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Utilizing Ecosystem Information to Improve Decision Support for Central California Salmon

Utilizing Ecosystem Information to Improve Decision Support for Central California Salmon Project Acronym: S almon A pplied F orecasting, A ssessment and R esearch I nitiative (SAFARI).

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Utilizing Ecosystem Information to Improve Decision Support for Central California Salmon

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  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. Wells2, M. Messie1, E. Danner2, W. Sydeman3, Y Chao4, F Chai5, S. Ralston2, J. Field2, D. Foley2, J. Santora3, S. Bograd2, S. Lindley2, and W. Peterson2. 5. 3. 1. 5. 4. 2.

  2. History • Ecological forecasting for fisheries started with collaboration with Peruvian anchovy managers • Developed remote sensing products • Developed 20year ROMS (physics/ecosystem) model hindcast • Developed 9 month model forecasts • Incorporated remote sensing and models into salmon decision support system • 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 • 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

  4. Key Messages • 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 • Favorable conditions for krill determined by large scale (ENSO, PDO) and local (winds, NPGO) forcing • Krill concentrate in upwelling shadows

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

  6. Key Messages • In situ data available for krill abundance and distribution • 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 +

  7. Key Messages • Salmon return to spawn at 3+ years – these are the harvest fish • 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 • 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 • Physical and biological conditions for prediction of salmon early ocean survival • Climate variability in the North Pacific in relation to salmon survival and productivity • Collections of indices of ecosystem state including upwelling, ENSO, PDO

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

  10. Lifecycle Adult salmon spawn Adult salmon return Adult salmon return Juveniles emigrate Jacks return = winter Freshwater Marine

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

  12. Data Model SST Sea level

  13. Observed krill rho = 0.96* R2 = 0.95* Modeled zooplankton 2008 2003 2002 2004 2007 2005 2006 T. spinifiera Modeled zoo

  14. Corollary and future • PFMC utilizes project output in the DSS for central California salmon • Process is very conservative • 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 • PFMC interested in tackling regulated forage species (sardine) next

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