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Measures of precision for dissimilarity-based multivariate analysis of ecological communities

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...

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Detalles Bibliográficos
Autores principales: Anderson, Marti J, Santana-Garcon, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311441/
https://www.ncbi.nlm.nih.gov/pubmed/25438826
http://dx.doi.org/10.1111/ele.12385
Descripción
Sumario: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.