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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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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. |
format | Online Article Text |
id | pubmed-6395803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT scherrerdaniel ecologicalindicatorvaluesrevealmissingpredictorsofspeciesdistributions AT guisanantoine ecologicalindicatorvaluesrevealmissingpredictorsofspeciesdistributions |