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Forecasting potential invaders to prevent future biological invasions worldwide.
Pili, Arman N; Leroy, Boris; Measey, John G; Farquhar, Jules E; Toomes, Adam; Cassey, Phillip; Chekunov, Sebastian; Grenié, Matthias; van Winkel, Dylan; Maria, Lisa; Diesmos, Mae Lowe L; Diesmos, Arvin C; Zurell, Damaris; Courchamp, Franck; Chapple, David G.
Afiliación
  • Pili AN; School of Biological Sciences, Faculty of Science, Monash University, Clayton, Victoria, Australia.
  • Leroy B; Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
  • Measey JG; Unité 8067 Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), Muséum National d'Histoire Naturelle, Sorbonne Université, Université de Caen Normandie, CNRS, IRD, Université des Antilles, Paris, France.
  • Farquhar JE; Centre for Invasion Biology, Institute of Biodiversity, School of Ecology and Environmental Science, Yunnan University, Kunming, China.
  • Toomes A; Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Stellenbosch, South Africa.
  • Cassey P; UMR7179 MECADEV CNRS/MNHN, Département Adaptations du Vivant, Muséum National d'Histoire Naturelle, Bâtiment d'Anatomie Comparée, Paris, France.
  • Chekunov S; School of Biological Sciences, Faculty of Science, Monash University, Clayton, Victoria, Australia.
  • Grenié M; Invasion Science and Wildlife Ecology Group, The University of Adelaide, Adelaide, South Australia, Australia.
  • van Winkel D; Invasion Science and Wildlife Ecology Group, The University of Adelaide, Adelaide, South Australia, Australia.
  • Maria L; Invasion Science and Wildlife Ecology Group, The University of Adelaide, Adelaide, South Australia, Australia.
  • Diesmos MLL; Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France.
  • Diesmos AC; Bioresearches (Babbage Consultants Limited), Auckland, New Zealand.
  • Zurell D; Biosecurity New Zealand-Tiakitanga Putaiao Aotearoa, Ministry for Primary Industries-Manatu Ahu Matua, Upper Hutt, New Zealand.
  • Courchamp F; Department of Biological Sciences, College of Science, University of Santo Tomas, Manila, Philippines.
  • Chapple DG; Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines.
Glob Chang Biol ; 30(7): e17399, 2024 Jul.
Article en En | MEDLINE | ID: mdl-39007251
ABSTRACT
The ever-increasing and expanding globalisation of trade and transport underpins the escalating global problem of biological invasions. Developing biosecurity infrastructures is crucial to anticipate and prevent the transport and introduction of invasive alien species. Still, robust and defensible forecasts of potential invaders are rare, especially for species without known invasion history. Here, we aim to support decision-making by developing a quantitative invasion risk assessment tool based on invasion syndromes (i.e., generalising typical attributes of invasive alien species). We implemented a workflow based on 'Multiple Imputation with Chain Equation' to estimate invasion syndromes from imputed datasets of species' life-history and ecological traits and macroecological patterns. Importantly, our models disentangle the factors explaining (i) transport and introduction and (ii) establishment. We showcase our tool by modelling the invasion syndromes of 466 amphibians and reptile species with invasion history. Then, we project these models to amphibians and reptiles worldwide (16,236 species [c.76% global coverage]) to identify species with a risk of being unintentionally transported and introduced, and risk of establishing alien populations. Our invasion syndrome models showed high predictive accuracy with a good balance between specificity and generality. Unintentionally transported and introduced species tend to be common and thrive well in human-disturbed habitats. In contrast, those with established alien populations tend to be large-sized, are habitat generalists, thrive well in human-disturbed habitats, and have large native geographic ranges. We forecast that 160 amphibians and reptiles without known invasion history could be unintentionally transported and introduced in the future. Among them, 57 species have a high risk of establishing alien populations. Our reliable, reproducible, transferable, statistically robust and scientifically defensible quantitative invasion risk assessment tool is a significant new addition to the suite of decision-support tools needed for developing a future-proof preventative biosecurity globally.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Reptiles / Especies Introducidas / Predicción / Anfibios Límite: Animals Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Reptiles / Especies Introducidas / Predicción / Anfibios Límite: Animals Idioma: En Año: 2024 Tipo del documento: Article