The distribution of larval fishes in estuaries is influenced by where they hatch and their movements after hatching. In the San Francisco Estuary, the threatened longfin smelt (Spirinchus thaleichthys) spawn adhesive eggs in shallow, fresh to brackish water. Attached eggs hatch and the larvae disperse seaward toward higher-salinity water. Actual locations of spawning are unknown, and cannot be inferred from distributions of larvae because intense tidal mixing erases the history of movement. Human interventions such as manipulations and diversions of freshwater flow may contribute to the ongoing decline of this species, and these effects depend on where the fish hatch. We combined connectivity estimates from hydrodynamic and particle-tracking modeling with trawl data in a Bayesian model to estimate the location and timing of hatching, as well as natural mortality of larvae and losses to freshwater diversions. Longfin smelt were estimated to have hatched further seaward than previously believed; estimated diversion losses were small compared to natural mortality, and therefore pose only a minor risk to the population. Similar methods could be applied in other estuarine and coastal systems where strong mixing reduces the ability of simpler models to predict spawning location and larval movement.
Speaker: Ed Gross, Principal, 3-D Modeling Lead, Research Management Associates Inc.
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