Utilizing remote sensing, modeling and data assimilation to sustain and protect fisheries: ecological forecasting at work

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Utilizing remote sensing, modeling and data
assimilation to sustain and protect fisheries
ecological forecasting at work
Francisco Chavez, M. Messie Monterey Bay Aquarium
Research Institute
F. Chai (U of Maine), Y. Chao (NASA/JPL), David
Foley (NOAA/NMFS), and R.T. Barber (Duke)
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Approach

• Develop remote sensing products for fisheries
  decision support systems
• Develop strong theoretical basis for forecasting
  using in situ and satellite data
• Develop 50 year model hindcasts and test theory
• Develop 2-9 month model forecasts and
  incorporate into fisheries decision support
  systems

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MODIS chlorophyll - first biological parameter
explicitly included in the CPC report
Mean trend
Mean
Trend Anomaly
Anomaly
Dave Foley, NOAA
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Science at the leading and/or bleeding edge
Why Peru?
Long term (9 month) forecasts of chlorophyll
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Progress in Oceanography 2008
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More fish (total and per unit primary production)
than any other place in the world!
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Change?
SST 1880 - 2006
Two Primary States
SSH 1983 2006 black line
Varia- bility
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Eddy-Resolving Ocean Model at 12-km
Regional Ocean Model Systems (ROMS)-CoSiNE CoSiNE
Carbon, Silicate, and Nitrogen Ecosystem (Chai
and Chao)
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Pacific Basin ROMS-CoSINE (12-km)
SimulationAnnual Mean Sea Surface Temperature
(SST)
Modeled SST (oC)
Satellite SST (oC)
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Zooplankton(ROMS-CoSINE)
Averaged from 1991-2007 by ROMS-CoSINE (blended
wind forcing)
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SST
50 year 50 km hindcast simulation
Data
Model
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Data
Model
Sea level
SST
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Large regime shift documented in Monterey Bay, CA
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ROMS-CoSINE (12 km) Temperature,
Currents, Plankton
ROMS-CoSINE (12 km) Temperature,
Currents, Plankton
Life Cycle of Peruvian Anchovy Individual Based
Model with ROMS-CoSINE
Yi Xu, U of Maine
ROMS-CoSINE (12 km) Temperature,
Currents, Plankton
ROMS-CoSINE (12 km) Temperature,
Currents, Plankton
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Anchovy Distribution Statistics

• Start with same amount of eggs
• Release eggs each year/month
• Calculate the total survivors after 6 months with
  spatial distribution
• Temperature and food (phytozoo) control
  survivorship

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Anchovy Distribution
Averaged from 1991-2007 by IBM
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Latitudinal direction
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Next steps

• Continue to improve forecasts and insert into DSS
• Retrospective analysis to get at mechanisms
  behind changes
• Clearly identified changes in the ecosystem
  1972 anchoveta decline, sardine increase, 1989
  anchoveta recovery and sardine decline, 1992
  humboldt squid appearance-jack mackerel/hake
  disappearance, 1998 appearance of cool water
  species