Abstract

The distance and direction of larval dispersal have considerable influence on the demography and genetic structure of marine species. Larvae may be diluted and dispersed by currents while actively moving, which make their in situ study very difficult. We explore stochastic modeling approaches for examining the influence of physical and biological processes on larval trajectories and population connectivity of coral reef fishes. We use a modeling system designed for high throughput trajectories and transition probability matrices to estimate the spatial probability of successful dispersal (i.e. the dispersal kernel, DK). Ocean general circulation models (OGCMs) are coupled offline with various stochastic schemes tracking individual larvae within a geographic information system (GIS)-based seascape. We demonstrate the power of transition probability matrices for examining the influences of mesoscale coastal oceanic processes on the prediction of DKs and the relative impact of life history traits on patterns of recruitment. Results suggest that 1) including the anisotropy of both diffusivity and decorrelation time scale and a spin parameter describing the eddy field into the Lagrangian model increases accuracy of tracking and is critical in estimating dispersal distances; 2) estimates of population connectivity are sensitive to mortality and to ontogenetic vertical migration; 3) larval behavior is essential to ensure self-recruitment and becomes significant for subsidies only with increasing pelagic larval duration; 4) even if the mortality function is not spatially explicit, it is still a key component for connectivity estimates, in particular for species with plasticity in pelagic duration or with extended competency period

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