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Ecological indicator values reveal missing predictors of species distributions

The questions of how much abiotic environment contributes to explain species distributions, and which abiotic factors are the most influential, are key when projecting species realized niches in space and time. Here, we show that answers to these questions can be obtained by using species’ ecologica...

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Detalles Bibliográficos
Autores principales: Scherrer, Daniel, Guisan, Antoine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395803/
https://www.ncbi.nlm.nih.gov/pubmed/30816150
http://dx.doi.org/10.1038/s41598-019-39133-1
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author Scherrer, Daniel
Guisan, Antoine
author_facet Scherrer, Daniel
Guisan, Antoine
author_sort Scherrer, Daniel
collection PubMed
description The questions of how much abiotic environment contributes to explain species distributions, and which abiotic factors are the most influential, are key when projecting species realized niches in space and time. Here, we show that answers to these questions can be obtained by using species’ ecological indicator values (EIVs). By calculating community averages of plant EIVs (397 plant species and 3988 vegetation plots), we found that substituting mapped environmental predictors with site EIVs led to a doubling of explained variation (22.5% to 44%). EIVs representing light and soil showed the highest model improvement, while EIVs representing temperature did not explain additional variance, suggesting that current temperature maps are already fairly accurate. Therefore, although temperature is frequently reported as having a dominant effect on species distributions over other factors, our results suggest that this might primarily result from limitations in our capacity to map other key environmental factors, such as light and soil properties, over large areas.
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spelling pubmed-63958032019-03-05 Ecological indicator values reveal missing predictors of species distributions Scherrer, Daniel Guisan, Antoine Sci Rep Article The questions of how much abiotic environment contributes to explain species distributions, and which abiotic factors are the most influential, are key when projecting species realized niches in space and time. Here, we show that answers to these questions can be obtained by using species’ ecological indicator values (EIVs). By calculating community averages of plant EIVs (397 plant species and 3988 vegetation plots), we found that substituting mapped environmental predictors with site EIVs led to a doubling of explained variation (22.5% to 44%). EIVs representing light and soil showed the highest model improvement, while EIVs representing temperature did not explain additional variance, suggesting that current temperature maps are already fairly accurate. Therefore, although temperature is frequently reported as having a dominant effect on species distributions over other factors, our results suggest that this might primarily result from limitations in our capacity to map other key environmental factors, such as light and soil properties, over large areas. Nature Publishing Group UK 2019-02-28 /pmc/articles/PMC6395803/ /pubmed/30816150 http://dx.doi.org/10.1038/s41598-019-39133-1 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Scherrer, Daniel
Guisan, Antoine
Ecological indicator values reveal missing predictors of species distributions
title Ecological indicator values reveal missing predictors of species distributions
title_full Ecological indicator values reveal missing predictors of species distributions
title_fullStr Ecological indicator values reveal missing predictors of species distributions
title_full_unstemmed Ecological indicator values reveal missing predictors of species distributions
title_short Ecological indicator values reveal missing predictors of species distributions
title_sort ecological indicator values reveal missing predictors of species distributions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395803/
https://www.ncbi.nlm.nih.gov/pubmed/30816150
http://dx.doi.org/10.1038/s41598-019-39133-1
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