Prediction of Potential Suitable Habitats of Cupressus duclouxiana Under Climate Change Based on Biomod2 Ensemble
Jialin Li1, Yi Huang2, Yunxi Pan1
1Forest Ecology and Conservation in the Upper Reaches of the Yangtze River Key Laboratory of Sichuan Province, Engineering Research Center for Forest and Grassland Disaster Prevention and Reduction at Mianyang Normal University of Sichuan Province, School of Life Sciences, College of Biology and Pharmacy, Mianyang Normal University, Mianyang 621000, China.
Abstract:
Cupressus duclouxiana is an ecologically and economically important conifer endemic to southwestern China (e.g., central Yunnan and southern Sichuan), yet its potential distribution under future climate change remains insufficiently understood. In this study, we employed an ensemble species distribution modeling framework implemented in biomod2 to predict the current and future suitable habitats of C. duclouxiana across China. A total of 154 occurrence records and 17 key environmental variables were used to construct ensemble models integrating twelve algorithms. The ensemble model showed high predictive performance (TSS = 0.99, Kappa = 0.98). Temperature-related variables dominated habitat suitability, with the minimum temperature of the coldest month identified as the primary limiting factor, accounting for 44.1%. Under current climatic conditions, suitable habitats are mainly concentrated in southwestern China, particularly in Sichuan, Yunnan, and Xizang (Tibet). Future projections under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5) consistently indicate habitat expansion by the late 21st century, accompanied by pronounced northward and northwestward range shifts. The largest expansion is projected under the SSP3-7.0 scenario, highlighting the sensitivity of C. duclouxiana to intermediate warming trajectories. Overall, climate warming is expected to increase habitat availability while reshaping the spatial distribution of C. duclouxiana across China. These findings provide scientific support for climate-adaptive afforestation planning and conservation management, and offer broader insights into the responses of subtropical coniferous species to future climate change.
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