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Marschall, E.A., D.C. Glover, M.E. Mather, and D.L. Parrish. 2021. Modeling larval American Shad recruitment in a large river. North American Journal of Fisheries Management 41: 939-954. https://doi.org/10.1002/nafm.10460

Abstract

We used an bioenergetics-based modeling approach to track American Shad Alosa sapidissima offspring within a template of spatial and temporal habitat conditions defined by a combination of abiotic conditions and prey availability models. We simulated spawning at each river kilometer (RKM 138-280) on each day (1 April-31 August) to understand how spawning date and location drive larval recruitment differentially across years and decades. For both temperature and flow, inter-annual variation was large in comparison to interdecadal differences. Variation in simulated recruitment was best explained by a combination of season-specific temperature and location in along the course of the river. Greatest potential recruitment occurred in years in which June temperatures were relatively high. In years when June and July were warmer than average, maximum recruitment resulted from spawning taking place at the upstream portion of the modeled reach. Model scenarios (stationary or passive-drift larvae and dams or no dams) had predictable effects. When dams were present, but offspring were stationary, the area directly above the dams resulted in poor recruitment, due to the habitat being inappropriate for eggs. When offspring exhibited passive drift, they traveled far downstream. If dams were present, they frequently ended their movement at the dams. When larvae moved downstream but their movement was not limited by dams, spatial differences in expected recruitment relative to spawning sites were reduced. Our results demonstrate the importance of spatiotemporal environmental heterogeneity for producing positive recruitment over the longterm. In addition, our results suggest the importance of successful passage of spawners to historical spawning sites upstream of Vernon Dam in the Connecticut River, especially as conditions shift with climate change.