U.S. GLOBECNortheast Pacific Program

Program OverviewSynthesis Goals

StatusFuture

This PPT is used to briefly describe the synthesis research activities of each of the funded NEP synthesis projects (for the November 2006 Pan-Regional Synthesis Meeting).

It was compiled by Hal Batchelder and Nick Bond from materials provided by the SIs at various meetings. This material is provided for information purposes only—any use of unpublished material beyond the November PR meeting must be approved by the originating scientist. If you need assistance in identifying whom to contact regarding use of materials here, please email Hal Batchelder at

hbatchelder@coas.oregonstate.edu

NE PACIFIC GLOBEC - CORE HYPOTHESES

I. Production regimes in the coastal Gulf of Alaska and California Current Systems co-vary, and are coupled through atmospheric and ocean forcing.

II. Spatial and temporal variability in mesoscale circulation constitutes the dominant physical forcing on zooplankton biomass, production, distribution, species interactions and retention and loss in coastal regions.

III. Ocean survival of salmon is primarily determined by survival of the juveniles in coastal regions, and is affected by interannual and interdecadal changes in physical forcing and by changes in ecosystem food web dynamics.

Coho salmon, Onchorhynchus kisutch, chosen as study species since populations (catch) span and vary inversely in CGOA and CCS, and US GLOBEC and other programs sample in both systems over multiple years.

Redrawn from W

are and McFarlane

(1999)

Hobday and Boehlert (2001)

Spawning

Eggs

OceanJuveniles

Maturing

Adults

SalmonLifecycle

ClimateOceanPhysics Nutrients

FoodSupply

Harvest

CompetitorsPredators

ExternalInfluence

Juveniles

Diseases/Parasites

Freshwater

Estuary

Coastal Shelf

RegionsOther Ocean

Areas

Salmon Life History

Courtesy of Ric Brodeur

UpwellingDownwelling

http://www.bom.gov.au/climate/current/soi2.shtml

Warm phase

Cool phase

Pacific Decadal Oscill. Anomaly Patterns

SST – colors

SLP – contours

Windstress - arrows

ENSO Scale VariabilityUpwelling Event (Intraseasonal) VariabilityPacific Decadal Oscillation Variability

U.S. GLOBEC Northeast Pacific ProgramData Sources

• Long-Term Observation Program• Stations• Along-track

• Process Cruises• Stations• Along-track

• Moorings• Time-series

• Drifters• Time-series

• Satellite• Time/Space Series

• CODAR (CCS only)• Time/Space Series

• Modeling• Idealized• Diagnostic Regional• Event driven mesoscale

• Retrospective Analysis

CCS Sampling Locations

CGOA Sampling Locations

GAK 4

GAK 9

GAK 13

GAK 1

Seward Line Nutrient Time Series

Cleare

Ocean Carrying Capacity – GLOBEC Trawl Survey Lines

August 2001

J F M JM SJ A OA N D

CGOA

J F M JM SJ A OA N D

Trawl SurveyTrawl SamplingProcessLTOP

CCS

NEP Field Work Timeline

2000 2002

2001 20031997-1999

NOPP COAST

Synthesis (2005-2009)

2006

2005

2004

BPA Trawling (1998-2006)

NEP EffortPhase Start #Proj #PI Activity

I Fall ‘97 14 49 Initial Activities

IIa Fall ’99 20 60 Field CCS

IIb Fall ‘00 14+1 45+3 Field CGOA

IIIa Fall ‘04 9 46 Synthesis

IIIb Fall ‘05 6+1 29+5 Synthesis

NEP Web Site – http://globec.coas.oregonstate.edu/

CCS Synthesis ProjectsA1 Effects of Meso- and Basin-Scale Variability on Zooplankton Populations in the CCS

using Data-Assimilative, Physical-Ecosystem Models - Haidvogel, Powell, Curchitser, Hermann, Allen, Egbert, Kurapov, Miller

A2 Large-scale Influences on Mesoscale Structure in the CCS, A Synthesis of Climate-forced Variability in Coastal Ecosystems - Schwing, Bograd, Mendelssohn, Palacios, Stegman, Strub, Thomas

A3 Changing Ocean Conditions in Northern California Current-Effects on Primary Production and Salmon - Huyer, Kosro, Smith, Wheeler

A4 Latitudinal variation of upwelling, retention, nutrient supply and freshwater effects in the California Current System - Kosro, Hickey, Ramp

A5 Coupled physical-biological dynamics in the Northern California Current System: A Synthesis of Seasonal and Interannual Mesoscale Variability and its Links to Regional Climate Change - Cowles, Barth, Letelier, Spitz, Zhou

