1. Projected changes to ocean food webs and oceanic fisheries

2. Based on……..

3. Outline Food webs for tuna
Differences in food webs among provinces of the Pacific Ocean
Effects of CC on provinces and their food webs
Sensitivity of tuna habitats to oceanic variables
Effects of climate change on tuna stocks

4. Image: Marc Taquet, FADIO, IRD/IFREMER

5. Tuna food web
Food webs are complex

6. Five oceanic provinces

7. Five oceanic provinces
Warm pool
Normal El Niño

8. Five oceanic provinces
North and South Gyres (case 3) and equatorial divergence (case 4)

9. Impact of climate change
Surface area of the provinces
↘ of rich equatorial divergence
↗ of poorer gyres and warm pool

10. Impact of climate change
present
future
Exchanges between deep rich water and surface poorer waters
↘ of nutrients reaching the surface where photosynthesis can occur

11. 3. The impact of climate change
Effect on phytoplankton and zooplankton
2100
2035
2050
present
↘ of phytoplankton and zooplankton

12. 3. The impact of climate change
Effect on micronekton
Image: Valerie Allain, SPC
↘ of micronekton

13. Now, turning to tuna

14. Tuna habitat – temperature
Each tuna species has evolved with a preferred range in temperature
Species
Temperature (°C)
Skipjack
20-29
Yellowfin
20-30
Bigeye
13-27
Albacore
15-21
Sth. bluefin
17-20
Impacts vertical & horizontal distribution (habitat and food) & reproduction location and timing
According to life stage sensitivity to SST degree e.g. larvae and adult. Spawning. Affects habitat and
Range of sea surface temperature with substantial catches
Source: Sund et al. (1981)

15. Tuna habitat – oxygen Estimated lower lethal oxygen Skipjack Albacore
Sensitive to combined effects of SST + O2
Less tolerant to low values
Estimated lower lethal oxygen
Skipjack
Albacore
Yellowfin
Bigeye
Species
Fork length
(cm)
Lower lethal O2 levels (ml l-1)
Skipjack 50
1.87
Albacore
1.23
Yellowfin
1.14
Bigeye
0.40
Most tolerant to low values

16. Tuna habitat – oxygen 0 m 100 m Well oxygenated Low oxygen 500 m+
0 m
100 m
Well oxygenated
Skipjack
Yellowfin
Albacore
500 m
Low oxygen
Bigeye
Typical vertical O2
profile
Change in subsurface may have more impact on low oxygen tolerant species

17. Better understanding of oceanography = better expected projections
Now that we understand the oceanography a bit better then before, we have spent some years making a model to better understand the projections expected. Spent years working on a model to incorporate these change. Through this model we see changes in fishing grounds and distributions towards eastern for tuna and this poses challenges for fishing operations like purse seinier and long liners.

18. Skipjack tuna
Samoa +7%
Samoa +10%
Unexploited
Fishing effort x 1.5

19. Albacore projection Sensative to O2 hence distribution changes
2000
2000
Larval density
Adult biomass
2050
2050
No change in O2
Sensative to O2 hence distribution changes
With modelled O2

20. Conclusions There is still uncertainty about impacts of climate change
Fishing has a strong impact and will continue to be a major driver of stocks
Point to the graph on complexation.

21. Conclusions
Resolution 2°
Resolution 1°
Resolution 0.25 °
Improved resolutions of SEAPODYM model are needed to update these preliminary results
Better projections of key ocean variables for tuna can be achieved using an ensemble of models
we expect to be better at these models to get down form coarse scale to finner scale to better capture the oceanic processes. What is important to remember is that even thou there are gaps of knowledge and uncertainty in SEAPODYM, this is currently the only model, which can incorporate all these processes mentioned. Lead the audience thru the diagram. Alex resloution and giving example places in red more tuna then the palces in blue if u go donw from 2 degrees to these with these sort of model we would hope to provide more information to the managers to maange long liners. So as you can see when we go donw from 2 degrees to 0.25 we are better able to see these processes.