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Managing biological invasions: the cost of inaction

Authors :
Danish A. Ahmed
Emma J. Hudgins
Ross N. Cuthbert
Melina Kourantidou
Christophe Diagne
Phillip J. Haubrock
Brian Leung
Chunlong Liu
Boris Leroy
Sergei Petrovskii
Ayah Beidas
Franck Courchamp
Gulf University for Science and Technology (GUST)
Department of Biology [McGill University]
McGill University = Université McGill [Montréal, Canada]
Department of Biology, Carleton University (Carleton University)
Carleton University
Helmholtz Centre for Ocean Research [Kiel] (GEOMAR)
Queen's University [Belfast] (QUB)
Woods Hole Oceanographic Institution (WHOI)
Hellenic Centre for Marine Research (HCMR)
University of Southern Denmark (SDU)
Ecologie Systématique et Evolution (ESE)
AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Senckenberg Research Institute and Natural History Museum [Frankfurt]
Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung
Leibniz Association-Leibniz Association
South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses [University of South Bohemia] (CENAKVA)
Faculty of Fisheries and Protection of Waters [University of South Bohemia]
University of South Bohemia -University of South Bohemia
Freie Universität Berlin
Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB)
Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB)
Institute of Hydrobiology [Wuhan]
Chinese Academy of Sciences [Beijing] (CAS)
Biologie des Organismes et Ecosystèmes Aquatiques (BOREA)
Université de Caen Normandie (UNICAEN)
Normandie Université (NU)-Normandie Université (NU)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)
University of Leicester
BNP-Paribas Foundation Climate Initiative for funding the InvaCost project that allowed the construction of the InvaCost database.
The present work was conducted following a workshop funded by the AXA Research Fund Chair of Invasion Biology and is part of the AlienScenarios project funded by BiodivERsA and Belmont-Forum call 2018 on biodiversity scenarios. DAA is funded by the Kuwait Foundation for the Advancement of Sciences (KFAS), grant no. PR1914SM-01 and the Gulf University for Science and Technology (GUST) internal seed fund, grant no. 234597. EJH is supported by a Fonds de recherche du Québec-nature et technologies B3X fellowship. RNC acknowledges funding from the Alexander von Humboldt Foundation. CL was sponsored by the PRIME programme of the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (BMBF).
ANR-14-CE02-0021,InvaCosts,Insectes envahissants et leurs couts pour la biodiversité, l'économie et la santé humaine(2014)
Source :
Biological Invasions, Biological Invasions, 2022, Special Issue: Economic Costs of Biological Invasions, 24, pp.1927-1946. ⟨10.1007/s10530-022-02755-0⟩, Ahmed, D A, Hudgins, E J, Cuthbert, R N, Kourantidou, M, Diagne, C, Haubrock, P J, Leung, B, Liu, C, Leroy, B, Petrovskii, S, Beidas, A & Courchamp, F 2022, ' Managing biological invasions: the cost of inaction ', Biological Invasions . https://doi.org/10.1007/s10530-022-02755-0
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Ecological and socioeconomic impacts from biological invasions are rapidly escalating worldwide. While effective management underpins impact mitigation, such actions are often delayed, insufficient or entirely absent. Presently, management delays emanate from a lack of monetary rationale to invest at early invasion stages, which precludes effective prevention and eradication. Here, we provide such rationale by developing a conceptual model to quantify the cost of inaction, i.e., the additional expenditure due to delayed management, under varying time delays and management efficiencies. Further, we apply the model to management and damage cost data from a relatively data-rich genus (Aedes mosquitoes). Our model demonstrates that rapid management interventions following invasion drastically minimise costs. We also identify key points in time that differentiate among scenarios of timely, delayed and severely delayed management intervention. Any management action during the severely delayed phase results in substantial losses $$( > 50\%$$ ( > 50 % of the potential maximum loss). For Aedes spp., we estimate that the existing management delay of 55 years led to an additional total cost of approximately $ 4.57 billion (14% of the maximum cost), compared to a scenario with management action only seven years prior (

Details

ISSN :
15731464 and 13873547
Volume :
24
Database :
OpenAIRE
Journal :
Biological Invasions
Accession number :
edsair.doi.dedup.....22af1cb5c62e3fa6e96844628aa99dd0
Full Text :
https://doi.org/10.1007/s10530-022-02755-0