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Unevenly distributed biological invasion costs among origin and recipient regions

Nature Sustainability volume 6, pages 1113–1124 (2023)Cite this article

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Abstract

Globalization challenges sustainability by intensifying the ecological and economic impacts of biological invasions. These impacts may be unevenly distributed worldwide, with costs disproportionately incurred by a few regions. We identify economic cost distributions of invasions among origin and recipient countries and continents, and determine socio-economic and biodiversity-related predictors of cost dynamics. Using data filtered from the InvaCost database, which inevitably includes geographic biases in cost reporting, we found that recorded costly invasive alien species have originated from almost all regions, most frequently causing impacts to Europe. In terms of cost magnitude, reported monetary costs predominantly resulted from species with origins in Asia impacting North America. High reported cost linkages (flows) between species’ native countries and their invaded countries were related to proxies of shared environments and shared trade history. This pattern can be partly attributed to the legacy of colonial expansion and trade patterns. The characterization of ‘sender’ and ‘receiver’ regions of invasive alien species and their associated cost can contribute to more sustainable economies and societies while protecting biodiversity by informing biosecurity planning and the prioritization of control efforts across invasion routes.

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Fig. 1: Continental distribution of studies, costs and IAS sent and received.
Fig. 2: Workflow illustrating the cost filtering process from the InvaCost database to permit analyses.
Fig. 3: Continental IAS and cost flows.
Fig. 4: Top 10 senders and receivers.
Fig. 5: Variable importance in the GAM pairwise cost flow model.

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Data availability

The InvaCost database v.4.1 is available in the form of a publicly available repository at https://doi.org/10.6084/m9.figshare.12668570. All derived data have been archived in Zenodo at https://doi.org/10.5281/zenodo.7778972.

Code availability

All code used for data analysis and producing figures has been archived in Zenodo at https://doi.org/10.5281/zenodo.7778972.

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Acknowledgements

We thank the French National Research Agency (ANR-14- CE02-0021) and the BNP-Paribas Foundation Climate Initiative for funding the InvaCost project and the InvaCost database development. The present work was conducted in the frame of the InvaCost workshop conducted in November 2019 (Paris, France) and funded by the AXA Research Fund Chair of Invasion Biology, and is part of the Alien-Scenario project funded by BiodivERsA and Belmont-Forum call 2018 on biodiversity scenarios. E.J.H. was funded by a Fonds de Recherche du Québec - Nature et Téchnologies Postdoctoral Fellowship. R.N.C. was funded through a Leverhulme Early Career Fellowship (ECF-2021-001) from the Leverhulme Trust. D.M. was supported by the Czech Science Foundation (project no. 19–13142S and EXPRO no. 19–28807X) and the Czech Academy of Sciences (long-term research development project RVO 67985939).

Author information

Author notes

  1. These authors contributed equally: Emma J. Hudgins, Ross N. Cuthbert, Phillip J. Haubrock.

Authors and Affiliations

  1. Department of Biology, Carleton University, Ottawa, Ontario, Canada

    Emma J. Hudgins

  2. Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast, Belfast, UK

    Ross N. Cuthbert

  3. Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany

    Phillip J. Haubrock

  4. South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Faculty of Fisheries and Protection of Waters, University of South Bohemia in České Budějovice, Vodňany, Czech Republic

    Phillip J. Haubrock

  5. Center for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, Hawally, Kuwait

    Phillip J. Haubrock

  6. Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, UK

    Nigel G. Taylor

  7. Department of Sociology, Environmental and Business Economics, University of Southern Denmark, Esbjerg, Denmark

    Melina Kourantidou

  8. Université de Bretagne Occidentale, AMURE, Plouzane, France

    Melina Kourantidou

  9. Department of Biology, McGill University, Montreal, Québec, Canada

    Dat Nguyen

  10. Society for Ecology Evolution and Development, Wardha, India

    Alok Bang

  11. School of Arts and Sciences, Azim Premji University, Bangalore, India

    Alok Bang

  12. Ecologie Systématique Evolution, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France

    Anna J. Turbelin & Franck Courchamp

  13. Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic

    Desika Moodley

  14. GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Kiel, Germany

    Elizabeta Briski & Syrmalenia G. Kotronaki

  15. Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA

    Syrmalenia G. Kotronaki

Authors
  1. Emma J. Hudgins
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Contributions

