A method of geo-information science for studying carbon cycle and its mechanism of terrestrial ecosystems

There exists about 1.4～1.7GtC missing sink in the global carbon budgets. The missing sink might happen in terrestrial biosphere and coastal continental shelf. However, this guess is lack of support from scientific observation data and research methods. Progress in geo-information science is paving way for studying carbon cycle and its mechanisms of terrestrial ecosystems. To address the scientific issues such as temporal and spatial pattern of terrestrial ecosystem carbon sink, and driving mechanism and scenarios of carbon cycle, this paper proposes a method of geo-information science for studying carbon cycle of terrestrial ecosystems.Bottom-up approach and top-down approach are combined by means of scaling models. The bottom-up approach is based on observations of comprehensive network of carbon storage and carbon cycle process of terrestrial ecosystems, adaptive experiments of biological processes, and researches on carbon transportation processes of rivers. the top-down approach is based on detecting land cover change and retrieving ecological parameters by using satellite data. Retrieval models of carbon budgets are developed by means of the capacity of satellite remote sensing that can frequently supply surface information of geographical processes and ecological processes. On the basis of analyzing data-at-points collected by stations of Chinese Ecosystem Research Network, stations of Chinese Forest Ecosystem Research Network, and observation stations of HINAFLUX, combined with the retrieval models, a numerical simulation model of terrestrial ecosystem carbon cycle is constructed by means of surface theorem, grid generation method and grid computing technique. Pattern and process of carbon cycle are to be simulated; natural and human impacts on carbon cycle of terrestrial ecosystems are to be analyzed; and evolution trends of carbon cycle process of terrestrial ecosystems are to be discussed under the condition of global climate change.