Title: MODELING DENITRIFICATION IN TERRESTRIAL AND AQUATIC ECOSYSTEMS AT REGIONAL SCALES
Abstract: Ecological ApplicationsVolume 16, Issue 6 p. 2123-2142 Denitrification across Landscapes and Waterscapes MODELING DENITRIFICATION IN TERRESTRIAL AND AQUATIC ECOSYSTEMS AT REGIONAL SCALES Elizabeth W. Boyer, Elizabeth W. Boyer University of California, Department of Environmental Science, Policy, and Management, Berkeley, California 94720 USA 9 E-mail: [email protected] for more papers by this authorRichard B. Alexander, Richard B. Alexander U.S. Geological Survey, National Water Quality Assessment Program, Reston, Virginia 20192 USASearch for more papers by this authorWilliam J. Parton, William J. Parton Colorado State University, Natural Resource Ecology Laboratory, Fort Collins, Colorado 80523 USASearch for more papers by this authorChangsheng Li, Changsheng Li University of New Hampshire, Institute for the Study of Earth, Oceans, and Space, Durham, New Hampshire 03824 USASearch for more papers by this authorKlaus Butterbach-Bahl, Klaus Butterbach-Bahl Institute for Meteorology and Climate Research, Garmisch-Partenkirchen, GermanySearch for more papers by this authorSimon D. Donner, Simon D. Donner Princeton University, Woodrow Wilson School of Public and International Affairs, Princeton, New Jersey 08544 USASearch for more papers by this authorR. Wayne Skaggs, R. Wayne Skaggs North Carolina State University, Department of Biological and Agricultural Engineering, Raleigh, North Carolina 27695 USASearch for more papers by this authorStephen J. Del Grosso, Stephen J. Del Grosso U.S. Department of Agriculture, Agricultural Research Service, Fort Collins, Colorado 80526 USASearch for more papers by this author Elizabeth W. Boyer, Elizabeth W. Boyer University of California, Department of Environmental Science, Policy, and Management, Berkeley, California 94720 USA 9 E-mail: [email protected] for more papers by this authorRichard B. Alexander, Richard B. Alexander U.S. Geological Survey, National Water Quality Assessment Program, Reston, Virginia 20192 USASearch for more papers by this authorWilliam J. Parton, William J. Parton Colorado State University, Natural Resource Ecology Laboratory, Fort Collins, Colorado 80523 USASearch for more papers by this authorChangsheng Li, Changsheng Li University of New Hampshire, Institute for the Study of Earth, Oceans, and Space, Durham, New Hampshire 03824 USASearch for more papers by this authorKlaus Butterbach-Bahl, Klaus Butterbach-Bahl Institute for Meteorology and Climate Research, Garmisch-Partenkirchen, GermanySearch for more papers by this authorSimon D. Donner, Simon D. Donner Princeton University, Woodrow Wilson School of Public and International Affairs, Princeton, New Jersey 08544 USASearch for more papers by this authorR. Wayne Skaggs, R. Wayne Skaggs North Carolina State University, Department of Biological and Agricultural Engineering, Raleigh, North Carolina 27695 USASearch for more papers by this authorStephen J. Del Grosso, Stephen J. Del Grosso U.S. Department of Agriculture, Agricultural Research Service, Fort Collins, Colorado 80526 USASearch for more papers by this author First published: 01 December 2006 https://doi.org/10.1890/1051-0761(2006)016[2123:MDITAA]2.0.CO;2Citations: 182 Corresponding Editor: A. R. Townsend. For reprints of this Invited Feature, see footnote 1, p. 2055. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source–transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures. Citing Literature Volume16, Issue6December 2006Pages 2123-2142 RelatedInformation
Publication Year: 2006
Publication Date: 2006-12-01
Language: en
Type: review
Indexed In: ['crossref', 'pubmed']
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Cited By Count: 249
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