Keteleeria evelyniana Mast., which is widespread in southwestern China, is valuable for studying under different future climate scenarios to assess potential distribution shifts in response to climate warming. Understanding these changes can provide theoretical support for species conservation, rational utilization, ecological restoration, and management of K. evelyniana habitats. The Maxent model was optimized using the package of ENMeval to adjust the Regularization Multiplier (RM) and Feature Class Combinations (FC) parameters. Utilizing 221 effective distribution points and 33 environmental variables, the potential distribution of K. evelyniana in current and future climate scenarios was predicted, with the key environmental variables analyzed. The model with FC = LQ and RM = 0.5, demonstrated low complexity, minimal overfitting, and high accuracy, achieving an AUC value of 0.946 with a standard deviation of 0.011. Under the current climate conditions, 68% of the suitable areas for K. evelyniana were focused on Yunnan Province, with additional areas in western and southwestern Guizhou, southwestern Sichuan, and the southeastern Xizang Autonomous Region. In various future climate scenarios, the suitable areas for K. evelyniana gradually decreased, with a maximum reduction of 33%. Simultaneously, the centroids of these areas are expected to migrate northward by up to 33 km. Temperature was the dominant factor affecting its distribution (77.8%), whereas the effects of soil variables and altitude were significant. This study clarified the current distribution of K. evelyniana, projected the potential shifts under different future climate scenarios, and identified the main environmental factors affecting the distribution. These findings offer valuable theoretical support for the conservation, ecological restoration, and sustainable use of K. evelyniana.
Assessing the impact of climate change on the potential distribution of Keteleeria evelyniana Mast. in southwest China: a Maxent modeling approach
Yuan Feng,Guanghui Dai,Hua Li,Yong Chai,Rui Bao,Meng Wang,Chunlin Luo,Yangping Qin
Published 2025 in Frontiers in Plant Science
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- Publication year
2025
- Venue
Frontiers in Plant Science
- Publication date
2025-04-25
- Fields of study
Medicine, Environmental Science
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Semantic Scholar, PubMed
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