Forecasting potential invaders to prevent future biological invasions worldwide

被引:0
|
作者
Pili, Arman N. [1 ,2 ]
Leroy, Boris [3 ]
Measey, John G. [4 ,5 ,6 ]
Farquhar, Jules E. [1 ]
Toomes, Adam [7 ]
Cassey, Phillip [7 ]
Chekunov, Sebastian [7 ]
Grenie, Matthias [8 ]
van Winkel, Dylan [9 ]
Maria, Lisa [10 ]
Diesmos, Mae Lowe L. [11 ,12 ]
Diesmos, Arvin C. [13 ]
Zurell, Damaris [2 ]
Courchamp, Franck [14 ]
Chapple, David G. [1 ]
机构
[1] Monash Univ, Fac Sci, Sch Biol Sci, Clayton, Vic 3800, Australia
[2] Univ Potsdam, Inst Biochem & Biol, Potsdam, Germany
[3] Univ Antilles, Unite Biol Organismes & Ecosyst Aquat BOREA 8067, Museum Natl Hist Nat, Sorbonne Univ,Univ Caen Normandie,CNRS,IRD, Paris, France
[4] Yunnan Univ, Inst Biodivers, Ctr Invas Biol, Sch Ecol & Environm Sci, Kunming, Peoples R China
[5] Stellenbosch Univ, Ctr Invas Biol, Dept Bot & Zool, Stellenbosch, South Africa
[6] Museum Natl Hist Nat, MECADEV CNRS MNHN UMR7179, Dept Adaptat Vivant, Batiment Anat Comparee, Paris, France
[7] Univ Adelaide, Invas Sci & Wildlife Ecol Grp, Adelaide, SA, Australia
[8] Univ Savoie Mont Blanc, Univ Grenoble Alpes, CNRS, LECA, Grenoble, France
[9] Biores Babbage Consultants Ltd, Auckland, New Zealand
[10] Minist Primary Ind Manatu Ahu Matua, Biosecur New Zealand Tiakitanga Putaiao Aotearoa, Upper Hutt, New Zealand
[11] Univ Santo Tomas, Coll Sci, Dept Biol Sci, Manila, Philippines
[12] Univ Santo Tomas, Res Ctr Nat & Appl Sci, Manila, Philippines
[13] ASEAN Ctr Biodivers, Los Banos, Philippines
[14] Univ Paris Saclay, CNRS, AgroParisTech, Ecol Systemat Evolut, Gif Sur Yvette, France
基金
澳大利亚研究理事会;
关键词
biodiversity informatics; blacklist; global biodiversity data; herpetofauna; invasive alien species; macroecology; pathways; phylogenetic imputation; LIFE-HISTORY TRAITS; ESTABLISHMENT SUCCESS; IMPACT CLASSIFICATION; GEOGRAPHIC ORIGIN; GLOBAL ASSESSMENT; ALIEN REPTILES; SPECIES TRAITS; MISSING DATA; AMPHIBIANS; ECOLOGY;
D O I
暂无
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
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. We developed a reliable, robust and defensible tool that can identify attributes of invading alien species and predict which species worldwide, with no prior history of invasion, have the potential to become invasive. Showcasing our tool on amphibians and reptiles worldwide, we found 160 species are likely to be unintentionally transported and introduced, and 57 have a high risk of establishing alien populations. Our tool is an invaluable addition to the suite of decision-support tools for preventing future biological invasions worldwide.image
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页数:22
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