1. SEAPODYM

3. 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.

4. The evolution in resolution
Pre degree x month physical forcing (no data assimilation)
degree x month physical forcing (with data assimilation)

5. The evolution in resolution
degree x month physical forcing (with data assimilation)
¼ degree x week physical forcing (with data assimilation)
December 2007 SODA 1°
06 December 2007 GLORYS ¼°

6. 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.

7. EEZ – Climate – Analyses Skipjack Recruitment (PNG)
NECC
SEC
SECC

8. EEZ – Climate – Analyses ENSO-SP Albacore recruitment3
NCEP
La Nina
Neutral
El Nino
SST anomalies - El Nino
ZONE 1 (Western)
SST decreased, thermocline shallowing
ZONE 2 (Central) & ZONE 3 (Eastern)
SST increased, thermocline deepening, weaker currents
150E
160W
110W
Longitude
Latitude

9. EEZ/Sub regional Fisheries Analyses
Fishery impacts

10. Area 1 Potential Yield (SKJ)

11. 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.

12. Skipjack and temperature
SKIPJACK LARVAE
(A2 scenario)
≠ 4°C
Temperature transect at longitude 180°
The model has a bias in temperature
1st Exp with IPSL-CM4
2nd Exp after T° correction
2000
2050
Bias correction
2099

13. Projecting Climate Change impact
(Both simulations used average fishing effort to project fishing impact)
SKIPJACK TOTAL BIOMASS
1st Exp with IPSL-CM4
2nd Exp after T° correction
2000 1 2
2050
actual fishing effort 1
average fishing effort 2
Under this fishing effort scenario, the stock biomass is predicted to be mainly driven by larval recruitment
2099

14. (ie no change from present conditions)
Albacore and oxygen
Albacore
(A2 scenario)
Increasing pCO2 could lead to changes of C/N ratio (Oschlies et al. 2008)
There is still a large uncertainty on O2 modeling while
this is a key variable for tunas
2000
2050
2099
Total biomass
With climatological O2
(ie no change from present conditions)
With modeled oxygen
Total biomass
2000
2050
Total biomass
2099

15. Bigeye (A2 scenario) First experiment with IPSL CM4
Larvae Larvae Total B Total B 2099
Second experiment (IPSL CM4) with T correction

16. 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.
Albacore
Skipjack
Bigeye
2000
2099

17. 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 years into the future probably more tangible for current fisheries planning.

18. Immediate Future Tagging 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 tuna
optimal spawning SST

19. 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.

20. 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.