• Climatic and non-climatic drivers of cotton yield were quantified at county scale. • Climate impacts on cotton yield show strong spatial heterogeneity across Xinjiang. • Future scenarios suggest average yield gains but increasing regional imbalance. Understanding the relative contributions of climatic and non-climatic factors to cotton yield variability is essential for developing climate-resilient production systems. Using county-level yield records from 1990 to 2024 together with gridded climate data, this study quantified the impacts of climate variability on cotton yield across Xinjiang, China, and assessed future yield responses under two CMIP6 scenarios (SSP2-4.5 and SSP5-8.5). Random forest models and a panel regression approach were applied to disentangle climatic and non-climatic yield components and to capture nonlinear climate–yield relationships. The results show that climate variability accounts, on average, for approximately one-third of the interannual yield variation across Xinjiang, while non-climatic factors dominate long-term yield growth. Pronounced spatial heterogeneity is observed in climate impacts: warming conditions are projected to benefit cotton production in southern and eastern Xinjiang, whereas about one-third of cotton-growing counties, predominantly situated in northern Xinjiang and high-altitude regions, are projected to experience negative climate impacts. At the regional scale, the net effect of climate change on cotton yield is projected to remain positive, with stronger yield enhancement under SSP5-8.5, although this overall gain masks substantial county-level disparities. Assuming constant planting areas, adverse climate impacts are projected to result in total production losses of approximately 2.4–3.2×10 5 t by mid-century and 2.8–3.0×10 5 t by the end of the century across negatively affected counties. These findings highlight the critical role of non-climatic drivers, including agronomic innovations and irrigation management, in sustaining yield growth and buffering adverse climate effects. From a policy perspective, the results underscore the need for region-specific adaptation strategies that enhance climate resilience in major production zones while guiding the spatial optimization of cotton production under future climate change.
Wang et al. (Sun,) studied this question.