利用大数据思维的湖泊湿地生态研究

Strengthening ecologic research of lakes and wetlands by big data thinking

针对水利工程运行对湖泊湿地影响动态关联研究、湖泊湿地生态系统保护与修复理论研究、湖泊生态补偿制度体系建立存在的数据匮缺问题,探讨了利用湖泊湿地生态监测积累生态大数据,强化湖泊湿地生态研究的基本思路。通过宏观监测和定位连续监测相结合的跨学科监测手段,将表征湿地生态系统结构、过程、功能、生物多样性的生态大数据进行多区域、多尺度耦合,定量化揭示湖泊水位-候鸟生境-候鸟种群数量的动态关联特征,为水利工程水位优化调度提供重要依据;利用大数据制定耦合生态系统各要素和主要生态过程的生态修复技术方案,并建立链接生态系统服务供给者和受益者的生态补偿制度,为湖泊湿地生态系统管理和生态修复、生态补偿措施实施提供数据支撑。

Aiming at the data lacking in the researches of the dynamic impact of water conservancy project on lakes and wetlands, the theoretical study of lake ecosystem protection and restoration, the establishment of lake ecological compensation system, this paper discusses the basic idea of using lake wetland ecological monitoring to accumulate ecological big data and strengthen lake wetland study. Through multi-disciplinary monitoring methods that combine macro-monitoring and positioning continuous monitoring, we can couple the ecological big data that characterizes wetland ecosystem structure, process, function and biodiversity in a multi-region and multi-scale way, so that the dynamic correlations of wetland water level, migratory bird habitats and migratory population can be quantitatively revealed, providing important basis for optimal regulation of water level in water conservancy projects. Big data can also help to develop ecological restoration technology solutions that link the various elements of ecosystems and major ecological processes, and ecological compensation systems that link ecosystem services providers and beneficiaries, providing data support for lake and wetland ecosystem management and ecological restoration, and ecological compensation measures.