SEAPODYM

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 2009- 2 degree x month physical forcing (no data assimilation) 2009-2010 2 degree x month physical forcing (with data assimilation)

5. The evolution in resolution 2010-2012 - 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°

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 – AnalysesSkipjack Recruitment (PNG) NECC SEC SECC

8. EEZ – Climate – AnalysesENSO-SP Albacore recruitment 3 La Nina Neutral El Nino NCEP 1971-2003 SST anomalies - El Nino • ZONE 1 (Western) • SST decreased, thermocline shallowing • ZONE 2 (Central) & ZONE 3 (Eastern) • SST increased, thermocline deepening, weaker currents 110W 160W 150E 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 The model has a bias in temperature SKIPJACK LARVAE (A2 scenario) Temperature transect at longitude 180° 2nd Exp after T° correction 1st Exp with IPSL-CM4 2000 ≠ 4°C 2050 Bias correction 2099

13. Projecting Climate Change impact (Both simulations used average 1990-2000 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 1990-2000 fishing effort 2 Under thisfishing effort scenario, the stock biomassispredicted to bemainlydriven by larvalrecruitment 2099

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

15. 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

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. Skipjack Bigeye Albacore 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 10-15 years into the future probably more tangible for current fisheries planning.

18. 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 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.