Bio-Physical Models: Tracking Invisible Larval Pathways from Spawning to Recruitment

Individual movement of millimeter-size pelagic eggs and larvae are driven by fluid characteristics and pelagic processes operating across multiple, spatial and temporal scales. These individual interactions can not be seen or measured, yet they impact the overall transport, fate, and recruitment of larval cohorts. To get a mechanistic understanding of these “invisible” processes from spawning to recruitment, it becomes important to develop biophysical models that can solve for individual attributes. A probabilistic, multi-scale model, the Connectivity Modeling System (CMS), was developed to solve dispersion, migration, and settlement processes in fish larvae. The model couples a new nested-grid technique to a stochastic Lagrangian framework introducing individual larval attributes at random from specified probability distributions of traits. In addition, CMS generates ensemble forecasts or hind casts of the particles' three dimensional trajectories, dispersal kernels, and transition probability matrices used for recruitment estimates. Techniques for evaluating the accuracy of simulated larval pathways using independent sources of empirical data are presented. Ongoing initiatives in high-resolution coupled atmospheric-hydrodynamic models, and a greater understanding of larval growth, mortality, and orientation behavior are necessary to capture critical pelagic processes that affect the spatial and temporal settlement of larval fishes, and ultimately stock-recruitment relationship.