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NEMURO.FISH: A NPZ-Fish Bioenergetics/Population
Dynamics Model for Pacific Saury and Herring
by
Bernard A. MegreyFrancisco E. Werner
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Process:
10 workshops over 7 years
strong international collaboration
several funding sources
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Acknowledgments
We are grateful to our sources of funding: • North Pacific Marine Science Organization (PICES)• City of Nemuro Japan• Heiwa-Nakajima Foundation • Japan International Science and Technology
Exchange Center• Japan Fisheries Research Agency • Asia-Pacific Network• GLOBEC
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Primary CollaboratorsKenneth Rose, Louisiana State University, USA
Rob Klumb, Great Plains Fish and Wildlife Management Assistance Office, USA
Douglas Hay, Pacific Biological Station, Canada
Dan Ware, Nanaimo, BC, Canada
Shin-ichi Ito, Tohoku National Fisheries Research Institute, Miyagi, Japan
Dave Eslinger, NOAA Coastal Services Centre, USA
Yasuhiro Yamanaka, Graduate School of Environmental Earth Science, Hokkaido, Japan
Michio J. Kishi, Graduate School of Fisheries Sciences, Hokkaido, Japan
Maki Aita-Noguchi & Lan Smith, Frontier Research Center for Global Change, Yokohama, Japan
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Outline
• Motivation: Charge to the PICES CCCC Model Task Team
• Background on N. Pacific Ocean Dynamics• Modeling approach – NEMURO LTL &
HTL• Example applications, model calibration
and uncertainty analysis• Future work
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PICES Climate Change & Carrying Capacity (CCCC) Program
• Ultimate Goal……
“to forecast the consequences of climate variability on the ecosystems of the subarctic North Pacific”
• Acknowledges that long-period changes occur in the PICES region and assumes that changes in zooplankton biomass, productivity and species composition will lead to changes in the carrying capacity of the subarctic Pacific
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Regimes and the Pacific Regimes and the Pacific Decadal OscillationDecadal Oscillation
• an El Niño-like pattern of climate variability
• 20 to 30 year periods of persistence in North American and Pacific Basin climate
• warm extremes prevailed from 1925-46, and again from 1977-98; a prolonged cold era spanned 1947-76
19981925 1947 1977
Mantua, Hare, Zhang, Wallace and Francis, BAMS 1997Mantua, Hare, Zhang, Wallace and Francis, BAMS 1997
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(Rodinov and Overland, 2005))
“Regimes” evident in HTL fish stocks
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CCCC Model Task Team Recommendations
• Since comparison of 12 regional ecosystems is at the core of the CCCC, a prototype LTL model should be adopted to examine climate impacts
• The prototype model should have a generalized structure that can correctly represent the characteristics of each system
• Structural and formulation differences should be minimized
• Prototype model will facilitate development of comparison protocols
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Lower Trophic Level Modeling
OBJECTIVE:
Used as a tool to test the hypothesis that physical forcing factors regulate primary production and that the effect is apparent in zooplankton standing stock and then transferred to variation in higher trophic levels
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NEMURO LTL• 1st workshop held in Nemuro Japan 2000• Participants – physical oceanographers, biological
oceanographers, fisheries oceanographers, fisheries biologists, oceanographic modelers, fisheries population dynamists, applied mathematicians
• A consensus conceptual model was designed representing the minimum trophic structure and biological relationships between and among all the marine ecosystem components thought to be essential in describing ecosystem dynamics in the North Pacific
• NEMURO-A compromise between generality and complexity
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NEMURO
North Pacific Ecosystem Model
for Understanding Regional
Oceanography
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NEMURO
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• 1D point model; 2 layers
• 2 phytoplankton groups; 3 zooplankton groups
• Fluxes calculated for nitrogen and silicate
• Sinking of POM and Opal
• Primary Production limited by nutrients (NO3 and NH4 via Michaelis-Menten), temperature (Q10), and light (self shading)
• Grazing via Ivlev function and temperature influence (Q10)
• Nutrient exchange between the deep and mixed layers
• Forced by annual signals of light, SST and MLD
• NO IRON
NEMURO Features
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Links to the Physics and Climate• All biological rates mediated by sea temperature• Ontogenetic large zoop vertical migration (where
appropriate based on local conditions of T and light)• Location specific physical variables
– Seasonal light– Mixed layer depth– Nutrient flux from bottom layers– Air temperature for fish recruitment function– NPPI index for fish recruitment function– Water temperature for fish recruitment function– Prey fields (for static coupling)
• Basin-scale climatology
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Parameter sets were assembled for three areas of the North Pacific Ocean
Apply the same model structure and climate scenarios to three different ecosystems – any observed differences in dynamic response will be due to locale characteristics
and forcing
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Example of model results that include state variable dynamics (top panel) as well as time dependent dynamics of the diagnostic variables (bottom panel).
