Biology Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2749
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Item Patterns of oyster natural mortality in Chesapeake Bay, Maryland during 1991-2017 and its relationships with environmental factors and disease(2019) Doering, Kathryn Leah; Wilberg, Michael J; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A common method of estimating natural mortality in bivalves includes several assumptions that are likely violated for oysters Crassostrea virginica in Chesapeake Bay, Maryland. In addition, while oyster disease dynamics are well studied spatially and temporally in the mid-Atlantic region, changes in disease-related relationships have not been investigated in Maryland. We developed a Bayesian estimator for natural mortality and applied it to oysters in Maryland. We then used the model output along with environmental factors and disease data to explore changes in the disease system over time. We found the largest differences in natural mortality estimates between the box count method and Bayesian model 1-3 years after a high mortality event. Some relationships changed over time in the disease system, most notably those associated with MSX, suggesting resistance to MSX has potentially developed. This work improves our estimates of natural mortality and understanding of oyster disease dynamics in Maryland.Item Mortality and Movement of Adult Atlantic Menhaden During 1966-1969 Estimated from Mark-Recapture Models(2017) Liljestrand, Emily Morgan; Wilberg, Michael J; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Atlantic Menhaden Brevoortia tyrannus is an economically and ecologically important forage fish. I built a multi-state mark-recapture model to estimate movement, fishing mortality, and natural mortality rates during 1966-1969. Movement from mid-Atlantic regions to North and South Carolina in the winter was lower than previously described, and natural mortality was approximately three times greater than previously estimated. Fishing mortality was highest in North and South Carolina. We evaluated the model’s performance by generating mark-recapture data sets from known values of mortality and movement then fitting the mark-recapture model to those data. The model estimated movement rates > 0.05 to within 33% of the true value even under different scenarios of spatiotemporally distributed releases and fishing effort. Distributing the fishing effort more evenly across regions substantially improved the estimates of movement and fishing mortality, and increasing the number of marked fish released had a small positive effect on accuracy of estimates.Item Understanding information use in multiattribute decision making(2016) Chrabaszcz, Jeffrey Stephen; Dougherty, Michael R; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An inference task in one in which some known set of information is used to produce an estimate about an unknown quantity. Existing theories of how humans make inferences include specialized heuristics that allow people to make these inferences in familiar environments quickly and without unnecessarily complex computation. Specialized heuristic processing may be unnecessary, however; other research suggests that the same patterns in judgment can be explained by existing patterns in encoding and retrieving memories. This dissertation compares and attempts to reconcile three alternate explanations of human inference. After justifying three hierarchical Bayesian version of existing inference models, the three models are com- pared on simulated, observed, and experimental data. The results suggest that the three models capture different patterns in human behavior but, based on posterior prediction using laboratory data, potentially ignore important determinants of the decision process.