Soto Ismael, Courtois Pierre, Pili Arman, Tordoni Enrico, Manfrini Eléna, Angulo Elena, Bellard Céline, Briski Elizabeta, Buřič Miloš, Cuthbert Ross N, Kouba Antonín, Kourantidou Melina, Macêdo Rafael L, Leroy Boris, Haubrock Phillip J, Courchamp Franck, Leung Brian
Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, University of South Bohemia in České Budějovice, Vodňany, Czech Republic.
CEE-M, University of Montpellier, CNRS, INRAE, Instit Agro, Montpellier, France.
Nat Ecol Evol. 2025 May 26. doi: 10.1038/s41559-025-02697-5.
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 1,646% higher for these species than previously recorded. This discrepancy was uneven geographically and taxonomically, respectively peaking in Europe 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.
生物入侵威胁着全球生物多样性、人类福祉和经济。最近已经产生了许多关于货币成本的区域和分类学综合研究，但由于地理和分类学研究强度不均衡，存在重要的知识空白。在这里，我们结合物种分布模型、宏观经济数据和InvaCost数据库，以产生目前可用的最高分辨率时空成本估计，以弥合这些差距。从162种在国家层面有 “高度可靠” 记录成本的入侵物种子集中，我们的插值法聚焦于那些尽管已知存在入侵物种但尚未报告任何成本的国家。该分析表明存在严重低估，这些物种的全球成本可能比之前记录的高出1646%。这种差异在地理和分类学上是不均衡的，分别在欧洲和植物类群中达到峰值。我们的结果表明，损害成本主要由国内生产总值、人口规模、农业面积和环境适宜性驱动，而管理支出与国内生产总值和农业面积相关。我们还发现损害成本有46年的滞后时间，但管理支出没有延迟。本研究的方法学预测方法提供了对生物入侵经济层面更完整的看法，并缩小了入侵成本报告中的全球差异。
