HR: 0800h
AN: OS51A-1295    [Abstracts]
TI: Stochastic Larval Settlement in Nearshore Marine Ecosystems
AU: * Mitarai, S
EM: satoshi@icess.ucsb.edu
AF: Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, CA 93106 United States
AU: Siegel, D A
EM: davey@icess.ucsb.edu
AF: Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, CA 93106 United States
AU: Winters, K B
EM: kraig@coast.ucsd.edu
AF: Integrative Oceanography Division, Scripps Institution of Oceanography, La Jolla, CA 92037 United States
AB: Key to the predictive understanding of nearshore marine ecosystems is the transport of larvae by ocean circulation processes. Only a very few lucky larvae successfully settle upon suitable habitat and are able to recruit to adult life stages. Methodologies for predicting this source/settlement relationship for larval transport is still very primitive and simple diffusive scaling analyses are used for many important applications. Here, we investigate source/settlement relationships of the larval transport using an idealized model of the coastal Regional Ocean Model System (ROMS) to provide time evolving coastal circulations in which many ($>10^6$) Lagrangian (and quasi-Lagrangian) particles are released and tracked as models of planktonic larvae. The Lagrangian simulation results are used to construct larval dispersal kernels which describe the probability distribution of settlement from a given location. These dispersal kernels are strong functions of several time scales including the planktonic larval duration, the frequency and duration of larval release events, inherent coastal circulation time scales and the planning time over which one wishes to predict changes in nearshore abundances. For typical situations (such as typify nearshore fish stock assessment), larval dispersal will be far from a simple diffusion process. This work provides new insights into the persistence and spatial structure of nearshore fish stock abundances.
DE: 4815 Ecosystems, structure and dynamics
DE: 4842 Modeling
DE: 4855 Plankton
DE: 4255 Numerical modeling
DE: 4546 Nearshore processes
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting