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Predicting future invaders and future invasions

Invasive alien species are a great threat to biodiversity and human livelihoods worldwide. The most effective way to limit their impacts and costs is to prevent their introduction into new areas. Identifying invaders and invasions before their occurrence would arguably be the most efficient strategy...

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Detalles Bibliográficos
Autores principales: Fournier, Alice, Penone, Caterina, Pennino, Maria Grazia, Courchamp, Franck
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475384/
https://www.ncbi.nlm.nih.gov/pubmed/30926662
http://dx.doi.org/10.1073/pnas.1803456116
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author Fournier, Alice
Penone, Caterina
Pennino, Maria Grazia
Courchamp, Franck
author_facet Fournier, Alice
Penone, Caterina
Pennino, Maria Grazia
Courchamp, Franck
author_sort Fournier, Alice
collection PubMed
description Invasive alien species are a great threat to biodiversity and human livelihoods worldwide. The most effective way to limit their impacts and costs is to prevent their introduction into new areas. Identifying invaders and invasions before their occurrence would arguably be the most efficient strategy. Here, we provide a profiling method to predict which species—with which particular ecological characteristics—will invade, and where they could invade. We illustrate our approach with ants, which are among the most detrimental invasive species, as they are responsible for declines of numerous taxa, are involved in local extinctions, disturb ecosystem functioning, and impact multiple human activities. Based on statistical profiling of 992 ant species from an extensive trait database, we identify 18 native ant species with an ecological profile that matches that of known invasive ants. Even though they are not currently described as such, these species are likely to become the next global invaders. We couple these predictions with species distribution models to identify the regions most at risk from the invasion of these species: Northern and Central America, Brazil, Central Africa and Madagascar, Southeast Asia, Papua New Guinea Northeast Australia, and many islands worldwide. This framework, applicable to any other taxa, represents a remarkable opportunity to implement timely and specifically shaped proactive management strategies against biological invasions.
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spelling pubmed-64753842019-04-26 Predicting future invaders and future invasions Fournier, Alice Penone, Caterina Pennino, Maria Grazia Courchamp, Franck Proc Natl Acad Sci U S A Biological Sciences Invasive alien species are a great threat to biodiversity and human livelihoods worldwide. The most effective way to limit their impacts and costs is to prevent their introduction into new areas. Identifying invaders and invasions before their occurrence would arguably be the most efficient strategy. Here, we provide a profiling method to predict which species—with which particular ecological characteristics—will invade, and where they could invade. We illustrate our approach with ants, which are among the most detrimental invasive species, as they are responsible for declines of numerous taxa, are involved in local extinctions, disturb ecosystem functioning, and impact multiple human activities. Based on statistical profiling of 992 ant species from an extensive trait database, we identify 18 native ant species with an ecological profile that matches that of known invasive ants. Even though they are not currently described as such, these species are likely to become the next global invaders. We couple these predictions with species distribution models to identify the regions most at risk from the invasion of these species: Northern and Central America, Brazil, Central Africa and Madagascar, Southeast Asia, Papua New Guinea Northeast Australia, and many islands worldwide. This framework, applicable to any other taxa, represents a remarkable opportunity to implement timely and specifically shaped proactive management strategies against biological invasions. National Academy of Sciences 2019-04-16 2019-03-29 /pmc/articles/PMC6475384/ /pubmed/30926662 http://dx.doi.org/10.1073/pnas.1803456116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Fournier, Alice
Penone, Caterina
Pennino, Maria Grazia
Courchamp, Franck
Predicting future invaders and future invasions
title Predicting future invaders and future invasions
title_full Predicting future invaders and future invasions
title_fullStr Predicting future invaders and future invasions
title_full_unstemmed Predicting future invaders and future invasions
title_short Predicting future invaders and future invasions
title_sort predicting future invaders and future invasions
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475384/
https://www.ncbi.nlm.nih.gov/pubmed/30926662
http://dx.doi.org/10.1073/pnas.1803456116
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