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林业科学 ›› 2020, Vol. 56 ›› Issue (5): 184-192.doi: 10.11707/j.1001-7488.20200521

• 研究简报 • 上一篇    下一篇

基于MaxEnt模型分析胡杨潜在适宜分布区

郭飞龙1,徐刚标1,*,卢孟柱1,2,孟艺宏1,袁承志1,郭恺琦1   

  1. 1. 中南林业科技大学林木遗传育种实验室 长沙 410004
    2. 浙江农林大学 杭州 311300
  • 收稿日期:2019-04-04 出版日期:2020-05-01 发布日期:2020-06-13
  • 通讯作者: 徐刚标
  • 基金资助:
    国家重点研发计划项目(2016YFC0503100);中南林业科技大学研究生科技创新基金项目(CX20192071)

Prediction of Potential Suitable Distribution Areas for Populus euphratica Using the MaxEnt Model

Feilong Guo1,Gangbiao Xu1,*,Mengzhu Lu1,2,Yihong Meng1,Chengzhi Yuan1,Kaiqi Guo1   

  1. 1. The Laboratory of Forest Genetics, Central South University of Forestry and Technology Changsha 410004
    2. Zhejiang A&F University Hangzhou 311300
  • Received:2019-04-04 Online:2020-05-01 Published:2020-06-13
  • Contact: Gangbiao Xu

摘要:

目的: 胡杨是干旱区的主要建群种,对维持干旱地区的生态环境稳定具有重要意义。探讨限制胡杨分布的主导环境变量,模拟胡杨潜在适宜分布区,可为胡杨资源保护与恢复提供理论依据。方法: 基于全球胡杨226个现有居群分布地理信息以及4类综合环境变量(气候、地形、土壤、水文),采用MaxEnt模型,模拟胡杨潜在适宜分布区;综合使用受试者工作特征曲线、刀切法、环境变量贡献率及置换重要值,分析MaxEnt模型可信度,比较采用单一气候变量与4类综合环境变量模拟结果的准确性,探讨制约胡杨地理分布的环境变量。结果: 1)受试者工作特征曲线下的面积(AUC值)显示,基于气候变量与4类综合环境变量的MaxEnt模型训练集分别为0.983±0.002、0.982±0.001,验证集分别为0.980±0.006、0.967±0.009,表明2种不同变量参数的数据集对AUC值影响较小,模拟效果好,可信度高。2)基于环境变量贡献率、置换重要值以及刀切法检验的结果,采用4类综合环境变量进行MaxEnt模型模拟,可挖掘影响胡杨分布的更多有效环境变量,胡杨地理分布主要受最干月份降水量、最热季节降水量、10~40 cm土壤含水量、根部土壤湿度、土壤水分蒸发量等4类综合环境变量影响;3)基于气候变量模拟的胡杨适宜分布面积是4类综合环境变量模拟结果的4.33倍,4类综合环境变量模拟的胡杨适宜分布区能够体现胡杨沿河岸分布的细节特征。4)基于MaxEnt模型模拟的胡杨适宜分布面积远大于胡杨的实际分布面积,暗示着胡杨人工林具有较大的发展潜力。结论: 胡杨地理分布受多种环境变量影响,仅以气候变量模拟的胡杨适宜分布区与实际分布范围存在较大偏差。4类综合环境变量模拟的结果,更能反映胡杨现实居群的分布特征。本研究结果可为退化的胡杨林保护、修复提供理论参考。

关键词: 胡杨, MaxEnt, 环境变量, 适宜分布区

Abstract:

Objective: Populus euphratica is an important tree species in arid areas,the species is of great significance for maintaining the ecological environment stability in arid areas. The paper tries to identify the dominant environmental variables that limit the distribution of P. euphratica, and to predict its suitable distribution area,in order to provide a theoretical basis for the protection and restoration of the species. Methods: The geographical information of 226 existing occurrences of P. euphratica and four types of environmental variables,including climate,topography,soil and hydrology were analyzed using the MaxEnt ecological niche modeling to simulate the potential suitable distribution areas for the species. Evaluation of credibility of the MaxEnt model,comparison of the accuracies of simulation using single climate variable and four types of environmental variables,and identification of the environmental variables limiting the distribution of the species were carried out with combination of method of the receiver-operating characteristic curve (ROC),the jack knife,the percent contribution of the environment variables and the permutation importance for the analyses. Results: 1) The area under the receiver-operating characteristic curve (AUC) showed that the training data of the single climate variable and four types of environmental variables was 0.983±0.002 and 0.982±0.001,respectively. The test data was 0.980±0.006 and 0.967±0.009,respectively. It indicated that two different quantitative data sets had less influence on AUC value and the simulation performed well with a very high credibility. 2) The percent contribution,permutation importance and jack knife showed that the simulation with the four types of environmental variables could identify more effective environmental variables affecting the distribution of P. euphratica. The geographical distribution of the species was affected by precipitation of the driest month and the warmest quarter,the soil moisture content (10-40 cm underground),the soil moisture around root system and the evapotranspiration of soil water. 3) The simulated potential suitable area based on climate variable expanded by 4.33 times compared to that on the four types of environmental variables. The simulation based on the four types of environmental variables reflects more details of distribution such that along riverbank. 4) The suitable distribution area simulated by the MaxEnt model was much larger than the actual distribution area,implying great potential for development of plantations of P. euphratica. Conclusion: The distribution of P. euphratica is affected by many environment variables. There is large deviation between the simulated distribution area using only climate variable and the actual distribution range of this species. The simulation based on four types of environmental variables reflects more characteristics of the actual distribution. This study provides a theoretical basis for the protection and restoration of the degraded P. euphratica forest.

Key words: Populus euphratica, MaxEnt, environmental variable, suitable distribution

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