Dataset Information

Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

ABSTRACT: In this study, we assessed the possible impacts of climate variability and change on growth and performance of maize using multi-climate, multi-crop model approaches built on Agricultural Model Intercomparison and Improvement Project (AgMIP) protocols in five different agro-ecological zones (AEZs) of Embu County in Kenya and under different management systems. Adaptation strategies were developed that are locally relevant by identifying a set of technologies that help to offset potential impacts of climate change on maize yields. Impacts and adaptation options were evaluated using projections by 20 Coupled Model Intercomparison Project-Phase 5 (CMIP5) climate models under two representative concentration pathways (RCPs) 4.5 and 8.5. Two widely used crop simulation models, Agricultural Production Systems Simulator (APSIM) and Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate the potential impacts of climate change on maize. Results showed that 20 CMIP5 models are consistent in their projections of increased surface temperatures with different magnitude. Projections by HadGEM2-CC, HadGEM2-ES, and MIROC-ESM tend to be higher than the rest of 17 CMIP5 climate models under both emission scenarios. The projected increase in minimum temperature (Tmin) which ranged between 2.7 and 5.8°C is higher than the increase in maximum temperature (Tmax) that varied between 2.2 and 4.8°C by end century under RCP 8.5. Future projections in rainfall are less certain with high variability projections by GFDL-ESM2G, MIROC5, and NorESM1-M suggest 8 to 25% decline in rainfall, while CanESM2, IPSL-CM5A-MR and BNU-ESM suggested more than 85% increase in rainfall under RCP 8.5 by end of 21st century. Impacts of current and future climatic conditions on maize yields varied depending on the AEZs, soil type, crop management and climate change scenario. Impacts are largely negative in the low potential AEZs such as Lower Midlands (LM4 and LM5) compared with the high potential AEZs Upper Midlands (UM2 and UM3). However, impacts of climate change are largely positive across all AEZs and management conditions when CO2 fertilization is included. Using the differential impacts of climate change, a strategy to adapt maize cultivation to climate change in all the five AEZs was identified by consolidating those practices that contributed to increased yields under climate change. We consider this approach as more appropriate to identify operational adaptation strategies using readily available technologies that contribute positively under both current and future climatic conditions. This approach when adopted in strategic manner will also contribute to further strengthen the development of adaptation strategies at national and local levels. The methods and tools validated and applied in this assessment allowed estimating possible impacts of climate change and adaptation strategies which can provide valuable insights and guidance for adaptation planning.

SUBMITTER: Gummadi S

PROVIDER: S-EPMC7643979 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

Gummadi Sridhar S Kadiyala M D M MDM Rao K P C KPC Athanasiadis Ioannis I Mulwa Richard R Kilavi Mary M Legesse Gizachew G Amede Tilahun T

PloS one 20201105 11

In this study, we assessed the possible impacts of climate variability and change on growth and performance of maize using multi-climate, multi-crop model approaches built on Agricultural Model Intercomparison and Improvement Project (AgMIP) protocols in five different agro-ecological zones (AEZs) of Embu County in Kenya and under different management systems. Adaptation strategies were developed that are locally relevant by identifying a set of technologies that help to offset potential impacts ...[more]

PMID: 33151967

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Project description:Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean (Phaseolus vulgaris L.), cowpea (Vigna unguiculata (L.) Walp.] and lablab [Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha-1. An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter production, reaching very high grain yields at high potential sites (3,000 kg ha-1) but being highly susceptible to in-season drought. Lablab seemed to be best adapted to dry environments. Its canopy architecture appeared to be best in compromising between the investment in biomass as a prerequisite to accumulate grain yield by minimizing water loss through soil evaporation and crop transpiration. This lead to grain yields of up to 2,000 kg ha-1 at high potential sites and >1,000 kg ha-1 at low potential sites. The variance of observed and simulated WUE was high and no clear dependency on total rainfall alone was observed for all three short-season grain legumes, highlighting that pattern of water use is also important in determining final WUEbiomass and WUEgrain. Mean WUEgrain was lowest for cowpea (1.5-3.5 kggrain ha-1 mm-1) and highest for lablab (5-7 kggrain ha-1 mm-1) reflecting the high susceptibility to drought of cowpea and the good adaptation to dry environments of lablab. Results highlight that, based on specific morphological, phonological, and physiological characteristics, the three short-season grain legumes follow different strategies to cope with climate variability. The climate-smart site-specific utilization of the three legumes offers promising options to design more resilient and productive farming systems in semi-arid Eastern Kenya.

Dataset Information

Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

Publications

Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

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