DAPA on World climate teach-in day

The implications of climate change on agriculture and small-farmers livelihoods

A. Eitzinger, P. Laderach, A. Jarvis, J.RamirezCIAT - (International Center of Tropical Agriculture)

Presentation in the context of the „World Climate Teach-In Day“

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

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

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

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, …

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

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

Suitability of crops: MaxEnt principleExample: Coffea arabica in Nicaragua

Input: Crop evidence (5.000 GPS points)19 bioclimatic variables ofcurrent (worldclim) & future climate (18 GCM)

Output:Crop suitability (%)

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

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

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…

Example: department of GuatemalaSuitability change of 14 mayor cropsby the year 2050

• Most crops are loosingsuitability between 20-40%

• Few are gaining

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

Data collection by surveys

• Questions based on indicators ofThe Five Capitals Model of sustainable development– natural– human– social– financial– manufacture

econometricmodels

• Current and future crop Suitability

• Socio-economic indicators• Economtetric models• System Vulnerability

Methodology

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

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.

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?

CIAT - DAPA Blog on climate changehttp://gisweb.ciat.cgiar.org/

dapablogs/ 

What can we do?

• investigate• share• compare• discuss

…. existing information on climate-change impacts on agriculture

THANK YOU VERY MUCH

DAPA – “Decision and Policy Analysis” Program of CIATP. Laderach, A. Eitzinger, J.Ramirez, A. Jarvis