Graduate Thesis Or Dissertation


Accounting for the Effects of Fish Detectability in Fishery-independent Surveys Public Deposited

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  • In recent years, there has been an increase in episodic coastal hypoxia along the mid to inner-shelf waters off the Oregon Coast. Wind-driven coastal upwelling events can exacerbate the magnitude of these hypoxic events, causing extremely hypoxic bottom water (<0.5ml l-1 dissolved oxygen) to move onshore towards the inner shelf. These events have the potential to impact the spatial and temporal distributions of nearshore species. Fishery-independent trawl surveys along the Pacific Northwest have reported low fish catch for a variety of demersal species overlapping with hypoxic events. These absences could reflect a behavioral response to severe hypoxia that drives species displacement, or hypoxic events may be affecting mortality rates on nearshore species. This uncertainty impacts the ability of fishery managers to accurately assess stock levels in a changing climate. I developed a state-space population model framework that can be fitted to a fishery-independent dataset in a manner that accounts for the effects of hypoxia on the sampling of nearshore groundfish. As examples we used Lingcod, Yellowtail Rockfish, and Greenstriped Rockfish. The model structure is a state-space integral projection model that uses length-frequency data to estimate model parameters. The key novelty is including model terms describing the probability of failing to observe fish that have moved away from the sampling station because of hypoxic conditions. This is done by modeling a logistic probability of sampling fish as a function of the dissolved oxygen concentration measured during a trawl. We applied this model to simulated timeseries of fish population dynamics and hypoxia and found that the model can reliably estimate the parameters of the detectability function. Further, model fits that included the hypoxia-based detectability function estimate population abundance and harvest rates with less bias than model fits that did not account for hypoxia. Estimating the probability that fish are absent from sampling stations because of behavioral avoidance of hypoxia provides a way to account for hypoxia-influenced absences in fishery assessments by reweighing survey data to account for hypoxic conditions. Our approach could be exported to more complex stock assessment methods to provide more robust assessments of shelf-dwelling groundfish in the face of increasingly frequent hypoxic ocean conditions.
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