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![Page 1: Utilizing remote sensing, modeling and data assimilation to sustain and protect fisheries: ecological forecasting at work Francisco Chavez, M. Messie Monterey.](https://reader036.fdocuments.in/reader036/viewer/2022062421/56649e615503460f94b5c95a/html5/thumbnails/1.jpg)
Utilizing remote sensing, Utilizing remote sensing, modeling and data modeling and data
assimilation to sustain and assimilation to sustain and protect fisheries: ecological protect fisheries: ecological
forecasting at workforecasting at workFrancisco Chavez, M. Messie
Monterey Bay Aquarium Research Institute
F. Chai (U of Maine), Y. Chao (NASA/JPL), David Foley (NOAA/NMFS), R. Guevara, M. Niquen
(IMARPE) and R.T. Barber (Duke)
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ApproachApproach• Develop remote sensing products for Develop remote sensing products for
fisheries decision support systemsfisheries decision support systems
• Develop strong theoretical basis for Develop strong theoretical basis for forecasting using in situ and satellite forecasting using in situ and satellite datadata
• Develop 20-50 year model hindcasts and Develop 20-50 year model hindcasts and test theorytest theory
• Develop 9 month model forecasts and Develop 9 month model forecasts and incorporate into fisheries decision incorporate into fisheries decision support systemssupport systems
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The ecosystem of the Peruvian anchovy is modulated locally by winds, the depth of the thermocline and oxygen minimum zone. These in turn are perturbed remotely by changes in basin-scale thermal dynamics.
NASA products:
Physical basin-scale model (ROMS) run at 12.5 km resolution and an embedded nutrient-phytoplankton-zooplankton ecosystem
Validated and forced with remote sensing time series:
SSTWindsChlorophyll
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More fish (total and per unit primary production) than any other place in the world!
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TwoPrimaryStates
Change?
Varia-bility
SST1880 - 2006
SSH1983 – 2006
black line
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Model
Data
Sea levelSST
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Anchovy
Oxygen
Thermoclinedepth
SST
Sardine
V panel
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Current statusCurrent status
• On 4On 4thth year no-cost extension year no-cost extension
• Working with V panel on the Working with V panel on the anchovetaanchoveta
• Determining skill of forecast (forcing Determining skill of forecast (forcing and ocean)and ocean)
• Improving skill of forecastImproving skill of forecast
• Determining and implementing US Determining and implementing US requirementsrequirements
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Recommendations from V Recommendations from V panelpanel• Develop an Develop an
environmental/biological index that environmental/biological index that can be used in predictive models can be used in predictive models (see Wells et al.)(see Wells et al.)
• Develop and improve Develop and improve environmental forecasts on time environmental forecasts on time scales of months to decadesscales of months to decades
• Integrate environmental forecasts Integrate environmental forecasts into upper trophic level and socio-into upper trophic level and socio-economic models economic models
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Global modes of SST variability
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Model resultsModel results• Excellent hindcast agreement between ocean Excellent hindcast agreement between ocean
model and observations – meaning solid model and observations – meaning solid atmospheric forcing and physics/ecosystematmospheric forcing and physics/ecosystem
• NCEP atmospheric forecasts at lower resolution NCEP atmospheric forecasts at lower resolution – excellent open ocean tropical Pacific skill, – excellent open ocean tropical Pacific skill, poor coastal skillpoor coastal skill
• Ocean forecast skill off Peru good but can be Ocean forecast skill off Peru good but can be improved by downscaling NCEP forcing – doing improved by downscaling NCEP forcing – doing this as part of a salmon project (see Wells et al. this as part of a salmon project (see Wells et al. presentation)presentation)
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Acoustic Ship Survey or other
Stock Assessment
Anchoveta population
Fishery
Classical quota is % of biomass from stock assessment
Environmental Information
Add environmental information
Remote sensing
ROMS model forecasts
Biomass
No ForecastWith Forecast
1
2
3
4
Ecosystem (fish, mammals,
seabirds, etc.)
5
Add remote sensing
Add forecasts
Quota
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Accomplishments:- Fishery resource managers are utilizing NASA remote
sensing and model forecasts to decide how much fish to catch each season
- Why? If fishery managers know what the environment will be in the future they can maximize fishery profits and maintain the health of the ecosystem at the same time
- Providing scientifically credible information so the managers pay attention