To analyse global costs of invasive crustaceans , we used data from the InvaCost database , which primarily presents costs from sources written in English , and sources from 16 additional languages ( Angulo et al . , 2020 . InvaCost captures cost data resulting from both systematic searches of the Web of Science , Google Scholar and Google search engine , and opportunistic contacts with experts and stakeholders . Each recorded cost entry was characterised by various descriptors as described by Diagne et al . ( 2020 ) and in the online database repository ( https://doi.org/10.6084/m9.figshare.12668570 ) . InvaCost is a dynamic database that allows new cost entries to be corrected and added as they develop or are reported over time . The current version of InvaCost includes 13,123 cost entries ( i.e. reported economic costs , or rows of data ) of invasive alien species extracted from published peer - reviewed and grey literature ( InvaCost version 4.0 ; as of June 2021 ) . Although there may be costs that we have not captured ( e.g. , unpublished or outside the search languages ) , InvaCost is the most up - to - date compilation of invasion costs and therefore the best tool available to draw parallels with the current stateof - the - art in cost reporting and associated knowledge gaps . However , the results may change with future research and as monetary cost data become available for different species , countries , sectors , and other factors .