. ICRISAT s strategy for climate change adaptation in the SAT: ESA as a case study (1) Background - Current and future climate-induced risk in the SAT (2) Against this background, our evolving interaction with partners on climate risk. (i) Resulting in collaborative projects and. (ii).. an Operational Research Strategy (2008-2015) (iii) Some tools we use (iv) Testing a Hypothesis of Hope using APSIM
Current and future climate risks in the SAT Current Climate Risks - Rainfed agriculture 90% of production of staples 70 60 Kenya Tanzania - Variable rainfall and production uncertainty - Farmers vulnerable to current climatic shocks C o e ffic ie n t o f v a ria tio n (% ) 50 40 30 20 10 Malawi Mozambique Zambia Botswana - They are risk-averse and unwilling to invest 0 0 500 1000 1500 2000 2500 Rainfall (mm) - Rain-fed agriculture in SAT is stagnating
Current and future climate risks in the SAT Future trends Increase in extreme events - agriculture more risk prone Analyses of historical data confirm increased temperature, but changes in rainfall patterns still hard to detect Nature, rate and extent of change still uncertain. Region Summary output from 21 General Circulation Models (IPCC 2007) Annual Temp. Response by end of 21 st century ( C) Annual Precipitation Response by end of 21 st century (%) Min. 25% 50% 75% Max. Min. 25% 50% 75% Max. E. Africa 1.8 2.5 3.2 3.4 4.3-3 2 7 11 25 S. Africa 1.9 2.9 3.4 3.7 4.8-12 -9-4 2 6
2004-2008: In depth interactions with partners 2004/05 - A NEPAD-endorsed consortium for SSA of 16 Nat., Reg. and International organizations 2007 - The Climate Change Challenge Programme (now approved) - 35 th Anniversary Symposium - Climate-proofing innovation 2007/08 - Co-edited special edition of AGEE (ICRAF ICRISAT) 2008 - ICRISAT web page on climate change adaptation. http://www.icrisat.org/gt-aes/adaption.htm Two important outcomes of this series of dialogue.
First important outcome:- 11 climate risk management projects developed on Africa and Asia 7 serve the region of Eastern and Southern Africa. We are learning lessons from these projects
Some lessons learned in ESA: (a) Climate- driven tools are useful : Quantifying climate-induced risk Supporting farmers decisions Often historical daily data is essential (b) Partnerships with NMS are vital: Capacity building Climate data access (c) Much historical data available Example of Machakos, Kitui, Mwingi and Makueni Districts in Kenya.
Second important outcome, an Operational Research Strategy (ORS):- Adaptations to climate change in the SAT Purpose: To enable investors in rain-fed farming to better understand and manage both the risks posed and opportunities offered by current rainfall variability and future climate change. ORS has a two - pronged strategy: (i) Short to medium term (ii) Medium to longer term
(i) Short to medium - term strategy: Helping farmers and stakeholders to cope better with current rainfall variability as a prerequisite to adapting to future climate change The focus of current suite of 7 projects in ESA with common elements of:- Climate driven tools for quantifying risk of current and innovative farming practices Outputs support medium term strategic and short term tactical planning. Building capacity of partners to use tools and the outputs
(ii) Medium to long - term strategy: Adapting and managing our crops to grow in a warmer world Likely Challenges: Higher temperatures Greater incidence of moisture extremes Distribution of pests and diseases Migration of our mandate crops Assets: Evolutionary advantage of our crops Tools available to assess climate risk
Examples of two important tools:- (1) Crop Growth Simulation Models (APSIM and DSSAT.) Driven by long-term daily weather data (precip; max/min temp, radiation) Calibrated for our mandate crops (sorghum, millet, groundnut, pigeon pea and chickpea) Can simulate contrasting environmental, management and genotype options Can quantify current climate-induced risk of a broad range of interventions An example
An APSIM example from Zimbabwe. Fertilizer use and risk: In ve st me n t Re tu rns o n N- ap pl icat io n to Maiz e - Masv ingo, Zimbabwe 100% 1 bag A N/ha 80% recomm ended 60% 40% 20% 0% - 10.0-5.0 0.0 5.0 10. 0 15.0 Z$ retu rn /Z$ in vested Nitrogen recommended on Maize (52kg N /ha) but not adopted. Why? Too expensive & thought too risky. We asked how much could farmers afford? The answer was about 17kg N /ha. Risk and returns analyses by APSIM using 47 years of daily historical climate data. Simulated Maize Yield, Masvingo, Zimbabwe Grain yield (kg/ha) 4000 3500 3000 2500 2000 1500 1000 500 0 1952 1962 1972 1982 1992 N0 n17 N52 and expressed in terms of probability of success? %Chance o f E xceedin g
An APSIM example from Zimbabwe Fertilizer use and risk: The probability of success IMPACT. Extension Services and Fertilizer Traders recently successfully evaluated nitrogen micro-dosing with 200,000 farmers in Zimbabwe. Perception of risk has changed. WHY? The first time a quantified estimate of climate risk had been provided. It allowed them to make more informed and objective decisions about fertilizer.
