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Patrick LehodeyOceanic Fisheries Programme
Secretariat of the Pacific CommunityNoumea, New Caledonia
Tuna and tuna forage: reconciling modeling and observation in a spatial
mixed-resolution ecosystem model
Conclusion
• Existing data on tuna and the pelagic ecosystem are numerous but at multiple temporal and spatial scales
• Using them to parameterize and evaluate an ecosytem model requires to develop a model that produces predictions at these same multiple temporal and spatial scales
Evaluation
Obs. Pred.same level of
details
Top-to-bottom integrated food web in marine ecosystem
Level of information (observation and knowledge) available for the pelagic ecosystem
Phys.
Prod I
Zoopk.
Interm. TL.
Top Pred.
marine ecosystem information marine ecosystem model(s)
Satellites, scientific cruises and ship of opportunity network, arrays of moorings…physical laws (Navier-Stoke, …)
3D GCM
Satellites, cruises, moorings…photosynthesis, physiology, dynamics… 3D NPZD
cruises, OPC, mesocosm…physiology, dynamics…
NPZD
Catchcruisesbiology
Functional group (s)
Catch and effort, length freq., large scale tagging exp, individual trackings, biology, physiology, stat. pop. Dyn. Mod.
Basin scale spatial pop. dyn. mod.
Pelagic ecosystem
Figure 1. A top to bottom schematic view of the pelagic food web. Most of the organisms in the meso- and deep- pelagic layers have nycthemeral migration patterns leading to higher concentration in the upper layer at night and in the deeper layer during the day.
mesoZpk
microZpk
DOM
Phytopk
Bact.
Pico & Nanopk
Detritus
Gel. org.
MesoPel.
EpiPel.
microbial loop
DAY NIGHT
200 m
500 m
Sharks
Billfish
Adult yft tuna
div. pisc.
skj, young tuna & scombrids
seabirds
mar. mam.
Adult bet tuna Swordfish
N2
macro and micro nutrients BathyPel.
day
night sunset, sunrise
200m
500m
surface
1 2 3 4 5 4a 4b
Figure 2. The different daily vertical distribution patterns of the micronekton in the tropical pelagic ecosystem. 1, epipelagic; 2, mesopelagic migrant; 3, mesopelagic non-
migrant; 4, bathy-pelagic migrant; 5, bathypelagic non-migrant. Group 4 can be detailed into bathypelagic migrant into the intermediate layer (4a) or the surface layer (4b).
Vertical structure of the pelagic food web
day night sunr
ise
surface layer
suns
et
1
2
3
4
5
deep layer
inter-mediate layer
Figure 3. Five typical vertical movement behaviours simulated using a 3-layer and 2-type of prey pelagic system (adapted from Dagorn et al. 2000):
1- epipelagic predators (e.g., skipjack, marlins and sailfish); 2- predators moving between the surface and intermediate layers during the day (e.g., yellowfin tuna); 3- predators mainly in the intermediate layer during the day (e.g., albacore tuna); 4- predators moving between deep and intermediate layer during the day (e.g., blue shark); 5- predators mainly in the deep layer during the day (e.g., bigeye tuna and swordfish).
day
night sunset, sunrise
200m
500m
1 2 3 64 5
Modelling forage components:
3-layer 6-forage functional groups
ToC & currents in the 200-500m layer
Day Length (DL) as a function of latitude and date
Total primary
production
E
ToC & currents in the 500-1000m layer
ToC & currents in the 0-200m layer
surface
Forage functional groups: modelling forage as multi-species populations
New Primary Production
Ecol
ogic
al tr
ansf
er
1%
t 0
F
t e S F
1
Tr Ln 01 . 0
1 t
1 Tr
“mean age”
“lifespan”
t
S
t e S .
