生物多样性 ›› 2018, Vol. 26 ›› Issue (1): 53-65.DOI: 10.17520/biods.2017189

• 生物编目 • 上一篇    下一篇

生物多样性信息资源.II.环境类型数据

张凤麟1,2, 王昕1,2, 张健1,2*()   

  1. 1 华东师范大学生态与环境科学学院, 浙江天童森林生态系统国家野外科学观测研究站, 上海 200241
    2 上海污染控制与生态安全研究院, 上海 200092
  • 收稿日期:2017-06-25 接受日期:2018-01-05 出版日期:2018-01-27 发布日期:2018-05-05
  • 作者简介:

    # 共同第一作者

  • 基金资助:
    中组部千人计划青年人才项目和国家自然科学基金(31670439)

Biodiversity information resources. II. Environmental data

Fenglin Zhang1,2, Xin Wang1,2, Jian Zhang1,2,*()   

  1. 1 Tiantong National Station for Forest Ecosystem Research, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241
    2 Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092
  • Received:2017-06-25 Accepted:2018-01-05 Online:2018-01-27 Published:2018-05-05
  • Contact: Zhang Jian
  • About author:

    # Co-first authors

摘要:

环境类型数据是研究生物多样性分布格局、多样性形成与维持机制、物种保育等很多重要生态学问题的基础。近年来, 随着环境监测网络在全球范围内的不断扩张与新监测手段的不断涌现, 区域和全球尺度上的不同类型的环境数据呈爆炸式增长。然而, 这些海量的数据零散地分布在互联网的各个角落, 给生物多样性研究人员了解数据信息、高效选择和利用数据等带来了挑战。面对环境数据来源广、分布零散的现状, 本文从气候、地形地貌土壤与生境异质性、土地覆盖、水文和其他等5个方面对环境数据进行整理, 并且选取其中一些使用频率较高的数据集, 从它们的数据来源、数据结构、数据获取方式、数据精度以及数据使用情况等方面举例介绍。本文共介绍了45个不同类型的数据集, 既包括WorldClim气候数据、HWSD (Harmonized World Soil Database)土壤数据等在生态学中频繁使用的数据集, 也包括气候变化速率、EarthEnv生境异质性数据、全球森林覆盖数据、全球光污染数据等最新发布或较少使用的数据集。另外, 需要指出的是, 这些数据集远不能涵盖目前所能获得并在持续增加的环境类型数据。作者希望本文的不完整总结能够为研究人员高效选择和有效利用这些和其它相似的环境数据提供参考。

关键词: 生物多样性信息学, 生物地理学, 宏生态学, 大数据, 数据共享

Abstract:

Environmental data are the basis for addressing many important ecological issues, including biodiversity distribution patterns, mechanisms of biodiversity formation and maintenance, and species conservation. Recently, many types of environment data at regional and global scales have dramatically increased, with the continuous expansion of global environment monitoring networks and emergence of new monitoring technologies. However, the vast amounts of data are scattered all around the world, making it much more difficult for biodiversity researchers to access detailed information and use these data efficiently. In this paper, we combine the main sources of environmental datasets, and classify them into five major groups, including (1) climate, (2) topography, soil and habitat heterogeneity, (3) land cover, (4) hydrology variables, and (5) other data sets. We then select several datasets with high-frequency usage to briefly introduce the data source, data structure, data availability, and data quality. We also select several previous studies to showcase the use of these datasets. In summary, we include 45 environmental data sets in this paper, covering several frequently used data in ecology (e.g., WorldClim and Harmonized World Soil Database), as well as some latest released or seldom used data (e.g., climate change velocity, EarthEnv habitat heterogeneity data, global forest coverage data, and global light pollution data). In addition, it is important to point out that these data sets are only a small fraction of currently available and continuously increasing environmental data. Overall, we hope that the incomplete list of environmental data can provide guidelines for researchers to select and utilize them and other similar data accurately and effectively.

Key words: Key Words: biodiversity informatics, biogeography, macroecology, big data, data sharing