|Document Type:||Journal Article|
|Title:||Secondary contact and changes in coastal hydrology influence the nonequilibrium population structure of a salmonid (Oncorhynchus keta)|
|Author:||Eleni Petrou, L. Hauser, Robin S. Waples, James E. Seeb, W. D. Templin, Daniel Gomez-Uchida, Lisa W. Seeb|
|Keywords:||chum salmon,isolation by distance,cline,glaciation,secondary contact|
Numerous empirical studies have reported lack of migration-drift equilibrium in wild populations. Determining the causes of nonequilibrium population structure is challenging because different evolutionary processes acting at a variety of spatiotemporal scales can produce similar patterns. Studies of contemporary populations in Northern latitudes suggest that nonequilibrium population structure is likely caused by recent colonization of the region after the last Pleistocene ice age ended ~13,000 years ago. The chum salmon’s (Oncorhynchus keta) range was fragmented by dramatic environmental changes during the Pleistocene. We investigated the population structure of chum salmon on the North Alaska Peninsula (NAP) and, using both empirical data and simulations, evaluated the effects of colonization timing and founder population heterogeneity on patterns of genetic differentiation. We screened 161 single nucleotide polymorphisms and found evidence of nonequilibrium population structure when the slope of the isolation by distance relationship was examined at incremental spatial scales. In addition, simulations suggested that this pattern closely matched models of recent colonization of the NAP by secondary contact. Our results agree with geological and archaeological data indicating that the NAP was a dynamic landscape that may have been more recently colonized than during the last deglaciation because of dramatic changes in coastal hydrology over the last several thousand years.
|Theme:||Recovery, Rebuilding and Sustainability of Marine and Anadromous Species|
Characterize vital rates and other demographic parameters for key species, and develop and improve methods for predicting risk and viability/sustainability from population dynamics and demographic information.
Develop methods to use physiological and biological information to predict population-level processes.