A6 Synthesis of Euphausiid Population Dynamics, Production, Retention and Loss under Variable Climatic Conditions - Peterson, Batchelder

A7 Juvenile Salmon Habitat Utilization in the Northern California Current-Synthesis and Prediction - Casillas, Batchelder, Peterson, Brodeur, Jacobson, Wainwright, Rau, Pearcy, Fisher, Teel, Beckman

A8 Effects of climate variability on Calanus dormancy patterns and population dynamics within the California Current - Leising, Runge, Johnson

A9 Scale-dependent Dynamics of Top Trophic Predators and Prey: Toward Predicting Predator Response to Climate Change - Tynan, Ainley

B1 US GLOBEC Northeast Pacific Coordinating and Synthesis Office - Batchelder, Casillas

B2 A synthesis of climate-forced variability on mesoscale structure in the CGOA with direct comparisons to the CCS - Thomas, Schwing, Bograd, Mendelssohn, Strub

B3 Bottom-up control of lower-trophic variability: A synthesis of atmospheric, oceanic and ecosystem observations - Bond, Mordy, Napp, Stabeno

B4 Habitat effects on feeding, condition, growth and survival of juvenile pink salmon in the northern Gulf of Alaska - Haldorson, Adkinson

B5 Synthesis of biophysical observations at multiple trophic levels using spatially nested, data-assimilating models of the coastal Gulf of Alaska - Hermann, Stabeno, Hinckley, DiLorenzo, Rand, Moore, Powell

B6 Modeling the effects of spatial-temporal environmental variability on stage-specific growth and survival of pink salmon in the coastal Gulf of Alaska - Beauchamp, Armstrong, Myers, Cokelet, Moss

B7 Environmental influences on growth and survival of Southeast Alaska coho salmon in contrast with other Northeast Pacific regions - Botsford, Hastings, Bond, Batchelder, Wertheimer, Adkinson

B8 Links between climate and planktonic food webs – Dagg, Strom, Hopcroft, Whitledge, Coyle

CGOA Synthesis Projects

Schwing

Cowles/Huyer/Kosro

Tynan

Casillas

Peterson/Leising

Haidvogel

PHYSICSBIOLOGY

Large-Scale – Mesoscale

Moorings &Transport

Seasonal/InterannualMesoscale

Climate &Salmon

CoreModeling

TopPredators

SalmonHabitat

Euphausiids

Copepods

Thomas

Hermann

Batchelder

HaldorsonBond

Botsford/Beauchamp

Dagg

Large-scale Influences on Mesoscale Structure in the CCS

A Synthesis of Climate-forced Variability in Coastal Ecosystems

A synthesis of climate-forced variability on mesoscale structure in the CGOA with

direct comparisons to the CCS

Schwing, Bograd, Mendelssohn, Palacios, Stegmann (SWFSC/ERD);Thomas (U Maine); Strub (OSU)

Project Goals

• characterize and compare relationship between basin-scale climate processes and mesoscale physical-ecosystem processes in CCS and CGOA

• identify mechanisms by which basin-scale climate variability cascades down to local ecosystem scales

• contrast differing CGOA & CCS ecosystem responses to same climate signals

• develop indicators representing ecological influences of climate forcing

• develop and operate data bases and servers

Synthesis Questions

Q1. How did CCS/CGOA mesoscale fields evolve during Field Programs in association with large-scale climate variability?

• use correlative methods to characterize mesoscale variability and concurrent basin-scale conditions during Field Programs and extend these comparisons to a longer historical time period where possible.

Q2. What are the mechanisms by which large-scale climate forcing cascades to mesoscale variability in CCS/CGOA?

• build on correlational linkages between basin and mesoscale patterns of variability and identify possible mechanisms by which local ocean processes respond to climate variability.

Q3. How does climate forcing of the CCS and GOA compare?• quantify and compare the relative impact of basin-scale variability on the

CGOA and CCS.

West Coast Upwelling Delayed and Weak

• Onset of coastal upwelling typically in April-May; July 2005 in northern CC

• Stronger upwelling in 2006, but May hiatus• Stronger upwelling late in season, total seasonal

upwelling normal but delayed• Weaker upwelling in southern CC in 2005 & 2006• Delayed upwelling in 2005 & 2006 unusual but not

unprecedented• Timing of upwelling and other processes very

critical to many species’ reproductive success• Illustrates ecosystem sensitivity to possible future

climate extremes

Six “Pipes”Define geostrophic surface velocities in broad channels, using the altimeter SSH along long rows of crossovers, to eliminate the “noise” caused by eddies and Rossby waves.

