Search

Like many fisheries in the world, the northern shrimp, Pandalus borealis, fishery in the Gulf of Maine is monitored with both fishery-dependent and independent sampling programs. A periodic review of sampling programs is essential to assess if they effectively and efficiently monitor spatial and temporal variations of key fisheries statistics, which provide the information critical to achieve management objectives. In this study we evaluated whether the northern shrimp port sampling program was representative of the commercial catch and effort. The combined federal and state vessel trip reports for 2007 and 2008 were considered to be complete in quantifying temporal and spatial variability, which allowed us to develop a simulation study for examining whether the port sampling program could be streamlined by reducing the number of samples collected each year. We found that the port sampling program in 2007 and 2008 represented the trap fishery but not the trawl fishery catch and effort in the Maine fishery. We recommend maintaining the level of sampling intensity for trap gear and increasing the sampling effort for trawl gear. The ports and weeks that significantly impacted key fishery statistics were identified. We found that selections of weeks and ports sampled were critical to the accuracy of the data. We suggest that both temporal and spatial factors be considered in optimizing sampling program design to capture variation of the catch and effort in this fishery. The evaluation methods developed in this study could be used in other fisheries to evaluate the efficiency of their sampling programs.

A Bayesian stock assessment framework with a size-structured population dynamics model used to assess the green sea urchin, Strongylocentrotus drobachiensis, fishery in Maine, USA was evaluated, using a simulation approach, for its performance in describing sea urchin population dynamics under different recruitment dynamics and data quality. This study suggests that the current stock assessment model performs well in estimating key sea urchin fishery parameters such as exploitable stock biomass, total stock biomass, natural mortality, and fishing mortality under different simulation scenarios, and can capture the dynamics of the Maine sea urchin population. The recruitment dynamics of the sea urchin are likely to vary greatly with large changes occurring in its ecosystem. The finding that the current assessment framework is able to capture different patterns of recruitment dynamics implies that the current assessment framework will remain effective in future stock assessments of the Maine sea urchin fishery.

The green sea urchin (Strongylocentrotus drobachiensis ) fishery is of great importance to Maine’s economy. The fishery took off in the late 1980s as a result of expanding export markets, but has experienced substantial decline in landings since 1992 because of large decreases in urchin stock abundance. Fishery-independent surveys have not been conducted, and no formal stock assessment has been done prior to this study. Using the data collected from the fishery and urchin life history parameters derived from scientific studies, we conducted a formal stock assessment for the urchin stock. A stochastic observation-error length-structured model is used to describe the dynamics of the sea urchin population. A robust Bayesian approach is used for estimating fishery parameters because of concerns of possible outliers in fisheries data and mis-specification of priors. This study shows that the current stock is only 10% of the virgin stock biomass and that the exploitation rate is close to 40% suggesting that a large reduction in exploitation rate is necessary. © 2002 Elsevier Science B.V. All rights reserved.