Publication
SSP: An R package to estimate sampling effort in studies of ecological communities
Publisher:
Cold Spring Harbor Laboratory
Date:
21-03-2020
DOI:
10.1101/2020.03.19.996991
Abstract: SSP (simulation-based s ling protocol) is an R package that uses simulation of ecological data and dissimilarity-based multivariate standard error ( MultSE ) as an estimator of precision to evaluate the adequacy of different s ling efforts for studies that will test hypothesis using permutational multivariate analysis of variance. The procedure consists in simulating several extensive data matrixes that mimic some of the relevant ecological features of the community of interest using a pilot data set. For each simulated data, several s ling efforts are repeatedly executed and MultSE calculated. The mean value, 0.025 and 0.975 quantiles of MultSE for each s ling effort across all simulated data are then estimated and standardized regarding the lowest s ling effort. The optimal s ling effort is identified as that in which the increase in s ling effort do not improve the precision beyond a threshold value (e.g. 2.5 %). The performance of SSP was validated using real data, and in all ex les the simulated data mimicked well the real data, allowing to evaluate the relationship MultSE – n beyond the s ling size of the pilot studies. SSP can be used to estimate s le size in a wide range of situations, ranging from simple (e.g. single site) to more complex (e.g. several sites for different habitats) experimental designs. The latter constitutes an important advantage, since it offers new possibilities for complex s ling designs, as it has been advised for multi-scale studies in ecology.