Hilborn, RayQuinn, Thomas PMcElroy, Katherine2023-09-272023-09-272023-09-272023McElroy_washington_0250E_25946.pdfhttp://hdl.handle.net/1773/50824Thesis (Ph.D.)--University of Washington, 2023Many ecological theories have been developed to shed light on the movement patterns of mobile predators foraging on their prey. Apex predators face additional challenges in needing to track mobile prey, both spatially and temporally, unlike herbivores and grazing animals who must only move to match the temporal dynamics of their stationary prey. The Ideal Free Distribution (IFD) was developed to predict the distribution of mobile individuals across heterogenous environments and is commonly used to investigate intraspecific competition of predators while they forage. Most research on the IFD has been done in controlled laboratory settings and has highlighted the need for field or observational studies of highly mobile predators facing complex environments. Bristol Bay, located in southwestern Alaska, hosts two intelligent and mobile apex predators of a large, mobile sockeye salmon population (Oncorhynchus nerka)—brown bears (Ursus arctos) and commercial salmon fishers. Bristol Bay’s sockeye salmon returns are the subject of a highly valuable commercial salmon fishery and the University of Washington’s Alaska Salmon Program (ASP), a long-term monitoring program that has collected data on the salmon, environment, and ecological communities in Bristol Bay since 1947. Through the ASP and in partnership with Alaska’s Commercial Fisheries Entry Commission (CFEC), data on both the bears and fishers and their discrete fishing locations was available spanning 20 or more years. This wealth of information, the discrete foraging choices, and the complex environments both predators face make Bristol Bay an excellent study system to test IFD predictions in a non-laboratory setting. In chapter 1, I apply the predictions of two ecological models, the IFD and Holling’s Type II functional response, to 25 years of foraging data on brown bears in a series of connected ponds. Using multiple parameterizations of each base ecological model, I determined that pond-specific variability and a year effect, likely influenced by bear abundance, were important in explaining bear foraging patterns. In chapter 2, I apply the predictions of the IFD to the participants of the drift gillnet fleet and their fishing locations from 1980-2019. I found the Bristol Bay drift gillnet fleet underutilized high catch rate areas, even when considering differences in mobility and relative fishing success (two potential IFD assumption violations), indicating that unmeasured safety concerns, travel costs, knowledge of fishing grounds, or other factors affecting movement could be preventing an IFD. In chapter 3, I investigate variation in the drift gillnet fleet movement to determine what causes this variation and potential departure from IFD predictions. I found that across years, average vessel characteristics and information through pre-season forecasted catch and the previous year’s catch affected both where captains first fished and how mobile the entire fleet was across a season. I also found that across captains, mobility increased with years of experience and a captain’s relative catch and was higher for nonresident and nonlocal captains than in local ones. Ultimately, my dissertation expands on the applications of the IFD in complex, field environments, by shedding light on how and why brown bears and commercial fishers violate IFD predictions. This work has important management implications because it is necessary to understand the movement of mobile predators in designing effective management strategies, whether ecosystem or fisheries related, to match the ecological, economic, and social needs of the area.application/pdfen-USCC BYBristol BayBrown bearsCommercial fisheriesIdeal Free DistributionmobilityPacific salmonEcologyWildlife managementFisheriesThesis