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© 2014 Dallas and Drake. Understanding the factors responsible for structuring ecological communities is a central goal in community ecology. Previous work has focused on determining the relative roles of two classes of variables (e.g., spatial and environmental) on community composition. However, this approach may ignore the disproportionate impact of variables within classes, and is often confounded by spatial autocorrelation leading to collinearity among variables of different classes. Here, we combine pattern-based metacommunity and machine learning analyses to characterize metacommunity structure of zooplankton from lakes in the northeast United States and to identify environmental, spatial, and geographic covariates associated with metacommunity structure. Analyses were performed for the entire metacommunity and for three zooplankton subsets (cladocerans, copepods, and rotifers), as the variables associated with community structure in these groups were hypothesized to differ. Species distributions of all subsets adhered to an environmental, spatial, and/or geographic gradient, but differed in metacommunity pattern, as copepod species distributions responded independently of one another, while the entire zooplankton metacommunity, cladocerans, and rotifers replaced one another in discrete groups. While environmental variables were nearly always the most important to metacommunity structure, the relative importance of variables differed among zooplankton subsets, suggesting that zooplankton subsets differ in their environmental tolerances and dispersal-limitation.

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