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Trait dimensionality and population choice alter estimates of phenotypic dissimilarity

The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niche...

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Autores principales: Carscadden, Kelly A., Cadotte, Marc W., Gilbert, Benjamin
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/PMC5383497/
https://www.ncbi.nlm.nih.gov/pubmed/28405291
http://dx.doi.org/10.1002/ece3.2780
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author Carscadden, Kelly A.
Cadotte, Marc W.
Gilbert, Benjamin
author_facet Carscadden, Kelly A.
Cadotte, Marc W.
Gilbert, Benjamin
author_sort Carscadden, Kelly A.
collection PubMed
description The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross‐study comparability of trait‐based approaches. Our results emphasize the importance of sampling among‐population trait variation and suggest that a high‐dimensional approach may best capture phenotypic variation among species with distinct niches.
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spelling pubmed-53834972017-04-12 Trait dimensionality and population choice alter estimates of phenotypic dissimilarity Carscadden, Kelly A. Cadotte, Marc W. Gilbert, Benjamin Ecol Evol Original Research The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross‐study comparability of trait‐based approaches. Our results emphasize the importance of sampling among‐population trait variation and suggest that a high‐dimensional approach may best capture phenotypic variation among species with distinct niches. John Wiley and Sons Inc. 2017-03-08 /pmc/articles/PMC5383497/ /pubmed/28405291 http://dx.doi.org/10.1002/ece3.2780 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
Carscadden, Kelly A.
Cadotte, Marc W.
Gilbert, Benjamin
Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title_full Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title_fullStr Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title_full_unstemmed Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title_short Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
title_sort trait dimensionality and population choice alter estimates of phenotypic dissimilarity
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5383497/
https://www.ncbi.nlm.nih.gov/pubmed/28405291
http://dx.doi.org/10.1002/ece3.2780
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