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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.

Larval dispersal is a critically important yet enigmatic process in marine ecology, evolution, and conservation. Determining the distance and direction that tiny larvae travel in the open ocean continues to be a challenge. Our current understanding of larval dispersal patterns at management-relevant scales is principally and separately informed by genetic parentage data and biological-oceanographic (biophysical) models. Parentage datasets provide clear evidence of individual larval dispersal events, but their findings are spatially and temporally limited. Biophysical models offer a more complete picture of dispersal patterns at regional scales but are of uncertain accuracy. Here, we develop statistical techniques that integrate these two important sources of information on larval dispersal. We then apply these methods to an extensive genetic parentage dataset to successfully validate a high-resolution biophysical model for the economically important reef fish species Plectropomus maculatus in the southern Great Barrier Reef. Our results demonstrate that biophysical models can provide accurate descriptions of larval dispersal at spatial and temporal scales that are relevant to management. They also show that genetic parentage datasets provide enough statistical power to exclude poor biophysical models. Biophysical models that included species-specific larval behaviour provided markedly better fits to the parentage data than assuming passive behaviour, but incorrect behavioural assumptions led to worse predictions than ignoring behaviour altogether. Our approach capitalises on the complementary strengths of genetic parentage datasets and high-resolution biophysical models to produce an accurate picture of larval dispersal patterns at regional scales. The results provide essential empirical support for the use of accurately parameterised biophysical larval dispersal models in marine spatial planning and management.