Date of Award

5-2003

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Marine Biology

Advisor

Yong Chen

Second Committee Member

Robert L. Vadas

Third Committee Member

Les E. Watling

Abstract

Fisheries research on the green sea urchin in Maine has been limited despite its importance to the state's fishing industry. The objective of this thesis was to generate critical information for the management and monitoring of the Maine green sea urchin fishery. In particular there are three main areas of interest: (1) an investigation of biological reference points; (2) spatial analysis and biomass estimation, and (3) the development of a simulation framework approach to determine an optimal sampling strategy for the fishery-independent survey program. Biological reference points are markers conlrnonly used to monitor and manage fisheries. For the Maine sea urchin fishery, no biological reference point had been estimated as a management target, which made it difficult to determine the status of the stock and develop appropriate management plans. The purpose of this study was to investigate if Fo., and Fmax are appropriate management targets for the Maine sea urchin fishery and how uncertainties associated with them affect their suitability as management targets. A Monte Carlo simulation approach was used with fishery-dependent data to estimate uncertainties in the biological reference points FOJ and Fmx. FO.~ was considered a more suitable as a management target than Fmx because it is precautionary, more robust to estimation uncertainty and usually well defined. Current fishing mortality was greater than Fo,, for all tested variations; in other words, the stock is overfished. Estimates of exploitable biomass and current exploitation rate are essential for determining the current status of the sea urchin stock. With the onset of a fisherindependent survey program, it became possible to conduct a stock assessment that incorporates spatial variability. The objective of this study was to investigate the largescale spatial patterns in sea urchin abundance to estimate the fishery's exploitable biomass. Triangulated irregular networks (TINS) were used to characterize the largescale patterns in the fishery-independent density data by size category and depth. Exploitable biomass estimates were almost identical to estimates calculated using a length-structured fisheries population dynamics model on fisheries-dependent data, providing independent validation of the estimates. The 2001 pilot study for the fishery-independent survey program was extensive, time-consuming and costly, and needed to be optimized to ensure its feasibility as a longterm scientific survey. The high degree of spatial variability in sea urchin abundance, however, prevented us fiom using standard optimization techniques, such as traditional statistics or even geostatistics. Kernel estimation and computer simulations were combined to create a framework for survey optimization. Optimization must decrease sampling intensity, yet produce accurate realizations of the large-scale spatial structure and be compatible with the planned statistical analysis. Considering that the sea urchin data will continue to be analyzed by traditional and spatial statistics, we chose the original fishery-independent survey with a reduction to 10 locations per strata as the optimal strategy. The research presented in this thesis provides the DMR with essential information on the sea urchin stock, suggests new analysis techniques, and recommends a cost and time effective plan for collecting quality long-term fishery-independent data.

Download

Share