Presentation on theme: "Aslihan Arslan (Co-authors: Nancy McCarthy, Leslie Lipper, Solomon Asfaw, Andrea Cattaneo and Misael Kokwe) 1 st Africa Congress on Conservation Agriculture."— Presentation transcript:
Aslihan Arslan (Co-authors: Nancy McCarthy, Leslie Lipper, Solomon Asfaw, Andrea Cattaneo and Misael Kokwe) 1 st Africa Congress on Conservation Agriculture 19.03.2014 Lusaka, Zambia Food security and adaptation in the context of potential CSA practices in Zambia
CSA & CA Background Data sources Climate variables Descriptive stats Results Conclusions Outline
FAO CSA 2010 definition: Agriculture that sustainably increases productivity, resilience (adaptation), reduces/removes GHGs (mitigation), and enhances achievements of national food security and development goals. Climate Smart Agriculture
CSA: is an approach to achieve agricultural development under climate change CA: has the potential to contribute to CSA pillars different impacts in different locations & experimental vs. farmer plots barriers to adoption (e.g. opp cost of residue, time delay) needs to be studied under farmer conditions & climate change lens CSA = CA?
Questions Addressed 1.What are the impacts of CSA practices on maize yields per hectare in Zambia? 2.What are the impacts of CSA practices on the probability of very low yields and on the yield shortfall? Practices Studied: 1.Minimum Soil Disturbance (MSD) 2.Crop Rotation (CR) 3.Legume Intercropping (LEGINT) 4.Inorganic Fertilizer Use (INOF) 5.Improved Maize Seeds (IMPS) CSA??
RILS 2004 and 2008: supplemental surveys (CSO/FSRP) to the annual post-harvest surveys (PHS) – Both nationally representative – Around 4,000 households interviewed in both years – 4,138 & 4,354 maize plots in 1 st and 2 nd rounds – Econometric analyses of productivity and probability of low production controlling for a large set of relevant socio-economic, climate and agro-ecological variables Data Sources 1
Rainfall (1983-2012): Dekadal (10 days) rainfall data from Africa Rainfall Climatology v2 (ARC2) of the National Oceanic and Atmospheric Administration’s Climate Prediction Center (NOAA- CPC) Temperature (1989-2010): Dekadal avg, min & max temperatures of the European Centre for Medium-Range Weather Forecasts (ECMWF) Soil: Soil nutrient availability and soil pH levels from the Harmonized World Soil Database (HWSD) Data Sources 2
Rainfall: 1.Growing Season Total (and its square) 2.Onset of the rainy season: 2 dekads of >=50mm rainfall after October 1. 3.Dry spells: # dekads with <20mm rain during germination&ripening 4.False onset: 1 dekad with <20mm rain after the onset Temperature: 1.Growing season average 2.Growing season max 3.Indicator if Tmax=28 degrees References: Tadross et al. 2009. “Growing-season rainfall and scenarios of future change in southeast Africa: implications for cultivating maize. “ Climate Research 40: 147-161. Thornton P., Cramer L. (eds.) 2012. “Impacts of climate change on the agricultural and aquatic systems and natural resources within the CGIAR’s mandate.” CCAFS Working Paper 23. Climate Variables
Econometric Analyses The methodology we use… Avoids confounding factors that affect average yield comparisons (e.g. farmer characteristics, plot characteristics, labor availability, other input use) Helps us identify the average impact of a practice on yields and probability of very low production Interaction terms between climate variables and practices help us identify how the average impacts vary with climatic conditions
Conclusions- yield effects Climatic shock variables significantly change the impacts of practices Rainfall variability drives yield effects: In high variability areas… Crop rotation has positive effects Inorganic fertilizer & hybrids not effective Legume intercropping has robust yield impacts No significant impact of minimum soil disturbance on yield outcomes Timely fertilizer delivery most important
Broader implications Data used are from years with limited rainfall stress Our analysis shows that some climate related variables determine which practices will yield best results Taking climate variables into consideration in developing strategies to support agricultural productivity increases is essential. Our results suggest SLM/CA practices could play an important role in responding to CC.
Further EPIC Work Similar analyses on the impacts of sustainable land management practices on yields, incomes and food security in Tanzania, Malawi, Uganda, Niger, Nigeria, Ethiopia with detailed climate data Analyses of climatic shocks and welfare in these countries Work with ministries of agriculture in Malawi & Zambia to design CSA policies Support to MS and PhD students to work on CSA Investment proposals for CSA (potentially targeting GCF/GEF for funding)