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预测一种濒危药用植物的栖息地适宜性:来自集成物种分布模型的见解

Predicting habitat suitability for an endangered medicinal plant, : insights from ensemble species distribution models.

作者信息

Guo Xiang, Bai Wei, Wang Yihua, Hao Senliang, Zhao Liping, Li Xin, Guo Zongliang, Li Xiaoyan

机构信息

Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, China.

Department of Radiation Oncology, Shanxi Province Cancer Hospital, Taiyuan, China.

出版信息

Front Plant Sci. 2025 Jun 24;16:1590206. doi: 10.3389/fpls.2025.1590206. eCollection 2025.

DOI:10.3389/fpls.2025.1590206
PMID:40630732
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12236372/
Abstract

INTRODUCTION

Global climate change has profound impacts on alpine ecosystems, and with climate warming, alpine plants often face a substantial risk of habitat loss. Maxim., known for its significant medicinal value, is a typical alpine plant predominantly found in the high-altitude regions of Southwest China. However, the impacts of climate change on the habitat suitability of have not been fully understood.

METHODS

We simulated ensemble species distribution models to assess the spatiotemporal habitat distribution pattern of under different climate scenarios (ssp126 and ssp585) for the periods 2040s, 2060s, and 2070s.

RESULTS AND DISCUSSION

The results show that the suitable habitats, under near current condition, are mainly distributed in the Qinghai-Xizang Plateau of China, covering the border regions of four provinces: Xizang, Qinghai, Sichuan, and Yunnan, with a total area of 14.06×10 km. Under future climate change scenarios, the area of suitable habitats, particularly the highly suitable habitats, is projected to contract significantly by 80.65%, accompanied by shifts in distribution centroids towards the southwest and higher altitudes in Xizang. These results indicate that the risk of survival due to the loss of suitable habitats would persist in the future. Among the environmental factors analyzed, elevation and three bioclimatic predictors, BIO18 (precipitation of the warmest quarter), BIO12 (annual precipitation) and BIO4 (temperature seasonality), exhibit significant impacts on the potential distribution of suitable habitats for . Our study provides an improved understanding of the potential habitat distribution dynamics of the endangered , thereby offering a crucial reference for its conservation and sustainable management.

摘要

引言

全球气候变化对高山生态系统有着深远影响,随着气候变暖,高山植物常常面临栖息地丧失的重大风险。Maxim. 因其显著的药用价值而闻名,是一种典型的高山植物,主要分布在中国西南部的高海拔地区。然而,气候变化对其栖息地适宜性的影响尚未得到充分了解。

方法

我们模拟了集合物种分布模型,以评估在不同气候情景(ssp126和ssp585)下,2040年代、2060年代和2070年代Maxim. 的时空栖息地分布格局。

结果与讨论

结果表明,在当前近似条件下,适宜栖息地主要分布在中国青藏高原,覆盖西藏、青海、四川和云南四省的边境地区,总面积为14.06×10平方千米。在未来气候变化情景下,适宜栖息地的面积,尤其是高度适宜栖息地的面积,预计将显著收缩80.65%,同时分布中心向西南方向移动,并向西藏的更高海拔地区转移。这些结果表明,未来由于适宜栖息地丧失导致的Maxim. 生存风险将持续存在。在所分析的环境因素中,海拔以及三个生物气候预测因子,即BIO18(最暖季度降水量)、BIO12(年降水量)和BIO4(温度季节性),对Maxim. 适宜栖息地的潜在分布具有显著影响。我们的研究增进了对濒危物种Maxim. 潜在栖息地分布动态的理解,从而为其保护和可持续管理提供了关键参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/42494e38e535/fpls-16-1590206-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/9b00076bae62/fpls-16-1590206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/594aa9479d29/fpls-16-1590206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/2cfbc0535355/fpls-16-1590206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/befd093efcff/fpls-16-1590206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/93dee0124715/fpls-16-1590206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/f52482b57a0c/fpls-16-1590206-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/e52168120356/fpls-16-1590206-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/42494e38e535/fpls-16-1590206-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/9b00076bae62/fpls-16-1590206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/594aa9479d29/fpls-16-1590206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/2cfbc0535355/fpls-16-1590206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/befd093efcff/fpls-16-1590206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/93dee0124715/fpls-16-1590206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/f52482b57a0c/fpls-16-1590206-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/e52168120356/fpls-16-1590206-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7f/12236372/42494e38e535/fpls-16-1590206-g008.jpg

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