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AON: Carbon, Water, and Energy Balance of the Arctic Landscape at

Flagship Observatories and in a Pan-Arctic Network Project.


Ridge Station

This AON project is a collaborative project between the Ecosystems Center at the Marine Biological Laboratory, the Institute of Arctic Biology at the University of Alaska and the Department of Ecology and Evolutionary Biology at the University of Michigan. It focuses on carbon, water, and surface energy exchanges of the Arctic landscape. These are major regulatory components of the Arctic System, forming a key interface between the land surface, the atmosphere, and the oceans. More information on the The Arctic Observing Network (AON) program is available from the National Science Foundation and from the Study of Environmental Arctic Change web site.

The first key aspect of this research is data collection as integrated, multivariable time series, with the aim of using the temporal correlations among variables to sort out controls on short- versus long-term rates of change of individual variables and of the whole system. A second key aspect of this project is the creation of a network of observatories, in the U.S. and other arctic countries, in which carbon, water, and surface energy budgets are monitored at the landscape scale. One long-term aim of this network is to facilitate the development of PanArctic models of terrestrial responses and feedbacks to climate change. Third, because each of the sites in this network is also the site of extensive long-term, fine-scale research on biogeochemical processes and on the individuals, populations, and communities of plants and animals that mediate those processes, we will establish a platform for scaling up this fine-scale knowledge to predict changes in the functioning of whole arctic landscapes. Fourth, a major product of this research will be the creation of a database for use in modeling the larger Arctic System, including terrestrial, atmospheric, and oceanic components and their interactions. Finally, the proposed research includes an education component that will provide undergraduate and graduate students with unique opportunities in the classroom, in the field, and in modeling and analysis.

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