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Predicting Nitrogen Loading With Land-Cover Composition: How Can Watershed Size Affect Model Performance?

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Abstract

Watershed-wide land-cover proportions can be used to predict the in-stream non–point source pollutant loadings through regression modeling. However, the model performance can vary greatly across different study sites and among various watersheds. Existing literature has shown that this type of regression modeling tends to perform better for large watersheds than for small ones, and that such a performance variation has been largely linked with different interwatershed landscape heterogeneity levels. The purpose of this study is to further examine the previously mentioned empirical observation based on a set of watersheds in the northern part of Georgia (USA) to explore the underlying causes of the variation in model performance. Through the combined use of the neutral landscape modeling approach and a spatially explicit nutrient loading model, we tested whether the regression model performance variation over the watershed groups ranging in size is due to the different watershed landscape heterogeneity levels. We adopted three neutral landscape modeling criteria that were tied with different similarity levels in watershed landscape properties and used the nutrient loading model to estimate the nitrogen loads for these neutral watersheds. Then we compared the regression model performance for the real and neutral landscape scenarios, respectively. We found that watershed size can affect the regression model performance both directly and indirectly. Along with the indirect effect through interwatershed heterogeneity, watershed size can directly affect the model performance over the watersheds varying in size. We also found that the regression model performance can be more significantly affected by other physiographic properties shaping nitrogen delivery effectiveness than the watershed land-cover heterogeneity. This study contrasts with many existing studies because it goes beyond hypothesis formulation based on empirical observations and into hypothesis testing to explore the fundamental mechanism.

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Acknowledgments

We thank for the Department of Geography at Florida State University and the Department of Fisheries and Wildlife at Michigan State University for time release in conducting this research. The research reported in this study was partially supported by Florida State University Council on Research and Creativity and United States Environmental Protection Agency’s Science to Achieve Results Estuarine and Great Lakes program through funding to the CEER-GOM, USEPA Agreement No. R829458. Acknowledgments are due to Morton Winsberg for help in reviewing the early version of the manuscript and to the anonymous reviewers for their constructive comments that helped improve the scholarly quality of our manuscript.

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Authors and Affiliations

  1. Department of Biology, University of Florida, P.O. Box 118525, 220 Bartram Hall, Gainesville, FL, 32611, USA

    Tao Zhang

  2. Department of Geography, Florida State University, 113 Collegiate Loop, Tallahassee, FL, 32306, USA

    Xiaojun Yang

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  1. Tao Zhang
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  2. Xiaojun Yang
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Correspondence to Tao Zhang.

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Zhang, T., Yang, X. Predicting Nitrogen Loading With Land-Cover Composition: How Can Watershed Size Affect Model Performance?. Environmental Management 51, 96–107 (2013). https://doi.org/10.1007/s00267-012-9897-3

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  • DOI: https://doi.org/10.1007/s00267-012-9897-3

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