An alternative protocol to estimate sample size at different spatial scales in studies of ecological communitie

, , ,
1 Facultad de Ciencias, CONACYT - Universidad Nacional Autónoma de México, Sisal, Yucatán, Mexico
2 Facultad de Ciencias, Universidad Nacional Autónoma de México, Sisal, Yucatán, Mexico
3 Department of Marine Sciences, Universidad de Puerto Rico, Mayagüez, Puerto Rico
DOI
10.7287/peerj.preprints.26823v1
Published
Accepted
Subject Areas
Biodiversity, Ecology, Marine Biology, Statistics
Keywords
simulation, community ecology, standard error, PERMANOVA, sampling design, dissimilarities, multivariate analysis, resampling
Copyright
© 2018 Guerra et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Guerra E, Simoes N, Cruz-Motta JJ, Mascaró M. 2018. An alternative protocol to estimate sample size at different spatial scales in studies of ecological communitie. PeerJ Preprints 6:e26823v1

Abstract

Deciding sample-size is a key step in any study based on statistical inference. Recently, a pioneer methodology applicable in the multivariate context was proposed by Anderson & Santana-Garcon (2015, DOI: 10.1111/ele.12385). This method is based on estimating the dissimilarity-based multivariate standard error (MultSE) of different sample efforts by double resampling the original data. However, this method has two limitations: (1) it is not possible to observe the behavior of MultSE beyond the original effort; and (2) the estimates are no longer independent when the same sampling units are used. We put forward an alternative method that overcomes both. The procedure consists in simulate a data matrix that contains the ecological properties of the community. Then, sampling is repeatedly executed, so that the following is achieved: (1) estimation of independent MultSE for greater efforts than the original; and (2) estimation of sample-size at different scales. These advantages were evaluated using four study cases.

Author Comment

This is an abstract which has been accepted for the World Conference on Marine Biodiversity (WCMB 2018)