Cotton is a vital cash crop that underpins regional agricultural systems and the global textile supply chain. However, climate change and increasing human activity are reshaping the spatial distribution of areas suitable for cotton cultivation, with the potential impacts being particularly pronounced in arid and semi-arid regions. This study integrated high-resolution cotton distribution data, environmental variables and human activities and employed ensemble model and niche analysis methods to systematically assess cotton suitability in Xinjiang under current and future climate scenarios. The results indicate that the ensemble models demonstrate high predictive performance, with both model types (Model 1: Environmental; Model 2: Environmental and human activity) achieving AUC values exceeding 0.97 and TSS values exceeding 0.84. Under current climatic conditions, suitable cotton-growing areas are primarily distributed on both sides of the Tianshan Mountains, and the inclusion of human activity factors results in a 13.71% reduction in suitable area. Moreover, Future climate change is projected to result in an increase in its suitable range of between 28.25% and 94.10%, with the most significant expansion occurring under the high-emissions scenario. MESS analysis indicates that the newly identified suitable areas in the future bear a high degree of similarity to current environmental conditions, whilst MOD analysis further highlights that temperature and precipitation are the key drivers of environmental variation. Additionally, Xinjiang cotton will retain a high degree of ecological niche under future climatic conditions. These findings provide important scientific evidence for optimizing the spatial distribution of cotton cultivation in Xinjiang and for climate-adaptive agricultural management.
Li et al. (Mon,) studied this question.