生态环境学报 ›› 2021, Vol. 30 ›› Issue (7): 1333-1341.DOI: 10.16258/j.cnki.1674-5906.2021.07.001

所属专题: 生物多样性专题汇编

• 研究论文 •    下一篇

基于矩阵分析法的鸟类与哺乳动物物种丰富度空间差异研究——以新疆为例

李海萍1(), 李光一2,*(), 万华伟3, 李利平4   

  1. 1.中国人民大学环境学院,北京 100872
    2.贵州省生态气象和卫星遥感中心,贵州 贵阳550002
    3.生态环境部卫星环境应用中心,北京 100093
    4.中国科学院空天信息创新研究院,北京 100094
  • 收稿日期:2021-02-07 出版日期:2021-07-18 发布日期:2021-10-09
  • 通讯作者: *李光一,女,助理工程师,硕士。E-mail: lgy_guangyi@163.com
  • 作者简介:李海萍(1965年生),女,副教授,博士,主要研究方向为环境地学、地理信息系统应用等。E-mail: lhping@ruc.edu.cn
  • 基金资助:
    国家自然科学基金项目(41801366);国家重点研发专项(2018YFC0507201)

Spatial Difference of Birds and Mammals Species Richness Based on Matrix Analysis: Taking Xinjiang as An Example

LI Haiping1(), LI Guangyi2,*(), WAN Huawei3, LI Liping4   

  1. 1. School of Environment & Natural Resources, Renmin University of China, Beijing 100872, China
    2. Guizhou Ecological Meteorology & Satellite Remote Sensing Center, Guiyang 550002, China
    3. Center for Satellite Applicationon Ecology and Environment, Ministry of Ecology and Environment, Beijing 100093, China
    4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
  • Received:2021-02-07 Online:2021-07-18 Published:2021-10-09

摘要:

新疆独特的地理环境和气候特征使之成为了野生动植物的基因宝库,复杂的生境孕育了众多特有的动物种群,探索其内部的物种丰富度空间差异,不仅充实了生物多样性的方法研究,同时也对维持该地区的生态稳定及生态环境可持续发展具有实际意义。该研究以新疆地区鸟类和哺乳动物10 km×10 km尺度的物种分布矢量数据为基础,结合其他多源空间数据,绘制出新疆鸟类与哺乳动物空间分布专题图,经矢量-栅格转换后进行重分类和空间统计,并据此分析鸟类与哺乳动物的物种丰富度空间分布模式及其核心聚集区,再通过矩阵分析等空间分析技术,深入探究了鸟类和哺乳动物丰富度的空间分布差异。结果显示,(1)北疆物种丰富度高于南疆,鸟类丰富度高于哺乳动物;二者高丰富度(H-H)区域主要集中在阿尔泰山、天山南北侧,占新疆全域5.46%;低丰富度(L-L)区域主要在西南部帕米尔高原一带,占全域面积2.85%。同一范围内二者物种丰富度存在两极化差异,即丰富度等级一高一低的地区(L-H和H-L)占2.99%,且主要位于中部地区,其余组合模式的区域分布比较分散。(2)不同的海拔高度内,物种丰富度差异显著,海拔高度低于0 m与高于4000 m的地区因生态系统单一,物种丰富度整体偏低,1000—2500 m高程内的生态系统最丰富,是鸟类与哺乳动物生长的适宜高度,物种不仅丰富多样,且丰富度也最复杂。

关键词: 物种丰富度, 矩阵分析, 叠加分析, 空间分布特征, 空间差异, 新疆

Abstract:

With its unique geographical environment and climatic characteristics, Xinjiang has become a genetic treasure house of wild animals and plants. The complex habitat has bred many unique animal populations. So exploring the spatial differences in species richness not only enriches the methodological research of biodiversity, but also it is of practical significance to maintain the ecological stability of the region and the sustainable development of the ecological environment. Therefore, based on the 10 km×10 km species vector data of birds and mammals in Xinjiang, combined with other multi-source data, the spatial distribution of species in Xinjiang was mapped and analyzed. And the data after vector to grid were used for reclassification and spatial statistics. The spatial patterns of richness and their core areas were analyzed. Then, through spatial analysis techniques such as matrix analysis, we have deeply explored the differences in the spatial distribution between birds and mammals. The results show that, (1) The richness in northern Xinjiang is higher than that in southern Xinjiang, and the abundance of birds is higher than that of mammals. The H-H areas are mainly in the Altai Mountains and the north and south of the Tianshan, accounting for 5.46% of the entire Xinjiang region, while the L-L areas are mainly in the southwestern Pamirs, accounting for 2.85%. There is a polarization difference between the two species in the same range. The H-L and L-H areas only account for 2.99%, and they are mainly located in the central region, and the regional distribution of the remaining combination modes is relatively scattered. (2) At different altitudes, the species richness is significantly different. Due to the single ecosystem where the altitude is lower than 0 m or higher than 4000 m, the species is less. The ecosystems within the height of 1000?2500 m are the most abundant, which is the appropriate altitudes for birds and mammals to grow. At the same time, the species is not only rich and diverse, but the difference in richness between the two is also the most complicated.

Key words: species richness, matrix analysis, overlay analysis, spatial distribution characteristics, spatial difference, Xinjiang

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