Human Influences on Water Quality in Great Lakes Coastal Wetlands

被引:0
|
作者
John A. Morrice
Nicholas P. Danz
Ronald R. Regal
John R. Kelly
Gerald J. Niemi
Euan D. Reavie
Tom Hollenhorst
Richard P. Axler
Anett S. Trebitz
Anne M. Cotter
Gregory S. Peterson
机构
[1] U.S. Environmental Protection Agency,Mid
[2] University of Minnesota Duluth,Continent Ecology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development
[3] University of Minnesota Duluth,Center for Water and the Environment, Natural Resources Research Institute
[4] University of Minnesota Duluth,Department of Mathematics and Statistics
[5] University of Minnesota Duluth,Department of Biology
来源
Environmental Management | 2008年 / 41卷
关键词
Water quality; Nutrients; Anthropogenic stress; Landscape; Coastal wetlands; Great Lakes; Biogeography; Hydrogeomorphic classification;
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中图分类号
学科分类号
摘要
A better understanding of relationships between human activities and water chemistry is needed to identify and manage sources of anthropogenic stress in Great Lakes coastal wetlands. The objective of the study described in this article was to characterize relationships between water chemistry and multiple classes of human activity (agriculture, population and development, point source pollution, and atmospheric deposition). We also evaluated the influence of geomorphology and biogeographic factors on stressor-water quality relationships. We collected water chemistry data from 98 coastal wetlands distributed along the United States shoreline of the Laurentian Great Lakes and GIS-based stressor data from the associated drainage basin to examine stressor-water quality relationships. The sampling captured broad ranges (1.5–2 orders of magnitude) in total phosphorus (TP), total nitrogen (TN), dissolved inorganic nitrogen (DIN), total suspended solids (TSS), chlorophyll a (Chl a), and chloride; concentrations were strongly correlated with stressor metrics. Hierarchical partitioning and all-subsets regression analyses were used to evaluate the independent influence of different stressor classes on water quality and to identify best predictive models. Results showed that all categories of stress influenced water quality and that the relative influence of different classes of disturbance varied among water quality parameters. Chloride exhibited the strongest relationships with stressors followed in order by TN, Chl a, TP, TSS, and DIN. In general, coarse scale classification of wetlands by morphology (three wetland classes: riverine, protected, open coastal) and biogeography (two ecoprovinces: Eastern Broadleaf Forest [EBF] and Laurentian Mixed Forest [LMF]) did not improve predictive models. This study provides strong evidence of the link between water chemistry and human stress in Great Lakes coastal wetlands and can be used to inform management efforts to improve water quality in Great Lakes coastal ecosystems.
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页码:347 / 357
页数:10
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