seapodym
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SEAPODYM. Applications. Understand Tuna Climate interactions. Forecast effects on climate change on tuna distribution and abundance. Capture meso-scale distribution information which allows for more EEZ level estimates of distribution and abundance. - PowerPoint PPT PresentationTRANSCRIPT
SEAPODYM
Applications
• Understand Tuna Climate interactions.• Forecast effects on climate change on tuna
distribution and abundance.• Capture meso-scale distribution information
which allows for more EEZ level estimates of distribution and abundance.
• Assistance for national and sub-regional tuna management planning.
The evolution in resolutionPre 2009- 2 degree x month physical forcing (no data assimilation)
2009-2010 2 degree x month physical forcing (with data assimilation)
The evolution in resolution2010-2012 - 1 degree x month physical forcing (with data assimilation)
2012 - ¼ degree x week physical forcing (with data assimilation)
December 2007 SODA 1°
06 December 2007 GLORYS ¼°
Improved Resolution
• Taken a number of years for the physical forcing data to become available.
• Need 1 degree resolution for EEZ level analyses otherwise results barely differ from regional averages.
• Optimised 1 degree models for skipjack, bigeye, south pacific albacore and swordfish.
• New ¼ degree data has become available in 2013 which corrects equatorial anomalies.
EEZ – Climate – AnalysesSkipjack Recruitment (PNG)
SEC
SECC
NECC
1
1
Month 1
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 2
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 3
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 4
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 5
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 6
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 7
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 8
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 9
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 10
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 11
140E 150E 160E 170E
15S
10S
5S
05N
1
1
Month 12
140E 150E 160E 170E
15S
10S
5S
05N
0 20 40 60 80 100
Primary Production (mgC/m2/day)
150 200 250
01
23
45
6
a
c
EEZ – Climate – AnalysesENSO-SP Albacore recruitment
150 200 250
01
23
45
6
d
f
10 15 20
01
23
45
6
e
f
La Nina
Neutral
El Nino
150 200 250
01
23
45
6
x
z
10 15 20
01
23
45
6
y
z
10 15 200
12
34
56
b
c
Longitude Latitude150E 160W 110W
ZONE 2 (Central) & ZONE 3 (Eastern)•SST increased, thermocline deepening, weaker currents
ZONE 1 (Western)• SST decreased, thermocline shallowing
3
NCEP 1971-2003
SST anomalies - El Nino
EEZ/Sub regional Fisheries Analyses
• Fishery impacts
Area 1 Potential Yield (SKJ)
0
2
4
6
8
10
12
0
10,000
20,000
30,000
40,000
50,000
60,000
0 10,000 20,000 30,000 40,000 50,000
Equi
libri
um C
PUE
(ton
nes /
day
)
Equi
libri
um c
atch
(ton
nes)
Equilibrium Effort (days)
Average catch Average CPUE
Climate Change
• Predicting the past to understand the future.• IPCC has developed an ensemble of models
predicting future climate scenarios under different atmospheric assumptions
• Only 1 (IPSL) has been coupled with the PISCES model to predict future primary production.
• Optimised the model with historical data and then simulate into the future under the A2 scenario defined by IPCC.
Skipjack and temperature
SKIPJACK LARVAE(A2 scenario)
2000
2050
2099
1st Exp with IPSL-CM4 2nd Exp after T° correction
≠ 4°C
Temperature transect at longitude 180°
The model has a bias in temperature
Bias correctionBias correction
Projecting Climate Change impact
SKIPJACK TOTAL BIOMASS
2000
2050
2099
1st Exp with IPSL-CM4 2nd Exp after T° correction
(Both simulations used average 1990-2000 fishing effort to project fishing impact)
1 2
12
actual fishing effortaverage 1990-2000 fishing effort
Under this fishing effort scenario, the stock biomass is predicted to
be mainly driven by larval recruitment
Total biomass
Albacore (A2 scenario)
2000
2050
2099
Albacore and oxygen
With modeled oxygen
Increasing pCO2 could lead to changes of C/N ratio
(Oschlies et al. 2008)
There is still a large uncertainty on O2 modeling whilethis is a key variable for tunas
2000
2050
2099
Total biomass
With climatological O2 (ie no change from present conditions)
Total biomass
Bigeye (A2 scenario)
First experiment with IPSL CM4 Larvae 2000 Larvae 2099 Total B 2000 Total B 2099
Second experiment (IPSL CM4) with T correction Larvae 2000 Larvae 2099 Total B 2000 Total B 2099
Summary for Climate Change Analyses• Results are consistent for the 3 species with an eastwards shift
in spawning and forage habitat.• Currently assuming no adaptation to changing temperatures
with SST >33-34°C estimated to be a threshold for spawning of tropical tunas.
Skipjack Bigeye
2000
2099
Albacore
Climate Change Summary• New simulations with temperature corrected forcing predict a lower
skipjack biomass and a decreasing trend after the 2070’s, driven by large extension of unfavourable equatorial spawning grounds.
• Application to albacore is highly sensitivity to O2, for which the biogeochemical models are still unclear.
• Parameter estimation using the IPCC models is adequate but inferior to ocean models with data assimilation. The climate models lack historical variability.
• Climate model ensemble simulations could help to solve the problem of bias.
• Ideally we would use climate model simulation with realistic historical variability (ENSO, PDO, NAO). These may be available in the near future.
• Climate projections for 10-15 years into the future probably more tangible for current fisheries planning.
Immediate FutureTagging really matters
• All optimisations so far have struggled to estimate movement.• Integrating conventional tagging data in the optimization
approach improves movement estimation.• Times series of tagging data extremely beneficial.
movement
threshold value of dissolved oxygen
optimal temperature for oldest tunaoptimal spawning SST
Incorporation of tagging data
• Preliminary (2 years of tagging data)
Predicted distributions of skipjack tuna in g/m2 (both young and adult life stages) as the result of experiments conducted with different likelihood composition: (left) including CPUE and length frequencies components only; (right) CPUE, LF and Tagging data components.
Summary• 1 degree models that allow meaningful EEZ and sub-
regional extraction of information.• Prepare national climate profiles. • Prepare climate change analyses within the IPCC
framework.• Assist sub-regional and SPC members with tuna
management planning.• New ¼ degree physical forcing available in 2013 that
will also allow simulation to end 2012. • Full incorporation of PTTP tagging data to better
parameterise movement.