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      Current GBIF occurrence data demonstrates both promise and limitations for potential red listing of spiders

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          Abstract

          Abstract

          Conservation assessments of hyperdiverse groups of organisms are often challenging and limited by the availability of occurrence data needed to calculate assessment metrics such as extent of occurrence (EOO). Spiders represent one such diverse group and have historically been assessed using primary literature with retrospective georeferencing. Here we demonstrate the differences in estimations of EOO and hypothetical IUCN Red List classifications for two extensive spider datasets comprising 479 species in total. The EOO were estimated and compared using literature-based assessments, Global Biodiversity Information Facility (GBIF)-based assessments and combined data assessments. We found that although few changes to hypothetical IUCN Red List classifications occurred with the addition of GBIF data, some species (3.3%) which could previously not be classified could now be assessed with the addition of GBIF data. In addition, the hypothetical classification changed for others (1.5%). On the other hand, GBIF data alone did not provide enough data for 88.7% of species. These results demonstrate the potential of GBIF data to serve as an additional source of information for conservation assessments, complementing literature data, but not particularly useful on its own as it stands right now for spiders.

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          Most cited references 21

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          Supporting Red List threat assessments with GeoCAT: geospatial conservation assessment tool

          Abstract GeoCAT is an open source, browser based tool that performs rapid geospatial analysis to ease the process of Red Listing taxa. Developed to utilise spatially referenced primary occurrence data, the analysis focuses on two aspects of the geographic range of a taxon: the extent of occurrence (EOO) and the area of occupancy (AOO). These metrics form part of the IUCN Red List categories and criteria and have often proved challenging to obtain in an accurate, consistent and repeatable way. Within a familiar Google Maps environment, GeoCAT users can quickly and easily combine data from multiple sources such as GBIF, Flickr and Scratchpads as well as user generated occurrence data. Analysis is done with the click of a button and is visualised instantly, providing an indication of the Red List threat rating, subject to meeting the full requirements of the criteria. Outputs including the results, data and parameters used for analysis are stored in a GeoCAT file that can be easily reloaded or shared with collaborators. GeoCAT is a first step toward automating the data handling process of Red List assessing and provides a valuable hub from which further developments and enhancements can be spawned.
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            Toward monitoring global biodiversity

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              Research and Societal Benefits of the Global Biodiversity Information Facility

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                Author and article information

                Contributors
                Journal
                Biodivers Data J
                Biodivers Data J
                1
                urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4
                urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02
                Biodiversity Data Journal
                Pensoft Publishers
                1314-2828
                2019
                19 December 2019
                : 7
                Affiliations
                [1 ] Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History, University of Helsinki Helsinki Finland
                [2 ] Georgetown University, Washington, DC, United States of America Georgetown University Washington, DC United States of America
                [3 ] The Academy of Natural Sciences of Drexel University, Philadelphia, United States of America The Academy of Natural Sciences of Drexel University Philadelphia United States of America
                Author notes
                Corresponding authors: Vaughn Shirey ( vmshirey@ 123456gmail.com ), Pedro Cardoso ( pedro.cardoso@ 123456helsinki.fi ).

                Academic editor: Jeremy Miller

                Article
                47369 12433
                10.3897/BDJ.7.e47369
                6933025
                Vaughn Shirey, Sini Seppälä, Vasco Veiga Branco, Pedro Cardoso

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 0, Tables: 2, References: 23
                Categories
                Research Article

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