Simulation of Suitable Distribution and Differentiation in Local Environments of Cercospora arachidicola in China

Peanut early leaf spot (ELS), caused by Cercospora arachidicola, is a major global threat to peanut production, leading to substantial economic losses. The development of ELS is closely linked to favorable climatic conditions. This study aimed to develop a predictive model, optimized using the Biomod tuning function, to assess the future risk and spatial distribution of ELS under various climate change scenarios. Our results suggest a northward expansion of suitable habitats for C. arachidicola driven by global warming, particularly under the SSP585-2050s and SSP585-2090s scenarios. Regions such as Shandong, Henan, and Shaanxi in northern China are predicted to become increasingly suitable for the pathogen, extending beyond traditional warm and humid zones. Climate-induced shifts in ecological niches were quantified, revealing significant changes in the pathogen’s distribution, with a reduction in niche overlap under future climatic conditions. Principal component analysis identified the bioclimatic variables bio5, bio6, and bio8 as key drivers of the pathogen’s niche shift. The first two principal components explained 71.82–75.02% of the variance in environmental factors. These findings provide crucial insights for proactive disease management and underscore the profound impact of climate change on ELS distribution, highlighting the necessity of adaptive strategies to mitigate its effects on agricultural systems. This model can also directly provide migration predictions for pathogenic bacteria for farmers and government departments, and make a great contribution to reducing disease losses.