南京林业大学学报(自然科学版) ›› 2024, Vol. 48 ›› Issue (5): 173-180.doi: 10.12302/j.issn.1000-2006.202302003

• 研究论文 • 上一篇    下一篇

基于MaxEnt模型的单花荠生境适宜性分析及其分布变化

李瑞兰1(), 樊锦雅2, 赵倩2, 李廷菊2, 王成辉1, 丁荣2, 古锐1,*(), 钟世红3   

  1. 1.成都中医药大学民族医药学院,四川 成都 611137
    2.成都中医药大学药学院,四川 成都 611137
    3.西南民族大学药学院,四川 成都 610041
  • 收稿日期:2023-02-03 修回日期:2023-05-19 出版日期:2024-09-30 发布日期:2024-10-03
  • 通讯作者: * 古锐(664893924@qq.com),教授。
  • 作者简介:

    李瑞兰(2370403423@qq.com)。

  • 基金资助:
    国家重点研发计划(2019YFC1712302);国家重点研发计划(2019YFC1712305)

Estimation of habitat suitability and climatic distribution change of Pegaeophyton scapiflorum based on the MaxEnt model

LI Ruilan1(), FAN Jinya2, ZHAO Qian2, LI Tingju2, WANG Chenghui1, DING Rong2, GU Rui1,*(), ZHONG Shihong3   

  1. 1. College of Ethnic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
    2. College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
    3. College of Pharmacy, Southwest Minzu University College, Chengdu 610041, China
  • Received:2023-02-03 Revised:2023-05-19 Online:2024-09-30 Published:2024-10-03

摘要:

【目的】探讨影响单花荠(Pegaeophyton scapiflorum)分布的主导气候因子,模拟其潜在适宜分布区,为单花荠的野生资源调查与保护提供合理依据。【方法】基于单花荠在中国的88个分布点数据和8个环境因子数据,运用最大熵(MaxEnt)模型预测在当前气候模式和RCP 2.6、RCP 4.5和RCP 8.5等3种未来气候变化模式下到2050年和2070年我国单花荠潜在适生区的变化情况,综合分析影响单花荠分布的主要环境因子及其适宜范围。【结果】①模型精度较高,AUC值为0.887。预测显示当代单花荠潜在适生区主要分布在青藏高原地区,总适生区面积约310万km2,含高适生区约80.81万km2。②地形地貌、温度和降水是影响单花荠分布的主要环境因子,其中分别以海拔、等温性和年平均降水量的影响最大。③在不同气候变化模式下,到2050年和2070年我国单花荠的适生区面积相对当前缩减24%~28%,高适生区降级成中适生区或低适生区,将表现为明显缩减甚至面临消失,且分布重心有向西、向高海拔区域偏移的趋势。【结论】研究结果可为单花荠野生资源的保护与可持续开发利用及人工栽培提供重要的参考依据。

关键词: 野生植物资源, 单花荠, 最大熵(MaxEnt)模型, 潜在适生区, 青藏高原

Abstract:

【Objective】 Pegaeophyton scapiflorum can be found mainly in the high altitudes of the Qinghai-Xizang Plateau in China, and the traditional surveys are difficult to implement. This study explored the dominant climatic factors that limit the distribution of P. scapiflorum in China and simulated its suitable distribution areas. The goal was to provide a theoretical basis for the investigation and protection of wild resources of P. scapiflorum. 【Method】 This study was based on 88 distribution sites and eight environmental factor variables of P. scapiflorum in China. The MaxEnt model was employed to predict the changes in its potential habitat. Additionally, the possible influence of climatic change under the extremely pessimistic representative concentration pathways scenarios RCP 2.6, RCP 4.5 and RCP 8.5 for the 2050s and 2070s were estimated. A comprehensive analysis of the main environmental factors affecting the distribution of P. scapiflorum was conducted. 【Result】 (1) The prediction accuracy of the MaxEnt model was high, and the AUC was 0.887. The prediction showed that P. scapiflorum is mainly located in the Qinghai-Xizang Plateau currently. The highly suitable areas were mainly distributed in the Kailas Range, Himalayas, southern valley of Xizang, Qaidam Basin, Nyainqêntanglha Mountains, Tanggula Mountains, the southern section of the Aemye Ma-chhen Range, the northern part of the Songpan-Ganzi Plateau, and Hengduan Mountain. The total suitable area of the potential geographical distribution of P. scapiflorum was approximately 310 × 104 km2, including 80.81 × 104 km2 of highly suitable areas. (2) The main environmental factor variables affecting the potential geographical distribution of P. scapiflorum were geomorphology, temperature, and precipitation, among which dem, isothermality, and annual precipitation aere the key environmental factors. (3) Under different climate change models, the suitable habitat will be reduced by 24%-28% compared with the present situation by 2050s and 2070s. The highly suitable area would be downgraded to the medium or low suitable area to significantly reduce or even disappear, and the distribution center of P. scapiflorum tended to migrate to the westward and higher altitudes. 【Conclusion】 Study results are an important reference for the conservation, sustainable development, and utilization of wild resources and artificial cultivation of P. scapiflorum.

Key words: wild plant resources, Pegaeophyton scapiflorum, maximum entropy (MaxEnt) model, the potential distribution, Qihai-Xizang Plateau

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