DOI: 10.5061/dryad.ns1rn8pzr
title: Biophysical data for: Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish

description: How to identify the drivers of population connectivity remains a
 fundamental question in ecology and evolution. Answering this question can
 be challenging in aquatic environments where dynamic lake and ocean
 currents coupled with high levels of dispersal and gene flow can decrease
 the utility of modern population genetic tools. To address this challenge,
 we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species
 with an ~40-day pelagic larval duration (PLD), collected from 20 sites
 circumscribing Lake Michigan. We also developed a novel, integrative
 approach that couples detailed biophysical models with eco-genetic
 agent-based models to generate 'predictive' values of genetic
 differentiation. By comparing predictive and empirical values of genetic
 differentiation, we estimated the relative contributions for known drivers
 of population connectivity (e.g., currents, behavior, PLD). For the main
 basin populations (i.e., the largest contiguous portion of the lake), we
 found that high gene flow led to low overall levels of genetic
 differentiation among populations (FST = 0.003). By far the best
 predictors of genetic differentiation were connectivity matrices that were
 derived from periods of time when there were strong and highly dispersive
 currents. Thus, these highly dispersive currents are driving the patterns
 of population connectivity in the main basin. We also found that
 populations from the northern and southern main basin are slightly
 divergent from one another, while those from Green Bay and the main basin
 are highly divergent (FST = 0.11). By integrating biophysical and
 eco-genetic models with genome-wide data, we illustrate that the drivers
 of population connectivity can be identified in high gene flow systems.
description: For the biophysical model, we
 used a Lagrangian particle tracking model previously developed to study
 the transport of larval cod (Churchill et al., 2011; Huret et al., 2007),
 where three-dimensional current velocities and turbulent diffusivity were
 output from the application of the Finite Volume Community Ocean Model
 (FVCOM). A random-walk scheme for spatially varying vertical diffusivity
 was used, including a vertical floating/sinking/swimming velocity (Gräwe,
 2011; Rowe et al., 2016). Particles were designated to be either 1.)
 neutrally buoyant or 2.) have an upward vertical swimming velocity of
 0.0003 m/s. We chose to use an upward vertical swimming velocity because
 yellow perch larvae are more likely to be collected in the upper layers of
 Lake Michigan (Martin et al. 2011). The Lagrangian particle tracking
 simulations were forced by output from FVCOM simulation of Lake
 Michigan-Huron (Anderson & Schwab, 2013) incorporating exchange
 currents in the Straits of Mackinac. Horizontal grid resolution varied
 with finer resolution nearshore and in regions with complex coastlines
 (<em>e.g.</em>, 100 m in the Straits of Mackinac to 2.5 km in
 the center of the lakes), and each horizontal grid was discretized into 20
 terrain-following (sigma) layers. 
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