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Jesus Jurado-Molina University of Washington Patricia A. Livingston

Multispecies Catch at Age Model (MSCAGEAN): incorporating predation interactions and statistical assumptions for a predator‑prey system in the eastern Bering Sea. Jesus Jurado-Molina University of Washington Patricia A. Livingston Alaska Fisheries Science Center. Fisheries models.

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Jesus Jurado-Molina University of Washington Patricia A. Livingston

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  1. Multispecies Catch at Age Model (MSCAGEAN): incorporating predation interactions and statistical assumptions for a predator‑prey system in the eastern Bering Sea Jesus Jurado-Molina University of Washington Patricia A. Livingston Alaska Fisheries Science Center

  2. Fisheries models Assumption: Population Isolated Constant Natural Mortality Age Structured Models Statistical Assumptions Statistical Catch at Age Models

  3. Fisheries models Predation Equations M=M1+M2 No statistical assumptions on error structure included Virtual Population Analysis Multispecies Virtual Population Analysis (MSVPA)

  4. Multispecies Catch at age Analysis? Predation interactions Age structured model Statistical assumptions on error structure Multispecies Catch at age Analysis

  5. Objectives: • To add the predation equations to a CAGEAN model (MSCAGEAN): • Comparison of the MSCAGEAN results to the ones estimated with the multispecies VPA, the Multispecies Forecasting Model (MSFOR) and the single species CAGEAN.

  6. Input and outputs of MSVPA-MSFOR

  7. Statistical models Error assumption Model equations Prior information Data

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

  9. Multispecies CAGEAN Error assumption Model equations Predation equations Prior information Data

  10. Equations:

  11. Advantages: • Multispecies approach • We can use the tools used in single species stock assessments • Likelihood profile • Bayesian statistics (probability distributions) • Model selection (Akaike’s information criterion,likelihood ratio )

  12. Assumptions • Stomach content measured without error • Suitabilities constant (estimated as the average of the annual suitabilities) • Recruitment for the simulation is log-normal distributed • Recruitment of age-0 individuals for the simulation takes place in the third quarter

  13. Walleye pollock and Pacific cod interactions Fishery Walleye pollock Pacific cod

  14. Methods • Initial run of the MSVPA updated to 1998. • Run of Multispecies forecasting (F40%). • Spawning Biomass in 2015 as indicator of performance. • Multispecies Catch at Age Analysis updated to 1998 • Single species CAGEAN updated to 1998

  15. MSVPA and MSCAGEAN results: Age-0 walleye pollock Natural mortality (1990) MSVPA MSCAGEAN 1.55 M2 = 1.70 ± 57

  16. MSVPA and MSCAGEAN results: suitability coefficients MSVPA MSCAGEAN 0.303 0.683 ± 0.140

  17. MSVPA AND MSCAGEAN results: Spawning biomass in 2015 MSFOR MSCAGEAN SUM=SUM+L SUM=SUM+1 SSB = 5.52E6± 2.36E6 SSB = 1.33E7 ± 5.25E6

  18. MSCAGEAN and CAGEAN results: Spawning biomass in 2015 CAGEAN MSCAGEAN SSB = 1.19E07 ± 5.06E06 SSB = 1.33E07 ± 5.25E06

  19. Future tasks • To implement the predation equations in the stock assessments methods used in the AFSC assessments

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