Davis and Berkson Effects of a simulated fistiing moratorium on tfie stock assessment of Pagrus pagrus 



591 



cies would most likely result in larger changes in sta- 

 tus indicator estimates, projections, and management 

 decisions because a larger proportion of information 

 would be removed. The results of our study on red porgy 

 identified the importance of investigating the potential 

 effects of reducing fishery-dependent information on 

 stock assessment results. If used before implementing 

 management actions, this kind of data simulation study 

 could estimate the potential impact of a lack of data 

 before harvest restrictions are put in place that would 

 cause data loss. 



Management implications 



These types of simulation studies aid in understanding 

 the impacts of data quantity on stock assessments, par- 

 ticularly with respect to uncertainty and variance. By 

 incorporating uncertainty due to data loss into manage- 

 ment decisions, managers will be better able to assess 

 and manage these populations. For example, SEDAR 

 population projections estimated that red porgy required 

 a 12-year moratorium for the population to rebuild to 

 ^MSY (^Fig. 3). However, our data simulations showed that 

 variability surrounding status indicators increased when 

 as few as three years of fishery-dependent data were 

 removed (Fig. 4) and that a tendency toward overesti- 

 mating productivity also increased with duration of the 

 moratorium (Fig. 7). Therefore, if managers implemented 

 a 12-year moratorium for red porgy (with no additional 

 sampling), it is possible that a stock assessment con- 

 ducted at the end of the moratorium would be unable to 

 accurately estimate stock status and identify whether or 

 not the population biomass had reached B(/j,y. 



This study highlights the importance of additional 

 sampling during periods of strict regulations to compen- 

 sate for the fishery-dependent data that are lost (Olney 

 and Hoenig, 2001). Because many reef fish species are 

 caught in the same fisheries, analysis of bycatch through 

 a fisheries observer program would yield valuable data 

 for a number of species. Another option for data collec- 

 tion would be to initiate a "test fishery" after a mora- 

 torium in order to collect fishery-dependent data in a 

 relatively short time and then use these data to estimate 

 stock status. A third option would be to use additional 

 sampling during a moratorium from fishery-independent 

 sources. Although MARMAP data are currently insuf- 

 ficient for assessments of many reef fishes, an expanded 

 survey (i.e., into deeper water, more gear types, etc.) 

 could prove to be valuable in future assessments. Even 

 without a moratorium in place, assessments of many 

 species would undoubtedly benefit from information col- 

 lected by a fisheries observer program or an expanded 

 fishery-independent survey. Data collected from these 

 sources before a period of strict regulation would im- 

 prove the ability of scientists to detect trends because a 

 longer time series would make population recovery more 

 apparent than that seen without such data. 



The data quantity simulations conducted in our study 

 could also be used for other species. This method al- 

 lows managers to simulate the effects of a lack of data 



before enacting regulations or sampling changes that 

 cause data loss. If a loss of information is shown to 

 affect stock assessment results, simulations can be 

 conducted to identify whether additional data will be 

 needed and to test the effectiveness of additional sam- 

 pling before implementing a sampling program. Stock 

 assessments frequently use population projections to 

 predict the effects of a policy on the stock. Our meth- 

 odology is an expansion of this idea, using simulations 

 to predict how a policy affects our ability to identify 

 changes in the stock. By incorporating uncertainty due 

 to data loss into management decisions, managers will 

 be better able to assess and manage these populations 

 and improve sampling to better fulfill future research 

 needs. 



Acknowledgments 



This research was funded by the South Atlantic Fishery 

 Management Council. We thank E. Williams, M. Prager, 

 D. Vaughan, and K. Shertzer for providing modeling 

 advice, J. Potts and P. Harris for information, J. Ney and 

 R. Neves for guidance, and the many state and federal 

 biologists and SAFMC staff members that assisted us in 

 this project. This manuscript was improved by the com- 

 ments and suggestions of M. Prager and two anonymous 

 reviewers. We greatly appreciate the time and effort of 

 all involved. 



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