Quantifying the probability of larval exchange among marine populations is key to predicting local population dynamics and optimizing networks of marine protected areas. The pattern of connectivity among populations can be described by the measure- ment of a dispersal kernel. However, a statistically robust, empirical dispersal kernel has been lacking for any marine species. Here, we use genetic parentage analysis to quantify a dispersal kernel for the reef fish Elacatinus lori, demonstrating that dispersal declines exponen- tially with distance. The spatial scale of dispersal is an order of mag- nitude less than previous estimates—the median dispersal distance is just 1.7 km and no dispersal events exceed 16.4 km despite intensive sampling out to 30 km from source. Overlaid on this strong pattern is subtle spatial variation, but neither pelagic larval duration nor direc- tion is associated with the probability of successful dispersal. Given the strong relationship between distance and dispersal, we show that distance-driven logistic models have strong power to predict dispersal probabilities. Moreover, connectivity matrices generated from these models are congruent with empirical estimates of spatial genetic structure, suggesting that the pattern of dispersal we uncovered re- flects long-term patterns of gene flow. These results challenge as- sumptions regarding the spatial scale and presumed predictors of marine population connectivity. We conclude that if marine reserve networks aim to connect whole communities of fishes and conserve biodiversity broadly, then reserves that are close in space (<10 km) will accommodate those members of the community that are short- distance dispersers.
Detecting patterns of spatial genetic structure (SGS) can help identify intrinsic and extrinsic barriers to gene flow within metapopulations. For marine organisms such as coral reef fishes, identifying these barriers is critical to predicting evolutionary dynam- ics and demarcating evolutionarily significant units for conservation. In this study, we adopted an alternative hypothesis-testing framework to identify the patterns and pre- dictors of SGS in the Caribbean reef fish Elacatinus lori. First, genetic structure was estimated using nuclear microsatellites and mitochondrial cytochrome b sequences. Next, clustering and network analyses were applied to visualize patterns of SGS. Finally, logistic regressions and linear mixed models were used to identify the predic- tors of SGS. Both sets of markers revealed low global structure: mitochondrial ΦST = 0.12, microsatellite FST = 0.0056. However, there was high variability among pairwise estimates, ranging from no differentiation between sites on contiguous reef (ΦST = 0) to strong differentiation between sites separated by ocean expanses ≥ 20 km (maximum ΦST = 0.65). Genetic clustering and statistical analyses provided additional support for the hypothesis that seascape discontinuity, represented by oceanic breaks between patches of reef habitat, is a key predictor of SGS in E. lori. Notably, the esti- mated patterns and predictors of SGS were consistent between both sets of markers. Combined with previous studies of dispersal in E. lori, these results suggest that the interaction between seascape continuity and the dispersal kernel plays an important role in determining genetic connectivity within metapopulations.