Coastal sharks represent a group of stocks for which observation, assessment, and management are particularly challenging. Large distributional ranges, complex migratory behavior, low economic value, and relatively few observations in fishery independent surveys hinder relative abundance estimation. Assessing stock status of coastal sharks is encumbered by limited data availability, data quality, and knowledge of life history strategy. Further, coastal sharks are challenging to manage due to their slow intrinsic population growth rates, competing stakeholder interests, history of overexploitation, and in some cases, subjection to international exploitation. This dissertation aimed to improve the capacity to observe relative abundance of coastal sharks. Because a comprehensive survey is unavailable across the full distribution of coastal shark species in the southeast United States, several spatially-limited surveys are conducted, each assumed to represent an independent measure of relative abundance. When compiled, these indices of abundance regularly conflict, obscuring the true trend in stock abundance and potentially biasing estimates of stock status from stock assessments. Using age-structured simulations for Atlantic sharpnose and sandbar sharks, we tested whether dynamic factor analysis (DFA) is an appropriate statistical approach to reconcile conflicting survey indices. The resulting DFA trends were then input into a stock assessment model and results were compared to those generated from inputting conflicting indices into a corresponding assessment model. DFA proved useful in clarifying underlying patterns in stock abundance when the stock abundance exhibited sufficient contrast, and DFA trends were shown to produce more consistent (precise) assessment results. This dissertation serves to improve the capacity to observe patterns in relative abundance over time and likewise expand the toolbox for coastal shark stock assessments. Fishery management procedures (MPs) are pre-agreed upon frameworks designed to manage a stock and typically include information on how the stock is monitored, assessed, how stock status will alter management regulations (‘harvest control rule;’ HCR), and how the management regulations will be applied to the stock. No MP has been developed for coastal sharks in the United States. Consequently, we examined the impact of various HCR parameterizations and stock assessment frequency for the large coastal sandbar shark using a simulation approach termed management strategy evaluation. Notably, sandbar sharks are subjected to unregulated, international removals by Mexico, and the level of future Mexican removals was found to have a significant impact on the ability of the sandbar shark to recover. Trade-offs in management objectives with respect to various parameterizations of the harvest control rule were presented. Further, the frequency of stock assessments had a relatively small impact on the management objectives of the sandbar shark fishery. Through management strategy evaluation, international removals were identified as a potential barrier to sandbar shark recovery. Further, the vast resources required to undergo more numerous stock assessments could be potentially alleviated by reduction of future large coastal shark assessment frequency without compromising management success.
Identifer | oai:union.ndltd.org:wm.edu/oai:scholarworks.wm.edu:etd-7225 |
Date | 01 January 2021 |
Creators | Peterson, Cassidy Dawn |
Publisher | W&M ScholarWorks |
Source Sets | William and Mary |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Dissertations, Theses, and Masters Projects |
Rights | © The Author, http://creativecommons.org/licenses/by/4.0/ |
Page generated in 0.013 seconds