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

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°

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 – Analyses Skipjack Recruitment (PNG) NECC SEC SECC

EEZ – Climate – Analyses ENSO-SP Albacore recruitment 3 NCEP 1971-2003 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

EEZ/Sub regional Fisheries Analyses Fishery impacts

Area 1 Potential Yield (SKJ)

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) ≠ 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

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 this fishing effort scenario, the stock biomass is predicted to be mainly driven by larval recruitment 2099

(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

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

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

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 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

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.