title: Predicting global invasion risks: a management tool to prevent future introductions.
abstract: Predicting regions at risk from introductions of non-native species and the subsequent invasions is a fundamental aspect of horizon scanning activities that enable the development of more effective preventative actions and planning of management measures. The Asian cyprinid fish topmouth gudgeon Pseudorasbora parva has proved highly invasive across Europe since its introduction in the 1960s. In addition to direct negative impacts on native fish populations, P. parva has potential for further damage through transmission of an emergent infectious disease, known to cause mortality in other species. To quantify its invasion risk, in regions where it has yet to be introduced, we trained 900 ecological niche models and constructed an Ensemble Model predicting suitability, then integrated a proxy for introduction likelihood. This revealed high potential for P. parva to invade regions well beyond its current invasive range. These included areas in all modelled continents, with several hotspots of climatic suitability and risk of introduction. We believe that these methods are easily adapted for a variety of other invasive species and that such risk maps could be used by policy-makers and managers in hotspots to formulate increased surveillance and early-warning systems that aim to prevent introductions and subsequent invasions.
authors.affiliation: UMR MIVEGEC IRD-CNRS-Universités de Montpellier 1 et 2, Centre IRD de Montpellier, B.P. 64501, Montpellier, France.|Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Poole, BH12 5BB, United Kingdom.
authors.forename: D H
authors.initials: DH
authors.lastname: Fletcher
authors.affiliation: Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Poole, BH12 5BB, United Kingdom.
authors.forename: P K
authors.initials: PK
authors.lastname: Gillingham
authors.affiliation: Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Poole, BH12 5BB, United Kingdom.
authors.forename: J R
authors.initials: JR
authors.lastname: Britton
authors.affiliation: Centre National de la Recherche Scientifique (CNRS); Station d'Ecologie Théorique et Expérimentale, UMR5321, Moulis, 09200 Saint-Girons, France.|Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier, École Nationale de Formation Agronomique (ENFA); UMR5174 EDB (Laboratoire Évolution &Diversité Biologique), 118 route de Narbonne, F-31062 Toulouse cedex 4, France.
authors.forename: S
authors.initials: S
authors.lastname: Blanchet
authors.affiliation: Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Poole, BH12 5BB, United Kingdom.|Unité Mixte de Recherche Biologie des Organismes et Écosystèmes Aquatiques (IRD 207, CNRS 7208, MNHN, UPMC) Muséum National d'Histoire Naturelle, 75231 Paris Cedex, France.
authors.forename: R E
authors.initials: RE
authors.lastname: Gozlan
mesh_terms: D063147:Animal Distribution; D000818:Animals; D017756:Aquaculture; D002980:Climate; D003530:Cyprinidae; D017753:Ecosystem; D005544:Forecasting; D058865:Introduced Species; D008962:Models, Theoretical