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

IF 4.5 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rachael M. Giglio, Courtney F. Bowden, Ryan K. Brook, Antoinette J. Piaggio, Timothy J. Smyser
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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.

Abstract Image

利用神经网络和基因数据描述野猪在美国毗连地区的移动特征。
全球化导致物种频繁迁出其原生栖息地。其中一些物种具有高度入侵性,能够深刻改变被入侵的生态系统。野猪(Sus scrofa × domesticus)是公认的最具破坏性的入侵物种之一,其种群已遍布除南极洲以外的各大洲。在美国,野猪对农作物造成了广泛的破坏,破坏了本地生态系统,并传播疾病。在过去的 30 年中,人类有目的的野猪移动导致了野猪分布范围的迅速扩大。由于野猪种群可能是通过小规模、无记录的放归建立或扩大的,因此对野猪的蓄意引入模式还没有很好的描述。通过利用由 18789 个样本组成的广泛的基因组数据库,对 35141 个单核苷酸多态性(SNPs)进行基因分型,我们使用深度神经网络来识别美国毗连地区的野猪迁移情况。我们将 20% 的采样动物(3364/16774 头)归类为被迁移过的动物,并在网络分析中使用中心度量描述了迁移的一般模式。这些发现揭示了野猪的广泛迁移,远远超出了它们的扩散能力,其中包括预测原产地距离采样地点大于 1000 公里的个体。我们的研究深入揭示了野猪在人类推动下横跨美国以及从加拿大向美国北部地区移动的模式。此外,我们的研究还验证了使用神经网络研究入侵物种传播的有效性。
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来源期刊
Molecular Ecology
Molecular Ecology 生物-进化生物学
CiteScore
8.40
自引率
10.20%
发文量
472
审稿时长
1 months
期刊介绍: Molecular Ecology publishes papers that utilize molecular genetic techniques to address consequential questions in ecology, evolution, behaviour and conservation. Studies may employ neutral markers for inference about ecological and evolutionary processes or examine ecologically important genes and their products directly. We discourage papers that are primarily descriptive and are relevant only to the taxon being studied. Papers reporting on molecular marker development, molecular diagnostics, barcoding, or DNA taxonomy, or technical methods should be re-directed to our sister journal, Molecular Ecology Resources. Likewise, papers with a strongly applied focus should be submitted to Evolutionary Applications. Research areas of interest to Molecular Ecology include: * population structure and phylogeography * reproductive strategies * relatedness and kin selection * sex allocation * population genetic theory * analytical methods development * conservation genetics * speciation genetics * microbial biodiversity * evolutionary dynamics of QTLs * ecological interactions * molecular adaptation and environmental genomics * impact of genetically modified organisms
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