[Data-driven study of complex socio-economic-natural ecosystems: Scales, processes and decision linkages].

The social-economic-natural system is a complex system for human survival and development, and the data-driven system research provides a new value-added orientation to enhance the cognition of the ecosystem. Under the new data context, the social-economic-natural complex system shows new features. The research object is gradually changing from a single element to a multi-factor coupling direction, which makes the data system more diversified, data sources more extensive, data expression more visualized. The research scale shows the characteristics of gradually expanding, and the research object would be more detailed. In the process of data identification, expression and visualization, it is therefore necessary to strengthen the coupling of time, space, structure, quantity and order, as well as to focus on the integration with decision making and local services. The future research of complex ecosystems in the new era should be carried out in terms of key scientific issues and supporting technologies, the role of scale and multi-factor coupling, as well as scientific and technological support for local and global governance. Under the continuous innovation of data, strengthening the cognition of multi-source data, long-term monitoring and time series still needs to be studied in depth. Carrying out data-driven analysis of complex ecosystems not only provides technical support for ecosystem services and sustainable development and enhances the long-term data sharing mechanism, but also provides more value support for realizing decision making and information dissemination.