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<p>Biological invasions threaten global biodiversity, human well-being and economies. Many regional and taxonomic syntheses of monetary costs have been produced recently but with important knowledge gaps owing to uneven geographic and taxonomic research intensity. Here we combine species distribution models, macroeconomic data and the InvaCost database to produce the highest resolution spatio-temporal cost estimates currently available to bridge these gaps. From a subset of 162 invasive species with ‘highly reliable’ documented costs at the national level, our interpolation focuses on countries that have not reported any costs despite the known presence of invasive species. This analysis demonstrates a substantial underestimation, with global costs potentially estimated to be 518% higher for these species than previously recorded. This discrepancy was uneven geographically and taxonomically, respectively peaking in Asia and for plants. Our results showed that damage costs were primarily driven by gross domestic product, human population size, agricultural area and environmental suitability, whereas management expenditure correlated with gross domestic product and agriculture areas. We also found a lag time for damage costs of 46 years, but management spending was not delayed. The methodological predictive approach of this study provides a more complete view of the economic dimensions of biological invasions and narrows the global disparity in invasion cost reporting.</p>

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Using species ranges and macroeconomic data to fill the gap in costs of biological invasions

  • 期刊论文

  • 发表日期：

    2025年5月26日

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  • Ismael Soto,
  • Pierre Courtois,
  • Arman Pili,
  • Enrico Tordoni,
  • Eléna Manfrini,
  • Elena Angulo,
  • Céline Bellard,
  • Elizabeta Briski,
  • Miloš Buřič,
  • Ross N. Cuthbert,
  • Antonín Kouba,
  • Melina Kourantidou,
  • Rafael L. Macêdo,
  • Boris Leroy,
  • Phillip J. Haubrock,
  • Franck Courchamp,
  • Brian Leung

摘要

Biological invasions threaten global biodiversity, human well-being and economies. Many regional and taxonomic syntheses of monetary costs have been produced recently but with important knowledge gaps owing to uneven geographic and taxonomic research intensity. Here we combine species distribution models, macroeconomic data and the InvaCost database to produce the highest resolution spatio-temporal cost estimates currently available to bridge these gaps. From a subset of 162 invasive species with ‘highly reliable’ documented costs at the national level, our interpolation focuses on countries that have not reported any costs despite the known presence of invasive species. This analysis demonstrates a substantial underestimation, with global costs potentially estimated to be 518% higher for these species than previously recorded. This discrepancy was uneven geographically and taxonomically, respectively peaking in Asia and for plants. Our results showed that damage costs were primarily driven by gross domestic product, human population size, agricultural area and environmental suitability, whereas management expenditure correlated with gross domestic product and agriculture areas. We also found a lag time for damage costs of 46 years, but management spending was not delayed. The methodological predictive approach of this study provides a more complete view of the economic dimensions of biological invasions and narrows the global disparity in invasion cost reporting.