Phyto P/B ratios
Zoop P/B ratios
Zoop C/B ratios
Ecotrophic Efficiency
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Linking the lower trophic level model to higher trophic levels
Development of NEMURO.FISH
NEMURO.For Including Saury and
Herring
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Rationale• Increasing appreciation of climate effects on fish
growth, recruitment, and population dynamics• Observed “regimes” of varying productivity in
exploited fish stocks• Recognition that effective management requires
understanding and quantitative tools (models) for predicting climate effects on fish populations
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Herring in the North Pacific• Extensive long-term data on size at age for
multiple locations around the Pacific Rim• All life stages eat zooplankton• Life history and biology well known• Goals:
– (1) better understand intra- and inter-population
variation in herring growth and survival– (2) relate results to climate change and carrying
capacity
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NEMURO.FISH
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Fish Bioenergetics Governing Equation
)(TfWaC Cb
CMAXC
( ) z
f
CALdWC R S F E H W
dt CAL
1
1
j ijMAX
ijj n
k ik
ikk
PD vC
KC
PD v
K=
××
=×
+å
W = weight (g ww)C = consumption (1/day)
R = respirationS = SDA
F = egestionE = excretion
H = reproductionCalz – caloric value of prey
Calf – caloric value of herring
PD = prey density (1=ZS; 2=ZL; 3=ZP)V = vulnerability
K = feeding efficiency
n
jjr CC
1
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Respiration
TcbA
AA eWaU
VTfWaR Rb
RR )(
TcR
ReTf )( UdReV
Process formulation different for age 0, 1 2+
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Herring Population Dynamics
• Age structured (11 age classes)
• Stage structured (feeding and biological process description specific to ontogenetic stage, age 0, age 1, age 2+)
• Realistic reproductive biology (closed life cycle)– Environment-dependent function to generate recruits
– Age-specific maturity schedules
– Age-specific fecundity schedules
• Seasonal energy density of herring
• Age-specific fishing removals and natural mortality
iiii NMF
dt
dN
RNMFdt
dN
)(
)( 11111
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YOY Recruitment
SSB - spawning stock biomass (g wet weight/m3)
NPPI - North Pacific Pressure Index
AIR - Air temperature
SST - Sea surface temperature
(Williams and Quinn. 2000. Fish Oceanogr 9: 300-315)
3.24 0.032 0.44 - 0.26 - 0.36-3•10 • t t t tSSB NPPI AIR SSTtYOY SSB e
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Benefits of Using Environment-Dependent SR Model
• Produces observed autocorrelation in recruitment time series
• Reproduces observed recruitment variation on annual and multi-decadal time scales
• Closed life cycle allows the stock to become self-sustaining after initialization
• More realistic compared to constant recruitment assumptions
• Important feature for regime shift and climate change scenario hypotheses as it allows direct environmental effects on recruitment influencing top down control
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Computations
• Differential equations solved with 4th order Runge-Kutta numerical solution technique
• dt=1 hour
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Saury
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Three Main Age Groups
• Biological process do not simply scale with size/age. Sometimes there are different processes unique to a life stage…..
