1. Vulnerability of oceanic fisheries to climate change
Presented by
Sri Nandini

2. Authors
This presentation is based on Chapter 8 ‘Vulnerability of oceanic fisheries to climate change’ in the book Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change, edited by JD Bell, JE Johnson and AJ Hobday and published by SPC in The authors of Chapter 8 are: Patrick Lehodey, John Hampton, Rich Brill, Simon Nicol, Inna Senina, Beatriz Calmettes, Hans O. Pörtner, Laurent Bopp, Tatjana Ilyina, Johann Bell and John Sibert
While beyond the control of fishery managers, it is important to take into account the influence of oceanography and climate in order to better manage fisheries.

3. Outline Sensitivity of tuna habitats to oceanic variables
Potential changes and impacts
Priority adaptations
Conclusions

4. 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)

5. Tuna habitat – temperature
Larvae are most sensitive to temperature changes (affects spawning ground)
The upper lethal limit for yellowfin (33 oC) is projected to occur more often in Western Pacific Ocean by 2100
Yellowfin larvae (Wexler et al 2011)
optimal range for growth is 26-31oC for Yellowfin
low and high lethal temperatures are 21 & 33oC

6. 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

7. 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

8. Tuna habitat – ocean production
Tuna larvae
Zooplankton
Source: Rudy Kloser and Jock Young CSIRO, Australia
Micronekton
Primary production
PP is vital for reproduction and feeding hence tuna move in search of food and better habitat, PP=spatial & vertical distribution. PP supports the food web linking ot tuna (VAL)

9. 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.

10. Skipjack projection
2000
2000
Larval density
Adult biomass
2050
2050
Reduced biomass in western pacific associated with SST overheating.
Gains & challenges faced by PICTs EEZ, e.g. FIJI
This is interesting gain for Fiji. Even thou skj is not a major fishery right now, it could be under the effects of CC and this may rise an oppurtunity for FIJI. Explain EPO n WCPO and describe the figures.

11. Bigeye projection
2000
2000
Larval density
Adult biomass
2050
2050
good fishing grounds could be displaced further eastward & Reduced biomass in western Pacific
GAINS TO VE MADE IN THESE COUNTRIES WHERE THE FISH MOVE EASTERN. So now I will tell u the fish move to the east and why

12. 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

13. Total Fishery catch Change in % relative to average catch 1980-2000
Change in % relative to average catch
% changes in projected biomass in Fiji ezz due to CC relative to virgin biomass and relative to the combined effects of CC and fishing effort 1.5X greater then for the period of different slides. Virgin with CC and period with fishing

14. Total Fishery FIJI
Projected changes in biomass (%) of Skipjack for FIJI EEZ
without fishing
with fishing
2035
2050
2100 3 4 -3 1 -7

15. Total Catch What will be the future trend of fishing effort?
there is uncertainity in future trends for fishing effort. Diff between cqtch and effort
What will be the future trend of fishing effort?

16. Status of Stocks Climate change ? Last place to be
Keep genereal, choose an example if skj are more to the surface cuz of low O2, we need more research to know whether cc will change this ??Risk for fisheries included with impacts of CC. The green shows. to monitor the status of the four species of tuna is
to estimate parameters that determine the probability that a stock has breached key
management thresholds.

17. Priority adaptations
Regional management org (WCPFC, FFA, PNA and Te Vaka Moana groups) and national agencies should include implications of climate change in management objectives and strategies
Maintain bigeye tuna stock in WCPO in a healthy state to avoid combining high fishing pressure and adverse environmental conditions

18. Priority adaptations
Develop management systems to ensure flexibility to cope with changing spatial distribution of fishing effort (e.g. PNA vessel day scheme- tool that exist to manage for climate variability and climate change).
Socio-economic scenarios likely to drive future fishing effort in the region need to be identified and incorporated in modelling e.g. the increasing demand for tuna, the likelihood of spatial changes in fishing effort, and increasing fuel costs.

19. Consider spatially-explicit management in archipelagic areas, to monitor and assess potential sub-regional effects.
Fiji archipelagic waters have potential to become more productive under CC predictions
Priority adaptations
Eg. Productivity associated with the Sepik-Ramu Rivers in PNG currently provide optimal habitat
So this is what we expect for Fiji. Explain the iagram with tuna at mouth with increase rainfall and nutrient and then maybe the same case with fiji.

20. Conclusions
Understanding impact of climate change on tuna depends on our capacity to explain, model and predict the effect of natural variability and fishing effects.
While there is still uncertainty about impacts of climate change (ENSO, pH, O2), we know 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 °
The model seems robust for historical period but its forecast skills are linked to those of the climate models - improved climate forcings (physics+biochemistry) are needed to update this first risk assessment
Better projections of key oceanic variables for tuna can be achieved using an ensemble of models
work in progress for SEAPODYM
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.