Combining Inference from Otolith Geochemistry and Population Genetics to Determine Scale of Dispersal in a River-Tributary Network

Humston, Robert

Combining Inference from Otolith Geochemistry and Population Genetics to Determine Scale of Dispersal in a River-Tributary Network

Wednesday, August 24, 2016: 11:00 AM

New York B (Sheraton at Crown Center)

Robert Humston , Biology, Washington and Lee University, Lexington, VA

Sasha Doss , Fisheries and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA

Simon Thorrold , Woods Hole Oceanographic Institution, Woods Hole, MA

Eric Hallerman , Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA

Caroline Wass , Washington and Lee University

Garrett Muckleroy , Washington and Lee University, Lexington, VA

Juli Sorenson , Washington and Lee University, Lexington, VA

Connor Hollenbeck , Washington and Lee University

Scott M. Smith , VA Department of Game and Inland Fisheries, Forest, VA

Dispersal of fish in river-tributary networks is a process that determines connectivity of populations, expansion of invasive species, and spatial patterns in community composition. We combined inference from otolith geochemistry and population genetics to determine the scale of dispersal in riverine populations of smallmouth bass (Micropterus dolomieu). Strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) in otoliths allowed us to reconstruct individual movement history between isotopically distinct regions or rivers. Results indicated a substantial degree of exchange between mainstem and tributary habitats, while estimating minimum probable movement paths provided direct estimates of individual dispersal distance. Analysis of population genetic data indicated partitioning of genetic clusters within the basin. We observed a pattern of isolation-by-distance among mainstem populations which allowed indirect estimation of average dispersal distance. These two sources of inference were combined to characterize dispersal over short and long timescales. Our results can be applied to understand how dispersal will influence the ability of populations to track changes in resource availability and the timescale of range expansion.