crop prediction models? What are the decisive climate factors to manage? Which livelihoods are most affected? How to translate to livelihoods? How can we design value-chain up-streaming adaptation strategies? What means participate analysis on climate change?

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22. discuss…. existing information on climate-change impacts on agriculture CIAT - DAPA Blog on climate change http://gisweb.ciat.cgiar.org/dapablogs/

23. THANK YOU VERY MUCH DAPA – “Decision and Policy Analysis” Program of CIAT P. Laderach, A. Eitzinger, J.Ramirez, A. Jarvis