生物多样性 ›› 2009, Vol. 17 ›› Issue (6): 652-663.DOI: 10.3724/SP.J.1003.2009.09065

所属专题: 群落中的物种多样性:格局与机制

• 论文 • 上一篇    下一篇

中国陆栖哺乳动物物种丰富度的地理格局及其与环境因子的关系

林鑫*(), 王志恒, 唐志尧, 赵淑清, 方精云   

  1. 北京大学城市与环境学院生态学系, 北京大学生态学研究与教育中心, 北京大学地表过程分析与模拟教育部重点实验室, 北京 100871
  • 收稿日期:2009-03-21 接受日期:2009-05-13 出版日期:2009-11-20 发布日期:2009-11-20
  • 通讯作者: 林鑫
  • 作者简介:*E-mail: linxin.pku@gmail.com
  • 基金资助:
    国家自然科学基金重点项目(40638039);国家自然科学基金重点项目(90711002);国家自然科学基金重点项目(30721140306)

Geographic patterns and environmental correlates of terrestrial mammal species richness in China

Xin Lin*(), Zhiheng Wang, Zhiyao Tang, Shuqing Zhao, Jingyun Fang   

  1. Department of Ecology, College of Urban and Environmental Sciences, Center for Ecological Research & Education, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871
  • Received:2009-03-21 Accepted:2009-05-13 Online:2009-11-20 Published:2009-11-20
  • Contact: Xin Lin

摘要:

物种丰富度的大尺度地理格局及其成因是宏观生态学和生物地理学的中心议题之一。本文利用中国陆栖哺乳动物分布数据, 结合高分辨率的气候、地形、植被等环境信息, 探讨了中国陆栖哺乳动物及主要类群的物种丰富度格局及其影响因素。结果显示, 中国陆栖哺乳动物物种丰富度具有显著的纬度梯度格局, 总体上呈现出由低纬度向高纬度逐渐减少的趋势, 并与宏观地形具有良好的对应关系; 其中, 亚热带、热带西部山区的物种丰富度最高, 而东部平原地区、西北干旱区和青藏高原腹地则是丰富度的低值区。各主要类群的物种丰富度格局既有相似性, 又存在差异。最优线性模型的分析结果显示, 由归一化植被指数(NDVI)、生态系统类型数和气温年较差构成的回归模型对哺乳动物物种丰富度格局的解释率最高, 其中NDVI对模型解释率的贡献最大, 这表明中国陆栖哺乳动物物种丰富度的地理分异受多种环境因素的共同影响, 其中植被生产力起主导作用。各主要类群的最优线性模型显示, 影响物种丰富度格局的主要环境因子因类群而异, 这可能反映了各类群进化历史及生理适应的差异。

关键词: 陆栖哺乳动物, 物种丰富度格局, 环境因子, 生产力假说

Abstract

Understanding macro-scale spatial patterns in species diversity and their underlying mechanisms is central to macroecology and biogeography. In this study, we explored geographic patterns of species richness and their environmental determinants for overall terrestrial mammals and each major mammalian order in China, using datasets of species distribution, climate, topography and vegetation. Species richness of terrestrial mammals exhibited significant latitudinal gradients, decreasing from south to north. High species richness generally occurred in tropical and subtropical mountains, whereas low species richness was found in the eastern plains, the arid areas of northwest regions, and central areas of the Qinghai-Tibet Plateau. Geographic patterns of species richness varied among mammalian orders. The best model, which included a remote sensing-based vegetation index (NDVI), number of ecosystems, and annual range of temperature, accounted for 66.2% of variation in overall mammal species richness, with NDVI being the most important determinant. This suggests that patterns of mammal richness in China are governed by the integrated effects of different environmental predictors, with vegetation productivity playing a major role. The best models for various orders of mammals identified different combinations of determinants, possibly reflecting differences in evolutionary history and physiological tolerances.

Key words: terrestrial mammals, patterns of species richness, environmental variables, productivity hypothesis