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Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients
A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendousl...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5243196/ https://www.ncbi.nlm.nih.gov/pubmed/28116060 http://dx.doi.org/10.1002/ece3.2657 |
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author | Godsoe, William Franklin, Janet Blanchet, F. Guillaume |
author_facet | Godsoe, William Franklin, Janet Blanchet, F. Guillaume |
author_sort | Godsoe, William |
collection | PubMed |
description | A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large‐scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs. |
format | Online Article Text |
id | pubmed-5243196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52431962017-01-23 Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients Godsoe, William Franklin, Janet Blanchet, F. Guillaume Ecol Evol Original Research A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large‐scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs. John Wiley and Sons Inc. 2016-12-20 /pmc/articles/PMC5243196/ /pubmed/28116060 http://dx.doi.org/10.1002/ece3.2657 Text en © 2016 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 Godsoe, William Franklin, Janet Blanchet, F. Guillaume Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title | Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title_full | Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title_fullStr | Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title_full_unstemmed | Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title_short | Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
title_sort | effects of biotic interactions on modeled species' distribution can be masked by environmental gradients |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5243196/ https://www.ncbi.nlm.nih.gov/pubmed/28116060 http://dx.doi.org/10.1002/ece3.2657 |
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