Predicting future invaders and future invasions

Alice A Fournier (1) , Caterina Penone (2) , Maria Grazia Pennino (3) , Franck Courchamp (1)

1 ESE - Ecologie Systématique et Evolution
2 Institute of Plant Sciences
3 UMR MARBEC - MARine Biodiversity Exploitation and Conservation

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 1,002 ant species from an extensive trait database, we identify 13 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: Florida 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.

Mots clés: alien invasive species; ants; biological invasion; data imputation; Formicidae

Domaines: Sciences de l'environnement; Biodiversité et Ecologie

Alice A Fournier, Caterina Penone, Maria Grazia Pennino, Franck Courchamp. Predicting future invaders and future invasions. Proceedings of the National Academy of Sciences of the United States of America, 2019, 116 (16), pp.7905-7910. ⟨10.1073/pnas.1803456116⟩. ⟨hal-02394345⟩