Characterizing feral swine movement across the contiguous United States using neural networks and genetic data

Abstract Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine ( Sus scrofa × domesticus ) are recognized as being among the most destructive invasive spec...

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Published in:Molecular Ecology
Main Authors: Giglio, Rachael M., Bowden, Courtney F., Brook, Ryan K., Piaggio, Antoinette J., Smyser, Timothy J.
Other Authors: Animal and Plant Health Inspection Service
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2024
Subjects:
Online Access:http://dx.doi.org/10.1111/mec.17489
https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.17489
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spelling crwiley:10.1111/mec.17489 2024-09-15T17:47:20+00:00 Characterizing feral swine movement across the contiguous United States using neural networks and genetic data Giglio, Rachael M. Bowden, Courtney F. Brook, Ryan K. Piaggio, Antoinette J. Smyser, Timothy J. Animal and Plant Health Inspection Service 2024 http://dx.doi.org/10.1111/mec.17489 https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.17489 en eng Wiley http://creativecommons.org/licenses/by-nc-nd/4.0/ Molecular Ecology volume 33, issue 17 ISSN 0962-1083 1365-294X journal-article 2024 crwiley https://doi.org/10.1111/mec.17489 2024-08-30T04:10:51Z Abstract Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine ( Sus scrofa × domesticus ) are recognized as being among the most destructive invasive species, with populations established on all continents except Antarctica. Within the United States (US), feral swine are responsible for extensive crop damage, the destruction of native ecosystems, and the spread of disease. Purposeful human‐mediated movement of feral swine has contributed to their rapid range expansion over the past 30 years. Patterns of deliberate introduction of feral swine have not been well described as populations may be established or augmented through small, undocumented releases. By leveraging an extensive genomic database of 18,789 samples genotyped at 35,141 single nucleotide polymorphisms (SNPs), we used deep neural networks to identify translocated feral swine across the contiguous US. We classified 20% (3364/16,774) of sampled animals as having been translocated and described general patterns of translocation using measures of centrality in a network analysis. These findings unveil extensive movement of feral swine well beyond their dispersal capabilities, including individuals with predicted origins >1000 km away from their sampling locations. Our study provides insight into the patterns of human‐mediated movement of feral swine across the US and from Canada to the northern areas of the US. Further, our study validates the use of neural networks for studying the spread of invasive species. Article in Journal/Newspaper Antarc* Antarctica Wiley Online Library Molecular Ecology 33 17
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine ( Sus scrofa × domesticus ) are recognized as being among the most destructive invasive species, with populations established on all continents except Antarctica. Within the United States (US), feral swine are responsible for extensive crop damage, the destruction of native ecosystems, and the spread of disease. Purposeful human‐mediated movement of feral swine has contributed to their rapid range expansion over the past 30 years. Patterns of deliberate introduction of feral swine have not been well described as populations may be established or augmented through small, undocumented releases. By leveraging an extensive genomic database of 18,789 samples genotyped at 35,141 single nucleotide polymorphisms (SNPs), we used deep neural networks to identify translocated feral swine across the contiguous US. We classified 20% (3364/16,774) of sampled animals as having been translocated and described general patterns of translocation using measures of centrality in a network analysis. These findings unveil extensive movement of feral swine well beyond their dispersal capabilities, including individuals with predicted origins >1000 km away from their sampling locations. Our study provides insight into the patterns of human‐mediated movement of feral swine across the US and from Canada to the northern areas of the US. Further, our study validates the use of neural networks for studying the spread of invasive species.
author2 Animal and Plant Health Inspection Service
format Article in Journal/Newspaper
author Giglio, Rachael M.
Bowden, Courtney F.
Brook, Ryan K.
Piaggio, Antoinette J.
Smyser, Timothy J.
spellingShingle Giglio, Rachael M.
Bowden, Courtney F.
Brook, Ryan K.
Piaggio, Antoinette J.
Smyser, Timothy J.
Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
author_facet Giglio, Rachael M.
Bowden, Courtney F.
Brook, Ryan K.
Piaggio, Antoinette J.
Smyser, Timothy J.
author_sort Giglio, Rachael M.
title Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
title_short Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
title_full Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
title_fullStr Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
title_full_unstemmed Characterizing feral swine movement across the contiguous United States using neural networks and genetic data
title_sort characterizing feral swine movement across the contiguous united states using neural networks and genetic data
publisher Wiley
publishDate 2024
url http://dx.doi.org/10.1111/mec.17489
https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.17489
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_source Molecular Ecology
volume 33, issue 17
ISSN 0962-1083 1365-294X
op_rights http://creativecommons.org/licenses/by-nc-nd/4.0/
op_doi https://doi.org/10.1111/mec.17489
container_title Molecular Ecology
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