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A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways

World trade has greatly increased in recent decades, together with a higher risk of introducing non-indigenous pests. Introduction trends show no sign of saturation, and it seems likely that many more species will enter and establish in new territories in the future. A key challenge in analysing pes...

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Autores principales: Rosace, Maria Chiara, Cendoya, Martina, Mattion, Giulia, Vicent, Antonio, Battisti, Andrea, Cavaletto, Giacomo, Marini, Lorenzo, Rossi, Vittorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590444/
https://www.ncbi.nlm.nih.gov/pubmed/37865703
http://dx.doi.org/10.1038/s41597-023-02643-9
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author Rosace, Maria Chiara
Cendoya, Martina
Mattion, Giulia
Vicent, Antonio
Battisti, Andrea
Cavaletto, Giacomo
Marini, Lorenzo
Rossi, Vittorio
author_facet Rosace, Maria Chiara
Cendoya, Martina
Mattion, Giulia
Vicent, Antonio
Battisti, Andrea
Cavaletto, Giacomo
Marini, Lorenzo
Rossi, Vittorio
author_sort Rosace, Maria Chiara
collection PubMed
description World trade has greatly increased in recent decades, together with a higher risk of introducing non-indigenous pests. Introduction trends show no sign of saturation, and it seems likely that many more species will enter and establish in new territories in the future. A key challenge in analysing pest invasion patterns is the paucity of historical data on pest introductions. A comprehensive dataset of pests’ introductions in the EU, including their spatial occurrences, is not currently available and information is scattered across different sources or buried in the scientific literature. Therefore, we collected pests’ introduction information (e.g., year, host) from online scientific databases and literature; we then gathered primary spatial data related to the site of first introductions. Finally, we identified the potential pathways of entry for each pest. The dataset contains expert-revised data on 278 pests introduced in the EU between 1999 and 2019, alongside their spatial occurrence and potential pathways of entry, providing a basis to better understand the factors associated with the likelihood of pest introduction. It is important to note that this dataset does not contain the current distribution of the introduced pests, but only records of their first introduction in the EU.
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spelling pubmed-105904442023-10-23 A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways Rosace, Maria Chiara Cendoya, Martina Mattion, Giulia Vicent, Antonio Battisti, Andrea Cavaletto, Giacomo Marini, Lorenzo Rossi, Vittorio Sci Data Data Descriptor World trade has greatly increased in recent decades, together with a higher risk of introducing non-indigenous pests. Introduction trends show no sign of saturation, and it seems likely that many more species will enter and establish in new territories in the future. A key challenge in analysing pest invasion patterns is the paucity of historical data on pest introductions. A comprehensive dataset of pests’ introductions in the EU, including their spatial occurrences, is not currently available and information is scattered across different sources or buried in the scientific literature. Therefore, we collected pests’ introduction information (e.g., year, host) from online scientific databases and literature; we then gathered primary spatial data related to the site of first introductions. Finally, we identified the potential pathways of entry for each pest. The dataset contains expert-revised data on 278 pests introduced in the EU between 1999 and 2019, alongside their spatial occurrence and potential pathways of entry, providing a basis to better understand the factors associated with the likelihood of pest introduction. It is important to note that this dataset does not contain the current distribution of the introduced pests, but only records of their first introduction in the EU. Nature Publishing Group UK 2023-10-21 /pmc/articles/PMC10590444/ /pubmed/37865703 http://dx.doi.org/10.1038/s41597-023-02643-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Rosace, Maria Chiara
Cendoya, Martina
Mattion, Giulia
Vicent, Antonio
Battisti, Andrea
Cavaletto, Giacomo
Marini, Lorenzo
Rossi, Vittorio
A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title_full A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title_fullStr A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title_full_unstemmed A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title_short A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways
title_sort spatio-temporal dataset of plant pests’ first introductions across the eu and potential entry pathways
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590444/
https://www.ncbi.nlm.nih.gov/pubmed/37865703
http://dx.doi.org/10.1038/s41597-023-02643-9
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