Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170593
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dc.contributor.authorMaslen, Benen_US
dc.contributor.authorPopovic, Gordanaen_US
dc.contributor.authorLim, Michelleen_US
dc.contributor.authorMarzinelli, Ezequiel Miguelen_US
dc.contributor.authorWarton, Daviden_US
dc.date.accessioned2023-09-20T01:30:03Z-
dc.date.available2023-09-20T01:30:03Z-
dc.date.issued2023-
dc.identifier.citationMaslen, 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. https://dx.doi.org/10.1111/2041-210X.14094en_US
dc.identifier.issn2041-210Xen_US
dc.identifier.urihttps://hdl.handle.net/10356/170593-
dc.description.abstractSample 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.en_US
dc.language.isoenen_US
dc.relation.ispartofMethods in Ecology and Evolutionen_US
dc.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.en_US
dc.subjectScience::Biological sciencesen_US
dc.titleHow many sites? Methods to assist design decisions when collecting multivariate data in ecologyen_US
dc.typeJournal Articleen
dc.contributor.researchSingapore Centre for Environmental Life Sciences and Engineeringen_US
dc.identifier.doi10.1111/2041-210X.14094-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85153529083-
dc.identifier.issue6en_US
dc.identifier.volume14en_US
dc.identifier.spage1564en_US
dc.identifier.epage1573en_US
dc.subject.keywordsCopulaen_US
dc.subject.keywordsMultivariateen_US
dc.description.acknowledgementThis research was funded by Australian Research Council, Grant/Award Number: DP180104041, DP190102030, DP210101923 and LP160100836; NSW Environmental Trust; NSW Recreational Fishing Trust.en_US
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