Use tide gauges at the coast to define the SSH, to eliminate any coastal gap.

This defines a north and south branch of the N. Pacific Current and broad regions of the California Current and Alaska Current System

(Strub, unpublished)

Large changes in the transports in the NPC were seen during the El Nino and especially during 2001-2004, when there was anomalous eastward transports.

(Strub, unpublished)

Monthly Chlorophyll Monthly Ekman Transport

Anomalous chlorophyll in spring 2005: Monthly as a function of latitude – links to wind forcing

climatology

climatological variance

2005

2005 (anomalies)

From Thomas and Brickley (GRL, 2006)

Spring negative

Late-summer positive

Large-scale switch from – to +

Changing Ocean Conditions in the Northern California Current: Objectives

- relate changing in situ phys & chem ocean conditions during 97-03 to primary production;

- is interannual variability of phys & chem ocean conditions and primary production similar north and south of Cape Blanco?

- do 97-03 seasonal averages & interannual variability of ocean conditions differ from 61-71?

- relate present indices of ocean conditions to local in situ measures of the currents, water masses, nutrients, etc., & search for improved indices and measures.

A. Huyer, P. M. Kosro, R. L. Smith, P. A. WheelerCOAS, Oregon State University

Progress Report: Changing Ocean Conditions in the Northern California

CurrentOcean Climate Variations Epoch-to-Epoch

- average temperatures: winter & summer Year-to-Year - winter & summer T anomalies - water-mass changes (esp. in halocline) - ecosystem responseSpatial Differences: NH, CR - midsummer - late summer - spring

Specific Events - July 2002 Subduction Event

Huyer project

Coho Survival & Climate Indices, 1960-2003

TENOC LTOP Huyer project

Bottom-up Control of Lower-trophic Variability: A Synthesis of Atmospheric, Oceanic and Ecosystem Observations

Nick Bond, Cal Mordy, Jeff Napp, Phyllis Stabeno

Plan of Attack• Atmospheric Forcing• Local Properties vs. Climate Indices• Along-shore Transport, Cross-shelf Exchange and Mixing• Nutrient Budgets and New Production• Mechanisms Controlling Zooplankton

Bond project

Q ui ckTi me™ and aTI FF ( LZW) decompressorare needed to see thi s pi cture.

Win

ds

Fluo

r.N+ N

Velo

city

Salinity

Bond project

Time-Series Measurements

“Latitudinal Variation of upwelling, retention, nutrient supply and

freshwater effects in the California Current System”

M. Kosro, B. Hickey, R. Letelier, S. RampA. Mesoscale variability and its alongshore variation, 42-48N, from synthesis of moored (u,v,T,S,chl), HF surface currents, hydrography, and remote sensing.B. Relate physical variability to primary production, zooplankton distributions, and salmon year-class strength.Alongshore variability of upwelling, nutrients, eddies, etc.Interannual variabilityRelation to higher trophic levels (collaborative with other groups) Kosro project

Temperature and Salinity Near Bottom from WA to Southern OR

Kosro project

Pink Salmon: Modeling Environmental Effects on Growth & Survival

Dave Beauchamp & Alison CrossUW-USGS:Washington Cooperative Fisheries

& Wildlife Research UnitKate Myers, Jan Armstrong, Nancy Davis,

Trey WalkerUW School of Aquatic and Fisheries Sciences

Jamal Moss, NOAA-Auke Bay LabNed Cokelet, NOAA-PMEL

Lew Haldorson, Jennifer Boldt, Jack PiccoloUniversity of Alaska-Juneau

UNIVERSITY OF WASHINGTON

Scales can be used to estimate growth history

scale radius ~ fish lengthcirculus spacing ~ growth rate

Prince William Sound Pink Salmon-Survivors grow faster than“average” juveniles duringfirst summer Ocean growth

-Timing and magnitude of divergent growth betweenaverage and surviving Juveniles vary amongyears

-Size-at-age higher for higher survival years

2004-2005

Circulus

0 5 10 15 200

200

400

600

800

AFK AdultsCCH AdultsSGH AdultsWNH Adults

2003-2004

0

200

400

600

800

Pooled Adults

2002-2003

Scal

e R

adiu

s (

m)

