Abstract
Population genetics is a powerful tool for measuring important larval connections between marine populations [1–4]. Similarly, oceanographic models based on environmental data can simulate particle movements in ocean currents and make quantitative estimates of larval connections between populations possible [5–9]. However, these two powerful approaches have remained disconnected because no general models currently provide a means of directly comparing dispersal predictions with empirical genetic data (except, see [10]). In addition, previous genetic models have considered relatively simple dispersal scenarios that are often unrealistic for marine larvae [11–15], and recent landscape genetic models have yet to be applied in a marine context [16–20]. We have developed a genetic model that uses connectivity estimates from oceanographic models to predict genetic patterns resulting from larval dispersal in a Caribbean coral. We then compare the predictions to empirical data for threatened staghorn corals. Our coupled oceanographic-genetic model predicts many of the patterns observed in this and other empirical datasets; such patterns include the isolation of the Bahamas and an east-west divergence near Puerto Rico [3, 21–23]. This new approach provides both a valuable tool for predicting genetic structure in marine populations and a means of explicitly testing these predictions with empirical data (Figure 1).