• Age 0 (age of a recruit)
• Age 1 (0-12 month)
• Age 2+ (24 months and older) ~180g ww
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30
35
40
45
130 135 140 145 150 155 160 165
Kuroshio Extension
Oyashio Front
spawning groundin winter
spawning groundin spring & autumn
Mixed water region
Migration
Migration
Feeding groundin summer
Fishing groundin autumn
Life History of Pacific Saury with Oceanographic Features
Modified from Watanabe et al. (1989)
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Table 2. Life stages of Pacific saury in the saruy bioenergetics modelStage region larvae Kuroshiojuvenile & young mixed regionsmall Oyashioadult mixed regionadult matured Kuroshioadult mixed regionadult Oyashioadult mixed regionadult matured Kuroshio
3-box version
OyashioMixed Waterregion
Kuroshio
9 life stages
Ito et al. (2004)
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30
35
40
45
130 135 140 145 150 155 160 165
Interannual Forcing (SST)
Oyashio
Mixed Water Region
Kuroshio
JMA SST product (1deg x 1deg, 10days)1950 - 2002
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Two Example Applications• Dynamic mode
– fish consumption removed from zooplankton, excretion adds NH4, and egestion adds PON
– quasi-West Vancouver Island (WVCI)
• Uncoupled mode– NEMURO imbedded a 3-D circulation model (Aita-
Noguchi et al., 2004)– predicted temperature and zooplankton used to drive
herring model
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Latitudinal Variation in Herring Growth
An Uncoupled Example
• Used predictions of temperature and zooplankton density from NEMURO imbedded in a 3-D circulation model (Aita-Noguchi et al. 2004).
• Data available from 1948-2002
• Look at regional response in herring growth. Do regime shifts cascade up the food web?
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3D Model BackgroundPhysical model: CCSR Ocean Component Model (COCO) 3.4 (developed at Center for Climate System Research,
University of Tokyo)
Biological model: NEMURO LTL
Configuration (same as Aita et al., 2003) Horizontal resolution : 1 degree * 1degree (360x180). Vertical resolution : 54 levels from the surface to the bottom
(5000m). 5m for all layers within upper 100m. Mixed layer processes: Noh and Kim turbulent closure scheme.
Boundary conditions (daily surface forcing) NCEP 6-hourly dataset from 1948 to 2002 : Sea surface temperature : Fresh water flux : Surface wind stress : Solar radiation Nitrate and Silicate concentrations: WOA 1998
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NEMURO.FISH applied to four areas of the North Pacific
Prince William Sound
Hokkaido-Sakhalin
West Coast Vancouver
Island
Oregon Coast
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Year
1950 1960 1970 1980 1990 2000
Wat
er T
empe
ratu
re (
oC
)
0
2
4
6
8
10
12
14
Bering SeaPrince William SoundWest Vancouver IslandOregon Coast
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Bering Sea
0.0
0.1
0.2
0.3
0.4
Prince William Sound
Co
nce
ntr
atio
n (
g w
w/m
3)
Small zooplanktonLarge zooplanktonPredatory zooplankton
West Vancouver Island
Oregon Coast
Year1950 1960 1970 1980 1990 2000
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Dynamic Example
• Calibrated NEMURO to field data on phytoplankton and zooplankton for WVCI– monthly concentrations– automated calibration with PEST software
• Used historical environmental indices for recruitment (Williams and Quinn, 2000)
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Model Calibration• NEMURO and NEMURO.FISH are complex models with
many parameters (190)
• Usually ad-hoc methods are used to calibrate ecological models where one “manually adjusts favorite parameters until a subjective good fit of predicted and observed values”
• We want to apply NEMURO to multiple locations throughout the open ocean and also to coastal environments for coupling to herring, saury and other models.
