Citizen science platforms can effectively support early detection of invasive alien species according to species traits
Abstract Early detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, bu...
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2025-01-01
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Online Access: | https://doi.org/10.1002/pan3.10767 |
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author | Pablo González‐Moreno Ana A. Anđelković Tim Adriaens Christophe Botella Jakovos Demetriou Rita Bastos Sandro Bertolino Celia López‐Cañizares Franz Essl Živa Fišer Milka Glavendekić Marc Herremans Philip E. Hulme Viola Jani Dimitra Katsada Periklis Kleitou Nicola La Porta Katharina Lapin Marta López‐Darias Vanessa Lozano Angeliki F. Martinou Damiano Oldoni Esra Per Stephanie Rorke Helen E. Roy Karl‐Manfred Schweinzer Kristijn Swinnen Elena Tricarico Joana R. Vicente Maarten de Groot Michael J. O. Pocock |
author_facet | Pablo González‐Moreno Ana A. Anđelković Tim Adriaens Christophe Botella Jakovos Demetriou Rita Bastos Sandro Bertolino Celia López‐Cañizares Franz Essl Živa Fišer Milka Glavendekić Marc Herremans Philip E. Hulme Viola Jani Dimitra Katsada Periklis Kleitou Nicola La Porta Katharina Lapin Marta López‐Darias Vanessa Lozano Angeliki F. Martinou Damiano Oldoni Esra Per Stephanie Rorke Helen E. Roy Karl‐Manfred Schweinzer Kristijn Swinnen Elena Tricarico Joana R. Vicente Maarten de Groot Michael J. O. Pocock |
author_sort | Pablo González‐Moreno |
collection | DOAJ |
description | Abstract Early detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, but this has not been tested. We evaluated the potential of data from existing citizen science platforms for early detection of IAS by obtaining 687 first records of species from 30 European countries where there was both an official first record (i.e. published in scientific literature or by a government agency) and a record in a citizen science platform. We tested how the difference between the two (time lag) was related to species traits, popularity in citizen science platforms, public and research attention and regulatory status. We found that for 50% of the time lag records, citizen science platforms reported IAS earlier than or in the same year as the official databases. Although we cannot determine causality (the first official record could have been from a citizen science platform, or contemporaneous with it), this demonstrates that citizen science platforms are effective for IAS early detection. Time lags were largely affected by species traits. Compared with official records, vertebrates were more likely to have earlier records on citizen science platforms, than plants or invertebrates. Greater popularity of the IAS in citizen science platforms and its observation in neighbouring countries resulted in earlier citizen science reporting. In contrast, inclusion in the EU priority list resulted in earlier official recording, reflecting the efficacy of targeted surveillance programmes. However, time lags were not affected by the overall activity of citizen platforms per country. Synthesis and applications. Multi‐species citizen science platforms for reporting nature sightings are a valuable source of information on early detection of IAS even though they are not specifically designed for this purpose. We recommend that IAS surveillance programmes should be better connected with citizen science platforms, including greater acknowledgement of the role of citizen scientists and better data flow from smaller citizen science initiatives into global databases, to support efficient early detection. Read the free Plain Language Summary for this article on the Journal blog. |
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spelling | doaj-art-456ca8a95bff4239bbff266492dbb38e2025-01-23T04:04:08ZengWileyPeople and Nature2575-83142025-01-017127829410.1002/pan3.10767Citizen science platforms can effectively support early detection of invasive alien species according to species traitsPablo González‐Moreno0Ana A. Anđelković1Tim Adriaens2Christophe Botella3Jakovos Demetriou4Rita Bastos5Sandro Bertolino6Celia López‐Cañizares7Franz Essl8Živa Fišer9Milka Glavendekić10Marc Herremans11Philip E. Hulme12Viola Jani13Dimitra Katsada14Periklis Kleitou15Nicola La Porta16Katharina Lapin17Marta López‐Darias18Vanessa Lozano19Angeliki F. Martinou20Damiano Oldoni21Esra Per22Stephanie Rorke23Helen E. Roy24Karl‐Manfred Schweinzer25Kristijn Swinnen26Elena Tricarico27Joana R. Vicente28Maarten de Groot29Michael J. O. Pocock30Department of Forest Engineering, ERSAF University of Córdoba Córdoba SpainInstitute for Plant Protection and Environment Department of Weed Research Belgrade SerbiaResearch Institute for Nature and Forest (INBO), Herman Teirlinckgebouw Brussels BelgiumCenter for Invasion Biology Stellenbosch University Stellenbosch South AfricaLaboratory of Vector Ecology and Applied Entomology, Joint Services Health Unit Cyprus Akrotiri CyprusCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão Universidade do Porto Vairão PortugalDepartment of Life Sciences and Systems University of Turin Turin ItalyDepartment of Zoology and Physical Anthropology University of Murcia Murcia SpainDivision of BioInvasions, Macroecology & Global Change, Department of Botany and Biodiversity Research University of Vienna AustriaUniversity of Primorska, Faculty of Mathematics Natural Sciences and Information Technologies Koper SloveniaDepartment of Landscape Architecture and Horticulture, Faculty of Forestry University of Belgrade Belgrade SerbiaNatuurpunt