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Combining food web and species distribution models for improved community projections
The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic in...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3856755/ https://www.ncbi.nlm.nih.gov/pubmed/24340196 http://dx.doi.org/10.1002/ece3.843 |
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author | Pellissier, Loïc Rohr, Rudolf P Ndiribe, Charlotte Pradervand, Jean-Nicolas Salamin, Nicolas Guisan, Antoine Wisz, Mary |
author_facet | Pellissier, Loïc Rohr, Rudolf P Ndiribe, Charlotte Pradervand, Jean-Nicolas Salamin, Nicolas Guisan, Antoine Wisz, Mary |
author_sort | Pellissier, Loïc |
collection | PubMed |
description | The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant–herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks. |
format | Online Article Text |
id | pubmed-3856755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-38567552013-12-11 Combining food web and species distribution models for improved community projections Pellissier, Loïc Rohr, Rudolf P Ndiribe, Charlotte Pradervand, Jean-Nicolas Salamin, Nicolas Guisan, Antoine Wisz, Mary Ecol Evol Original Research The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant–herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks. Blackwell Publishing Ltd 2013-11 2013-10-21 /pmc/articles/PMC3856755/ /pubmed/24340196 http://dx.doi.org/10.1002/ece3.843 Text en © 2013 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation. |
spellingShingle | Original Research Pellissier, Loïc Rohr, Rudolf P Ndiribe, Charlotte Pradervand, Jean-Nicolas Salamin, Nicolas Guisan, Antoine Wisz, Mary Combining food web and species distribution models for improved community projections |
title | Combining food web and species distribution models for improved community projections |
title_full | Combining food web and species distribution models for improved community projections |
title_fullStr | Combining food web and species distribution models for improved community projections |
title_full_unstemmed | Combining food web and species distribution models for improved community projections |
title_short | Combining food web and species distribution models for improved community projections |
title_sort | combining food web and species distribution models for improved community projections |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3856755/ https://www.ncbi.nlm.nih.gov/pubmed/24340196 http://dx.doi.org/10.1002/ece3.843 |
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