0

200

400

600

800

OCC AdultsObserver Adults

2001-2002

0

200

400

600

800

1000

JuvenilesPooled Adults

S = 3%

S = 3%

S = 9%

S = 8%

Source-Alison Cross, UW High Seas Salmon Group,

Jamal Moss, Lew Haldorson

Ocean Growth and Size-Selective Mortality

GROWTH:Larger juveniles =Higher survival

DISTRIBUTION:Higher survival =Earlier, wider dispersalduring Aug-Sep

Wt (

g)

0102030405060

S=8-9%2002,2004

20032001S=3%

0.5

1.0

Die

t Pro

port

ion

by W

t

0.51.0

Jul Aug Sep0.0

0.5

1.0

CopepodLarvacean

HyperiidEuphausiidFish

Pteropod

Jul Aug Sep0.0

0.5

1.0

2001PWS PWS-ACC-TRANS

2002Hi Surv

PWS TRANS TRANS-dispersed

2003ACC-TRANSPWS-TRANSPWS

2004Hi Surv

Juvenilesdispersedbeyond sampling area

PWS TRANS

TRANS

Survival, Growth, Distribution, Diet & Feeding Rate

DIET:Diet highly variableamong months & Years.Non-CrustaceansImportant.

Avg summerFeeding rate:

85-100% of Cmax

65-85% Cmax

Critical Period

Feeding rate higherDuring High SurvivalYears—

Suggests higher preyavailability

Jamal Moss, Lew Haldorson, unpub.

Synthesis of Euphausiid Population Dynamics, Production,

Retention and Loss under Variable Climatic Conditions

William T. Peterson, NMFS, NWFSC, NewportHarold P. Batchelder, Oregon State University

Why euphausiids?• Everyone eats them• Numbers and rates highly variable in time and space• Therefore, variations in euphausiid abundance may explain

variations in species dependent upon them (e.g., salmon, hake, herring, marine birds)

• Euphausiids now incorporated into the Coastal Pelagics Fisheries Management Plan; need to collect data on an going basis, on rates & biomass to properly manage them.

• Will develop indices that track interannual variations in euphausiid biomass and productivity

Peterson project

1. Synthesis of target zooplankton abundance and distributiona) Seasonal and Interannual variability of nutrients, chlorophyll and

ZPb) Variability of Euphausiid spawning seasonc) Spatial variations in euphausiid distribution and abundance

2. Processes that affect abundance and distributiona) Stage structure and mortality ratesb) Egg productionc) Development time and molting ratesd) Growth and production

3. Physical-biological modelinga) Population dynamics using IBM’sb) Cross-shelf zonation, retention and loss

4. Future Expansion -- PIRE: The Year of the Euphausiid—Comparative Life History of North Pacific Krill in Shelf and Slope Waters Around the Pacific Rim (proposed, incl. Aust., Kor, Japan, China, Canada, Mexico)

Research Activities

Peterson project

Effects of climate variability on Calanus dormancy patterns and population

dynamics within the California CurrentAndrew W. LeisingNOAA-SWFSC-ERD

1352 Lighthouse Ave.Pacific Grove, CA 93950

Andrew.leising@noaa.govJeffrey Runge, and Catherine Johnson

University of New HampshireOcean Process Analysis Laboratory

Morse Hall39 College Road

Durham, NH 03824

With a lot of help from: Bill Peterson, NOAA; Dave Mackas, IOS; Bruce Frost, UW

Leising project

Project Goals:• Determine the most likely factors (biological and

physical) that control the dormancy response of Calanus pacificus and Calanus marshallae– These two copepod species often dominate the biomass of

macrozooplankton, and are warm/cold indicators– Surprisingly, dormancy triggers remain unknown

• Use this information to more accurately model the population response and sensitivity of these species to climate change

• Produce a coastwide index of relative population abundance and production of these two species

Leising project

Appearance/Dormancy Timing in Relation to Upwelling

Upwelling Gradient (ave of difference between ±5, 10 and 15 days) on the date of Calanus marshallae and C. pacificus entry

and exit from dormancy at NH5

-8

-6

-4

-2

0

2

4

6

8

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Date

Upw

ellin

g G

radi

ent

C. marshallae - ExitC. marshallae - EntranceC. pacificus - ExitC. pacificus - Entrance

C. marshallae almost always wakes up from dormancy during periods of increasing upwelling, and enters dormancy during periods of decreasing upwelling

Increasing Upwelling

Decreasing Upwelling

Leising project

This work directly addresses NE PACIFIC GLOBEC - CORE HYPOTHESES III.

Ocean survival of salmon is primarily determined by survival of the juveniles in coastal regions, and is affected by interannual and interdecadal changes in physical forcing and by changes in ecosystem food web dynamics.

