• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

两种植物适宜种植区预测:基于生境与植物化学适宜性的分析

Suitable Planting Area Prediction for Two Species: An Analysis Based on Habitat and Phytochemical Suitability.

作者信息

Wang Yanlin, Yan Shuo, Gao Shanshan, Liu Huanchu, Wang Qi

机构信息

Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Key Laboratory of Oasis Town and Mountain-Basin System Ecology of Xinjiang Production and Construction Corps, College of Life Sciences, Shihezi University, Shihezi 832003, China.

Liaoning Shenyang Urban Ecosystem Observation and Research Station, Shenyang 110164, China.

出版信息

Plants (Basel). 2025 May 30;14(11):1669. doi: 10.3390/plants14111669.

DOI:10.3390/plants14111669
PMID:40508343
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12157611/
Abstract

The distribution of suitable habitats for medicinal plants is affected by climate, soil, land use, and other factors. , an important traditional Chinese medicinal resource in Xinjiang, includes (Royle) I. M. Johnst. and Bunge and is at risk of over-exploitation. This study predicted suitable planting areas by integrating habitat and phytochemical suitability using the MaxEnt model and ArcGIS. The AUC values for and were 0.977 and 0.952, with TSS values of 0.829 and 0.725, respectively, validating the high accuracy of the prediction model. Under the current scenario, the areas of suitable habitats for and were 108,914 and 176,445 km, mainly distributed along the main mountains in Xinjiang. Under future climate scenarios, the suitable habitat area of increased by 11-18%, except in the ssp126-2090s scenario, while the suitable habitat area of area decreased by 3-18%. Both species were influenced by land use/land cover and soil available nitrogen content; additionally, was affected by the precipitation in the driest month, and by the mean diurnal range. The content of secondary metabolites was positively correlated with habitat suitability, with soil factors contributing 35.25% to the total secondary metabolite content. Their suitable habitats predominantly occur in grasslands (42-82%). As habitat and phytochemical suitability distributions aligned, the eastern and western sides of the northern Kunlun Mountain Pass emerged as key areas for cultivation. This research can provide a scientific foundation for selecting optimal planting regions for the two species.

摘要

药用植物适宜生境的分布受气候、土壤、土地利用等因素影响。新疆一种重要的传统中药资源包括新疆阿魏(Ferula sinkiangensis (K. M. Shen) X. T. Guan & R. H. Shan)和新疆阿魏(Ferula fukanensis K. M. Shen),面临过度开发风险。本研究利用MaxEnt模型和ArcGIS整合生境与植物化学适宜性来预测适宜种植区域。新疆阿魏(Ferula sinkiangensis (K. M. Shen) X. T. Guan & R. H. Shan)和新疆阿魏(Ferula fukanensis K. M. Shen)的AUC值分别为0.977和0.952,TSS值分别为0.829和0.725,验证了预测模型的高精度。在当前情景下,新疆阿魏(Ferula sinkiangensis (K. M. Shen) X. T. Guan & R. H. Shan)和新疆阿魏(Ferula fukanensis K. M. Shen)适宜生境面积分别为108,914平方千米和176,445平方千米,主要分布在新疆的主要山脉沿线。在未来气候情景下,除ssp126 - 2090年代情景外,新疆阿魏(Ferula sinkiangensis (K. M. Shen) X. T. Guan & R. H. Shan)适宜生境面积增加11% - 18%,而新疆阿魏(Ferula fukanensis K. M. Shen)适宜生境面积减少3% - 18%。两个物种均受土地利用/土地覆盖和土壤有效氮含量影响;此外,新疆阿魏(Ferula sinkiangensis (K. M. Shen) X. T. Guan & R. H. Shan)受最干旱月份降水量影响,新疆阿魏(Ferula fukanensis K. M. Shen)受日较差影响。次生代谢产物含量与生境适宜性呈正相关,土壤因素对次生代谢产物总含量贡献35.25%。它们的适宜生境主要出现在草地(42% - 82%)。由于生境和植物化学适宜性分布一致,昆仑山口北部的东西两侧成为关键种植区域。本研究可为这两种阿魏属植物选择最佳种植区域提供科学依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/3563e6e62079/plants-14-01669-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/33677f9dec47/plants-14-01669-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/d4a52a51f9d8/plants-14-01669-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/26cf34d10b47/plants-14-01669-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/7a87688d48bb/plants-14-01669-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/65d5c38e2c7b/plants-14-01669-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/09b234ecbed6/plants-14-01669-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/68f2e07034c6/plants-14-01669-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/91a7ed996a58/plants-14-01669-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/5671b2bb0f2b/plants-14-01669-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/9acc39bdd306/plants-14-01669-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/2f59531d4499/plants-14-01669-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/b77388507bb1/plants-14-01669-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/ff27e7642d3f/plants-14-01669-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/3563e6e62079/plants-14-01669-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/33677f9dec47/plants-14-01669-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/d4a52a51f9d8/plants-14-01669-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/26cf34d10b47/plants-14-01669-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/7a87688d48bb/plants-14-01669-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/65d5c38e2c7b/plants-14-01669-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/09b234ecbed6/plants-14-01669-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/68f2e07034c6/plants-14-01669-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/91a7ed996a58/plants-14-01669-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/5671b2bb0f2b/plants-14-01669-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/9acc39bdd306/plants-14-01669-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/2f59531d4499/plants-14-01669-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/b77388507bb1/plants-14-01669-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/ff27e7642d3f/plants-14-01669-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a05/12157611/3563e6e62079/plants-14-01669-g014.jpg

