NSFGEO-NERC: Using population genetic models to resolve and predict dispersal kernels of marine larvae

Populations of most marine species are functionally, demographically, and genetically connected by planktonic dispersal of tiny larvae. Understanding the spatial distribution of dispersal events (the dispersal kernel) is a fundamental goal of marine ecology and is critical to predicting population dynamics and evolutionary outcomes. Yet, general principles for predicting dispersal outcomes across communities remain elusive. We propose to develop the first-ever data-assimilated biophysical models of larval dispersal by: 1) applying isolation-by-distance (IbD) theory to estimate mean parent-offspring distance (sigma IbD) for six reef fish species co-sampled and RAD-seq genotyped at three isolated South Pacific archipelagos that each replicate the IbD process with relatively continuous reef systems; 2) using our empirical estimates of sigmaIbD to constrain biophysical models of larval dispersal, which will be iterated over twenty years of high- resolution hydrodynamic models, we will test hypotheses about the relative role of species traits and seascape characteristics in shaping larval dispersal kernels; and 3) developing a new conservation portfolio approach to design managed area networks that capture temporal variability in larval dispersal over many generations, and engage with local stakeholders in each archipelago to implement this approach.