A general biogeochemical model describing the responses of the C and N cycles in terrestrial ecosystems to changes in CO2, climate, and N deposition

A model that simulates carbon (C) and nitrogen (N) cycles in terrestrial ecosystems is developed. The model is based on the principle that the responses of terrestrial ecosystems to changes in CO 2 , climate, and N deposition will encompass enzymatic responses, shifts in tissue stoichiometry, change...

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Bibliographic Details
Published in:Tree Physiology
Main Authors: Rastetter, Edward B., Ryan, Michael G., Shaver, Gaius R., Melillo, Jerry M., Nadelhoffer, Knute J., Hobbie, John E., Aber, John D.
Format: Text
Language:English
Published: Oxford University Press 1991
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Online Access:http://treephys.oxfordjournals.org/cgi/content/short/9/1-2/101
https://doi.org/10.1093/treephys/9.1-2.101
Description
Summary:A model that simulates carbon (C) and nitrogen (N) cycles in terrestrial ecosystems is developed. The model is based on the principle that the responses of terrestrial ecosystems to changes in CO 2 , climate, and N deposition will encompass enzymatic responses, shifts in tissue stoichiometry, changes in biomass allocation among plant tissues, altered rates of soil organic matter turnover and N mineralization, and ultimately a redistribution of C and N between vegetation and soils. The model is a highly aggregated, process-based, biogeochemical model designed to examine changes in the fluxes and allocation of C and N among foliage, fine roots, stems, and soils in response to changes in atmospheric CO 2 concentration, temperature, soil water, irradiance, and inorganic nitrogen inputs. We use the model to explore how changes in CO 2 concentration, temperature, and N inputs affect carbon storage in two ecosystems: arctic tundra and temperate hardwood forest. The qualitative responses of the two ecosystems were similar. Quantitative differences are attributed to the initial distribution of C and N between vegetation and soils, to the amounts of woody tissue in the two ecosystems, and to their relative degree of N limitation. We conclude with a critical analysis of the model’s strengths and weaknesses, and discuss possible future directions.