Habitat effects on feeding, condition, growth and survival of

juvenile pink salmon in the northern Gulf of Alaska

P.I.s: Lew Haldorson and Milo Adkison

School of Fisheries and Ocean SciencesUniversity of Alaska Fairbanks

Haldorson project

Synthesis Research:

I. Compile a comprehensive data set on pink salmon - 4 projectsA. LTOP and Process Studies - U. of AlaskaB. Ocean Carrying Capacity (OCC) - NFMS, Auke Bay Lab.C. PWS Juvenile Pink Salmon Monitoring - ADF&G, CordovaD. SE Alaska Monitoring Project - NMFS, Auke Bay Lab.

II. Examine salmon response variable by year, season, habitatA. Short term - Feeding Intensity (SCI) B. Medium term - Condition (L/W residuals, energy content)C. Long term - Growth (Hatchery fish, exponential, bioenergetic)D. Examine response variable in upper size-based quantiles

III. Identify characteristics of habitats associated with positive or negative performance of salmon response variables.

A. TemperatureB. StratificationC. Zooplankton

1. Direct sampling - process, LTOP, OCC2. Salmon diets

Haldorson project

Juvenile Salmon Habitat Utilization in the Northern California Current –

Synthesis and PredictionPI’s – Casillas, Batchelder, Peterson, Brodeur,

Jacobson

AI’s – Wainwright, Rau, Pearcy, Fisher, Teel, Beckman

Principle Hypotheses/Objectives• Habitat for juvenile salmon can be characterized by suite of physical

and biological variables (e.g. temperature, salinity, stratification, prey and predator distribution & abundance, etc)

• Fine-scale habitat characteristics can be related to meso- to regional-scale ocean features that can be used to construct a ‘salmon ocean habitat index’ to provide near-term prediction of salmon success

Casillas project

Example: Logistic RegressionPredictor

Chinook Coho0.0 1.0 1.1 1.0 1.1

Chlorophyll - 0.13 -0.14 -0.19 -0.095 -0.36Depth 0.0044 0.0054 0.0234 0.0046 0.012Temperature - 0.22 -0.31

Analysis on Presence/Absence; Only statistically significant coefficients shown.

Presence/Absence and environmental data from June 1998-2004 cruises used to specify model; Data from June 2005 held in reserve for testing.

Subyearling Chinook: Absence accuracy: 100% Presence accuracy: 17% Overall: 87%

Yearling Chinook: Absence accuracy: 80% Presence accuracy: 75% Overall: 79%

Subadult Chinook:Absence accuracy: 79% Presence accuracy: N/A* Overall: 79%

Yearling cohoAbsence accuracy: 4% Presence accuracy: 100% Overall: 33%**

Subadult cohoAbsence accuracy: 88% Presence accuracy: 100% Overall: 89%

Bi, R

uppe

l, an

d Pe

ters

on,

Subm

itted

.

Casillas project

What are we doing for management?

• Our approach: continue long-term time series. THIS IS CRITICAL!• Need indices based on biological variables, measured on cruises,

at the same times-places as the stocks being managed• Developed indices that (so far) predict returns of coho salmon one

year in advance; they work because survival is set during the first summer at sea. Supported chiefly by the FATE program (Fisheries and the Environment). – Northern copepod index– Spring Transition Index

• Logerwell • Peterson (biological spring transition)

– Salmon catches on our Bonneville-funded juvenile salmonid surveys

• Coho catches in September predict returns following year• Spring Chinook catches in June predict returns 2-3 years

later• Will develop indices based on euphausiids—using easily measured

variables (= egg abundances, ratio of eggs/larvae; adult abundances). Casillas project

Juvenile migration year Forecast of adult returns

2000 2004 2005 2006

(to June) Coho

2006 Chinook

2007

Large-scale ocean and atmospheric indicators

PDO ■ ■ ■ ■ ● ●

MEI ■ ■ ■ ■ ● ●

Local and regional physical indicators

Sea surface temperature ■ ■ ■ ■ ● ●

Coastal upwelling ■ ■ ■ ■ ● ●

Physical spring transition ■ ■ ■ ■ ● ●

Deep water temp. & salinity ■ ■ ■ ■

Local biological indicators

Copepod biodiversity ■ ■ ■ ? ● ●

Northern copepod anomalies ■ ■ ■ ? ● ●

Biological spring transition ■ ■ ■ ■ ● ●

Spring Chinook--June ■ ■ ■ ■ ● ●

Coho--September ■ ■ ■ ? ● ●

■ good conditions for salmon marine survival ● good returns expected ■ intermediate conditions for salmon marine survival

