InvaCost is the most up-to-date, comprehensive, standardized and robust data compilation and description of economic cost estimates associated with invasive species worldwide1. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making. The ongoing work made by the InvaCost consortium2,3,4 leads to constantly improving the structure and content of the database (see sections below). The list of actual contributors to this data resource now largely exceeds the list of authors listed in this page. All details regarding the previous versions of InvaCost can be found by switching from one version to another using the “version” button above. IMPORTANT UPDATES: 1. All information, files, outcomes, updates and resources related to the InvaCost project are now available on a new website: http://invacost.fr/2. The names of the following columns have been changed between the previous and the current version: ‘Raw_cost_estimate_local_currency’ is now named ‘Raw_cost_estimate_original_currency’; ‘Min_Raw_cost_estimate_local_currency’ is now named ‘Min_Raw_cost_estimate_original_currency’; ‘Max_Raw_cost_estimate_local_currency’ is now named ‘Max_Raw_cost_estimate_original_currency’; ‘Cost_estimate_per_year_local_currency’ is now named ‘Cost_estimate_per_year_original_currency’3. The Frequently Asked Questions (FAQ) about the database and how to (1) understand it, (2) analyse it and (3) add new data are available at: https://farewe.github.io/invacost_FAQ/. There are over 60 questions (and responses), so there’s probably yours.4. Accordingly with the continuous development and updates of the database, a ‘living figure’ is now available online to display the evolving relative contributions of different taxonomic groups and regions to the overall cost estimates as the database is updated: https://borisleroy.com/invacost/invacost_livingfigure.html5. We have now added a new column called ‘InvaCost_ID’, which is now used to identify each cost entry in the current and future public versions of the database. As this new column only affects the identification of the cost entries and not their categorisation, this is not considered as a change of the structure of the whole database. Therefore, the first level of the version numbering remains ‘4’ (see VERSION NUMBERING section).

CONTENT: This page contains four files: (1) 'InvaCost_database_v4.1' which contains 13,553 cost entries depicted by 66 descriptive columns; (2) ‘Descriptors 4.1’ provides full definition and details about the descriptive columns used in the database; (3) ‘Update_Invacost_4.1’ has details about the all the changes made between previous and current versions of InvaCost; (4) ‘InvaCost_template_4.1’ (downloadable file) provides an easier way of entering data in the spreadsheet, standardizing all the terms used on it as much as possible to avoid mistakes and saving time at post-refining stages (this file should be used by any external contributor to propose new cost data).

METHODOLOGY: All the methodological details and tools used to build and populate this database are available in Diagne et al. 20201 and Angulo et al. 20215. Note that several papers used different approaches to investigate and analyse the database, and they are all available on our website http://invacost.fr/.

VERSION NUMBERING: InvaCost is regularly updated with contributions from both authors and future users in order to improve it both quantitatively (by new cost information) and qualitatively (if errors are identified). Any reader or user can propose to update InvaCost by filling the ‘InvaCost_updates_template’ file with new entries or corrections, and sending it to our email address (updates@invacost.fr). Each updated public version of InvaCost is stored in this figShare repository, with a unique version number. For this purpose, we consider the original version of InvaCost publicly released in September 2020 as ‘InvaCost_1.0’. The further updated versions are named using the subsequent numbering (e.g., ‘InvaCost_2.0’, InvaCost_2.1’) and all information on changes made are provided in a dedicated file called ‘Updates-InvaCost’ (named using the same numbering, e.g., ‘Updates-InvaCost_2.0’, ‘Updates-InvaCost_2.1’). We consider changing the first level of this numbering (e.g. ‘InvaCost_3.x’ ‘InvaCost_4.x’) only when the structure of the database changes. Every user wanting to have the most up-to-date version of the database should refer to the latest released version.

RECOMMENDATIONS: Every user should read the ‘Usage notes’ section of Diagne et al. 20201 before considering the database for analysis purposes or specific interpretation. InvaCost compiles cost data published in the literature, but does not aim to provide a ready-to-use dataset for specific analyses. While the cost data are described in a homogenized way in InvaCost, the intrinsic disparity, complexity, and heterogeneity of the cost data require specific data processing depending on the user objectives (see our FAQ). However, we provide necessary information and caveats about recorded costs, and we have now an open-source software designed to query and analyse this database6.

CAUTION: InvaCost is currently being analysed by a network of international collaborators in the frame of the InvaCost project2,3,4 (see https://invacost.fr/en/outcomes/). Interested users may contact the InvaCost team if they wish to learn more about or contribute to these current efforts. Users are in no way prevented from performing their own independent analyses and collaboration with this network is not required. Nonetheless, users and contributors are encouraged to contact the InvaCost team before using the database, as the information contained may not be directly implementable for specific analyses.

