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Steepness for West Coast rockfishes: Results from a twelve-year experiment in iterative regional meta-analysis

Thorson, James T., Dorn, Martin W., Hamel, Owen S.
Fisheries research 2019 v.217 pp. 11-20
Sebastes, applied research, autocorrelation, biomass, coasts, developmental stages, managers, marine fish, meta-analysis, models, rockfish, scientists, spawning, survival rate, Pacific Ocean, United States
Theoretical and applied research suggests that survival rates during early life stages will increase when spawning biomass is reduced in marine fishes (termed “recruitment compensation”). However, the magnitude of recruitment compensation is generally difficult to estimate for individual fish stocks, and its average value for marine fishes remains highly contested. Scientists and managers for Pacific rockfishes (Sebastes spp.) on the US West Coast have used a regional meta-analysis to estimate the likely distribution of the steepness parameter of the Beverton-Holt stock-recruit relationship using stock assessment models since 2007, and the method has been updated every two years as new assessments are conducted (i.e., five biennial updates). Here, we provide a short history of this approach, its methodological assumptions, changes in results over time, and ongoing efforts to validate its assumptions. While the regional meta-analysis has been successful in ensuring a consistent approach to treatment of steepness across assessments, the estimates of mean steepness have been unexpectedly variable as the meta-analysis has been updated. Specifically, we show that the estimated average value of steepness for West Coast rockfish increased markedly from 2007 (average: <0.6) to 2011 (average:>0.75), before decreasing somewhat again in the 2017 update. We also show that this value has a strong impact on rockfish rebuilding plans, and showcase the example of canary and widow rockfishes, where the estimated rates of rebuilding are strongly influenced by the assumed value of steepness. We conclude by discussing the bias-variance tradeoff between using global and regional meta-analysis, as well as the likely implications of difficult-to-validate assumptions including: (1) no recruitment autocorrelation within each stock; (2) no correlations among stocks; and (3) no bias from individual stocks resulting from mis-specification of the stock assessment models used in the meta-analysis.