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A comprehensive framework for the evaluation of metacommunity structure

Authors

  • Steven J. Presley,

    1. Center for Environmental Sciences and Engineering and Dept of Ecology and Evolutionary Biology, Univ. of Connecticut, Storrs, CT 06269-4210, USA
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  • Christopher L. Higgins,

    1. Center for Environmental Sciences and Engineering and Dept of Ecology and Evolutionary Biology, Univ. of Connecticut, Storrs, CT 06269-4210, USA
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  • Michael R. Willig

    1. Center for Environmental Sciences and Engineering and Dept of Ecology and Evolutionary Biology, Univ. of Connecticut, Storrs, CT 06269-4210, USA
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S. J. Presley, Center for Environmental Sciences and Engineering and Dept of Ecology and Evolutionary Biology, Univ. of Connecticut, Storrs, CT 06269-4210, USA. E-mail: steven.presley@uconn.edu

Abstract

The metacommunity framework is a powerful platform for evaluating patterns of species distribution in geographic or environmental space. Idealized patterns (checkerboard, Clementsian, evenly spaced, Gleasonian and nested distributions) give the framework shape. Each pattern represents an area in a multidimensional continuum of metacommunity structures; however, the current approach to analysis of spatial structure of metacommunities is incomplete. To address this, we describe additional non-random structures and illustrate how they may be discerned via objective criteria. First, we distinguish three distinct forms of species loss in nested structures, which should improve identification of structuring mechanisms for nested patterns. Second, we define six quasi-structures that are consistent with the conceptual underpinnings of Clementsian, Gleasonian, evenly spaced and nested distributions. Finally, we demonstrate how combinations of structures at smaller spatial extents may aggregate to form Clementsian structure at larger extents. These refinements should facilitate the identification of best-fit patterns, associated structuring mechanisms, and informative scales of analysis and interpretation. This conceptual and analytical framework may be applied to network properties within communities (i.e. structure of interspecific interactions) and has broad application in ecology and biogeography.

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