E.J.H., R.N.C., P.J.H. and F.C. conceptualized the project. E.J.H., R.N.C., P.J.H., N.G.T., M.K., D.N., A.B., A.J.T., D.M., E.B. and S.G.K. screened data. E.J.H., R.N.C. and D.N. analysed data. E.J.H., R.N.C., P.J.H., F.C., N.G.T., M.K. and A.B. wrote the manuscript. All authors edited the manuscript. E.J.H., P.J.H., A.J.T. and F.C. created the figures.

Corresponding author

Correspondence to Emma J. Hudgins.

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The authors declare no competing interests.

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Nature Sustainability thanks Tobias Kuemmerle, Sven Bacher and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Continental flows after controlling for research effort.

The average cost of intercontinental flows of IAS per publication associated with each continental pair in 2017 US$ millions. Arrow thickness indicates the magnitude of reported costs. Arrows indicate species’ known native ranges and final recipient regions of costs, and therefore do not necessarily indicate direct flows between continents. Base map is the intellectual property of Esri and its licensors and is used under license. Copyright © 2013 Esri and its licensors. All rights reserved.

Extended Data Fig. 2 Decadal cost flows.

Costs sent and received per decade. Base map is public domain, courtesy of Wikimedia Commons.

Extended Data Fig. 3 Decadal species flows.

Numbers of species sent and received per decade. Base map is public domain, courtesy of Wikimedia Commons.

Extended Data Fig. 4 Decadal cost flows after controlling for research effort.

Costs sent and received per decade, qualified by numbers of publications. Base map is public domain, courtesy of Wikimedia Commons.

Extended Data Fig. 5 Top sender and receiver countries after controlling for research effort.

Top 10 IAS cost sender countries (a), top 10 IAS cost receiver countries (b) and top 10 sender-receiver country pairs (c) in the InvaCost database when total reported costs are qualified by numbers of publications per country. Costs correspond to qualified invasion impacts in 2017 US$ values of species native to a country across all receiving countries (a), qualified invasion costs per country attributable to individual species native to any other country (b), and qualified invasion costs incurred per receiver country attributable to species native to the corresponding sender country (c). In (c), darker red hues indicate greater senders of costs, darker blue hues indicate greater receivers of costs, and blacker hues represent countries that both receive and send high costs. Countries are not to scale. Arrows indicate species’ known native ranges and final recipient regions of costs and therefore do not necessarily indicate direct flows between countries. Base map is the intellectual property of Esri and its licensors and is used under license. Copyright © 2013 Esri and its licensors. All rights reserved.

Extended Data Fig. 6 Relative extent of IAS flows compared to trade flows.

Percentiles of the extent of trade plotted on the x-axis (where greater net importers are further to the right) and percentiles of the net flow of IAS costs on the y-axis (where greater net importers of IAS risk are higher up) for each country plotted by ISO3C code. Countries in the top left quadrant have greater net export of goods and greater net import of IAS costs (for example Canada, Australia, and Colombia). Countries in the top right quadrant have greater net import of both goods and IAS costs (for example USA, United Kingdom, Philippines). Countries in the bottom left quadrant have greater net export of both goods and IAS costs (for example Brazil, South Korea, Russia), and countries in the bottom right quadrant have greater net import of goods and net export of IAS costs (for example China, India, Mexico). Country text colour was allocated by continent analogously to Fig. 1.

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Supplementary Information

Supplementary Figs. 1–8, Tables 1–6 and Notes 1–6.

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Hudgins, E.J., Cuthbert, R.N., Haubrock, P.J. et al. Unevenly distributed biological invasion costs among origin and recipient regions. Nat Sustain 6, 1113–1124 (2023). https://doi.org/10.1038/s41893-023-01124-6

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