相似文献

1
Suitable Planting Area Prediction for Two Species: An Analysis Based on Habitat and Phytochemical Suitability.两种植物适宜种植区预测:基于生境与植物化学适宜性的分析
Plants (Basel). 2025 May 30;14(11):1669. doi: 10.3390/plants14111669.
2
Phylogenomics and Genetic Diversity of and Its Allies (, Boraginaceae) in China.中国紫草科软紫草属及其近缘类群的系统发育基因组学与遗传多样性
Front Plant Sci. 2022 Jun 9;13:920826. doi: 10.3389/fpls.2022.920826. eCollection 2022.
3
Simulation of distribution in China: assessing habitat suitability and bioactive component abundance under future climate change scenariosplant components.中国分布模拟:评估未来气候变化情景下的栖息地适宜性和生物活性成分丰度植物成分。
Front Plant Sci. 2024 Dec 4;15:1498229. doi: 10.3389/fpls.2024.1498229. eCollection 2024.
4
Phytochemical constituents, distributions and traditional usages of Arnebia euchroma: A review.植物化学成分、分布及传统用途的骆驼蓬:综述。
J Ethnopharmacol. 2021 May 10;271:113896. doi: 10.1016/j.jep.2021.113896. Epub 2021 Jan 29.
5
Impacts of Climate Change on the Habitat Suitability and Natural Product Accumulation of the Medicinal Plant L. Based on the MaxEnt Model.基于MaxEnt模型的气候变化对药用植物L.生境适宜性和天然产物积累的影响
Plants (Basel). 2024 May 21;13(11):1424. doi: 10.3390/plants13111424.
6
[Applying Biomod2 for modeling of species suitable habitats:a case study of Paeonia lactiflora in China].[应用Biomod2对物种适宜栖息地进行建模:以中国芍药为例]
Zhongguo Zhong Yao Za Zhi. 2022 Jan;47(2):376-384. doi: 10.19540/j.cnki.cjcmm.20211023.101.
7
The optimized Maxent model reveals the pattern of distribution and changes in the suitable cultivation areas for being driven by climate change.优化后的最大熵模型揭示了气候变化驱动下适宜种植区的分布格局和变化情况。
Ecol Evol. 2024 Jul 17;14(7):e70015. doi: 10.1002/ece3.70015. eCollection 2024 Jul.
8
[Correlation between rhizosphere environment and content of medicinal components of Arnebia euchroma].[新疆紫草根际环境与药用成分含量的相关性]
Zhongguo Zhong Yao Za Zhi. 2023 Nov;48(22):6030-6038. doi: 10.19540/j.cnki.cjcmm.20230725.101.
9
Projecting the impacts of climate change on habitat distribution of Varroa destructor in Ethiopia using MaxEnt ecological modeling.使用最大熵生态模型预测气候变化对埃塞俄比亚狄斯瓦螨栖息地分布的影响。
Sci Total Environ. 2025 Mar 10;968:178904. doi: 10.1016/j.scitotenv.2025.178904. Epub 2025 Feb 20.
10
Modeling soybean cultivation suitability in China and its future trends in climate change scenarios.中国大豆种植适宜性建模及其在气候变化情景下的未来趋势
J Environ Manage. 2023 Nov 1;345:118934. doi: 10.1016/j.jenvman.2023.118934. Epub 2023 Sep 12.

