2. Jesús Jurado-Molina School of Fisheries, University of Washington

4. zTo apply the single and multispecies forecasting models to assess the effects produced by climate regime shifts and fishing on spawning biomass of some species from the Bering Sea. zDetermine relative roles of fishing, climate regime, and predation in population dynamics

6. BS - suitable prey biomass S - suitability coefficient of prey p for predator i R - annual ration of the predator i W - weight at age of prey p M1- residual mortality M2 - predation mortality

8. zM = M1 + M2 zPredator’s annual ration = constant zAverage constant suitability coefficients (from MSVPA) zOther food of predators remains constant zSuitability coefficients reflect the preferences of the predator, the vulnerability and the availability of the prey and other factors such as the overlapping of predator and prey populations etc. zSuitabilities define the predation interaction dynamics in the forecasting models

9. zEl Niño Southern Oscillation (ENSO) 1.Duration of 2 to 7 years 2.Global influence zPacific Decadal Oscillation (PDO) 1. Persistency of 20 to 30 years 2. Main influence in the North Pacific and North American sector

10. z If recruitment success were dependent on a sequence of events, then a semi-permanent shift in ocean conditions would influence only one of several conditions necessary for successful recruitment. Stocks that exhibit this type of recruitment response would show a change in the probability of a strong year class, or a change in the amplitude of strong year classes when they occurred, expressed as a change in the mean level of recruitment (Hollowed and Wooster, 1995).

11. zThere is a mean recruitment and variance associated with each climate regime zRecruitment of age-0 individuals takes place in the third quarter zRecruitment is log-normal distributed zFirst scenario: 1977 temperature Regime continues beyond zSecond scenario: There is regime shift in 1989

12. zMSVPA run updated to 1998 data to obtain average suitabilities, average recruitment values and population initial values (1998) for all species. zANOVA analysis and comparison of the CV’s for the recruitment from MSVPA for the periods 1979-1988 and 1989-1998 zMultispecies forecasting using the mean and standard deviation of recruitment values associated with the two regime shifts, average suitabilities, initial population values (1998) and four levels of fishing mortality, F 30, F 40, F 50 and no fishing mortality zSingle species forecasting using the corresponding input parameters. zSpawning biomass ratio selected as indicator of performance: SSB ratio = SSB(2015)/SSB(1998)

13. ANOVA and CV’s comparison results for the 1979-1989 and 1989-1998 periods

22. z Climate regime shifts produced an effect comparable to the ones produced by fishing and predation on the species analyzed from the eastern Bering Sea, therefore accurate models for fisheries management will require considering all three factors and their potential interactions. z To incorporate regime shifts in fisheries management it is necessary to have a better understanding of recruitment behavior during a particular climate regime and a reliable way to identify a potential shift based on biological and/or physical indices. z Species respond differently to both climate change assumptions and fishing mortality depending on their position on the food web and on their generation time. Responses are complex and difficult to predict therefore it is necessary to take an even more conservative approach in managing the species with the largest potential variation.

23. zAnalysis of additional indicators including predation mortality, total population and catch. zInclusion of stochastic Ricker and Beverton and Holt recruitment