Search for: All records

Urban expansion can fundamentally alter wildlife movement and gene flow, but how urbanization alters pathogen spread is poorly understood. Here, we combine high resolution host and viral genomic data with landscape variables to examine the context of viral spread in puma (Puma concolor) from two contrasting regions: one bounded by the wildland urban interface (WUI) and one unbounded with minimal anthropogenic development (UB). We found landscape variables and host gene flow explained significant amounts of variation of feline immunodeficiency virus (FIV) spread in the WUI, but not in the unbounded region. The most important predictors of viral spread also differed; host spatial proximity, host relatedness, and mountain ranges played a role in FIV spread in the WUI, whereas roads might have facilitated viral spread in the unbounded region. Our research demonstrates how anthropogenic landscapes can alter pathogen spread, providing a more nuanced understanding of host-pathogen relationships to inform disease ecology in free-ranging species.

Urbanization is decreasing wildlife habitat and connectivity worldwide, including for apex predators, such as the puma (Puma concolor). Puma populations along California's central and southern coastal habitats have experienced rapid fragmentation from development, leading to calls for demographic and genetic management. To address urgent conservation genomic concerns, we used double‐digest restriction‐site associated DNA (ddRAD) sequencing to analyze 16,285 genome‐wide single‐nucleotide polymorphisms (SNPs) from 401 pumas sampled broadly across the state. Our analyses indicated support for 4–10 geographically nested, broad‐ to fine‐scale genetic clusters. At the broadest scale, the four genetic clusters had high genetic diversity and exhibited low linkage disequilibrium, indicating that pumas have retained genomic diversity statewide. However, multiple lines of evidence indicated substructure, including 10 finer‐scale genetic clusters, some of which exhibited fixed alleles and linkage disequilibrium. Fragmented populations along the Southern Coast and Central Coast had particularly low genetic diversity and strong linkage disequilibrium, indicating genetic drift and close inbreeding. Our results demonstrate that genetically at risk populations are typically nested within a broader‐scale group of interconnected populations that collectively retain high genetic diversity and heterogenous fixations. Thus, extant variation at the broader scale has potential to restore diversity to local populations if management actions can enhance vital gene flow and recombine locally sequestered genetic diversity. These state‐ and genome‐wide results are critically important for science‐based conservation and management practices. Our nested population genomic analysis highlights the information that can be gained from population genomic studies aiming to provide guidance for the conservation of fragmented populations.

The extent and nature of genetic differentiation inSemotilus atromaculatus, one of the most abundant and widespread leuciscids in North America, were evaluated based on mitochondrial (mt) and nuclear DNA sequence variation. Phylogenetic relationships were first inferred based on a fragment of the cytochrome b (cytb) region and the nuclear introns7gene forS. atromaculatusand all other congeners as well as representative species from all other genera in the creek chub–plagopterin clade. The phylogeography of major haplogroups ofS. atromaculatuswas also assessed according to variation in a fragment of the mitochondrialcytbregion from 567 individuals across its range. All analyses identifiedS. thoreauianus,S. lumbeeandS. corporalisas reciprocally monophyletic groups. Analyses of nuclear sequence variation resolvedS. atromaculatusas a single clade, whereS. thoreauianusandS. lumbeewere recovered as the sister group toS. atromaculatus, andS. corporaliswas resolved as sister to all other species in the genus. Analyses of mtDNA sequence variation recoveredS. atromaculatusas three well supported and differentiated monophyletic groups, with a widespread genetically homogeneous lineage extending across most of the current range of the species; a more geographically restricted and geographically structured lineage in the southern Appalachians, sister group toS. lumbee; and a geographically restricted lineage was identified from two Gulf Slope basins. Evidence of complex mito‐nuclear discordance and phylogeographic differentiation withinS. atromaculatusillustrates that further analysis of widespread species is warranted to understand North American freshwater fish diversity and distributions.

We introduce a new R package “MrIML” (“Mister iml”; Multi‐response Interpretable Machine Learning). MrIML provides a powerful and interpretable framework that enables users to harness recent advances in machine learning to quantify multilocus genomic relationships, to identify loci of interest for future landscape genetics studies, and to gain new insights into adaptation across environmental gradients. Relationships between genetic variation and environment are often nonlinear and interactive; these characteristics have been challenging to address using traditional landscape genetic approaches. Our package helps capture this complexity and offers functions that fit and interpret a wide range of highly flexible models that are routinely used for single‐locus landscape genetics studies but are rarely extended to estimate response functions for multiple loci. To demonstrate the package's broad functionality, we test its ability to recover landscape relationships from simulated genomic data. We also apply the package to two empirical case studies. In the first, we model genetic variation of North American balsam poplar (Populus balsamifera, Salicaceae) populations across environmental gradients. In the second case study, we recover the landscape and host drivers of feline immunodeficiency virus genetic variation in bobcats (Lynx rufus). The ability to model thousands of loci collectively and compare models from linear regression to extreme gradient boosting, within the same analytical framework, has the potential to be transformative. The MrIML framework is also extendable and not limited to modelling genetic variation; for example, it can quantify the environmental drivers of microbiomes and coinfection dynamics.

Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were genotyped using double‐digest, restriction site‐associated DNA sequencing (ddRADseq). We investigated patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, genome‐scale markers to document subtle impacts of urbanization on a wide‐ranging carnivore living near a large urban center.