Climate change-driven distribution shifts of pigeonpea sterility mosaic disease in India: a MaxEnt modeling approach

Introduction Climate change is affecting the regional patterns of plant diseases worldwide, including pigeonpea sterility mosaic disease (PPSMD). Its prevalence, severity, and potential spread are being progressively influenced by changes in India's temperature and moisture regimes. Methods Using Coupled Model Intercomparison Project (CMIP6) projections for 2050 and 2070 under the shared socioeconomic pathways (SSP) 126 and SSP 585 scenarios, we applied a thorough Maximum Entropy Modelling (MaxEnt) modelling approach to evaluate the climatic appropriateness of PPSMD under present and future conditions, and to assess the effects of climate change on PPSMD. Results The model showed high predictive performance during testing using a random subsample, with an area under the curve (AUC) of 0.986, True skill statistics (TSS) of 0.945, and Continuous Boyce index (CBI) of 0.935. The most significant climate parameters for the disease's ecological niche were annual average temperature (BIO1, 39.3%), precipitation of the wettest month (BIO13, 24.2%), temperature seasonality (BIO4, 12.8%), and precipitation of the warmest quarter of the year (BIO18, 12%). Current suitability maps identified high-risk regions in Southern and Central India. Future forecasts indicated that the geographical extent of climatically suitable areas will increase by 18.4% under SSP126 (2050s and 2070s) and by 20.6% with SSP585 for the same time period. Discussion This findings imply that pigeonpea systems are increasingly susceptible to climate change. These results provide insightful information about how diseases and climate combine to affect PPSMD dynamics. Additionally, they offer a strong scientific basis for enhancing early warning systems, monitoring, and management tactics in response to potential future climatic scenarios.