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      InvaCost, a public database of the economic costs of biological invasions worldwide

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          Abstract

          Biological invasions are responsible for tremendous impacts globally, including huge economic losses and management expenditures. Efficiently mitigating this major driver of global change requires the improvement of public awareness and policy regarding its substantial impacts on our socio-ecosystems. One option to contribute to this overall objective is to inform people on the economic costs linked to these impacts; however, until now, a reliable synthesis of invasion costs has never been produced at a global scale. Here, we introduce InvaCost as the most up-to-date, comprehensive, harmonised and robust compilation and description of economic cost estimates associated with biological invasions worldwide. We have developed a systematic, standardised methodology to collect information from peer-reviewed articles and grey literature, while ensuring data validity and method repeatability for further transparent inputs. Our manuscript presents the methodology and tools used to build and populate this living and publicly available database. InvaCost provides an essential basis (2419 cost estimates currently compiled) for worldwide research, management efforts and, ultimately, for data-driven and evidence-based policymaking.

          Abstract

          Measurement(s) economic cost of biological invasions
          Technology Type(s) digital curation
          Sample Characteristic - Environment aquatic environment • terrestrial biome • semi-aquatic environment
          Sample Characteristic - Location Earth (planet)

          Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11627406

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          Most cited references18

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          The history of ecosystem services in economic theory and practice: From early notions to markets and payment schemes

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                Author and article information

                Contributors
                christophe.diagne@u-psud.fr
                franck.courchamp@u-psud.fr
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                8 September 2020
                8 September 2020
                2020
                : 7
                : 277
                Affiliations
                [1 ]GRID grid.4444.0, ISNI 0000 0001 2112 9282, Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique Evolution, ; 91405 Orsay, France
                [2 ]Unité Biologie des Organismes et Ecosystèmes Aquatiques (BOREA, UMR 7208), Muséum national d’Histoire naturelle, Sorbonne Université, Université de Caen Normandie, CNRS, IRD, Université des Antilles, Paris, France
                [3 ]GRID grid.462058.d, ISNI 0000 0001 2188 7059, ISEM, Univ. Montpellier - CNRS - IRD, ; Montpellier, France
                [4 ]GRID grid.462603.5, ISNI 0000 0004 0382 3424, MIVEGEC, UMR IRD 224 - CNRS 5290 - Univ. Montpellier, ; Montpellier, France
                [5 ]GRID grid.493975.5, ISNI 0000 0004 5948 8741, Santé publique France, ; Saint-Maurice, France
                [6 ]GRID grid.448010.9, ISNI 0000 0001 2193 0563, Biology Centre of the Czech Academy of Sciences, Institute of Hydrobiology, Na Sádkách 702/7, ; 37005 České Budějovice, Czech Republic
                [7 ]GRID grid.14509.39, ISNI 0000 0001 2166 4904, University of South Bohemia, Faculty of Science, Department of Ecosystem Biology, Branišovska 1645/31a, ; 37005 České Budějovice, Czech Republic
                Author information
                http://orcid.org/0000-0002-6406-1270
                http://orcid.org/0000-0002-7686-4302
                http://orcid.org/0000-0001-7948-1051
                http://orcid.org/0000-0002-5819-3648
                http://orcid.org/0000-0002-2185-297X
                http://orcid.org/0000-0001-7605-4548
                Article
                586
                10.1038/s41597-020-00586-z
                7479195
                31896794
                f9c496f8-f194-4ad3-a711-e082962f859d
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

                History
                : 14 October 2019
                : 10 January 2020
                Categories
                Data Descriptor
                Custom metadata
                © The Author(s) 2020

                environmental economics,invasive species,databases
                environmental economics, invasive species, databases

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