APSIM can also be used to look at the impacts of climate change scenarios: For example:- disaggregated impacts can be assessed 50 years historical daily data CO 2 = 350 700ppm T O C = 3 O C R = - 10% Pro bab ility o f Exceed ence Figure: Disaggregated impacts of CC on groundnut production at Bulawayo 1 Groundnut Baseline 0.9 CO2_effect 0.8 Rain_effect 0.7 Temp_effect 0.6 CC_effect 0.5 0.4 0.3 0.2 0.1 0 0 1000 2000 3000 4000 5000 Yield (kg ha -1 )
Scenario. 47 years of data from Katumani, Kenya, Looking at impact of climate change (CO 2 from 350 700ppm, temperature increase of 3 O C rainfall increase of 10%). Impact on growth and yield of Pigeonpea Table: Mean model output across 47 seasons Climate Scenario. Current Current CO 2 Current CO 2 T O C Em to Flw (d) 167 167 131 Flw. To Mat.(d) 86 86 54 Yield (kg/ha) 1096 1123 673 % chance of exceeding. 100 90 80 70 60 50 40 30 20 10 Figure 4a. Probability distribution of Pigeon Pea grain yield (kg/ha) at Katumani Control ControlCO2 ControlCO2Temp ControlCO2tempRF Current CO 2 T O C R 131 54 761 0 0 500 1000 1500 2000 2500 Yield (kg/ha)
Another important tool (2) CLIMEX. Based on long-term weather records Analogue locations (Makindu currently has climate of Katumani under CC scenario) Distribution and abundance of pests and diseases under CC Crop variety deployment under current and future climate scenarios.
Adapting and managing our crops to grow in a warmer world Testing a Hypothesis of Hope Yield Gap 1 can be mitigated though improved crop and NRM Yield Gap 2 can be mitigated through crop adaptation to CC Average Crop Yields Low input Practices Current Climate Yield Gap 1 Current Climate Yield Gap Low input Practices Climate Change Yield Gap 2 Improved Practices Climate Change Improved practices Adapted germplasm Climate change Management and Climate Scenarios Improved practices Improved germplasm Current climate
Variable Low input Imp. practice Low input Imp. practice Imp. input ad. variety Current climate Row sp.(m) 1.2 0.75 1.2 0.75 0.75 ToP Late Early Current climate 3 O C Late Early Early Maturity (days) 156 Chalimbana 121 156 121 138 (=119 under CC) Average Crop Yields Groundnut yield (kg/ha) simulations (APSIM) at Kasungu, Malawi. 1927-1999 1400 Low input Practices Current Climate Yield Gap 1 1262 Low input Practices Climate Change Yield Gap 2 1788 Improved Practices Climate Change 2280 Improved practices Adapted germplasm Climate change 2525 Improved practices Improved germplasm Current climate Management and Climate Scenarios
Thanks for listening Time for any questions!
Managing Uncertainty: Innovation Systems for Coping with Climate Variability and Change Summary Points. ICRISAT The first ASARECA CGS-Stream C Project with funds from the African Development Bank for a 3-year period. ($ 575,000) It brings together 2 NARS (Uganda and Sudan), 4 CGIAR Centres (ICRISAT, ILRI, ICRAF and CIAT) and 1 ARI (Reading University, UK) Inception workshop held one year ago in Kenya The project purpose is:- Coping with both risks and opportunities associated with climate variability and change in ECA enhanced through appropriate strategies and institutional innovation.
Managing Uncertainty: Innovation Systems for Coping with Climate Variability and Change. The project will achieve its Purpose through 3 linked results. Result 1. Knowledge will be synthesized and disseminated to agricultural and meteorological researchers and planners to help them make optimal choices with respect to direct and indirect impacts of climate variability and change in ECA (Led by ILRI) Result 2. An innovation system will be established, through learning alliances and information exchange, to assist NMS and NARS to jointly mainstream climate risk assessment and management into their agendas. (Led by Reading University) Result 3. Tested and proven strategies and tools that address priority NPP concerns and provide an enhanced understanding of climate induced risk will be demonstrated and disseminated through Proof of Concept studies in ECA. (Led by ICRAF and ICRISAT) Underway in Uganda, Rwanda, Sudan and Kenya.