本文引用的文献

1
The sensitivity and response of the threatened endemic shrub Arbutus pavarii to current and future climate change.受威胁的特有灌木帕氏杨梅对当前和未来气候变化的敏感性及响应
BMC Ecol Evol. 2025 Apr 24;25(1):36. doi: 10.1186/s12862-025-02370-2.
2
Riverine Realities: Evaluating Climate Change Impacts on Habitat Dynamics of the Critically Endangered Gharial () in the Indian Landscape.河流现状:评估气候变化对印度地区极度濒危的恒河鳄栖息地动态的影响。
Animals (Basel). 2025 Mar 20;15(6):896. doi: 10.3390/ani15060896.
3
Plant invasion risk assessment in Argentina's arid and semi-arid rangelands.
阿根廷干旱和半干旱牧场的植物入侵风险评估
J Environ Manage. 2025 Mar;377:124648. doi: 10.1016/j.jenvman.2025.124648. Epub 2025 Feb 24.
4
Climate change impacts on worldwide ecological niche and invasive potential of Sternochetus mangiferae.气候变化对芒果果肉象甲全球生态位及入侵潜力的影响。
Pest Manag Sci. 2025 Feb;81(2):667-677. doi: 10.1002/ps.8465. Epub 2024 Oct 9.
5
Effects of geographical, soil and climatic factors on the two marker secondary metabolites contents in the roots of L.地理、土壤和气候因素对L.根部两种标记次生代谢产物含量的影响
Front Plant Sci. 2024 Jun 11;15:1419392. doi: 10.3389/fpls.2024.1419392. eCollection 2024.
6
Impacts of Climate Change on the Habitat Suitability and Natural Product Accumulation of the Medicinal Plant L. Based on the MaxEnt Model.基于MaxEnt模型的气候变化对药用植物L.生境适宜性和天然产物积累的影响
Plants (Basel). 2024 May 21;13(11):1424. doi: 10.3390/plants13111424.
7
Medicinal plants meet modern biodiversity science.药用植物与现代生物多样性科学相遇。
Curr Biol. 2024 Feb 26;34(4):R158-R173. doi: 10.1016/j.cub.2023.12.038.
8
[Correlation between rhizosphere environment and content of medicinal components of Arnebia euchroma].[新疆紫草根际环境与药用成分含量的相关性]
Zhongguo Zhong Yao Za Zhi. 2023 Nov;48(22):6030-6038. doi: 10.19540/j.cnki.cjcmm.20230725.101.
9
Prediction of the potentially suitable areas of in China based on future climate change using the optimized MaxEnt model.基于未来气候变化,利用优化的最大熵模型预测中国[具体事物未给出]的潜在适宜区域。
Ecol Evol. 2023 Oct 19;13(10):e10597. doi: 10.1002/ece3.10597. eCollection 2023 Oct.
10
Integrating microbial community properties, biomass and necromass to predict cropland soil organic carbon.整合微生物群落特性、生物量和死有机物质以预测农田土壤有机碳。
ISME Commun. 2023 Aug 23;3(1):86. doi: 10.1038/s43705-023-00300-1.