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, E. Danner2, W. Sydeman3, Y Chao4, F Chai5, S. Ralston2, J. Field2, D. Foley2, J. Santora3, S. Bograd2, S. Lindley2, and W. Peterson2.
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ApproachApproach• Develop strong theoretical basis for Develop strong theoretical basis for
forecasting using in situ and satellite dataforecasting using in situ and satellite data
• Develop forecasts using in situ and Develop forecasts using in situ and satellite datasatellite data
• Develop 20 year model hindcast and test Develop 20 year model hindcast and test theorytheory
• Develop 9 month model forecastsDevelop 9 month model forecasts
• Incorporate into salmon decision support Incorporate into salmon decision support systemsystem
Recent declines in the fishery implicate the ocean and instigated our interest in this work.
Background
= winter
Lifecycle
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Jac
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San Francisco
Monterey Bay
Environmental conditions
Wells, B.K., J. Field, J. Thayer, C. Grimes, S. Bograd, W. Sydeman, F. Schwing, and R. Hewitt. 2008 Untangling the relationships among climate, prey, and top predators in an ocean ecosystem. Marine Ecology Progress Series. 364:15-29
Developing conceptual models between physics and biology
Cape Mendocino
Pt. Conception
WindKrill
Santora, J.A., W.J. Sydeman, I.D. Schroeder, B.K. Wells, J.C. Field. 2011. Mesoscale structure and oceanographic determinants of krill hotspots in the California Current: Implications for trophic transfer and conservation. Progress in Oceanography.
Quantifying the observed relationships between physics and biology
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Wells, B.K., J.A. Santora, J.C. Field, R.B. MacFarlane, B.B. Marinovic, and W.J. Sydeman. In review. An ecosystem perspective for quantifying the dynamics of juvenile Chinook salmon (Oncorhynchus tshawyscha) and prey in the central California coastal region. Marine Ecology Progress Series.
20 years of trawl catch: Juvenile salmon rear in a plug of T. spinifera located in a relaxed area.
Quantifying the observed relationships between physics and biology
Advection/Upwelling T. spinifera Salmon
Santora, J.A., W.J. Sydeman, I.D. Schroeder, B.K. Wells, J.C. Field. 2011. Mesoscale structure and oceanographic determinants of krill hotspots in the California Current: Implications for trophic transfer and conservation. Progress in Oceanography. http://www.sciencedirect.com/science/article/pii/S0079661111000371
Quantifying the observed relationships between physics and biology
Kri
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With estimates of krill and SLH to Fall we can extend our predictions to the previous cohort.
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SI = T. Spin GOF + SLHfall
Quantifying and then forecasting
R2 = 0.75
Kri
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SLH
With estimates of krill and SLH to Fall we can extend our predictions to the previous cohort.
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SI = T. Spin GOF + SLHfall
Quantifying and then forecasting
Physical model run over Physical model run over entire Pacific at 12.5 km entire Pacific at 12.5 km resolutionresolution
Taking the next step: Modeling the ocean environment (ROMS-COSINE)
To play 80M .mpg movieclick here.
Model
Data
Sea levelSST
Chavez, F. P. M. Messié, and J.T. Pennington (2011) Marine primary production in relation to climate variability and change. Annual Review of Marine Science, 3:227–60, doi:10.1146/annurev.marine.010908.163917
The modeling approach is capable of reproducing the zooplankton climatology demonstrated in empirical studies
Modeled zooplanktonObserved krill
Taking the next step: Modeling the ocean environment (ROMS-COSINE)
Zooplankton 0-100 m Isobath
40 60 80 100 120 140 160
T. spinifera
Abundance, A
ll Areas 3
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8 rho = 0.96*R2 = 0.95*
2007
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2003 2002
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Modeled meso-zooplankton
T. s
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The modeling approach is capable of reproducing the temporal patterns observed in empirical studies
Taking the next step: Modeling the ocean environment (ROMS-COSINE)
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There is potential for management improvement
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Har
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Taking the next step: Modeling the ocean environment (ROMS-COSINE)
SI = T. Spin GOF + SLHfall
2009
2003 2005 2007 2009 2011 2013
Salmon against climate index 4 years previous
DSS, Management, Challenges• Regular presentations to salmon working group
for Pacific Fisheries Management Council, next October 2012 – requires continual presence
• Developments incorporated into NOAA’s Integrated Ecosystem Assessment of the CCLME, a decision-support system that uses diverse data and ecosystem models to forecast future conditions
• How to make models operational
