An alternative protocol to estimate sample size at different spatial scales in studies of ecological communitie
Author and article information
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.
Cite this as
2018. An alternative protocol to estimate sample size at different spatial scales in studies of ecological communitie. PeerJ Preprints 6:e26823v1 https://doi.org/10.7287/peerj.preprints.26823v1Author comment
This is an abstract which has been accepted for the World Conference on Marine Biodiversity (WCMB 2018)
Sections
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Edlin Guerra conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Nuno Simoes conceived and designed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Juan J Cruz-Motta performed the experiments, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Maite Mascaró conceived and designed the experiments, analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
The data and codes have not yet been deposited, but will be once the article is published
Funding
EGC was supported by a DGAPA Post-doctoral Fellowship at the Universidad Nacional Autónoma de México (UNAM). This research was benefited by two research projects: (1) PE207416 (PAPIME, UNAM) under the supervision of MM, and (2) the Harte Research Institute de Texas A&M University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.