Abstract
Looking through the three tendencies of Global Change Ecology in the past several years, there are two related to this chapter: (i) insisting on a long term of systematic observation, and building a data acquisition network; and (ii) strengthening systematic simulation study, deeply understanding the mechanism and rules of the earth’s coupling change and doing further prediction research. It is the scholars’ consensus that in the background of global changing, a long-term and multi-scale networking observational study of ecosystem would be the most effective method to reveal its evolvement rule, and system simulation is a basic tool to build and test theoretical assumptions and to predict the ecosystem’s evolvement directions. The Chinese Ecosystem Research Network (CERN) and the Chinese Terrestrial Ecosystems Flux Observation and Research Network (ChinaFLUX) take a wide participation in the International Long-Term Ecosystem Research Network (ILTER) and the Global Flux Observation and Research Programme (FLUXENT), and play an important role pushing the development of relevant academic subjects. At present, China’s stations in the ecosystem observation network almost cover its main diverse ecosystem types, and with these observation data, we launched deep analysis on the main types of ecosystems, of its photosynthetic carbon fixation, respiration of carbon emissions, dynamic time and space distribution rules of ecosystem’s net carbon exchange flux and the environmental and biological control mechanism, etc., with which we acquired a series of important scientific findings, and developed terrestrial ecosystem carbon-cycle process-mechanism model of forest, farmland, grassland, etc. and satellite remote sensing system of carbon balance evaluation. Readers can also get a comprehensive understanding of ecosystem modeling’s theories, methods, and its practice from this chapter’s massive cases and relevant essays.
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Yu, G. et al. (2015). Ecosystem Positioning Research and Models. In: Li, W. (eds) Contemporary Ecology Research in China. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48376-3_14
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DOI: https://doi.org/10.1007/978-3-662-48376-3_14
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