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Damage costs from invasive species exceed management expenditure in nations experiencing lower economic activity

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  • Bradshaw, Corey J.A.
  • Hulme, Philip E.
  • Hudgins, Emma J.
  • Leung, Brian
  • Kourantidou, Melina
  • Courtois, Pierre
  • Turbelin, Anna J.
  • McDermott, Shana M.
  • Lee, Katherine
  • Ahmed, Danish A.
  • Latombe, Guillaume
  • Bang, Alok
  • Bodey, Thomas W.
  • Haubrock, Phillip J.
  • Saltré, Frédérik
  • Courchamp, Franck

Abstract

While data on biological invasions and their economic toll are increasingly available, drivers of susceptibility to damage and cost-effectiveness of management in reducing long-term costs remain poorly understood. We used data describing the damage costs of, and management expenditure on, invasive species among 56 nations between 2000 and 2020 reported in the InvaCost database to test the overarching hypothesis that higher-income nations and those with higher trade volume have a higher efficiency to limit the damage incurred by invasive species by spending relatively more on management. We also tested whether nations with (i) more corruption have a reduced capacity to manage invasive species, leading to relatively higher damage costs, (ii) more educated citizens or greater technological and scientific output allow for improved incentives and ability to manage invasive species, thereby reducing relative damage costs, and (iii) economies based on higher primary resource dependencies (e.g., agriculture) are at greater risk of incurring high costs of invasive species, and so all other conditions being equal, have higher relative damage costs compared to management expenditure. By focusing on the ratio between damage costs and management expenditure, we analyse the willingness of countries to invest in management as a function of the extent of the damage suffered. We show that economic activity, measured by the volume of trade, is the main determinant of this ratio — the greater the volume, the smaller the ratio. We also found a higher rate of increase in the damage:management ratio as a country's proportion of total land area devoted to agriculture increased, suggesting that a higher economic dependency on agriculture predisposes a country to greater damage costs from invasive species over time. When considering the proportion of total costs identified as damage-related, results indicated that higher government investment in education produced higher proportional damage, and lower corruption and lower trade volume both reduced proportional damage. Our overall results suggest that wealthier nations with high per-capita imports of goods and services are more susceptible to damage, but also have a greater capacity to reduce it, and are therefore less threatened by biological invasions than countries with fewer resources and lower imports.

Suggested Citation

  • Bradshaw, Corey J.A. & Hulme, Philip E. & Hudgins, Emma J. & Leung, Brian & Kourantidou, Melina & Courtois, Pierre & Turbelin, Anna J. & McDermott, Shana M. & Lee, Katherine & Ahmed, Danish A. & Latom, 2024. "Damage costs from invasive species exceed management expenditure in nations experiencing lower economic activity," Ecological Economics, Elsevier, vol. 220(C).
  • Handle: RePEc:eee:ecolec:v:220:y:2024:i:c:s0921800924000636
    DOI: 10.1016/j.ecolecon.2024.108166
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    1. Boris Leroy & Andrew M. Kramer & Anne‐charlotte Vaissière & Melina Kourantidou & Franck Courchamp & Christophe Diagne, 2022. "Analysing economic costs of invasive alien species with the INVACOST R package," Post-Print hal-03860634, HAL.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. McDermott, Shana M. & Finnoff, David C. & Shogren, Jason F., 2013. "The welfare impacts of an invasive species: Endogenous vs. exogenous price models," Ecological Economics, Elsevier, vol. 85(C), pages 43-49.
    4. Benjamin A. Jones & Shana M. McDermott, 2018. "Health Impacts of Invasive Species Through an Altered Natural Environment: Assessing Air Pollution Sinks as a Causal Pathway," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 23-43, September.
    5. Christophe Diagne & Boris Leroy & Anne-Charlotte Vaissière & Rodolphe E. Gozlan & David Roiz & Ivan Jarić & Jean-Michel Salles & Corey J. A. Bradshaw & Franck Courchamp, 2021. "High and rising economic costs of biological invasions worldwide," Nature, Nature, vol. 592(7855), pages 571-576, April.
    6. Jones, Benjamin A., 2019. "Infant health impacts of freshwater algal blooms: Evidence from an invasive species natural experiment," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 36-59.
    7. C. Diagne & B. Leroy & Rodolphe Gozlan & A.-C. Vaissière & C. Assailly & L. Nuninger & David A Roiz & Frédéric Jourdain & I. Jarić & F. Courchamp, 2020. "InvaCost, a public database of the economic costs of biological invasions worldwide," Post-Print hal-03085161, HAL.
    8. Philip E Hulme & Danish A Ahmed & Phillip J Haubrock & Brooks A Kaiser & Melina Kourantidou & Boris Leroy & Shana M Mcdermott, 2024. "Widespread imprecision in estimates of the economic costs of invasive alien species worldwide," Post-Print hal-04633043, HAL.
    9. Corey J. A. Bradshaw & Boris Leroy & Céline Bellard & David Roiz & Céline Albert & Alice Fournier & Morgane Barbet-Massin & Jean-Michel Salles & Frédéric Simard & Franck Courchamp, 2016. "Massive yet grossly underestimated global costs of invasive insects," Nature Communications, Nature, vol. 7(1), pages 1-8, December.
    10. Ross N Cuthbert & Christophe Diagne & Emma J Hudgins & Anna Turbelin & Danish A Ahmed & Céline Albert & Thomas W Bodey & Elizabeta Briski & Franz Essl & Phillip J Haubrock & Rodolphe E Gozlan & Natali, 2022. "Biological invasion costs reveal insufficient proactive management worldwide," Post-Print hal-03860581, HAL.
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