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with attendant consequences for the overall system structure (Fogarty et al., 1989). Population modeling suggests that the stock-recruitment relationship for haddock might have been changed and that the population cannot now withstand as heavy fishing mortality as it could before the increase in predation pressure.

Risk assessment for exploited systems must take into account uncertainties in population abundance, harvest rates, and system structure. Adoption of risk-averse management strategies would minimize the possibility of stock depletion or undesirable alterations in the structure of the system.

Discussion

(Led by R. M. Peterman, Simon Fraser University, and J. L. Ludke, National Fisheries Research Center-Leetown)

Discussion focused on the idea of statistical power—the probability that an experiment (or set of observations) will correctly reject a null hypothesis that is false, i.e., the probability that an experiment will detect effects that actually exist. In fisheries cases, the high degree of variability in population parameters means that most studies have very low power to detect changes, unless the studies are continued for many years or involve frequent measurements (Peterman and Bradford, 1987). Published papers in fisheries biology (and in other disciplines related to risk assessment) rarely report statistical power and hence can misleadingly report negative findings. The case study recommended adopting a conservative null hypothesis to allow for the low power of the observational studies. Other approaches are to improve the design of studies (e.g., by more frequent sampling), to incorporate uncertainties into formal decision analysis, and to reverse the burden of proof (to put the burden of documenting whether detrimental effects are occurring on exploiters of the resource, rather than in the management agency). If "proof" of safety is required, a formal statement of the power of studies should be provided for a size of effect deemed relevant.

The Georges Bank fishery is only one of a long series of cases in which overexploitation has occurred despite a nominal system of scien-



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OCR for page 307
APPENDIX E 307 original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. with attendant consequences for the overall system structure (Fogarty et al., 1989). Population modeling suggests that the stock-recruitment relationship for haddock might have been changed and that the population cannot now withstand as heavy fishing mortality as it could before the increase in predation pressure. Risk assessment for exploited systems must take into account uncertainties in population abundance, harvest rates, and system structure. Adoption of risk- averse management strategies would minimize the possibility of stock depletion or undesirable alterations in the structure of the system. Discussion (Led by R. M. Peterman, Simon Fraser University, and J. L. Ludke, National Fisheries Research Center-Leetown) Discussion focused on the idea of statistical power—the probability that an experiment (or set of observations) will correctly reject a null hypothesis that is false, i.e., the probability that an experiment will detect effects that actually exist. In fisheries cases, the high degree of variability in population parameters means that most studies have very low power to detect changes, unless the studies are continued for many years or involve frequent measurements (Peterman and Bradford, 1987). Published papers in fisheries biology (and in other disciplines related to risk assessment) rarely report statistical power and hence can misleadingly report negative findings. The case study recommended adopting a conservative null hypothesis to allow for the low power of the observational studies. Other approaches are to improve the design of studies (e.g., by more frequent sampling), to incorporate uncertainties into formal decision analysis, and to reverse the burden of proof (to put the burden of documenting whether detrimental effects are occurring on exploiters of the resource, rather than in the management agency). If "proof" of safety is required, a formal statement of the power of studies should be provided for a size of effect deemed relevant. The Georges Bank fishery is only one of a long series of cases in which overexploitation has occurred despite a nominal system of scien

OCR for page 307
APPENDIX E 308 original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. tific stock assessment and fishery management. Discussants generally felt that overexploitation was due to failures of management, rather than to deficiencies in assessment or failure to communicate results to managers. The assessment of the risk to fish populations associated with exploitation in the Georges Bank case study is implicitly consistent with the 1983 health risk assessment framework, although the explicit steps differ. The case study illustrates the 1983 risk assessment paradigm within the larger context of problem-solving. However, the dose-response and exposure steps might be only loosely analogous. Differing circumstances of function, scale, and certitude could require variation in the method of risk assessment. The numerous sources of uncertainty in assessing risk associated with exploitation of fish populations vary and increase in magnitude with increase in scale. Regulation of harvest of geographically confined populations can be achieved with greater confidence than can regulation of wide-ranging populations such as Chesapeake Bay striped bass and Lake Michigan lake trout. Sources of uncertainty include variation in recruitment, measurement (which requires many assumptions), and management and institutional characteristics. Management techniques for reducing risks associated with overexploitation of populations are fairly blunt instruments, and strong actions are usually taken only after the fact. Rarely, if ever, are risk reduction measures considered until an actual impact is noticed or a potential threat emerges. Subtle and cumulative factors that are unknown or are measured imprecisely —e.g., chronic or episodic changes in predation, migration, and disease—are some of the issues with information gaps that contribute to uncertainties in ecological risk assessment. The Georges Bank case study describes multispecies interactions and consequences of selective harvesting practices within the fish community, but falls short of a systematic understanding of cause and effect with regard to changes in multispecies abundance.