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Elements of Metacommunity Structure

EMS Guide

Using EMS Analyses in Macroecological Studies

In 2009, we expanded the approach of Leibold and Mikkelson (2002) to include multiple axis of variation to more adequately assess metacommunity structure in Paraguayan bats, which are know to respond to multiple environmental gradients (Presley et al. 2009). In 2010, we distinguish three distinct forms of species loss in nested structures, which should improve identification of structuring mechanisms for nested patterns; we also define six quasi-structures that are consistent with the conceptual underpinnings of Clementsian, Gleasonian, evenly spaced, and nested distributions (Presley et al. 2010). This analytical approach has been applied to a variety of systems, including Hungarian stream fishes (Eros et al. 2014), Mexican bats (Lopez-Gonzalez et al. 2012), and Puerto Rican Snails (Presley et al. 2011, Willig et al. 2011). Most recently we used this approach to examine the effects of deforestation in the Atlantic Forest; small mammal distributions were consistent with expectations based on historical biogeography, suggesting that anthropogenic activities have not yet greatly affected biogeographic distributions and emergent metacommunity structure (de la Sancha et al. 2014).

  • Medina Torres, K.M.* and C.L. Higgins. 2016. Taxonomic and functional organization in metacommunity structure of stream-fish assemblages among and within river basins in Texas. Aquatic Ecology 50:247-259.
  • De la Sancha, N.U., C.L. Higgins, S.J. Presley, and R.E. Strauss. 2014. Metacommunity structure in a highly fragmented forest: has deforestation in the Atlantic Forest altered historic biogeographic patterns? Diversity and Distributions 20:1058-1070.
  • Erős, T., P. Takács, P. Sály, C.L. Higgins, P. Bíró, and D. Schmera. 2014. Quantifying temporal variability in the metacommunity structure of stream fishes: the influence of non-native species and environmental drivers. Hydrobiologia 722:31-43.
  • Lopez-Gonzalez, C., S.J. Presley, A. Lozano, R.D. Stevens, and C.L. Higgins. 2012. Metacommunity structure of Mexican bats: a test of metacommunity paradigms in an area of high geographic and environmental complexity. Journal of Biogeography 39:177-192.
  • Willig, M.R., S.J. Presley, C.P. Bloch, I. Castro-Arellano, L. Cisneros, C.L. Higgins, and B.T. Klingbeil. 2011. Tropical metacommunities and elevational gradients: disentangling effects of forest type from other elevational factors. Oikos 120:1497-1508.
  • Presley, S.J., M.R. Willig, C.P. Bloch, I. Castro-Arellano, C.L. Higgins, and B.T. Klingbeil. 2011. A complex metacommunity structure for gastropods along an elevational gradient: axes of specialization and environmental variation. Biotropica 43:480-488.
  • Presley, S.J., C.L. Higgins, and M.R. Willig. 2010. A comprehensive framework for the evaluation of metacommunity structure. Oikos 119:908-917.
  • Presley, S.J., C.L. Higgins, C. Lopez-Gonzalez C, and R.D. Stevens. 2009. Elements of metacommunity structure of Paraguayan bats: multiple gradients require analysis of multiple ordination axes. Oecologia 160:781:793.
  • See the Metacommunity Structure website at the University of Connecticut (maintained by S.J. Presley) for more information

The computer programs used in the aforementioned studies are available in the following library of MATLAB functions.  MATLAB is a "high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation." (The MathWorks). The folder should be downloaded and unzipped into a directory within the "toolbox" folder of the MATLAB directory and the name of the directory must be added to the MATLAB search path (type help addpath in MATLAB for additional information). In addition to these functions, you will need the basic Matlab software and the Statistics toolbox provided from Mathworks.  Once everything is installed, you will only need to call the "metacommunity" function. You should copy the usage statement below and paste it into the MATLAB COMMAND WINDOW. Supply the necessary input arguments, and away you go!!!