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Urban landscapes can change virus gene flow and evolution in a fragmentation‐sensitive carnivore
Authors:Nicholas M Fountain‐Jones  Meggan E Craft  W Chris Funk  Chris Kozakiewicz  Daryl R Trumbo  Erin E Boydston  Lisa M Lyren  Kevin Crooks  Justin S Lee  Sue VandeWoude  Scott Carver
Institution:1. School of Biological Sciences, University of Tasmania, Hobart, Australia;2. Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, USA;3. Department of Biology, Colorado State University, CO, USA;4. Western Ecological Research Center, U.S. Geological Survey, Thousand Oaks, CA, USA;5. Department of Fish, Wildlife, and Conservation Biology, Colorado State University, CO, USA;6. Department of Microbiology, Immunology, and Pathology, Colorado State University, CO, USA
Abstract:Urban expansion has widespread impacts on wildlife species globally, including the transmission and emergence of infectious diseases. However, there is almost no information about how urban landscapes shape transmission dynamics in wildlife. Using an innovative phylodynamic approach combining host and pathogen molecular data with landscape characteristics and host traits, we untangle the complex factors that drive transmission networks of feline immunodeficiency virus (FIV) in bobcats (Lynx rufus). We found that the urban landscape played a significant role in shaping FIV transmission. Even though bobcats were often trapped within the urban matrix, FIV transmission events were more likely to occur in areas with more natural habitat elements. Urban fragmentation also resulted in lower rates of pathogen evolution, possibly owing to a narrower range of host genotypes in the fragmented area. Combined, our findings show that urban landscapes can have impacts on a pathogen and its evolution in a carnivore living in one of the most fragmented and urban systems in North America. The analytical approach used here can be broadly applied to other host–pathogen systems, including humans.
Keywords:bobcat  disease biology  feline immunodeficiency virus  fragmentation  machine learning  phylodynamics
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