Multi-scaled drivers of ecosystem state: quantifying the importance of the regional spatial scale

Authors

  • K. S. Cheruvelil,

    Corresponding author
    1. Department of Fisheries and Wildlife, 480 Wilson Road, Michigan State University, East Lansing, Michigan 48824 USA
    2. Lyman Briggs College, 919 E Shaw Lane, Room E-35 East Holmes Hall, Michigan State University, East Lansing, Michigan 48825 USA
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  • P. A. Soranno,

    1. Department of Fisheries and Wildlife, 480 Wilson Road, Michigan State University, East Lansing, Michigan 48824 USA
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  • K. E. Webster,

    1. Department of Fisheries and Wildlife, 480 Wilson Road, Michigan State University, East Lansing, Michigan 48824 USA
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    • Present address: Trinity College Dublin, School of Natural Sciences, Dublin 2 Ireland.

  • M. T. Bremigan

    1. Department of Fisheries and Wildlife, 480 Wilson Road, Michigan State University, East Lansing, Michigan 48824 USA
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  • Corresponding Editor: E. H. Stanley.

Abstract

The regional spatial scale is a vital linkage for the informed extrapolation of results from local to continental scales to address broad-scale environmental problems. Among-region variation in ecosystem state is commonly accounted for by using a regionalization framework, such as an ecoregion classification. Rarely have alternative regionalization frameworks been tested for variables measuring ecosystem state, nor have the underlying relationships with the variables that are used to define them been assessed. In this study, we asked two questions: (1) How much among-region variation is there for ecosystems and does it differ by regionalization framework? (2) What are the likely causes of this among-region variation? We present a case study using a large data set of lake water chemistry, uni- and multi-scaled hydrogeomorphic and anthropogenic driver variables that likely influence lake chemistry at the subcontinental scale, and seven existing regionalization frameworks. We used multilevel models to quantify and explain within- and among-region variation in lake water chemistry. Our models account for local driver variables of ecosystem variation within regions, differences in regional mean ecosystem state (i.e., random intercepts in multilevel models), and differences in relationships between local drivers and ecosystem state by region (i.e., random slopes in multilevel models). Using one of the best performing regionalization frameworks (Ecological Drainage Units), we found that for lake phosphorus and alkalinity: (1) a majority of all the variation in water chemistry among the studied lakes occurred among regions, (2) very few regional-scale landscape driver variables were required to explain among-region variation in lake water chemistry, (3) a much higher proportion of the total variation among lakes was explained at the regional scale than at the local scale, and (4) some relationships between local-scale driver variables and lake water chemistry varied by region. Our results demonstrate the importance of considering the regional spatial scale for broad-scale research and ecosystem management and conservation. Our quantitative approach can be easily applied to other response variables, ecosystem types, geographic areas, and spatial extents to inform ecosystem responses to global environmental stressors.

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