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Dispersal emerges as a consequence of how an individual's phenotype interacts with the environment. Not all dispersing individuals have the same phenotype, and variation among individuals can generate complex variation in the distribution of dispersal distances and directions. While active locomotion performance is an obvious candidate for a dispersal phenotype, its effects on dispersal are difficult to measure or predict, especially in small organisms dispersing in wind or currents. Therefore, we analyzed the effects of larval swimming on dispersal and settlement of coral‐reef fish larvae using a high‐resolution biophysical model. The model is, to date, the only biophysical model of marine larval dispersal that has been statistically validated against genetic parentage estimates of larval origin and destination, and incorporates empirically‐estimated larval behaviors and their ontogeny. Larval swimming, in combination with depth, orientation and navigation behaviors, actually reduced dispersal distances compared to those of passive larvae. Swimming had no consistent effects on long distance dispersal, but increased the spread of settlement locations. Swimming speed, in contrast, did not consistently affect median dispersal distances, but faster swimming larvae had greater mean and maximum dispersal distances than slower swimming larvae. Finally, faster larval swimming speeds consistently increased the probability of settlement. Our analysis shows how larval swimming differentially affects multiple properties of dispersal kernels. In doing so, it indicates how selection could favor faster larval swimming to increase settlement and local retention, which may actually result in longer dispersal distances as a by‐product of larvae trying to locate habitat rather than to disperse greater distances. [ABSTRACT FROM AUTHOR]

Understanding larval connectivity patterns in exploited fishes is a fundamental prerequisite for developing effective management strategies and assessing the vulnerability of a fishery to recruitment overfishing and localised extinction. To date, however, researchers have not considered how regional variations in fishing pressure also influence recruitment.We used genetic parentage analyses and modelling to infer the dispersal patterns of bumphead parrotfish Bolbometopon muricatum larvae in the Kia fishing grounds, Isabel Province, Solomon Islands. We then extrapolated our Kia dispersal model to a regional scale by mapping the available nursery and adult habitat for B. muricatum in six regions in the western Solomon Islands, and estimated the relative abundance of adult B. muricatum populations in each of these regions based on available adult habitat and historical and current fishing pressure.Parentage analysis identified 67 juveniles that were the offspring of parents sampled in the Kia fishing grounds. A fitted larval dispersal kernel predicted that 50% of larvae settled within 30 km of their parents, and 95% settled within 85 km of their parents. After accounting for unsampled adults, our model predicted that 34% of recruitment to the Kia fishery was spawned locally. Extrapolating the spatial resolution of the model revealed that a high proportion of the larvae recruiting into the Kia fishing grounds came from nearby regions that had abundant adult populations. Other islands in the archipelago provided few recruits to the Kia fishing grounds, reflecting the greater distances to these islands and lower adult abundances in some regions.Synthesis and applications. This study shows how recruitment into a coral reef fishery is influenced by larval dispersal patterns and regional variations in historical fishing pressure. The scales of larval connectivity observed for bumphead parrotfish indicate that recruitment overfishing is unlikely if there are lightly exploited reefs up to 85 km away from a heavily fished region, and that small (<1 km2) marine‐protected areas (MPAs) are insufficient to protect this species. We recommend greater efforts to understand the interactions between larval dispersal and gradients of fishing pressure, as this will enable the development of tailored fisheries management strategies. [ABSTRACT FROM AUTHOR]