S
E
0300600900
12001500180021002400
0 5 10 15 20 25 30ambient Temperature (oC)
Age
(day
)
1/lambdaobs (age at maturity)TrTr+1/lambdaobs (min age of prey)
Lehodey P. et al., 1998. Fisheries Oceanography 7(3/4): 317-325.Lehodey P. 2001. Progress in Oceanography 49: 439-468.Lehodey P., Chai F., Hampton J. 2003. Fisheries Oceanography 12(4): 483-494
2-layer, 3-component forage
Epipelagic forage Migrant mesopelagic forage
Deep mesopelagic forage
Top : La NiñaBottom: El Niño
Spatial forage biomass
–Day concentrations (ml / 1000 m3) of “skipjack forage” measured during the EASTROPAC cruise (left) and biomass of epi-pelagic forage predicted by the model for the same period (February-March 1967). (Blackburn and Laurs, 1972)
Day: 0-200m
Night: 0-200m
Spatial forage biomass
• Acoustic data
(A. Bertrand, E. Josse)
600
1600
2600
3600
4600
5600
Jan-
48
Jan-
51
Jan-
54
Jan-
57
Jan-
60
Jan-
63
Jan-
66
Jan-
69
Jan-
72
Jan-
75
Jan-
78
Jan-
81
Jan-
84
Jan-
87
Jan-
90
Jan-
93
Jan-
96
Jan-
99
Jan-
02
Biom
ass
epi-p
elag
ic
0
2000
4000
6000
8000
10000
12000
Biom
ass
mig
rant
- and
dee
p-pe
lagi
cepi eq3 migrant eq3 deep eq3
1500
2500
3500
4500
5500
6500
7500
Jan-
48
Jan-
51
Jan-
54
Jan-
57
Jan-
60
Jan-
63
Jan-
66
Jan-
69
Jan-
72
Jan-
75
Jan-
78
Jan-
81
Jan-
84
Jan-
87
Jan-
90
Jan-
93
Jan-
96
Jan-
99
Jan-
02
Biom
ass
epi-p
elag
ic
0
5000
10000
15000
20000
25000
30000
35000
Biom
ass
mig
rant
- adn
dee
p-pe
lagi
cepi eq2 migrant eq2 deep eq2
500
1000
1500
2000
2500
Jan-
48
Jan-
51
Jan-
54
Jan-
57
Jan-
60
Jan-
63
Jan-
66
Jan-
69
Jan-
72
Jan-
75
Jan-
78
Jan-
81
Jan-
84
Jan-
87
Jan-
90
Jan-
93
Jan-
96
Jan-
99
Jan-
02
Biom
ass
epi-p
elag
ic
01000
20003000
4000500060007000
80009000
10000
Biom
ass
mig
rant
- and
dee
p-pe
lagi
cepi eq4 migrant eq4 deep eq4
Biomass time seriesPredicted biomass of forage components in eastern and western equatorial regions
90E 110E 130E 150E 170E 170W 150W 130W 110W 90W 70W
60N
50N
40N
30N
20N
10N
0
10S
20S
30S
40S
50S
Kurex
Tas Chi
li
Eq1 Eq2 Eq3
Eq4
Structure of the tuna population
> 40 cm15 - > 40 cm5-15 cm2 mm -5 cm2 mmSize
1st maturity to last quarter
2nd quarter to age of 1st maturity
2nd and 3rd month1st montht0
Time/ age structure
AdultYoungJuvenileLarvaeSpawning
To, oxygen, Food (F), spawning
seasonality
To, oxygen, Food (F),
Predators (all adult tuna)
To, Food (Zpk),
Predators (all largest
tuna)
To, Food (P), Predators (F)
Habitat factors
1- Habitat based movement (following increasing gradient)2- Proportional to fish size3- Decreasing with increasing habitat4- impact of currents ?
Currents in upper layer
Transport / movement(advection-diffusion)
Independent estimates + habitat-related variabilityNatural mortality
Independent estimates (+ habitat-related variability)Growth
Spawning Habitat : (Temperature, Food, Predators, currents)
Jun 1971
distribution of skipjack larvae(Nishikawa et al.)
Fisheries: Pred. vs Obs.
0102030
J-72
J-74
J-76
J-78
J-80
J-82
J-84
J-86
J-88
J-90
J-92
J-94
J-96
J-98
J-00
J-02
cpue
02468obs skj_PSWFAD pred skj_PSWFAD
020
4060
80100
10 20 30 40 50 60 70 800.E+00
1.E+04
2.E+04
3.E+04
4.E+04sum_PSWFAD_skj
0
5000
10000
15000
10 20 30 40 50 60 70 800.E+002.E+044.E+046.E+048.E+041.E+051.E+05sum_PSWUNA_skj
CPUE
Spatially-disaggregated monthly catch
Length-frequency distribution ( by fishery, time and space)
Accessibility to forage components
epipelagic36%
mesopelagic non-migrant
13%
mesopelagic migrant
39%
bathypelagic non-migrant
1%
bathypelagic migrant 1
3%
bathypelagic migrant 2
8%
epipelagic48%
mesopelagic non-migrant
4%
mesopelagic migrant
46%
bathypelagic migrant 2
2%
bathypelagic migrant 1
0%
bathypelagic non-migrant
0%
Skipjack (age = 8 quarter) Yellowfin (age = 16 quarter)
By species, age, space and time Build up a database to classify all tuna prey species according to these 6 groups
Adult Habitat: (temperature, food, spawning seasonality)
Bigeye tuna (FL = 80 cm) habitat Jun 1999
Observed individual movements and predicted habitat
Predicted movement (arrows) of bigeye tuna (FL ~ 80 cm) based on the gradient of habitat (background colour) combining forage, temperature and oxygen, and estimated track of a bigeye
released wit h an archival tag during the same period.
Nov 1999
Mixed resolution (PFRP project)
Mixed resolution (PFRP project) Physical-biogeochemical outputs: ESSIC (R. Murtugudde, Univ. Maryland)
•1950-present•½ deg spatial resolution•10 day time resolution
Forage and tuna:SEAPODYM
- 6 forage components (production and biomass)
- Tuna species (Larvae, juveniles, young, adults, total biomass)
- Tuna fisheries (many)
Visualization software : SeapodymView:
• Replay the simulations
• Extract/aggregate data
Can be distributed with files of predicted variables to colleagues interested to compare their results/observations to these predictions