Studie Mechelen BelgiumBioprotection Aotearoa, Department of Pest Management and Conservation Lincoln University Canterbury New ZealandDepartment of Epidemiology and Control of Infectious Diseases, Vectors' Control Unit Institute of Public Health Tirana AlbaniaiSea, Environmental Organization for the Preservation of the Aquatic Ecosystems Thessaloniki GreeceMarine & Environmental Research (MER) Lab Ltd Limassol CyprusIASMA Research and Innovation Centre Trento ItalyAustrian Research Centre for Forests, Natural Hazards and Landscape (BFW) Vienna AustriaInstituto de Productos Naturales y Agrobiología (IPNA‐CSIC) Tenerife SpainDepartment of Agricultural Sciences University of Sassari Sassari ItalyLaboratory of Vector Ecology and Applied Entomology, Joint Services Health Unit Cyprus Akrotiri CyprusOpen Science Lab for Biodiversity, Herman Teirlinckgebouw Research Institute for Nature and Forest (INBO) Brussels BelgiumDepartment of Biology, Faculty of Science Gazi University Ankara TurkeyUK Centre for Ecology & Hydrology Wallingford UKUK Centre for Ecology & Hydrology Wallingford UKAustrian Federal Research Centre for Forests, Natural Hazards and Landscape (BFW) Vienna AustriaNatuurpunt Studie Mechelen BelgiumNational Biodiversity Future Center (NBFC) Palermo ItalyCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão Universidade do Porto Vairão PortugalDepartment of Forest Protection Slovenian Forestry Institute Ljubljana SloveniaUK Centre for Ecology & Hydrology Wallingford UKAbstract Early detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, but this has not been tested. We evaluated the potential of data from existing citizen science platforms for early detection of IAS by obtaining 687 first records of species from 30 European countries where there was both an official first record (i.e. published in scientific literature or by a government agency) and a record in a citizen science platform. We tested how the difference between the two (time lag) was related to species traits, popularity in citizen science platforms, public and research attention and regulatory status. We found that for 50% of the time lag records, citizen science platforms reported IAS earlier than or in the same year as the official databases. Although we cannot determine causality (the first official record could have been from a citizen science platform, or contemporaneous with it), this demonstrates that citizen science platforms are effective for IAS early detection. Time lags were largely affected by species traits. Compared with official records, vertebrates were more likely to have earlier records on citizen science platforms, than plants or invertebrates. Greater popularity of the IAS in citizen science platforms and its observation in neighbouring countries resulted in earlier citizen science reporting. In contrast, inclusion in the EU priority list resulted in earlier official recording, reflecting the efficacy of targeted surveillance programmes. However, time lags were not affected by the overall activity of citizen platforms per country. Synthesis and applications. Multi‐species citizen science platforms for reporting nature sightings are a valuable source of information on early detection of IAS even though they are not specifically designed for this purpose. We recommend that IAS surveillance programmes should be better connected with citizen science platforms, including greater acknowledgement of the role of citizen scientists and better data flow from smaller citizen science initiatives into global databases, to support efficient early detection. Read the free Plain Language Summary for this article on the Journal blog.https://doi.org/10.1002/pan3.10767biosecuritycitizen scienceearly detectionearly warningnon‐native species traitsparticipation |
spellingShingle | Pablo González‐Moreno Ana A. Anđelković Tim Adriaens Christophe Botella Jakovos Demetriou Rita Bastos Sandro Bertolino Celia López‐Cañizares Franz Essl Živa Fišer Milka Glavendekić Marc Herremans Philip E. Hulme Viola Jani Dimitra Katsada Periklis Kleitou Nicola La Porta Katharina Lapin Marta López‐Darias Vanessa Lozano Angeliki F. Martinou Damiano Oldoni Esra Per Stephanie Rorke Helen E. Roy Karl‐Manfred Schweinzer Kristijn Swinnen Elena Tricarico Joana R. Vicente Maarten de Groot Michael J. O. Pocock Citizen science platforms can effectively support early detection of invasive alien species according to species traits People and Nature biosecurity citizen science early detection early warning non‐native species traits participation |
title | Citizen science platforms can effectively support early detection of invasive alien species according to species traits |
title_full | Citizen science platforms can effectively support early detection of invasive alien species according to species traits |
title_fullStr | Citizen science platforms can effectively support early detection of invasive alien species according to species traits |
title_full_unstemmed | Citizen science platforms can effectively support early detection of invasive alien species according to species traits |
title_short | Citizen science platforms can effectively support early detection of invasive alien species according to species traits |
title_sort | citizen science platforms can effectively support early detection of invasive alien species according to species traits |
topic | biosecurity citizen science early detection early warning non‐native species traits participation |
url | https://doi.org/10.1002/pan3.10767 |
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