Francisco Chavez, M. Messie Monterey Bay Aquarium Research Institute
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Transcript of Francisco Chavez, M. Messie Monterey Bay Aquarium Research Institute
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), and R.T. Barber (Duke)
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 50 year model hindcasts and Develop 50 year model hindcasts and test theorytest theory
• Develop 2-9 month model forecasts and Develop 2-9 month model forecasts and incorporate into fisheries decision incorporate into fisheries decision support systemssupport systems
Mean
TrendAnomalyAnomaly
Mean trend
MODIS chlorophyll - first biological parameter explicitly included in the CPC report
Dave Foley, NOAA
Science at the leading and/or bleeding edge
Long term (9 month) forecasts of chlorophyll
Why Peru?
Progress in Oceanography 2008
More fish (total and per unit primary production) than any other place in the world!
TwoPrimaryStates
Change?
Varia-bility
SST1880 - 2006
SSH1983 – 2006
black line
Regional Ocean Model Systems (ROMS)-CoSiNECoSiNE: Carbon, Silicate, and Nitrogen Ecosystem (Chai and Chao)
Eddy-Resolving Ocean Model at 12-kmEddy-Resolving Ocean Model at 12-km
1010
Pacific Basin ROMS-CoSINE (12-km) Pacific Basin ROMS-CoSINE (12-km) SimulationSimulationAnnual Mean Sea Surface Temperature (SST)Annual Mean Sea Surface Temperature (SST)
ModeledSST (oC)
SatelliteSST (oC)
10
1111
Zooplankton(ROMS-Zooplankton(ROMS-CoSINE)CoSINE)
Averaged from 1991-2007 by ROMS-CoSINE (blended wind forcing)
50 year 50 km hindcast simulation
Data
Model
SST
Model
Data
Sea levelSST
Large regime shift documented in Monterey Bay, CA
EGGSDURATION: 24 HR
MORTALITY RATE>99%
YOLK-SAC LARVELEN: 2-4MM
DURATION: 24-28 HRMORTALITY RATE 80%-98%
FIRST-FEEDERFEED BY PHYTOPL.
LEN: 4.25CM, WT: ~2 gmDURATION: 80 DAYS
AGE-1(JUVENILE)BECOME SEXUAL MATRUE
LEN: 8-10CMWT: ~10 gm
AGE-2LEN: ~20CM WT: ~55 gm
OPT TEMP: 18.6°CSPAWN ~20 TIMES/YR
AGE-2+LIFE SPAN ~3 YR
PREDATOR: SEA BIRDS, MARINE MAMMALS
Life Cycle of Peruvian AnchovyIndividual Based Model with ROMS-CoSINE
ROMS-CoSINE (12 km)
Temperature, Curre
nts,
Plankton
ROMS-CoSIN
E (12 km
)
Temperature
, Curre
nts,
Plankton
ROMS-CoSINE (12 km)
Temperature, Currents,
Plankton
ROMS-CoSINE (12 km)
Temperature, Currents,
Plankton
Yi Xu, U of Maine
2020
Anchovy Distribution Anchovy Distribution StatisticsStatistics
• Start with same amount of eggsStart with same amount of eggs
• Release eggs each year/monthRelease eggs each year/month
• Calculate the total survivors after 6 Calculate the total survivors after 6 months with spatial distributionmonths with spatial distribution
• Temperature and food (phyto+zoo) Temperature and food (phyto+zoo) control survivorshipcontrol survivorship
2121
Anchovy DistributionAnchovy Distribution
Averaged from 1991-2007 by IBM
2222
2323
Latitudinal directionLatitudinal direction
Next stepsNext steps
• Continue to improve forecasts and insert Continue to improve forecasts and insert into DSSinto DSS
• Retrospective analysis to get at Retrospective analysis to get at mechanisms behind changesmechanisms behind changes
• Clearly identified changes in the ecosystem Clearly identified changes in the ecosystem – 1972 anchoveta decline, sardine increase, – 1972 anchoveta decline, sardine increase, 1989 anchoveta recovery and sardine 1989 anchoveta recovery and sardine decline, 1992 humboldt squid appearance-decline, 1992 humboldt squid appearance-jack mackerel/hake disappearance, 1998 jack mackerel/hake disappearance, 1998 appearance of cool water speciesappearance of cool water species