Key ■ poor conditions for salmon marine survival ● poor returns expected

Juvenile migration year Forecast of adult returns

2000 2004 2005 2006

(to June) Coho

2006 Chinook

2007

Large-scale ocean and atmospheric indicators

PDO ■ ■ ■ ■ ● ●

MEI ■ ■ ■ ■ ● ●

Local and regional physical indicators

Sea surface temperature ■ ■ ■ ■ ● ●

Coastal upwelling ■ ■ ■ ■ ● ●

Physical spring transition ■ ■ ■ ■ ● ●

Deep water temp. & salinity ■ ■ ■ ■

Local biological indicators

Copepod biodiversity ■ ■ ■ ? ● ●

Northern copepod anomalies ■ ■ ■ ? ● ●

Biological spring transition ■ ■ ■ ■ ● ●

Spring Chinook--June ■ ■ ■ ■ ● ●

Coho--September ■ ■ ■ ? ● ●

Juvenile migration year Forecast of adult returns

2000 2004 2005 2006

(to June) Coho

2006 Chinook

2007

Large-scale ocean and atmospheric indicators

PDO ■ ■ ■ ■ ● ●

MEI ■ ■ ■ ■ ● ●

Local and regional physical indicators

Sea surface temperature ■ ■ ■ ■ ● ●

Coastal upwelling ■ ■ ■ ■ ● ●

Physical spring transition ■ ■ ■ ■ ● ●

Deep water temp. & salinity ■ ■ ■ ■

Local biological indicators

Copepod biodiversity ■ ■ ■ ? ● ●

Northern copepod anomalies ■ ■ ■ ? ● ●

Biological spring transition ■ ■ ■ ■ ● ●

Spring Chinook--June ■ ■ ■ ■ ● ●

Coho--September ■ ■ ■ ? ● ●

■ good conditions for salmon marine survival ● good returns expected ■ intermediate conditions for salmon marine survival

Key ■ poor conditions for salmon marine survival ● poor returns expected

http://www.nwfsc.noaa.gov/research/divisions/fed/climatechange.cfm Casillas project

Environmental influences on growth and survival of Southeast Alaska coho salmon

in contrast with other Northeast Pacific regions

Milo Adkison, U.Alaska, JuneauHal Batchelder, Oregon State U.Nick Bond, NOAA, U.W.Loo Botsford, U.C., DavisAlan Hastings, U.C., DavisAlex Wertheimer, N.M.F.S. Auke BayUnfunded Collaborator: Marc Trudel (DFO-Canada)

Focus on coho salmon, Oncorhynchus kisutch, which does covary out of phase, in CGOA and CCS. Compare on regional (100s of km) to basin scales.

Botsford project

Hypotheses H1. Alaska coho salmon survival depends positively on conditions favoring biological productivity.[RETRO, CWT, LOCIND]H2. Alaska coho salmon survival depends on variability in mortality rate due to varying predator buffering by other salmon species.[RETRO, CWT]H3. Survival of coho salmon is determined by availability and spatial arrangement of high quality habitat during early ocean life. [FIELD, IBM]H4. A single model of early growth and survival can explain coho salmon population response to the environment throughout the NEP from the CCS through the CGOA. [CWT, RETRO]Project Components FIELD – coho occurrence, abundance, growth vs. physical/biologicalIBM – Growth/survival in space/time; including movement/habitat selectionRETRO – Expand Auke Creek analysis spatially to examine predator/competitor effectsLOCIND – Develop indices of local physical state, e.g., wind stress curl, MLDCWT – Reanalysis of CWT data; fit CGOA and CCS CWT to early life history model with variable grwoth, survival on regional scaleBotsford project

NEP

U.S. GLOBEC Nested Model Domains

Botsford project

Coho SalmonRegion

How well do the ROMS NEP physics match our perception and data from the real NEP ocean?

1) Compare SSH from the model with altimetry1) Large scale climatology2) Seasonality

2) Compare SST3) Compare Subsurface Temperatures4) California Undercurrent Strength/Posn/Variability5) Interannual Variability in Strength of the Alaskan

Gyre Circulation and Bifurcation of the North Pacific Current (particle tracking)

Botsford project

Climatological Dynamic Height from Strub and

James (2002)

1958-2004 Climatologial SSH from Model

Batchelder unpub.

The 1976-77 Regime Shift SST Patterns

From Schwing et al.

(2002)

Note: Left panel is May only; Right is Annual

1961-75

1978-96

-PDO

+PDO

Batchelder unpub.

