Date of Award
2024
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Marine Affairs
Department
Marine Affairs
First Advisor
Tracey Dalton
Abstract
As the US Blue Economy expands, the commercial and recreational fishing industries in Southern New England face a plethora of challenges. Demand for ocean space is increasing with the expansion of offshore wind development, proposals for additional marine monuments and sanctuaries, and plans for offshore aquaculture farms. Spatial conflicts are therefore increasing, while climate change is driving physical oceanographic changes and biological responses in species at all levels of the food web, resulting in shifts in species distributions and therefore fishing grounds. These challenges contribute to the conditions that businesses must adapt to in order to survive. Therefore, fishing businesses require flexibility, and sometimes assistance, to adjust to changing industry conditions. This dissertation aims to improve decision-making to support fishing industry resilience by using fishing industry input and improved fisher-dependent data, using both mixed- and quantitative data collection approaches. Manuscript 1 evaluates performance of a pilot aggregate landings program tested in Rhode Island for summer flounder and black sea bass. A mixed methods approach involving interviews with program participants and quantitative analysis of landings and effort data was used to assess program impacts on participants. Aggregate program participants described improvements in quality of life and safety, as well as cost savings and reductions in regulatory discards, while difference-in-differences analysis of landings data indicated improvements in price for black sea bass. Allowing commercial harvesters to land two high value species in aggregate amounts was found to increase flexibility in business operations and consequently improved fishermen’s well-being in general.
Manuscript 2 transitioned into a more analytical approach to understanding potential exposure of the scallop fishery to offshore wind development in Southern New England. AIS, VMS, VTR, and dealer reports were linked and analyzed using random forest supervised classification, where model features were developed with industry input. Following feature engineering and model hyperparameter tuning, the model was able to predict fishing activity locations in AIS data with close to 98% accuracy. This novel methodology, that hinged on fishermen’s input, significantly improved upon accuracy of existing fishery-dependent tools, and was coupled with other fishery-dependent datasets where AIS data were unavailable to allow for comparison of fishery exposure estimates in wind development areas. Accurate exposure data are essential to understanding possible impacts of development on fishing communities and to developing informed mitigation programs where appropriate.
Manuscript 3 focused directly on the fisheries compensatory mitigation aspects of offshore wind development and included creation of a framework for fair compensation programs based on components of energy justice. Programs developed for wind farms currently online or under construction in the US were evaluated against the framework, looking at their performance with respect to transparency, procedural consistency, inclusivity, being informed by objective data, and burden on stakeholders and government agencies. To date, programs have only partially succeeded in meaningfully engaging the fishing industry; some demanded too much time of fishermen while other programs did not engage them at all. Process transparency could be improved in all programs moving forward and fishing data limitations created challenges, especially for addressing possible impacts to recreational anglers.
All three research projects demonstrated the immense value of effective fishing industry engagement in research, development planning, and fisheries management decision making. Fishermen’s insight was essential to understanding the social and economic implications of changes to fisheries to management measures, it improved model performance in fishery-dependent data analysis applications, and it serves to achieve more equitable and informed compensation programs. Fishing industry participants’ values, preferences, and perspectives are crucial to achieving informed decision-making in light of changing ocean conditions.
Recommended Citation
Livermore Sheehan, Julia C., "USING FISHING INDUSTRY INPUT AND FISHERY-DEPENDENT DATA TO IMPROVE UNDERSTANDING OF OFFSHORE FISHING ACTIVITY AND BUSINESS OPERATIONS" (2024). Open Access Dissertations. Paper 1705.
https://digitalcommons.uri.edu/oa_diss/1705