Previously, American black bears (Ursus americanus) were thought to follow the pattern of female philopatry and male-biased dispersal. However, recent studies have identified deviations from this pattern. Such flexibility in dispersal patterns can allow individuals greater ability to acclimate to changing environments. We explored dispersal and spatial genetic relatedness patterns across ten black bear populations - including long established (historic), with known reproduction >50 years ago, and newly established (recent) populations, with reproduction recorded <50 years ago - in the Interior Highlands and Southern Appalachian Mountains, United States. We used spatially explicit, individual-based genetic simulations to model gene flow under scenarios with varying levels of population density, genetic diversity, and female philopatry. Using measures of genetic distance and spatial autocorrelation, we compared metrics between sexes, between population types (historic and recent), and among simulated scenarios which varied in density, genetic diversity, and sex-biased philopatry. In empirical populations, females in recent populations exhibited stronger patterns of isolation-by-distance (IBD) than females and males in historic populations. In simulated populations, low-density populations had a stronger indication of IBD than medium- to high-density populations; however, this effect varied in empirical populations. Condition-dependent dispersal strategies may permit species to cope with novel conditions and rapidly expand populations. Pattern-process modeling can provide qualitative and quantitative means to explore variable dispersal patterns, and could be employed in other species, particularly to anticipate range shifts in response to changing climate and habitat conditions.
|Number of pages||13|
|State||Published - Apr 1 2018|
Bibliographical noteFunding Information:
Acknowledgements We thank Frank van Manen, Jennapher Teu-nissen van Manen, and Ronald A. Van Den Bussche for sample contributions; Sébastien R. Paquette for R code for linear regressions; and Edward Gbur for statistical advice. We thank Jill S. Miller, Jason Munshi-South, three anonymous reviewers, and the editor for their comments that improved the manuscript. Funding sources for sample collection and analysis included Arkansas Game and Fish Commission, Federal Aid in Wildlife Restoration, Safari Club International Foundation, the University of Tennessee, the United States Geological Survey, the University of Arkansas, Oklahoma State University, West Virginia Department of Natural Resources, Virginia Department of Game and Inland Fisheries, the University of Kentucky, Kentucky Department of Fish and Wildlife, Missouri Department of Conservation, the University of Missouri, and Mississippi State University. T.V. K. was supported by the Distinguished Doctoral Fellowship at the University of Arkansas and EEP was supported by a University of Missouri Life Sciences Fellowship.
© 2017 The Genetics Society.
ASJC Scopus subject areas