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No description available.

The Biden Administration has set aggressive offshore wind energy goals, aiming to have 30 gigawatts of offshore energy in place by 2030. This amount of energy has the potential to power 10 million homes (White House, 2022), helping the administration to reach larger clean energy goals. In Virginia, Dominion Energy aims to have 2.6 gigawatts of offshore wind energy by 2026, enough to power up to 660,000 homes (Dominion Energy). While the upcoming offshore wind energy development will create clean energy and green jobs, the ocean is no longer an open field for development and already supports a complex matrix of industries (Schupp et al., 2019). The number of competing uses for space is continually expanding, causing increases in conflicts between sectors (de Groot et al., 2014). From fisheries and offshore aquaculture to shipping channels and military use, the need for sustainably managed offshore development is greater now than ever before (Gill et al., 2020). This research uses European stakeholder knowledge and experiences to highlight opportunities for conflict mitigation in the United States. Europe is about 20 years ahead of the United States in offshore wind development (Gill et al., 2020), and due to the diversity in regulatory statuses across countries (Schupp et al., 2019), a multitude of case studies exist for examining strategies to deal with competing ocean uses.

Derelict fishing gear, particularly pots or traps, occupy waters worldwide and cause negative ecological and economic impacts. Derelict pots persist throughout Chesapeake Bay, the largest estuary in the U.S., that supports a valuable commercial fishery for the blue crab Callinectes sapidus. Chesapeake Bay is responsible for 30-40% of U.S. commercial blue crab harvests. Yet, few studies have quantified the impacts of derelict pots on harvest or the perceptions of commercial fishers on derelict pot mitigation activities in this predominantly pot fishery. This thesis examined the impacts of derelict pots on harvest in a field experiment and worked with commercial fishers to develop and disseminate a mail survey that was used to quantify the preferences and decision-making of commercial fishers for addressing derelict pots. The field experiment simulated the presence of derelict pots near actively fished pots and found that derelict pots can reduce harvests by up to 30% during the summer, but not during the fall. Female capture rates were consistently lower when derelict pots were present, but male capture rates were not negatively affected. To better understand the perceptions of commercial fishers and their preferences for derelict pot mitigation actions (e.g., location and removal program, installation of identification tags on pots), a stated preference survey with a discrete choice experiment was distributed to all commercial fishers licensed to deploy hard pots in Virginia. There was a 42% response rate (430 of 1,032 fishers returned the survey packet), and most mitigation activities included in the survey were too costly for commercial fishers to willingly participate in. Management incentives (e.g., bushel limit increase, pot limit increase, season extension) alone were not enough to offset costs and encourage participation in activities that were disliked by commercial fishers. However, there was strong heterogeneity observed across the population, thus some segments of the population would be far more willing to participate in mitigation efforts than others. For instance, participants that perceived derelict pots to cause only negative impacts were 37% more willing to participate in any mitigation activity on average. Results from this study can be used to better inform resource managers and policymakers responsible for addressing the issue of derelict pots and other types of derelict fishing gear plaguing fisheries around the world.

