基于最大熵模型的不同尺度物种分布概率优化热点分析:以红色木莲为例

庄鸿飞1,2 张殷波3 王伟1,4 任月恒1 刘方正1 杜金鸿1 周越1

(1.国家环境保护区域生态过程与功能评估重点实验室中国环境科学研究院, 北京 100012)
(2.山西大学黄土高原研究所, 太原 030006)
(3.山西大学环境与资源学院, 太原 030006)
(4.中国三江并流区域生物多样性协同创新中心, 云南大理 671003)

【摘要】单一空间尺度构建的最大熵 (maximum entropy, MaxEnt) 模型是否具有代表性, 是MaxEnt模型应用与发展中面临的重要问题。本研究基于有效的地理分布位点数据, 利用最小凸多边形法 (the minimum convex polygon method) 在三江并流、云南省及全国3个空间尺度下分别识别了红色木莲 (Manglietia insignis) 的建模区域, 并进一步建立MaxEnt模型:使用ROC曲线分析法与遗漏率 (omission rate, OR) 检验评估MaxEnt模型预测精度;基于ArcGIS分析分布概率及其热点区域的分布趋势, 并通过分区统计工具Zonal识别潜在适宜分布区域的质心位置;采用刀切法检验环境因子贡献率。结果表明: (1) 不同尺度下红色木莲的MaxEnt模型都有良好的预测效果, 三江并流、云南省及全国尺度下的AUC值分别为0.936、0.887和0.930, OR值分别为0.18、0.15和0.20; (2) 各尺度红色木莲的适生区格局呈现一致性分布趋势, 集中在独龙江、怒江和澜沧江3个流域; (3) 3个空间尺度下红色木莲的地理分布受不同环境因子影响, 存在着尺度依赖效应。由此可见, 红色木莲在不同空间尺度下的预测模型有着稳定的性能表现与良好的预测效果。此外, 我们建议在野外实地调查与野生生物资源保护中加强对普通物种的关注, 在预测物种地理分布的研究中将MaxEnt模型与热点分析结合使用。

【关键词】 MaxEnt模型; 空间尺度; 红色木莲; 最小凸多边形; 热点分析; 普通物种;

【DOI】

【基金资助】 国家重点研发计划 (2016YFC0503304)

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    脚注

    [1]. (1) 尚忠慧 (2016) 基于Maxent的物种空间分布预测不确定性分析--以当归为例.硕士学位论文, 陕西师范大学, 西安. [^Back]

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This Article

ISSN:1005-0094

CN:11-3247/Q

Vol 26, No. 09, Pages 931-940

September 2018

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Article Outline

摘要

  • 1 材料与方法
  • 2 结果
  • 3 讨论
  • 附录Supplementary Material
  • 脚注

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