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 This material is provided for information purposes only—any use of unpublished material beyond the November PR meeting must be approved by the originating scientist.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
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
[email protected] 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.