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利用最大熵模型预测中国头状蓼的分布情况及其在不同气候情景下的变化。

Predicting Polygonum capitatum distribution in China across climate scenarios using MaxEnt modeling.

机构信息

Pharmacy Department, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, 550001, Guizhou, China.

School of Biological Sciences, Guizhou Education University, Guiyang, 550018, China.

出版信息

Sci Rep. 2024 Aug 28;14(1):20020. doi: 10.1038/s41598-024-71104-z.

DOI:10.1038/s41598-024-71104-z
PMID:39198562
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11358317/
Abstract

Climate change affects the geographical distribution of species. Predicting the future potential areas suitable for certain species is of great significance for understanding their distribution characteristics and exerting their value. Based on the data of 276 effective distribution points of Polygonum capitatum and 20 ecological factors, the maximum entropy (MaxEnt) model and the ArcGIS software were employed to predict the areas suitable for P. capitatum growth, and the main environmental factors affecting the geographical distribution of this species were explored. Under the current climatic conditions, the areas highly suitable for P. capitatum are mainly distributed in southwestern China, with a small number of sites in coastal areas and most sites in Guizhou Province. Under different climate scenarios, the suitable areas were reduced to varying degrees. The dominant environmental variables affecting the distribution of P. capitatum were precipitation in the driest month, annual precipitation, and elevation, with a cumulative contribution rate of 84.1%. Against the background of a changing climate, the areas suitable for P. capitatum in China will be widely distributed in the southwestern region, with Guizhou Province and Yunnan Province as the main distribution areas; some sites will also be distributed throughout the southwest of Tibet Autonomous Region, the south of Sichuan Province, the north of Guangxi Autonomous Region, and the coastal area of Fujian Province. Optimal conditions for P. capitatum include a dry month precipitation range of 13.4 to 207.3 mm, elevations from 460.3 to 7214.3 m, and annual precipitation between 810 and 1575 mm. Given these insights, we recommend enhanced conservation efforts in current prime habitats and exploring potential cultivation in newly identified suitable regions to ensure the species' preservation and sustainable use.

摘要

气候变化影响物种的地理分布。预测未来某些物种适宜生长的潜在区域对于了解它们的分布特征和发挥它们的价值具有重要意义。本研究基于 276 个有效分布点和 20 个生态因子的Polygonum capitatum 数据,采用最大熵(MaxEnt)模型和 ArcGIS 软件预测了该物种适宜生长的区域,并探讨了影响其地理分布的主要环境因素。在当前气候条件下,高度适宜 P. capitatum 生长的区域主要分布在中国西南部,沿海地区有少量适宜区,贵州省适宜区数量最多。在不同的气候情景下,适宜区面积均有不同程度的减少。影响 P. capitatum 分布的主导环境变量是最干旱月降水量、年降水量和海拔,累计贡献率为 84.1%。在气候变化的背景下,中国适宜 P. capitatum 生长的区域将广泛分布在西南地区,以贵州省和云南省为主要分布区;部分适宜区也将分布在西藏自治区西南部、四川省南部、广西壮族自治区北部和福建省沿海地区。最适宜 P. capitatum 生长的条件是干旱月降水量在 13.4 到 207.3mm 之间,海拔在 460.3 到 7214.3m 之间,年降水量在 810 到 1575mm 之间。有鉴于此,我们建议在当前的主要栖息地加强保护工作,并探索新确定的适宜区域的潜在种植,以确保物种的保护和可持续利用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/c66983da9583/41598_2024_71104_Fig8_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/83c795593cd4/41598_2024_71104_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/a0a81120a7da/41598_2024_71104_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/dc96959ea80b/41598_2024_71104_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/c66983da9583/41598_2024_71104_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/c6e6688f8f47/41598_2024_71104_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/59205440037a/41598_2024_71104_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/c652969298ba/41598_2024_71104_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/3ca1fc98c59b/41598_2024_71104_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/83c795593cd4/41598_2024_71104_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/a0a81120a7da/41598_2024_71104_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/dc96959ea80b/41598_2024_71104_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1bb/11358317/c66983da9583/41598_2024_71104_Fig8_HTML.jpg

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