For data-limited fisheries, length-based mortality estimators are attractive as alternatives to age-structured models due to the simpler data requirements and ease of use of the former. This dissertation develops new extensions of mean length-based mortality estimators and applies them to federally-managed stocks in the southeastern U.S. and U.S. Caribbean. Chapter 1 presents a review of length-based methods from the literature. Common themes regarding the methodology, assumptions, and diagnostics in these length-based methods are discussed. In Chapter 2, a simulation study evaluates the performance of the length-converted catch curve (LCCC), Beverton-Holt equation (BHE), and Length Based-Spawner Potential Ratio (LB-SPR) over a range of scenarios. Although the LCCC and BHE are older methods than LB-SPR, the former outperformed LB-SPR in many scenarios in the simulation. Overall, it was found that the three length-based mortality estimators are less likely to perform well for low M/K stocks (M/K is the ratio of the natural mortality rate and the von Bertalanffy growth parameter; this ratio describes different life history strategies of exploited fish and invertebrate populations), while various decision rules for truncating the length data for the LCCC and BHE were less influential. In Chapter 3, a multi-stock model is developed for the non-equilibrium mean length-based mortality estimator and then applied to the deepwater snapper complex in Puerto Rico. The multispecies estimator evaluates synchrony in changes to the mean length of multiple species in a complex. Synchrony in mortality can reduce the number of estimated parameters and borrows information from more informative species to lesser sampled species in the model. In Chapter 4, a new method is developed to estimate mortality from both mean lengths and catch rates (MLCR), which is an extension of the mean length-only (ML) model. to do so, the corresponding behavior for the catch rate following step-wise changes in mortality is derived. Application of both models to Puerto Rico mutton snapper shows that the MLCR model can provide more information to support a more complex mortality history with the two data types compared to the ML model. In Chapter 5, a suite of mean length-based mortality estimators is applied to six stocks (four in the Gulf of Mexico and two in the U.S. Atlantic) recently assessed with age-structured models. There was general agreement in historical mortality trends between the age-structured models and the mean length-based methods, although there were some discrepancies which are discussed. All models also agreed on the overfishing status in the terminal year of the assessment of the six stocks considered here when the mortality rates were compared relative to reference points. This dissertation develops new length-based assessment methods which consider multiple sources of data. The review guides prospective users on potential choices for assessment with length-based methods. Issues and diagnostics associated with the methods are also discussed in the review and highlighted in the example applications.

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No description available.

Sea level rise (SLR) has become a serious threat for coastal communities in recent years. Many communities, including South Florida, are already having the security of their daily lives impacted as climate change causes SLR and other environmental impacts to worsen. This study reviews the Miami-Dade Sea Level Rise Task Force Report to determine how this coastal county government views SLR as a threat. Using mixed content analysis to analyze the report qualitatively and quantitatively, the Task Force's recommendations are categorized based on their focus on security, infrastructure, economics, and the environment. One finds the concerns of the people to maintain their property and infrastructure, as well as their access to water and other basic needs, as insurance costs spike and funding becomes more difficult to obtain. Policies will have to be revised using updated scientific studies, modeling, and mapping to mitigate against the worse-case scenarios.

Hazardous waste site remediation cost estimation requires a good estimate of the contaminated soil volume. The United States Environmental Protection Agency (U.S. EPA) currently uses deterministic point values to estimate soil volumes but the literature suggests that probability bounds analysis (PBA) is the more accurate method to make estimates under uncertainty. The underlying statistical theory is that they are more accurate than deterministic estimates because probabilistic estimates account for data uncertainties. However, the literature does not address the problem of selecting an optimal decision point from the interval-valued PBA estimates. The purpose of this study was to identify the optimal PBA decision point estimator and use it to demonstrate that because the PBA method also accounts for data uncertainties, PBA estimates of remedial soil volumes are more accurate than the U.S. EPA deterministic estimates. The research questions focused on determining whether the mean or the 95th percentile decision point is the optimal PBA estimator. A convenience sample of seven sites was selected from the U.S. EPA Superfund Database. The PBA method was used to estimate the remedial soil volumes for the sites. Correlation analyses were performed between the mean and 95th percentile PBA estimates and the actual excavated soil volumes. The study results suggest that the lower bound 95th percentile PBA estimate, which had the best R2-value of 89%, is the optimal estimator. The R2-value for a similar correlation analysis using the U.S. EPA deterministic estimates was only 59%. This confirms that PBA is the better estimator. The PBA estimates are less contestable than the current U.S. EPA deterministic point estimates. Thus, the PBA method will reduce litigation and speed up cleanup activities to the benefit of the U.S. EPA, corporations, the health and safety of nearby residents, and society in general.

Major paper (M.U.A.)--Virginia Polytechnic Institute and State University, 1991. / Abstract. Includes bibliographical references (leaves 59-60). Also available via the Internet.