One of the clearest signals of human impact on a global scale is the rapidly rising concentration of greenhouse gases like carbon dioxide (CO2) in the atmosphere as a result of combustion of fossil fuels and deforestation. While human-driven changes in the composition of the atmosphere are well documented, interactions and feedbacks between the biosphere (plants, animals and microbes) and the changing atmospheric composition are not adequately understood. Research using global satellite observation is helping to refine our understanding of the seasonal changes in the way climate and soils control the exchange of greenhouse gases between the land surface and the air.
Computer modeling studies assist in understanding the role of terrestrial plants and soils in the cycling of carbon to and from the atmosphere. Historical climate and land surface data sets are used as additional inputs to drive a global ecosystem model at 1 degree latitude/longitude resolution. This research has produced a dynamic picture of the contemporary balance between photosynthetic fixation and microbial respiration of CO2.
As depicted in the image shown here , the CASA model predicts that high seasonal levels of net ecosystem respiration already occur in northern forests and tundra zones where future climate change is expected to be greatest. The use of satellite sensor data to estimate global plant production captures many of the effects of land cover change (urbanization, deforestation and cultivation) on the dynamics of the carbon cycle. Model results also suggest that the large amounts of carbon shown to be stored in soils may be released to the atmosphere at significantly faster rates if the climate becomes warmer.
The CASA model is a good example of using satellite data to assist in forming public policy related to land use change and agricultural development and how these influence the global atmosphere. In addition, CASA furthers our understanding of the role of natural ecosystems in the greenhouse effect.
COLLABORATORS: Carnegie Institution of Washington, Stanford University, University of California at Berkeley.
For more information on the CASA model and this research project, click here.
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