2002

2000

1997

1998

19999-11 July

2002

7-8 July2000

Northward Velocity – Newport Line - July

Well defined core of CUC in 1997, 1998, 2000;close to slope

Weaker, more diffuse CUC in 1999 & 2002;not adjacent to slope Batchelder unpub.

Coupled Physical-Biological Dynamics in the Northern CCS: A Mesoscale Synthesis of Seasonal

and Interannual Mesoscale Variability

Tim Cowles OSUJack Barth OSU

Ricardo Letelier OSUYvette Spitz OSU

Meng Zhou U Mass

Steve Pierce, Chris Wingard, Amanda Ashe, Julie Keister, Di Wu, Amanda Whitmire

Cowles project

We have two primary objectivesdetermine the contribution of variability in mesoscale physical forcing and ocean dynamics to the variability in ecosystem dynamics, as expressed by phytoplankton and zooplankton abundance, spatial pattern, size distribution and indices of production;

extend this mesoscale understanding across a larger spatial domain and across longer time scales through the use of coupled models, satellite remote sensing observations, and collaboration with other GLOBEC synthesis teams.

These overall objectives will be addressed through a set of linked, interdisciplinary analyses of Spatial Pattern, Ecosystem Function, and Mesoscale to Regional Linkages

Cowles project

Links between climate and planktonic food webs

(Funded in September 2006)

Mike Dagg (LUMCON)Suzanne Strom (Western Washington Univ)Ken Coyle (UAF)Russ Hopcroft (UAF)Terry Whitledge (UAF)

Dagg Project

Synthesis Goals (1)

(1) Describe planktonic food web:

- Controls on amount and type of primary production- Controls on fraction of pp to higher tropic levels, esp Neocalanus, euphausiids and mucous net feeders- Develop statistical relationships from field data for

refining our 1-D ecosystem model

Initially this will be done with data from the 3 process cruises in 2001 and 2 process cruises in 2003 (our most data-intense years)

Dagg Project

Synthesis Goals (2)

(2) Expand to conditions during LTOP years (1998-2004), then to multi-decadal time scale:- Describe ecosystem throughout LTOP years- Determine best indicators of cross shelf zonation, - Determine most important factors for spring bloom:

timing and magnitudenutrient patterns (incl Fe)phytoplankton community

- Determine factors affecting microzooplankton and mesozooplankton abundance and distribution

Dagg Project

Synthesis Goals (3)

(3) Combine environmental descriptions for each year (2) with foodweb processes (1) to develop a general understanding of ecosystem processes and controls, including consequences of system structure for Neocalanus, euphausiids and juvenile pink salmon, incl:

- Add mucous net feeders to NPZ model- Compare NPZ model parameterizations with empirical

relationships- Run 1-D model with different physical conditions- Compare modeled PP with empirical- Link modeled mucous-net feeders to pink salmon.

Dagg Project

Scale-dependent Dynamics of Top Trophic Predators and Prey: Toward Predicting Predator Response to Climate Change

C. Tynan and D. Ainley

1) predictive biophysical model of factors affecting top–predator distribution, based on 2000 data and tested using 2002 data; 2) foraging model; 3) prey depletion model; 4) model of energy and carbon flow through top-predators.

ChlCopBBirdB

T5mCohoJChinJHumpys

Batchelder et al. (2002)

GLOBEC NEP Core Modeling Projects

Effects of Meso- and Basin-Scale Variability on Zooplankton Populations in the CCS using Data-

Assimilative, Physical-Ecosystem ModelsHaidvogel, Powell, Curchitser, Hermann, Allen, Egbert, Kurapov, Miller

Synthesis of biophysical observations at multiple trophic levels using spatially nested, data-assimilating

models of the coastal Gulf of AlaskaHermann, Stabeno, Hinckley, DiLorenzo, Rand, Moore, Powell

Core Model Projects

Spatially nested biophysical modelsSpatially nested biophysical modelsNCEP/MM5 -> ROMS/NPZ -> IBMNCEP/MM5 -> ROMS/NPZ -> IBM

Core Model Projects

Selected Research Components

•Physical modeling and DA (HF radar) for the coastal CCS (focus on 2000 and 2002)•Comparison of NCOM model to GLOBEC CCS data (nesting evaluation)•4DVAR DA using IROMS•40+ year runs of NPac and NEP domains; shorter runs of CGOA and CCS grids•Use CCSM (Community Climate System Model) forcing to downscale climate projections to regional domains•NEP-wide ecosystem model (needed by many other projects)•Model/Data comparisons•Sensitivity Studies

Core Model Projects

ApproachApproachA 3 km coastal model based on the ROMS is being nested in the Navy Coastal Ocean Model–California Current System (NCOM–CCS) regional model.

