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Title: How many sites? Methods to assist design decisions when collecting multivariate data in ecology
Authors: Maslen, Ben
Popovic, Gordana
Lim, Michelle
Marzinelli, Ezequiel Miguel
Warton, David
Keywords: Science::Biological sciences
Issue Date: 2023
Source: Maslen, B., Popovic, G., Lim, M., Marzinelli, E. M. & Warton, D. (2023). How many sites? Methods to assist design decisions when collecting multivariate data in ecology. Methods in Ecology and Evolution, 14(6), 1564-1573.
Journal: Methods in Ecology and Evolution 
Abstract: Sample size estimation through power analysis is a fundamental tool in planning an ecological study, yet there are currently no well-established procedures for when multivariate abundances are to be collected. A power analysis procedure would need to address three challenges: designing a parsimonious simulation model that captures key community data properties; measuring effect size in a realistic yet interpretable fashion; and ensuring computational feasibility when simulation is used both for power estimation and significance testing. Here, we propose a power analysis procedure that addresses these three challenges by: using for simulation a Gaussian copula model with factor analytical structure, fitted to pilot data; assuming a common effect size across all taxa, but applied in different directions according to expert opinion (to “increaser”, “decreaser” or “no effect” taxa); using a critical value approach to estimate power, which reduces computation time by a factor of 500 (if we would otherwise use 999 resamples to estimate each p-value) with minor loss of accuracy. The procedure is demonstrated on pilot data from fish assemblages in a restoration study, where it was found that the planned study design would only be capable of detecting relatively large effects (change in abundance by a factor of 1.7 or more). The methods outlined in this paper are available in accompanying R software (the ecopower package), which allows researchers with pilot data to answer a wide range of design questions to assist them in planning their studies.
ISSN: 2041-210X
DOI: 10.1111/2041-210X.14094
Research Centres: Singapore Centre for Environmental Life Sciences and Engineering 
Rights: © 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCELSE Journal Articles

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