Title page for ETD etd-01062004-090503


Type of Document Master's Thesis
Author Davis, Michelle Leigh
Author's Email Address midavis1@vt.edu
URN etd-01062004-090503
Title Assessment of the South Atlantic Red Porgy (Pagrus pagrus) Population Under a Moratorium
Degree Master of Science
Department Fisheries and Wildlife Sciences
Advisory Committee
Advisor Name Title
Berkson, James M. Committee Chair
Neves, Richard J. Committee Member
Ney, John J. Committee Member
Keywords
  • red porgy
  • stock assessment
  • model
  • moratorium
  • management
  • snapper-grouper complex
Date of Defense 2003-12-10
Availability unrestricted
Abstract
Red porgy Pagrus pagrus is a reef fish important to both recreational and commercial fisheries off the coast of the southeastern United States. Stock assessments performed on this species since 1985 have shown a population in decline. As a result, a number of management actions were put in place, including a harvest moratorium in 1999. Stock assessments for many marine species, including red porgy, rely on a combination of fishery-dependent and fishery-independent data. When a moratorium is in place, the flow of fishery-dependent data is interrupted, making assessments more reliant on fishery-independent information.

To investigate how loss of fishery-dependent data, as during a moratorium, would affect stock assessment results for red porgy, I conducted model simulations to represent moratoria of various durations. The most recent red porgy stock assessment model developed during a 2002 workshop was used as a tool in these simulations. I found that biological reference points, such as biomass and fishing mortality, and population projections were more variable for longer simulated moratoria. When fishery-dependent data were removed, minor fluctuations in length and age frequencies resulted in larger fluctuations in estimates of biological reference points. The simulated moratoria also resulted in a slight bias toward over-estimating stock productivity.

Similar simulations and analyses were conducted to determine the effects of reducing fishery-independent data from the Marine Resources Monitoring, Assessment, and Prediction (MARMAP) program. Length and age data of reduced MARMAP sample sizes were bootstrapped from original data, and used as input for the stock assessment model. Biological reference points and population projections were more variable for small MARMAP sample sizes, due to the incomplete representation of the length and age frequencies of the population. Reduced sample sizes also showed a slight bias toward predicting a more productive population. These types of simulations emphasize the benefits of investigating potential effects of data reduction on assessment results prior to implementing management strategies, such as a moratorium or sampling change, that cause data loss.

Although decreasing red porgy data resulted in slight changes in assessment results, there are more data available for this species than other species in the snapper-grouper complex. For these lesser-studied species, reducing data could dramatically affect assessment capabilities. To investigate this, I compiled available data for these species and identified the stock assessment method used. I then predicted assessment capabilities for each species under a moratorium and if the MARMAP survey was eliminated. A moratorium could reduce assessment capabilities for 37 of the 73 species, and 63 species would require management based on key species. Removing MARMAP data would reduce assessment capabilities of eight species, many of which are economically important. There was an overwhelming need for a reliable catch-per-effort index, information that could improve assessment capabilities of 67 species. This index could be obtained by expanding the MARMAP survey, from a fishery observer program, or from commercial logbooks. By linking the red porgy stock assessment, an evaluation of sampling regimes and data loss during a moratorium, and the expansion of this stock assessment strategy to multiple species, managers will ultimately benefit from increased ability to manage stocks experiencing varying regulations and data availability.

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