ZHANG Baode
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500CAI Chui
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500XIE Zhun
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500YU Hongya
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500LIU Guanghua
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500LYU Defang
Qujing Zhanyi District Bio-resource Development and Technology Promotion Station, Qujing 655000, YunnanYUAN Liping
Qujing Zhanyi District Bio-resource Development and Technology Promotion Station, Qujing 655000, YunnanHU Yanfang
Qujing Zhanyi District Bio-resource Development and Technology Promotion Station, Qujing 655000, YunnanXU Furong
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 6505001.College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500;2.Qujing Zhanyi District Bio-resource Development and Technology Promotion Station, Qujing 655000, Yunnan
Foundation projects: The National Natural Science Foundation of China (82060694, 81860674); Science and Technology Project of Yunnan Province(202304BI090004); Yunnan Science and Technology Talent and Platform Program (202105AG070012)
The impact of climate change on the ecological suitability of species is a crucial concern for biodiversity conservation. This study employed a combination of 128 reliable distribution records of Paris polyphylla var. yunnanensis in China and 32 bioclimatic variables utilizing the MaxEnt model and ArcGIS software, in order to investigate the primary ecological factors that influence the distribution of ecological suitability for this species. Furthermore, we have made projections regarding the spatial distribution pattern of potential suitable areas and the trajectory of centroid displacement during the last glacial maximum, the middle holocene, the present, and future periods (2050s, 2070s) under three distinct greenhouse gas emission scenarios (RCP2.6, RCP4.5, RCP8.5). The findings indicate that the MaxEnt model exhibited a remarkable level of precision in its predictions, as evidenced by a mean AUC value of 0.951 across all time periods. Notably, the geographical distribution of the studied entity was primarily influenced by several significant bioclimatic factors, namely precipitation annually, seasonality of temperature, warmest quarter precipitation, and elevation. Since the last glacial maximum, the areas of significant change in the potential habitat of Dianzhilou have been concentrated in the high habitability zone. Particularly, under the projected scenario of high greenhouse gas emissions in the future. In this scenario, the area of shrinkage reaches a maximum of 16.86×104 km2, primarily concentrated in the northeastern region of Sichuan province. Simultaneously, the analysis of centroids revealed a tendency for the distribution of P. polyphylla var. yunnanensis to shift towards latitudes and altitudes of greater magnitude in response to climate change scenarios. These findings suggested that global warming contributed to the contraction of areas highly conducive for P. polyphylla var. yunnanensis. Consequently, the outcomes of this study furnish a theoretical framework for the judicious utilization of wild resources pertaining to P. polyphylla var. yunnanensis.