1. Utilizing Ecosystem Information to Improve Decision Support for Central California Salmon Project Acronym: Salmon Applied Forecasting, Assessment and Research Initiative (SAFARI) Chavez, F. 1, B.K. Wells 2, M. Messie 1, E. Danner 2, W. Sydeman 3, Y Chao 4, F Chai 5, S. Ralston 2, J. Field 2, D. Foley 2, J. Santora 3, S. Bograd 2, S. Lindley 2, and W. Peterson 2. 3. 4. 5. 1. 2. 5.

2. History Ecological forecasting for fisheries started with collaboration with Peruvian anchovy managers Ecological forecasting for fisheries started with collaboration with Peruvian anchovy managers Developed remote sensing products Developed remote sensing products Developed 20 year ROMS (physics/ecosystem) model hindcast Developed 20 year ROMS (physics/ecosystem) model hindcast Developed 9 month model forecasts Developed 9 month model forecasts Incorporated remote sensing and models into salmon decision support system Incorporated remote sensing and models into salmon decision support system Presently working on integrated river, SF Bay, ocean model (Danner et al.) Presently working on integrated river, SF Bay, ocean model (Danner et al.)

3. Key Messages Pacific Fisheries Management Council is customer - sets harvest rules for salmon stocks in central CA, WA, OR, and ID Pacific Fisheries Management Council is customer - sets harvest rules for salmon stocks in central CA, WA, OR, and ID Partners in NOAA/NMFS have close working relationship with PFMC Partners in NOAA/NMFS have close working relationship with PFMC Central California salmon had just had several years with poor returns and ocean was implicated Central California salmon had just had several years with poor returns and ocean was implicated

4. Key Messages Salmon spawn in rivers, fingerlings make way down rivers to San Francisco Bay and then ocean Salmon spawn in rivers, fingerlings make way down rivers to San Francisco Bay and then ocean Early ocean period critical for survival, in particular availability of krill Early ocean period critical for survival, in particular availability of krill Favorable conditions for krill determined by large scale (ENSO, PDO) and local (winds, NPGO) forcing Favorable conditions for krill determined by large scale (ENSO, PDO) and local (winds, NPGO) forcing Krill concentrate in upwelling shadows Krill concentrate in upwelling shadows

5. Key Messages Cool, upwelling conditions favor krill and salmon Cool, upwelling conditions favor krill and salmon Sea level in the Fall indicator of large- scale conditions during following Spring Sea level in the Fall indicator of large- scale conditions during following Spring High sea level, warm, low, cool High sea level, warm, low, cool Remote sensing and models provide sea level information Remote sensing and models provide sea level information

6. Key Messages In situ data available for krill abundance and distribution In situ data available for krill abundance and distribution Coupled model capable of reproducing krill spatial pattern and abundance of critical species Coupled model capable of reproducing krill spatial pattern and abundance of critical species Remote sensing and models can improve and extend predictions for salmon returns by a year + Remote sensing and models can improve and extend predictions for salmon returns by a year +

7. Key Messages Salmon return to spawn at 3+ years – these are the harvest fish Salmon return to spawn at 3+ years – these are the harvest fish A few 2 year (jacks) salmon return with spawners A few 2 year (jacks) salmon return with spawners The number of 2 year fish is correlated with the number of 3+ fish returning the following year The number of 2 year fish is correlated with the number of 3+ fish returning the following year PFMC uses the jack model as a starting point and tunes from there PFMC uses the jack model as a starting point and tunes from there

8. PFMC utilizes project output for: Climate and ocean status, trends, and scenarios for stock assessment, harvest levels and rebuilding plans Climate and ocean status, trends, and scenarios for stock assessment, harvest levels and rebuilding plans Physical and biological conditions for prediction of salmon early ocean survival Physical and biological conditions for prediction of salmon early ocean survival Climate variability in the North Pacific in relation to salmon survival and productivity Climate variability in the North Pacific in relation to salmon survival and productivity Collections of indices of ecosystem state including upwelling, ENSO, PDO Collections of indices of ecosystem state including upwelling, ENSO, PDO

9. Recent declines in the fishery implicate the ocean and instigated our interest in this work. Background

10. = winter Lifecycle Adult salmon returnAdult salmon spawnJuveniles emigrateAdult salmon return Jacks return Freshwater Marine

11. Physical model run over entire Pacific at 12.5 km resolution Taking the next step: Modeling the ocean environment (ROMS-COSINE)

12. Model Data Sea levelSST

13. Modeled zooplankton Observed krill rho = 0.96* R 2 = 0.95* 2007 2006 2005 2004 20032002 2008 Modeled zoo T. spinifiera

15. Corollary and future PFMC utilizes project output in the DSS for central California salmon PFMC utilizes project output in the DSS for central California salmon Process is very conservative Process is very conservative NOAA utilizes project output as part of Integrated Ecosystem Assessment (IEA) process for the CCLME NOAA utilizes project output as part of Integrated Ecosystem Assessment (IEA) process for the CCLME Forage species (krill, anchovy, sardine) are critical component of IEA Forage species (krill, anchovy, sardine) are critical component of IEA PFMC interested in tackling regulated forage species (sardine) next PFMC interested in tackling regulated forage species (sardine) next