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采用最大熵模型预测气候变化下中国黄芪的潜在分布。

Predicting the potential distribution of Astragali Radix in China under climate change adopting the MaxEnt model.

作者信息

Wen Zixuan, Yan Ke, Zhang Man, Ma Ruiqing, Zhu Xiaoyan, Duan Qing, Jiang Xiaolin

机构信息

School of Public Health, Shandong Second Medical University, Weifang, China.

Department of Science and Education, Shandong Center for Disease Control and Prevention, Jinan, China.

出版信息

Front Plant Sci. 2024 Dec 6;15:1505985. doi: 10.3389/fpls.2024.1505985. eCollection 2024.

DOI:10.3389/fpls.2024.1505985
PMID:39711593
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11659014/
Abstract

INTRODUCTION

Astragali Radix is the dried root of Astragalus mongoliae or Astragalus membranaceus, a leguminous plant. Since ancient times, Astragali Radix has been widely used in Chinese traditional Chinese medicine. As people become more health-conscious, the market demand for Astragali Radix grows and its popularity is increasing in the international market. As an important medicinal plant, the growth of Astragali Radix is strongly influenced by environmental conditions. In order to meet the market demand for high quality Astragali Radix herbs, it is necessary to search and find areas suitable for the growth of Astragali Radix.

METHODS

In this study, we assessed the potential impacts of climate change on the distribution of the Chinese medicinal plant Astragali Radix using the maximum entropy (MaxEnt) model in combination with a geographic information system(GIS). Distribution data and environmental variables were analyzed to predict suitable areas for Astragali Radix under the SSP126, SSP245 and SSP585 scenario for current and future (2041-2060, 2061-2080, 2081-2100). Jackknife is used to assess the importance of environmental variables, and environmental variables with a model contribution greater than 5% were considered to be the main drivers.

RESULTS

The results showed that the current area of suitable area for Astragali Radix is 188.41 km, and the three climate scenarios show an increasing trend in the future, with a maximum of 212.70 km. North China has always been the main suitable area, while the area of suitable area in Southwest China is decreasing, and Xinjiang will be developed as a new suitable area in the future. Annual precipitation (41.6%), elevation (15.9%), topsoil calcium carbonate (14.8%), annual mean temperature (8.3%), precipitation seasonality (8%) and topsoil pH (6%) contributed more to the model and were the main environmental influences on the distribution of Astragali Radix. In addition, the centroids of the suitable areas shifted northward under all three climate scenarios, indicating a migratory response to global warming.

DISCUSSION

Our study found that suitable area of Astragali Radix has been expanding for most of the time in each period of the three climate scenarios compared with the current situation. In the future, humans can focus on enhancing the cultivation techniques of Astragali Radix in these suitable areas. This study provide a scientific basis for the development of planting strategies and spatial distribution management of Astragali Radix. It helps to optimize the selection of planting areas and resource conservation of Chinese herbs.

摘要

引言

黄芪是豆科植物蒙古黄芪或膜荚黄芪的干燥根。自古以来,黄芪就在中国传统医学中被广泛应用。随着人们健康意识的提高,市场对黄芪的需求不断增长,其在国际市场上的知名度也日益提高。作为一种重要的药用植物,黄芪的生长受到环境条件的强烈影响。为了满足市场对高品质黄芪药材的需求,有必要寻找适合黄芪生长的区域。

方法

在本研究中,我们结合地理信息系统(GIS),使用最大熵(MaxEnt)模型评估气候变化对中国药用植物黄芪分布的潜在影响。分析分布数据和环境变量,以预测当前和未来(2041 - 2060年、2061 - 2080年、2081 - 2100年)在SSP126、SSP245和SSP585情景下黄芪的适宜区域。使用刀切法评估环境变量的重要性,模型贡献大于5%的环境变量被视为主要驱动因素。

结果

结果表明,当前黄芪适宜种植面积为188.41平方千米,三种气候情景下未来呈现增加趋势,最大可达212.70平方千米。华北地区一直是主要适宜种植区,而西南地区适宜种植面积在减少,新疆未来将发展成为新的适宜种植区。年降水量(41.6%)、海拔(15.9%)、表土碳酸钙(14.8%)、年平均温度(8.3%)、降水季节性(8%)和表土pH值(6%)对模型贡献较大,是影响黄芪分布的主要环境因素。此外,在三种气候情景下适宜区域的重心均向北移动,表明对全球变暖的迁移响应。

讨论

我们的研究发现,与当前情况相比,在三种气候情景的每个时期,黄芪适宜种植面积大部分时间都在扩大。未来,人类可以专注于加强这些适宜区域的黄芪种植技术。本研究为黄芪种植策略的制定和空间分布管理提供了科学依据。有助于优化种植区域的选择和中药材资源的保护。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/76c0dd461586/fpls-15-1505985-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/30845d157214/fpls-15-1505985-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/ab6edd96006c/fpls-15-1505985-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/76c0dd461586/fpls-15-1505985-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/30845d157214/fpls-15-1505985-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/ab6edd96006c/fpls-15-1505985-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7de4/11659014/76c0dd461586/fpls-15-1505985-g007.jpg

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