Cargando…

Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference

Habitat‐selection analysis lacks an appropriate measure of the ecological significance of the statistical estimates—a practical interpretation of the magnitude of the selection coefficients. There is a need for a standard approach that allows relating the strength of selection to a change in habitat...

Descripción completa

Detalles Bibliográficos
Autores principales: Avgar, Tal, Lele, Subhash R., Keim, Jonah L., Boyce, Mark S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528224/
https://www.ncbi.nlm.nih.gov/pubmed/28770070
http://dx.doi.org/10.1002/ece3.3122
_version_ 1783253027119955968
author Avgar, Tal
Lele, Subhash R.
Keim, Jonah L.
Boyce, Mark S.
author_facet Avgar, Tal
Lele, Subhash R.
Keim, Jonah L.
Boyce, Mark S.
author_sort Avgar, Tal
collection PubMed
description Habitat‐selection analysis lacks an appropriate measure of the ecological significance of the statistical estimates—a practical interpretation of the magnitude of the selection coefficients. There is a need for a standard approach that allows relating the strength of selection to a change in habitat conditions across space, a quantification of the estimated effect size that can be compared both within and across studies. We offer a solution, based on the epidemiological risk ratio, which we term the relative selection strength (RSS). For a “used‐available” design with an exponential selection function, the RSS provides an appropriate interpretation of the magnitude of the estimated selection coefficients, conditional on all other covariates being fixed. This is similar to the interpretation of the regression coefficients in any multivariable regression analysis. Although technically correct, the conditional interpretation may be inappropriate when attempting to predict habitat use across a given landscape. Hence, we also provide a simple graphical tool that communicates both the conditional and average effect of the change in one covariate. The average‐effect plot answers the question: What is the average change in the space use probability as we change the covariate of interest, while averaging over possible values of other covariates? We illustrate an application of the average‐effect plot for the average effect of distance to road on space use for elk (Cervus elaphus) during the hunting season. We provide a list of potentially useful RSS expressions and discuss the utility of the RSS in the context of common ecological applications.
format Online
Article
Text
id pubmed-5528224
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-55282242017-08-02 Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference Avgar, Tal Lele, Subhash R. Keim, Jonah L. Boyce, Mark S. Ecol Evol Original Research Habitat‐selection analysis lacks an appropriate measure of the ecological significance of the statistical estimates—a practical interpretation of the magnitude of the selection coefficients. There is a need for a standard approach that allows relating the strength of selection to a change in habitat conditions across space, a quantification of the estimated effect size that can be compared both within and across studies. We offer a solution, based on the epidemiological risk ratio, which we term the relative selection strength (RSS). For a “used‐available” design with an exponential selection function, the RSS provides an appropriate interpretation of the magnitude of the estimated selection coefficients, conditional on all other covariates being fixed. This is similar to the interpretation of the regression coefficients in any multivariable regression analysis. Although technically correct, the conditional interpretation may be inappropriate when attempting to predict habitat use across a given landscape. Hence, we also provide a simple graphical tool that communicates both the conditional and average effect of the change in one covariate. The average‐effect plot answers the question: What is the average change in the space use probability as we change the covariate of interest, while averaging over possible values of other covariates? We illustrate an application of the average‐effect plot for the average effect of distance to road on space use for elk (Cervus elaphus) during the hunting season. We provide a list of potentially useful RSS expressions and discuss the utility of the RSS in the context of common ecological applications. John Wiley and Sons Inc. 2017-06-14 /pmc/articles/PMC5528224/ /pubmed/28770070 http://dx.doi.org/10.1002/ece3.3122 Text en © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Avgar, Tal
Lele, Subhash R.
Keim, Jonah L.
Boyce, Mark S.
Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title_full Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title_fullStr Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title_full_unstemmed Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title_short Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference
title_sort relative selection strength: quantifying effect size in habitat‐ and step‐selection inference
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528224/
https://www.ncbi.nlm.nih.gov/pubmed/28770070
http://dx.doi.org/10.1002/ece3.3122
work_keys_str_mv AT avgartal relativeselectionstrengthquantifyingeffectsizeinhabitatandstepselectioninference
AT lelesubhashr relativeselectionstrengthquantifyingeffectsizeinhabitatandstepselectioninference
AT keimjonahl relativeselectionstrengthquantifyingeffectsizeinhabitatandstepselectioninference
AT boycemarks relativeselectionstrengthquantifyingeffectsizeinhabitatandstepselectioninference