大数据背景下的生态系统观测与研究

Ecosystem Observation and Research under Background of Big Data

全球变化和可持续发展等一系列全球化的资源环境问题日益严峻,成为国际社会关注及科学研究热点,生态学的研究重点也逐渐开始由小尺度的个体、群落和生态系统向区域、大陆乃至全球尺度转变。同时,伴随传感器技术和信息网络技术发展,生态系统观测也从短时间观测逐渐向长期观测以及生态系统的宏观结构和生态服务时空格局变化协同观测转变;由过去的定位及小规模合作观测向区域甚至全球大规模联合的网络化观测、天-空-地立体综合观测方向转变。生态学研究已经进入大数据时代,如何应用大数据技术,实现传统的基于过程的生态学研究与基于大数据驱动的生态学研究的有机整合,推动生态学大理论发展、区域及全球生态系统演变机理研究,支撑以应对全球气候变化、生态系统功能维持等为核心的人类社会可持续发展理论和应用研究,是大数据时代生态观测研究面临的重大挑战及机遇。文章评述了生态系统观测研究现状,探讨了大数据背景下生态系统观测研究的重要特征,并建议遵循"大科学、大数据"理念,组织实施国家生态系统观测大科学工程建设,实现我国生态观测研究与全球生态观测研究体系的融合,实现在区域、国家及全球尺度上观测地球生命系统变化,诊断生态系统功能状态,理解生态系统过程机理、维持和保护生态系统功能,服务人类社会可持续发展的科技目标。

As a series of global problems, such as global change and sustainable development, have become the hotspots in the literature, ecological research has evolved from local scale to regional, continental or even global scale. Meanwhile, with the development of sensor and network technology, the focus of ecosystem observations has changed from short-time observations to long-term observations on the macrostructure of ecosystem and the spatio-temporal pattern of ecosystem services, also from the small-scale observation to regional and even global scale network observation and space-ground integrated observation. In summary, ecological studies have entered the big data era. It is a challenge and opportunity that how to apply the new technology, multi-disciplinary knowledge integration, multi-scale and multisource data integration, and big-data-driven ecological model development to achieve the integration between traditional ecological processbased ecological research and big-data-driven ecological research. Big-data-driven ecology should promote the development of ecological theory, mechanism research of regional and global ecosystem evolution and sustainable development of human society under the background of global climate change, biodiversity protection, and ecosystem function maintenance. This paper reviews the current status of ecosystem observation and research, and discusses the important characteristics of ecosystem observation and research under the background of big