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 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.