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Missing in action: Species competition is a neglected predictor variable in species distribution modelling

The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species compe...

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Autores principales: Mpakairi, Kudzai Shaun, Ndaimani, Henry, Tagwireyi, Paradzayi, Gara, Tawanda Winmore, Zvidzai, Mark, Madhlamoto, Daphine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5510852/
https://www.ncbi.nlm.nih.gov/pubmed/28708854
http://dx.doi.org/10.1371/journal.pone.0181088
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author Mpakairi, Kudzai Shaun
Ndaimani, Henry
Tagwireyi, Paradzayi
Gara, Tawanda Winmore
Zvidzai, Mark
Madhlamoto, Daphine
author_facet Mpakairi, Kudzai Shaun
Ndaimani, Henry
Tagwireyi, Paradzayi
Gara, Tawanda Winmore
Zvidzai, Mark
Madhlamoto, Daphine
author_sort Mpakairi, Kudzai Shaun
collection PubMed
description The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.
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spelling pubmed-55108522017-08-07 Missing in action: Species competition is a neglected predictor variable in species distribution modelling Mpakairi, Kudzai Shaun Ndaimani, Henry Tagwireyi, Paradzayi Gara, Tawanda Winmore Zvidzai, Mark Madhlamoto, Daphine PLoS One Research Article The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts. Public Library of Science 2017-07-14 /pmc/articles/PMC5510852/ /pubmed/28708854 http://dx.doi.org/10.1371/journal.pone.0181088 Text en © 2017 Mpakairi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mpakairi, Kudzai Shaun
Ndaimani, Henry
Tagwireyi, Paradzayi
Gara, Tawanda Winmore
Zvidzai, Mark
Madhlamoto, Daphine
Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title_full Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title_fullStr Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title_full_unstemmed Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title_short Missing in action: Species competition is a neglected predictor variable in species distribution modelling
title_sort missing in action: species competition is a neglected predictor variable in species distribution modelling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5510852/
https://www.ncbi.nlm.nih.gov/pubmed/28708854
http://dx.doi.org/10.1371/journal.pone.0181088
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