Climate-Induced Shifts in Agricultural Suitability: Spatial Modelling of Cropping Risk and Rural Adaptation

Abstract

Climate change is increasingly altering agricultural suitability by influencing temperature regimes, precipitation patterns, and environmental conditions, thereby threatening food security and rural livelihoods. This study evaluated the spatial distribution of climate-induced shifts in agricultural suitability and identified the key environmental determinants influencing future cropping potential using a spatial modelling framework. A secondary geospatial dataset comprising 600 agricultural observation units was analysed using Python. Descriptive statistics, Wilcoxon signed-rank testing, Pearson correlation analysis, variance inflation factor assessment, and multiple linear regression were employed to examine projected changes in agricultural suitability and their associated drivers. The results revealed a significant decline in mean agricultural suitability under future climate conditions (p < 0.001), with 62.83% of locations experiencing reduced suitability. The Western Drylands and Southern River Basin exhibited the greatest projected declines, whereas the Northern Highlands demonstrated localized improvements. Elevation was positively associated with future agricultural suitability, while temperature change, rainfall change, and slope significantly reduced suitability. The regression model explained 16.55% of the variation in projected suitability and satisfied key diagnostic assumptions. These findings demonstrate that climate change will affect agricultural landscapes unevenly, requiring region-specific adaptation strategies. Integrating spatial modelling with climate risk assessment provides valuable evidence for supporting climate-resilient agricultural planning, sustainable land management, and informed policy development aimed at strengthening rural adaptation and long-term food security.