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The increase in genetic distance between marine individuals or populations with increasing distance has often been assumed to be influenced by dispersal distance. In turn, dispersal distance has often been assumed to correlate strongly with pelagic larval duration (PLD). We examined the consistency of these assumptions in species with long planktonic durations. Reviewing multiple marine species, Selkoe & Toonen (2011; Mar Ecol Prog Ser 436:291-305) demonstrated significant fit of a species’ PLD with metrics of genetic distance between sampling sites. However, for long dispersers (PLD >10 d) whose dispersal is more influenced by ocean currents, the fit of PLD and genetic connectivity metrics was not significant. We tested if using realistic ocean currents to determine simulated dispersal distances would produce an improved proxy for larval dispersal that correlates more strongly with genetic connectivity metrics. We estimated the dispersal distance of propagules for locations in the genetic studies compiled by Selkoe and Toonen with a global ocean model (Mercator, 1/12° resolution). The model-derived estimates of dispersal distance did not correlate better than PLD against the genetic diversity metrics globalFSTkm-1and isolation-by-distance (IBD) slope. We explored 2 explanations: (1) our ocean circulation-based dispersal distance estimates are too simple to produce biologically meaningful improvement over PLD, and (2) IBD slope is not a powerful predictor of variation in dispersal distance between species with long PLD. Exploring these explanations suggests directions for future research which will enable better quantitative understanding of genetic diversity and its spatial distribution in coastal marine organisms.
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Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish
Abstract 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.
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- PAR ID:
- 10434082
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Evolutionary Applications
- Volume:
- 16
- Issue:
- 7
- ISSN:
- 1752-4571
- Format(s):
- Medium: X Size: p. 1284-1301
- Size(s):
- p. 1284-1301
- Sponsoring Org:
- National Science Foundation
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