NCOM-CCS is a 9 km data assimilating model which is nested in a global 1/8o data assimilating model.

The ROMS model domain includes the Coastal Transition Zone (CTZ) and the region of the GLOBEC field experiments.

Oregon CTZ(ROMS)

California Current System (NCOM-CCS)

Global(NCOM )

ObjectivesObjectives1.Obtain high quality model estimates for the physical fields in the region of the GLOBEC field experiments off the Oregon coast during the 2000 and 2002 summer months of May–August.

2.Determine the important physical dynamics in the region of the GLOBEC field experiment through synthesis of model results and observational data (in collaboration with other GLOBEC PIs).

Core Model Projects

Newport Hydrography Line 2002-07-10 (Huyer)

Oregon CTZ model was initialized on April 1st, 2002 and simulated the circulation to Aug 31st (153 days).

Model-Data comparisons and dynamical analyses are in progress.

Evaluate Oregon CTZ modelEvaluate Oregon CTZ model

Data AssimilationData AssimilationAssimilation of Assimilation of Sea Surface HeightSea Surface Height from satellite altimeter from satellite altimeter measurements and measurements and Surface CurrentsSurface Currents from from long range HF radarlong range HF radar measurements is planned. measurements is planned.

Core Model Projects

Cross-shelf total phyt (x-z plot) Mar-Jun ave: w/ Felim or PS -> lower total phyt offshore

Model w/ Felim

Model w/o Felim

Model w/ ONLY PL

Model w/ PL + PS

NNPZDFe

NNPPZZDNNPZD

NNPPZZDFe

dist offshorez

Shelf break

Core Model Projects

Recent/Future NEP Activities

•CGOA Gap-filling Opportunity•Goal: “to integrate estimates of in situ zooplankton

abundances, their condition, and reproductive rates” in the CGOA

•Must be integrated with models and make connections to juvenile salmon

•Focus on ZP community structure, composition•1 project funded: NEP Phase IIIb-CGOA: Links between

climate and planktonic food webs“, PI - Michael Dagg; Co-PI’s: Russell Hopcroft, University of Alaska (includes Terry Whitledge and Ken Coyle) & Suzanne Strom, Western Washington University

•Next NEP SI meeting•8-10 January 2007 (Seattle)

•Next NEP Special Journal Issue – 15 April 2007 Target Date for MS submissions

Future NEP Activities(continued)

• Venues for Presentations of NEP Results•Near-past

•ASLO Summer 2006 (Victoria, BC, 5-9 June)•Time Series of the NEP (Victoria, CAN, 5-8 July 2006)•Invited talks by Wheeler, Weingartner, Schwing

•EPOC2006 (Timberline Lodge, Portland, 27-30 Sep)•2. Integrated Regional Oceanography using in-situ and remote observations and models•4. Multidisciplinary Modeling

•PICES 2006 (Yokohama, JPN, 16-20 October)•Future

•AGU Fall Mtg (SF, 11-15 Dec)•ASLO Aq. Sci. Mtg. (Santa Fe, 4-9 Feb 2007)•4th Intl. ZP Prod Symp. (Hiroshima, JPN, 28 May-1 June 2007) •2007 PICES Mtg (Victoria, BC, October)•2008 Ocean Sci. Mtg (Orlando, 2-7 Mar) •Effects of Climate Change on the World’s Oceans (Gijon,

Spain, May 2008)

Future NEP Activities(continued)

• Future Research Activities in the Northeast Pacific•PICES FUTURE (Forecasting and Understanding

Trends, Uncertainty and Responses of the North Pacific Ecosystem)

•New integrative science program of PICES (North Pacific Marine Science Organization); to eventually replace the Climate Change and Carrying Capacity (CCCC) Integrative Science Program

•Timeline is to have the FUTURE Science Plan completed by October 2007; CCCC ramp down; FUTURE ramp up in 2008.

•NOAA Climate and California Current Ecosystems•Scoping workshop held 14-16 Nov 2006 in La Jolla, CA•Overall goals are fairly similar to GLOBEC NEP goals:

Understand climate driven changes to enable societal response

•GLOBEC participants on organizing committee: Barth, Batchelder, Peterson, Strub

•Many other GLOBEC NEP SI’s attended (ca. 50 participants overall)

•Science Plan to be developed by March 2007 for NOAA Fisheries (Murawski) and NOAA Climate (Koblinsky) programs.