RELATED LINKS AND PUBLICATIONS:

1 Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z

2 Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37. https://doi.org/10.3897/neobiota.63.55260

3 Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions

4 InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/

5 Angulo E, Diagne C, Ballesteros-Mejia L. et al. (2021) Non-English languages enrich scientific knowledge: the example of economic costs of biological invasions. Science of the Total Environment 775:144441. https://doi.org/10.1016/j.scitotenv.2020.144441

6Leroy B, Kramer A M, Vaissière A-C, Courchamp F and Diagne C (2020) Analysing global economic costs of invasive alien species with the invacost R package. BioRXiv. doi: https://doi.org/10.1101/2020.12.10.419432

This dataset contains key characteristics about the data described in the Data Descriptor INVACOST, a public database of the economic costs of biological invasions worldwide. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format

CAUTION: InvaCost is currently being analysed by a network of international collaborators in the frame of the InvaCost project (https://www.biodiversitydynamics.fr/invacost-workshop/). Interested users may contact the authors if they wish to learn more about or contribute to these current efforts. Users are in no way prevented from performing their own independent analyses and collaboration with this network is not required. Nonetheless, users and contributors are encouraged to contact the authors before using the database, as the information contained may not be directly implementable for specific analyses.

InvaCost ('InvaCost_database' file) is the most up-to-date, comprehensive, harmonised and robust data compilation and description of economic cost estimates associated with invasive species worldwide.

Currently, this database contains 2419 cost estimates described by 46 variables. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making issues.

All the methodological details and tools used to build and populate this living and publicly available database are available at https://www.nature.com/articles/s41597-020-00586-z. All scientific peer-reviewed articles and grey literature (along with their bibliographic details and/or links) collected and examined for collating and describing these cost data are also provided in the 'InvaCost_references' file (see the related published paper abovementioned for specific details).

InvaCost is intended to be regularly updated with contributions from both authors and future users in order to improve it both quantitatively (by new cost information) and qualitatively (if errors are identified). Any reader or user can propose to update InvaCost by contacting our e-mail address (updates@invacost.fr). Each updated version of InvaCost will be stored in the same repository as the original version, with a unique version number. For this purpose, we consider the original version of InvaCost publicly released on (date of publication) as ‘InvaCost_1.0’. The further updated versions will be named using the order of this numbering (e.g., ‘InvaCost_1.1’, InvaCost_1.2’) with all information on changes made that will be provided in a dedicated file called ‘Updates_Changes.xlsx’. We will consider ‘InvaCost_2.0’ only when the structure of the database will change.IMPORTANT: In the frame of our general InvaCost project, we have now generated two other databases on the economic costs of invasions worldwide: one based on the remaining references collected (but not yet processed when constructing the original InvaCost database) that is available at https://doi.org/10.6084/m9.figshare.12928145.v1; and the other one based on documents available on languages other than English, which is available at https://doi.org/10.6084/m9.figshare.12928136.

This database is complementary to the original version of Invacost[1]. An updated version of this database is now incorporated within this core database.CONTENT: This page contains (a) the original version of the 'Complementary Search’ database' ('InvaCost_SC database') and (b) full definition and details about the descriptive columns used in this database (‘Descriptors’ file). METHODOLOGY: The construction of this complementary database results from a collective work made by members of the InvaCost consortium[2] following the InvaCost workshop[3,4]. We have screened a total of 304 new references (collected but not processed in the building process of original InvaCost) from which we extracted 2,374 cost entries. Most of the screened references belong to plants; however, they also contain costs for other invasive organisms (animals and pathogens). All cost entries have been standardized for both costs and text, however not all have been yet double-checked (i.e. process to ensure quality of the integrated information, usually made by one or two independent researchers) as the other parts of the Invacost database (i.e. original InvaCost_1.0 and Non-English).UPDATES, RECOMMENDATIONS & CAUTION: Please consider information already described elsewhere[5] for the original InvaCost database. RELATED LINKS AND PUBLICATIONS: [1]Database: https://figshare.com/articles/dataset/InvaCost_References_and_description_of_economic_cost_estimates_associated_with_biological_invasions_worldwide_/12668570 [2] Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions[3] InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/ [4] Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37.https://doi.org/10.3897/neobiota.63.55260[5] Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z

Table S2. Observed costs for Brazil from the invacost database organized into the following group of intervention: damage, management, and mixed

This dataset accompanies a published paper (Evans et al. 2023) which aims to identify links between the biodiversity impacts and monetary costs of alien bird species. In this paper we used mixed-effects models to test: (1) whether alien bird species with severe biodiversity impacts also had high monetary costs; (2) whether specific types of biodiversity impacts were associated with high monetary costs; and (3) whether certain factors caused alien bird species to have both severe biodiversity impacts and high monetary costs. This dataset includes all data used for the analysis, including biodiversity impact scores and monetary costs for each alien bird species, and the variables tested for their influence on these biodiversity impacts and costs. Please refer to Evans et al. (2023) for details on the methods used. The abstract to the published paper follows.

Alien species can be damaging to native biodiversity, human well-being and the economy. Identifying the complete range of impacts t...

