Analysis of crop suitability index for current and future climates using statistically downscaled CMIP6 outputs over Africa
Imoleayo Ezekiel Gbode, Vincent Olanrewaju Ajayi, Amadou Coulibaly, Daniel Abel, Katrin Ziegler, Torsten Weber, Seydou Brehima Traore, Ibraheem Ayomide Raji, Heiko Paeth Abstract
The study aimed to assess the impact of climate change on the crop suitability index (CSI) of selected staple crops for current (1981–2010) and future (2021–2050 and 2051–2080) climates across Africa. Precipitation and mean temperature data from gridded observations, and 10 Global Climate Models (GCMs) were utilized to calculate the CSI for maize, soybean, wheat, plantain, cassava, rice, millet, sorghum, and yam. The Ecocrop model implemented in R, utilizing the FAO‐Ecocrop database alongside climatic variables for different climatic zones across the continent, was employed to compute the CSI. The results indicate that all crops, except rain‐fed rice, are suitable in parts of West and Central African regions, with wheat being inclusive in some parts of the Guinea Coast. The northern, eastern, and southern African regions are identified as the least suitable for any crop production based on the balance between the base climate parameters over the historical period. Analysis over this historical period reveals an increasing trend for major crops in most regions, except for wheat crop production, which demonstrates a decreasing trend in most areas. Projection analysis reveals that the Sahel region is expected to be the most affected by climate change, with a significant reduction in the suitability index for most crops. Conversely, the Southeastern Africa and the Guinea Coast regions are likely to be the least affected, as the suitability index increases for the considered crops. This analysis provides crucial information for effective agricultural planning and resource allocation, optimizing land use by identifying crops aligned with prevailing environmental conditions, including soil type, climate, and water availability. Such information enhances the understanding of crop suitability, contributing to improved agricultural productivity and sustainability.