生物多样性 ›› 2017, Vol. 25 ›› Issue (4): 355-363.  DOI: 10.17520/biods.2017037

所属专题: 生物多样性与生态系统功能

• 综述 • 上一篇    下一篇

大数据时代的生物多样性科学与宏生态学

张健*()   

  1. 华东师范大学生态与环境科学学院, 上海 200241
  • 收稿日期:2017-02-15 接受日期:2017-04-07 出版日期:2017-04-20 发布日期:2017-04-20
  • 通讯作者: 张健
  • 基金资助:
    基金项目: 中组部千人计划青年人才项目和华东师范大学紫江优秀青年项目

Biodiversity science and macroecology in the era of big data

Jian Zhang*()   

  1. School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241
  • Received:2017-02-15 Accepted:2017-04-07 Online:2017-04-20 Published:2017-04-20
  • Contact: Zhang Jian

摘要:

高质量的生物多样性数据是认知生物多样性的起源和维持机制及应对其丧失风险的科学基础。当前, 在新物种发现、已知物种的地理分布、种群数量与时空动态、物种进化史、功能性状、物种与环境之间以及物种与物种之间的相互作用等7个方面都存在着知识上的空缺。大数据时代的到来为弥补这些知识空缺提供了可能,大数据的挖掘及其应用最近已成为国际生物多样性与宏生态学研究的前沿内容。如何有效地利用和分析不断增长的生物多样性大数据是生物多样性研究面临的一个极大挑战。本文通过全球、大陆和区域尺度上的研究案例展示了大数据在生物多样性研究中应用的新进展, 内容涉及森林覆盖变化、保护生态学、生物多样性与生态系统功能、气候变化对生物多样性的影响等。最后, 对大数据在生物多样性研究中存在的数据采集、处理和分析等方面的问题进行了总结, 并对其潜在应用前景进行了探讨。

关键词: 大数据科学, 保护生物学, 生物多样性信息学, 宏系统生态学, 公众科学

Abstract

High-quality biodiversity data are the scientific basis for understanding the origin and maintenance of biodiversity and dealing with its extinction risk. Currently, we identify at least seven knowledge shortfalls or gaps in biodiversity science, including the lack of knowledge on species descriptions, species geographic distributions, species abundance and population dynamics, evolutional history, functional traits, interactions between species and the abiotic environment, and biotic interactions. The arrival of the current era of big data offers a potential solution to address these shortfalls. Big data mining and its applications have recently become the frontier of biodiversity science and macroecology. It is a challenge for ecologists to utilize and effectively analyze the ever-growing quantity of biodiversity data. In this paper, I review several biodiversity-related studies over global, continental, and regional scales, and demonstrate how big data approaches are used to address biodiversity questions. These examples include forest cover changes, conservation ecology, biodiversity and ecosystem functioning, and the effect of climate change on biodiversity. Furthermore, I summarize the current challenges facing biodiversity data collection, data processing and data analysis, and discuss potential applications of big data approaches in the fields of biodiversity science and macroecology.

Key words: big data science, conservation biology, biodiversity informatics, macrosystems ecology, citizen science