{"refrec":{"BRefID":405951,"RR":"<b>Pagnier, J.; Daraghmeh, N.; Obst, M.</b> (2025). Using the long-term genetic monitoring network ARMS-MBON to detect marine non-indigenous species along the European coasts. <i>Biological Invasions 27(2)</i>: 77. <a href=\"https://dx.doi.org/10.1007/s10530-024-03503-2\" target=\"_blank\">https://dx.doi.org/10.1007/s10530-024-03503-2</a>","BEntID":403746,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":0,"RefStringPartII":". <i>Biological Invasions 27(2)</i>: 77. <a href=\"https://dx.doi.org/10.1007/s10530-024-03503-2\" target=\"_blank\">https://dx.doi.org/10.1007/s10530-024-03503-2</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Pagnier, J.; Daraghmeh, N.; Obst, M.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Pagnier, J.; Daraghmeh, N.; Obst, M.","Englishabstract":"The increasing prevalence of non-indigenous species (NIS) in marine ecosystems poses significant challenges for biodiversity conservation and ecosystem management. Advances in molecular techniques enable early detection and long-term monitoring of such taxa, especially when coupled with spatio-temporally wide sampling by networks such as the European ARMS Marine Biodiversity Observation Network (ARMS-MBON). This initiative performs standardised sampling campaigns using autonomous reef monitoring structures (ARMS) along European coasts and adjacent regions, providing open-access DNA metabarcoding data sets. We tested the potential of genetic observatory networks to detect and monitor marine NIS by analysing all publicly available ARMS-MBON cytochrome c oxidase subunit I (COI) and 18S rRNA amplicon sequencing data as of February 2024 using a customised bioinformatic pipeline. Screening against the World Register of Introduced Marine Species (WRiMS) and applying manual curation, we identified 63 marine taxa considered non-indigenous at one or more locations. This included widespread taxa and potential new introductions, such as <i>Eucheilota menoni</i> in the Adriatic Sea. We found no significantly higher number of NIS in samples from locations particularly impacted by maritime traffic compared to other areas. Our results suggest that the genetic observatory network approach is powerful for detecting and monitoring marine NIS, and that manual curation still is an essential step for obtaining reliable results. We recommend key improvements including more spatially intense sampling across diverse environments as well as enhancement of NIS reference checklists and genetic databases to ensure accurate identification of both known and unknown NIS across Europe.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Using the long-term genetic monitoring network ARMS-MBON to detect marine non-indigenous species along the European coasts","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2025-03-11 01:33:21.907208","timezone_type":1,"timezone":"+01:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"Invasive species · Autonomous reef monitoring structures (ARMS) · COI · 18S rRNA · Amplicon sequencing","OtherDescriptors":null,"Notes":null,"AnaPub":2025,"MonPub":null,"DateUpdate":"2025-03-04","DateCreate":"2025-03-04","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":null,"VABBcode":null,"OpenAcc":1,"DOI":"10.1007/s10530-024-03503-2"},"refs":null,"anarec":{"AnaID":405951,"PubliDate":2025,"Pagination":"77","XtraPublOfAnaID":null,"ISBN":null,"Volume":"27","Issue":"2","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":45217,"SerRR":"Biological Invasions. 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