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.

Soto, I., Courtois, P., Pili, A., Tordoni, E., Manfrini, E., Angulo, E., et al. (2025). Using species ranges and macroeconomic data to fill the gap in costs of biological invasions. NATURE ECOLOGY & EVOLUTION, 9(6), 1021-1030 [10.1038/s41559-025-02697-5].

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

Tordoni E;
2025

Abstract

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.
2025
Soto, I., Courtois, P., Pili, A., Tordoni, E., Manfrini, E., Angulo, E., et al. (2025). Using species ranges and macroeconomic data to fill the gap in costs of biological invasions. NATURE ECOLOGY & EVOLUTION, 9(6), 1021-1030 [10.1038/s41559-025-02697-5].
Soto, I; Courtois, P; Pili, A; Tordoni, E; Manfrini, E; Angulo, E; Bellard, C; Briski, E; Buřič, M; Cuthbert, ; R, ; Kouba, A; Kourantidou, M; Macêdo,...espandi
File in questo prodotto:
File Dimensione Formato  
41559_2025_2697_MOESM6_ESM.xlsx

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per accesso libero gratuito
Dimensione 10.33 kB
Formato Microsoft Excel XML
10.33 kB Microsoft Excel XML Visualizza/Apri
41559_2025_2697_MOESM5_ESM.xlsx

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per accesso libero gratuito
Dimensione 29.04 kB
Formato Microsoft Excel XML
29.04 kB Microsoft Excel XML Visualizza/Apri
41559_2025_2697_MOESM4_ESM.xlsx

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per accesso libero gratuito
Dimensione 18.67 kB
Formato Microsoft Excel XML
18.67 kB Microsoft Excel XML Visualizza/Apri
41559_2025_2697_MOESM3_ESM.pdf

accesso aperto

Descrizione: Peer Review File
Tipo: Versione (PDF) editoriale / Version Of Record
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione 378.69 kB
Formato Adobe PDF
378.69 kB Adobe PDF Visualizza/Apri
41559_2025_2697_MOESM2_ESM.pdf

accesso aperto

Descrizione: Reporting Summary
Tipo: File Supplementare
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione 99.04 kB
Formato Adobe PDF
99.04 kB Adobe PDF Visualizza/Apri
41559_2025_2697_MOESM1_ESM.pdf

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per accesso libero gratuito
Dimensione 1.5 MB
Formato Adobe PDF
1.5 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1058453
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 21
  • ???jsp.display-item.citation.isi??? 21
  • OpenAlex ND
social impact