Beyond Topography: Climate‐Based Functional Zoning for Adaptive Cotton Management in Arid Regions
Pengfei Wu, Zhongli Liu, Zhancheng Zhao, Jian HuangABSTRACT
Background
Climate change is exacerbating vulnerabilities in industrial cotton systems of arid regions. Effective agricultural zoning is therefore crucial for implementing targeted management practices that mitigate climate risks and optimise cotton productivity. However, traditional topography‐based zoning fails to capture the spatial heterogeneity of key hydrothermal factors, thus limiting precision in adaptive management.
Methods
We integrated 2010–2021 climate data and county‐level cotton yield records from 91 counties in Xinjiang, China. Functional cultivation zones were delineated using consensus clustering of 10‐day precipitation and accumulated temperatures above 10°C and above 15°C. Key discriminants among zones were identified via empirical Bayes shrinkage of linear models. Zone‐specific climate–yield relationships were modelled using random forest and polynomial regression to validate agroecological coherence, which informs differentiated adaptive strategies.
Results
Three newly delineated functional zones were identified: Dispersed Class, Tianshan Northern Piedmont, and Basin‐Desert. Accumulated temperatures above 15°C during critical phenological windows was the primary discriminator. Climate–yield relationships diverged markedly: Basin‐Desert yields were predominantly precipitation‐sensitive, whereas Tianshan Northern Piedmont and Dispersed Class yields were heat‐associated, with peak sensitivity during flowering‐to‐boll and pre‐sowing/pre‐harvest periods, respectively. While the traditional North‐South Xinjiang topographic zoning provides a conventional geographical framework, the hydrothermal functional zoning achieved a 2.9‐fold higher multi‐year mean η 2 and showed a lower weighted CV than the traditional scheme (17.9% vs. 20.3%), indicating improved explanatory power and within‐zone homogeneity. Collectively, these findings reveal climate–yield dynamics that transcend conventional topographic boundaries, highlighting how functional zoning, underpinned by superior temporal robustness, captures agroecological heterogeneity more effectively than static geographic classifications for guiding adaptive management.
Conclusion
This study demonstrates a paradigm shift from static geographic zoning to dynamic functional zoning based on hydrothermal patterns. The framework is transferable to other warm‐climate crops and serves as a decision‐support tool for precision agriculture, enabling evidence‐based targeted adaptation strategies for sustainable cotton production in arid regions.