Non-native species list to examine non-native species diversity globally

DOI

A comprehensive dataset of non-native species (NNS) was assembled by combining the SInAS database of alien species occurrences (Seebens, 2021) with several other publicly available databases and NNS lists to examine NNS diversity globally (Bailey et al., 2020; Campbell et al., 2016; Carlton & Eldredge, 2009; Casties et al., 2016; Eldredge & Carlton, 2015; Hewitt et al., 2002, 2004; Lambert, 2002; Meyer, 2000; NEMESIS, 2017, 2020; Paulay et al., 2002; Richardson et al., 2020; Schwindt et al., 2020; Sturtevant et al., 2019; U.S. Geological Survey, 2017; Wonham & Carlton, 2005) to examine NNS diversity globally. The SInAS_AlienSpeciesDB_2.4.1 file was used as the base file for our dataset. Species without assignment of invaded country/region were removed from the dataset. Then, species assigned only as CASUAL and ABSENT in the columns degreeOfEstablishment (N) and occurrenceStatus (L), respectively, were also removed due to their undetermined non-native establishment status in those particular regions (Groom et al., 2019). Following, species from other publicly available databases and NNS lists that had not been listed for particular region/s in the SInAS database were added to the file. The species that were both native and NNS within a continent were retained in the dataset. Accordingly, the dataset consisted 36 822 species established outside of their native regions, out of which 36 326 came from Seebens (2021) and 496 species from other databases and NNS lists. Binominal scientific names, phylum, class, and family levels were assigned to each species based on the SInAS_AlienSpeciesDB_2.4.1_FullTaxaList file that was originally determined following Global Biodiversity Information Facility (GBIF). When a species was not automatically assigned to binominal scientific name and/or taxonomic level, an additional manual search of GBIF, World Register of Marine Species (WoRMS) and a general internet search engine was conducted in June and July 2022, and September 2023. Also, to examine NNS diversity among different habitats (i.e., terrestrial, freshwater, and marine), we assigned one or more habitats for each species based on the Step2_StandardTerms_GRIIS file; habitat data in the Step2_StandardTerms_GRIIS file originated from the Global Register of Introduced and Invasive Species (GRIIS). Again, if habitat(s) was(were) not automatically assigned to a species, an additional manual search of WoRMS and a general internet search engine was conducted from July to September 2022. We emphasize that due to the great number of species in our dataset and changing information availability over time, there is a possibility that we did not list all potential habitats for all species. Brackish habitats were defined as marine based on the Venice System (1958). Regions were assigned based on the geographic continental definitions (i.e., North America, South America, Europe, Africa, Asia, and Australia), with Pacific islands as a separate region due to their unclear/undefined continental affiliations (National Geographic Society, 2022). Finally, global estimated biodiversity (i.e., numbers of species per taxonomic group) of each particular phylum, class, and family was obtained from the GBIF in October 2022 (GBIF, 2022).

Identifier
DOI https://doi.org/10.1594/PANGAEA.940752
Related Identifier https://doi.org/10.1111/geb.13781
Related Identifier https://www.gbif.org
Related Identifier https://invasions.si.edu/nemesis/calnemo/overview
Related Identifier https://nas.er.usgs.gov/queries/SpeciesList.aspx?group=&state=WA&Sortby=1#(2017)
Related Identifier https://doi.org/10.1111/ddi.13167
Related Identifier https://doi.org/10.3391/mbi.2016.7.4.05
Related Identifier https://doi.org/10.1002/ece3.2528
Related Identifier https://doi.org/10.1353/psc.2002.0016
Related Identifier https://doi.org/10.1007/s00227-003-1173-x
Related Identifier https://doi.org/10.1353/psc.2002.0026
Related Identifier https://www.sprep.org
Related Identifier https://doi.org/10.1353/psc.2002.0036
Related Identifier https://doi.org/10.1007/978-3-030-32394-3_3
Related Identifier https://doi.org/10.3391/ai.2020.15.1.02
Related Identifier https://doi.org/10.5281/zenodo.5562892
Related Identifier https://doi.org/10.1016/j.jglr.2019.09.002
Related Identifier https://doi.org/10.1007/s10530-004-2581-7
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.940752
Provenance
Creator Briski, Elizabeta ORCID logo; Kotronaki, Syrmalenia G (ORCID: 0009-0002-4295-055X); Cuthbert, Ross N (ORCID: 0000-0003-2770-254X); Bortolus, Alejandro (ORCID: 0000-0003-3035-315X); Campbell, Marnie L ORCID logo; Dick, Jaimie; Fofonoff, Paul; Galil, Bella S; Hewitt, Chad L ORCID logo; Lockwood, Julie; MacIsaac, Hugh J; Ricciardi, Anthony; Ruiz, Gregory M (ORCID: 0000-0003-2499-441X); Schwindt, Evangelina ORCID logo; Sommer, Ulrich; Zhan, Aibin; Carlton, James T ORCID logo
Publisher PANGAEA
Publication Year 2022
Rights Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Representation
Resource Type Dataset
Format text/tab-separated-values
Size 664480 data points
Discipline Earth System Research