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Measures of precision for dissimilarity‐based multivariate analysis of ecological communities
Authors:Marti J Anderson  Julia Santana‐Garcon
Institution:1. New Zealand Institute for Advanced Study (NZIAS), Massey University, Auckland, New Zealand;2. The UWA Oceans Institute (M470) and School of Plant Biology, The University of Western Australia, Perth, Australia
Abstract:Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity‐based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity‐based standard error (MultSE) as a useful quantity for assessing sample‐size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided.
Keywords:Assemblage data  community ecology  dissimilarities  multivariate analysis     permanova     precision  replicates  sampling design  standard error  variability
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