• Need an objective way to calibrate the model
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PEST Automatic Calibration Software
• Need only PEST setup files and an executable model
• Variation of Gauss-Marquardt-Levenberg algorithm
• Minimize the weighted sum of squared deviations between predicted and observed values
• Relationship between model and parameters approximated by a Taylor series expansion, involves computing the Jacobian and Hessian matrices
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PEST
NEMUROPEST
Input Parameters
Output Variables
Observations
Setup Files
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Calibration Data
• West Vancouver Island: 1991-2001• California Current
– Wainwright et al.– Wang
• Created a dataset of monthly values of nitrate, total phytoplankton, small zooplankton, large zooplankton, and predatory zooplankton
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(b) Small Zooplankton
0.0
0.1
0.2
0.3(a) Total Phytoplankton
0.0
2.5
5.0
7.5
WVCICalifornia Current
(c) Large Zooplankton
Co
nce
ntr
atio
n (
mic
ro-m
ole
s N
/Lite
r)
0.0
0.2
0.4
0.6(d) Predatory Zooplankton
0.0
0.1
0.2
0.3
Month
0.0
0.3
0.6
0.9
Month
0
10
20
30(e) Total Zooplankton >200 microns (ZL+ZP)
(f) Nitrate
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(d) Small Zooplankton
0.0
0.1
0.2
0.3
(a) Total Phytoplankton
0.0
2.5
5.0
7.5
Field dataAd-hocPEST
(e) Large Zooplankton
0.0
0.2
0.4
0.6(f) Predatory Zooplankton
0.0
0.1
0.2
0.3
(b) Small Phytoplankton
0.0
1.5
3.0
(c) Large Phytoplankton
Co
nce
ntr
atio
n (
mic
ro-m
ole
s N
/Lite
r)
0.0
1.5
3.0
(g) Total Zooplankton >200 microns (ZL+ZP)
Month
0.0
0.3
0.6
0.9 (h) Nitrate
Month
0
10
20
30
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12 14 16 18 20 22 24 260
2
4
6
Simulated Year
Tot
al B
iom
ass
(g w
w/m
2 )
12 14 16 18 20 22 24 260
100
200
300
Simulated Year
Wei
ght
(g w
w)
1
23
4
5
6
7
89
10
0 20 40 60 80 100 120 1400
100
200
300
Month
Wei
ght
(g w
w) Predicted Size-at-age
Observed-Size-at-age
Herring Calibration
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saury (150E) pest for phalf's & ac
0
50
100
150
200
0 200 400 600 800
age (date)
wet
wei
ght
WobsWinitWpest+ac
Saury Calibration
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Uncertainty Analysis
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I21
Model
Run P1 P2 P3
Value of Output
Variable
1 I14 I23 I35 Y1
2 I12 I21 I36 Y2
3 I11 I26 I31 Y3
4 I16 I24 I34 Y4
5 I13 I22 I33 Y5
6 I15 I25 I32 Y6
Latin Hypercube Monte Carlo Sampling
I22 I23 I24 I25 I26
I13
I34 I35I33I32 I36I31
I14 I15I12I11 I16
P1
P2
P3
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Sensitivity Analysis
Sensitivity of Total Population
Biomass and Weight-at-age 5
under conditions of
Low Fish Biomass-High Prey Biomass
High Fish Biomass-Low Prey Biomass
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NEMURO ECOPATH/ECOSIM
Data Flow
LTL
HTL
NEMURO ECOPATH/ECOSIM Linkage
Fine temporal scale
Mechanistic
Process oriented
Course temporal scale
Aggregated
Approximate ecosystem through P/B and C/B ratios
Climate Change Scenario
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Concluding Remarks
Work is (clearly) ongoing, but:
• We have linked the LTL with the HTL successfully in certain locations and for two fish species with very different life histories
• Both dynamic and one-way coupling versions yield interesting result
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Future Work
• Complete publications – special issue of Ecological Modelling
• Extensions to sardines and anchovies (Fall 2005)
• Spatially explicit
• Future climate change scenarios
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5 NEMURO Posters• Yamanaka, Hashioka, Aita, and Kishi. Changes in ecosystem
and pelagic fish in western North Pacific associated with global warming
• Terui and Kishi. Population dynamics model of Copepoda in the Northwestern Pacific
• Aita, Tadokoro, Yamanaka, and Kishi. Interdecadal variation of the lower trophic ecosystem in the Northern Pacific between 1948-2002-in a 3D implementation of the NEMURO model
• Hashioka and Yamanaka. Seasonal and regional variations in phytoplankton groups by top-down and bottom-up controls obtained by a 3D ecosystem model
• Nakajima, Hashioka and Kishi. Analysis of spatial differences in wet weight of Japanese common squid in the Japan Sea