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Effects of Land Cover on Stream Ecosystems: Roles of Empirical Models and Scaling Issues

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Abstract

We built empirical models to estimate the effects of land cover on stream ecosystems in the mid-Atlantic region (USA) and to evaluate the spatial scales over which such models are most effective. Predictive variables included land cover in the watershed, in the streamside corridor, and near the study site, and the number and location of dams and point sources in the watershed. Response variables were annual nitrate flux; species richness of fish, benthic macroinvertebrates, and aquatic plants; and cover of aquatic plants and riparian vegetation. All data were taken from publicly available databases, mostly over the Internet. Land cover was significantly correlated with all ecological response variables. Modeled R 2 ranged from 0.07 to 0.5, but large data sets often allowed us to estimate with acceptable precision the regression coefficients that express the change in ecological conditions associated with a unit change in land cover. Dam- and point-source variables were ineffective at predicting ecological conditions in streams and rivers, probably because of inadequacies in the data sets. The spatial perspective (whole watershed, streamside corridor, or local) most effective at predicting ecological response variables varied across response variables, apparently in concord with the mechanisms that control each of these variables. We found some evidence that predictive power fell in very small watersheds (less than 1–10 km2), suggesting that the spatial arrangement of landscape patches may become critical at these small scales. Empirical models can replace, constrain, or be combined with more mechanistic models to understand the effects of land-cover change on stream ecosystems.

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Acknowledgements

This work was conducted as part of the “The Ecological Consequences of Altered Hydrologic Regimes” Working Group supported by the National Center for Ecological Analysis and Synthesis, a center funded by the National Science Foundation (NSF) (Grant DEB94-21535), the University of California at Santa Barbara, and the State of California. Additional funding for this project was provided by the Scientific Committee on Water Research (SCOWAR) of the International Council for Science (ICSU); REB and SB were supported by the USEPA STAR (WWS) program. We thank the other participants in the working group for helpful discussions and ideas. Margaret Palmer, Nina Caraco, and two anonymous reviewers provided helpful reviews of the manuscript. We are extremely grateful to everyone who took the time to suggest potential data sources and supply us with data, especially Joyce Boyd, Dan Parker, Craig Shirey, Shelly Miller, Paul Cocca, and David Argent. Finally, we acknowledge the contributions of the people who have worked over many years to collect and analyze samples, enter data, and maintain the databases that made this study possible. This is a contribution to the program of the Institute of Ecosystem Studies and SCOWAR. Although the data described in this article have been funded wholly or in part by the USEPA through its EMAP Surface Waters Program, it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement of the conclusions should be inferred.

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Authors and Affiliations

  1. Institute of Ecosystem Studies, Box AB, Millbrook, New York 12545, USA

    David L. Strayer

  2. Department of Civil and Environmental Engineering, University of Maryland, College Park, Maryland 20742, USA

    R. Edward Beighley

  3. National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, 735 State Street, Santa Barbara, California 93101, USA

    Lisa C. Thompson

  4. Department of Biology, University of Maryland, College Park, Maryland 20742, USA

    Shane Brooks

  5. Landscape Ecology Group, Department of Ecology and Environmental Science, Umeå University, SE-901 87 Umeå and Department of Natural and Environmental Sciences, Mid Sweden University, SE-851 70 Sundsvall, Sweden

    Christer Nilsson

  6. ECOBIO, Université de Rennes I, UMR ECOBIO 6553, Campus de Beaulieu, Avenue de General Leclerc, Rennes Cedex F-35242, France

    Gilles Pinay

  7. College of Ocean and Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195, USA

    Robert J. Naiman

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  1. David L. Strayer
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Strayer, D., Beighley, R., Thompson, L. et al. Effects of Land Cover on Stream Ecosystems: Roles of Empirical Models and Scaling Issues . Ecosystems 6, 407–423 (2003). https://doi.org/10.1007/PL00021506

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