D A Kiefer, D P Harrison, M G Hinton, Li Luo

Climate Events and Their Impacts on Fishery Dynamics of EPO

• 4 dimensional system for marine applications WGS 84/geodetic representation •interfaces for models, spreadsheets, databases, and Internet • PC Desktop & Web-enabled GIS applications

Models

EASY software architecture

SST SSChl_a

Mode 1

Mode 2

Mode 3

EOF Analysis of Time Series of Satellite Imagery

SSH

Mode 1

Mode 2

Mode 3

PC1 SST 20.9% Chl_A 10.58%

PC2 SST 7.6% Chl_A 8.31% SSH 6.81%

PC3 SST 6.5% Chl_A 6.13% SSH 4.43%

Linkages Between Sea Surface Temperature, Chlorophyll, and Dynamic Height

SSH 14.31%

ECCO-2 Global Ocean Model AVISOSSH 1992-2008

Cube92PC 1: 16.54%AvisoPC1: 14.31%

Cube92PC 1: 6.16%AvisoPC1: 6.81%

Cube92PC3: 5.08%AvisoPC3: 4.43%

Purse Seine & Longline Fishing Grounds

Longline Fishing Ground

Fishscape Eastern Pacific Tuna Region

Schmittner, A., A. Oschlies, H. D. Matthews, and E. D. Galbraith (2008), Future changes in climate, ocean circulation,ecosystems, and biogeochemical cycling simulated for a business-as-usual CO2 emission scenario until year 4000 AD, Global Biogeochem. Cycles, 22

The purse seine fishing ground, which we believe is the nursery ground for Eastern Pacific tuna, also matches the ocean’s largest site of CO2 release to the atmosphere.

The upper panel shows maps field calculations of CO2 release from the atmosphere. Takahashi et al. (2002)

The lower panel maps field simulations of CO2 from a biogeochemical climate model developed by Schmittner and co-workers.

Purse seine recording stations superimposed upon a MODIS satellite image of surface chlorophyll concentration.

Purse seine recording stations superimposed upon a climatological image of annual average oxygen concentration at 150 m depth.

PHAM screen shots.The purse seine fishing ground (indicated by +) matches well surface waters where chlorophyll concentration exceeds 1 mg/m3 (upper panel) & overlies the hypoxic layer (lower panel).

The Holy Grail of Stock Assessment Models: Recruitment!

We have now incorporated into PHAM EOF analysis of time series information from satellites sea surface temperature, chlorophyll, and height and NASA’s ECCO 2 3-dimentsional global circulation model. This analysis yields underlying patterns in spatial and temporal variability that are then compared by cross correlation analysis to the temporal patterns in recruitment.

Adults[Age+1] Larvae Juveniles Recruits[ Age] Adults[Age+i]

Spawning

Survival SurvivalSurvival Survival

Survival is a function of food availability and predation (both natural and human).

EOF 1st Seasonal spatial component & temporal expansion coefficient (right hand corner)

EOF 1st nonseasonal spatial component & temporal expansion coefficient

We have developed an algorithm to predict the recruitment of yellowfin tuna based upon EOF extraction of patterns from time series of satellite imagery.

1 9 8 5 1 9 9 0 1 9 9 5 2 0 0 0 2 0 0 5 2 0 1 0

5 0

1 0 0

1 5 0

2 0 0

Y F T R e c r ui ts P e r S p a w ne r B io m a s s :

S to c k A s s e s s m e ntb lue, S a te l l i te S S T P r e d i c ti o ns r e d

Correlation between temporal expansion coefficients and yellowfin recruitment lead tohypothesis of temporal evolution.

August 79: average weekly sets overlying ECCO 2 mixed layer depth

August 98: Skipjack catch overlyingECCO 2 meridional velocity

Equatorial current

Equatorial counter current

N Equatorial current

10/1997-4/1998 SKJ catch overlaying El Nino surface tracks

10/1998-4/1999 SKJ catch overlaying La Nina surface tracks

Time Series Runs: Yellowfin Catch along Eddy Front ?

Convention for the Conservation of Antarctic Marine Living ResourcesConvention on the Conservation of Antarctic Marine Living Resources)The Convention on the Conservation of Antarctic Marine Living Resources, also Commission on the Conservation of Antarctic Marine Living Resources, and CCAMLR, is part of the Antarctic Treaty System. The Convention was opened for signature on 1 August 1980 and entered into force on 7 April 1982 by the Commission for the Conservation of Antarctic Marine Living Resources, headquartered in Tasmania, Australia. The goal is to preserve marine life and environmental integrity in and near Antarctica.

1000 km

Example of Application to Fisheries: Pacific Herring Population Dynamics

Sitka Sound Prince William Sound

Pacific Decal OscillationNational Climate Data Center

1975-1977 start of “Great Regime Shift”

Bight Watch Information System

GISStatistical Tools EOF, pattern assessment, correlation analyses, predictor

Biogeochemical Models Plankton, Productivity, Nutrient, CO2, O2

Fishery Models Small and Large Pelagics

satellite imagery

e.g. GHRSST, SSChl, AVISO SLA

ocean resourcese.g. CALCOFI,

SWFSC

circulation modelse.g. ECCO, S.C. ROMS

ocean monitoring e.g. Buoys, Scripps

Pier, SPOT, SCCWRP

Time Series Information

UtilityTest models Explore Linkages Track Climatic Drivers Identify Anomalies

ENSO, PDO, EMI, NPGO

The hypoxic layer also shapes the distribution of the purse seine catch for each of the 3 species. Here we see that average yellowfin catch/month fished is largest in waters where the hypoxic layer is most intense. The dots are color coded catch with warmest colors indicating larger catch. The lowest concentrations of O2 at 150 m is dark blue and the highest are dark red.

PHAM screen of habitat analysis interface, map of calculated spawning sites, and graphical results of analysis

Coupled to ENSO

Coupled to Modoki Coupled to PDO