The ‘Non-English database’ is part of the InvaCost project (1) that compiles cost information associated with biological invasions. These records describe cost estimates reported in documents written in ten languages other than English (i.e. Chinese, French, German, Greek, Japanese, Portuguese, Russian, Spanish, Dutch, and Ukrainian). An updated version of this database is now incorporated within the core InvaCost Database (3).CONTENT: This page contains (a) the original version of the 'InvaCost_Non-English database' and (b) full definition and details about the descriptive columns used in this database (‘Descriptors’ file).METHODOLOGY: The methodology was similar to the one used to compile the original version of InvaCost (2), but targeting more national webpages and specific literature databases, as well as directly contacting stakeholders that could provide data. The search was carried out by native speakers. Entries were checked by two contributors, except for the entries in Ukrainian and Greek. These ‘non-English’ searches originally resulted in 356 documents and 5,212 entries.UPDATES, RECOMMENDATIONS & CAUTION: Please consider information already described elsewhere (3) for the original InvaCost database. RELATED LINKS AND PUBLICATIONS:1. Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37. https://doiorg/10.3897/neobiota.63.552602. Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z3.Database: https://figshare.com/articles/dataset/InvaCost_References_and_description_of_economic_cost_estimates_associated_with_biological_invasions_worldwide_/12668570 4. Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions5. InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/

Table S2. The classification and description of seven sectors impacted by invasive species

Description of the sectors considered in the InvaCost database

Table S1. Dataset of the economic costs of biological invasion in Japan

Description of the sectors considered in the InvaCost database

Pistia stratiotes, Eichhornia crassipes, Alternanthera philoxeroides, and Cabomba caroliniana are officially recognized as invasive aquatic plants in China. Accurately predicting their invasion dynamics under climate change is crucial for the future safety of aquatic ecosystems. Compared to single prediction models, ensemble models that integrate multiple algorithms provide more accurate forecasts. However, there has been a notable lack of research utilizing ensemble models to collectively predict the invasive regions of these four species in China. To address this gap, we collected and analyzed comprehensive data on species distribution, climate, altitude, population density, and the normalized difference vegetation index to accurately predict the future invasive regions and potential warnings for aquatic systems concerning these species. At the same time, we analyzed the economic losses caused by these four aquatic plants in China.

Table S1. Dataset on economic losses associated with biological invasions in terrestrial ecosystems in Russia

Distribution of the reliable observed costs

Invasive aquatic plants obstruct waterways, disrupt fisheries, and cause significant economic, social, and ecological impacts. This study focuses on four globally widespread invasive species: Eichhornia crassipes, Pistia stratiotes, Cabomba caroliniana, and Alternanthera philoxeroides. Distribution points and integrated environmental datasets were collected, and the global potential distribution of these species was predicted using the species distribution modeling framework Biomod2. Additionally, the Invacost database was employed to evaluate economic losses, which included statistical analyses and model fitting. The results indicate that the potential suitable habitats for E. crassipes and P. stratiotes are primarily located in South Asia, parts of Africa, Europe, and Oceania, as well as low- to mid-latitude regions in North and South America. The current potential distribution of A. philoxeroides is concentrated in South Asia, the southeastern United States, most of South America, and some low-suitability areas in Europe and Africa. For C. caroliniana, the predicted suitable habitats are relatively limited and primarily distributed across South Asia, Southeast Asia, the southeastern United States, and southeastern South America. Under future climate scenarios, the suitable habitats for these species are projected to expand and shift toward higher latitudes, with E. crassipes and P. stratiotes experiencing the largest increases in suitable areas, at 9.99% and 10.21%, respectively. In contrast, the increases for A. philoxeroides and C. caroliniana are relatively modest. Key environmental variables contributing to these predictions include mean annual temperature, population density, and mean temperature of the coldest season. The global economic losses caused by these four invasive aquatic plants are estimated at $7,380.30 million from 1990 to 2025, with an average annual loss of $205.01 million. The model fitting suggests that economic losses have been increasing over time. This study provides predictions of the global potential distribution of four invasive aquatic plants and examines changes in their suitable habitats under future climate conditions. It also evaluates the associated global economic losses. The findings highlight the regions at high risk of invasion by P. stratiotes, E. crassipes, C. caroliniana, and A. philoxeroides, as well as the economic impacts of these invasions. Furthermore, the study underscores the influence of human activities and climate change on the distribution of invasive aquatic plants. These results contribute to the monitoring, early detection, and rapid response to invasive aquatic plants, aiding the development of prevention and management strategies. They provide theoretical support for research on biological invasions and climate change while offering recommendations for raising public awareness and informing government policy decisions. The study aims to offer new perspectives on the prediction of biological invasion risks and economic losses, thereby laying a foundation for improved management and innovative prevention strategies for invasive species.

Web of Science search terms for UK invasive species publication numbers, alongside resulting study numbers

Economic costs of invasive alien species in Mexico

Annual average costs of biological invasions in Singapore. Note the y-axis is on a log10 scale

Description of the different sectors of the InvaCost database

Dataset of the economic costs of invasive alien species in Spain and descriptive variables