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Vulnerability of oceanic fisheries to climate change

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

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Vulnerability of oceanic fisheries to climate change

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  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 2011. 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

  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 • Impacts vertical & horizontal distribution (habitat and food) & reproduction location and timing 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 Sensitive to combined effects of SST + O2 Lesstolerant to low values Estimated lower lethal oxygen Skipjack Albacore Yellowfin Bigeye Most tolerant to low values

  7. Tuna habitat – oxygen + 0 0 m 100 m Welloxygenated Albacore Bigeye Lowoxygen 500 m Skipjack Yellowfin Typical vertical O2 profile Change in subsurfacemay have more impact on lowoxygentolerantspecies

  8. Tuna habitat – ocean production Tunalarvae Zooplankton Micronekton Primary production Source: Rudy Kloser and Jock Young CSIRO, Australia

  9. Better understanding of oceanography = better expected projections

  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

  11. Bigeye projection 2000 2000 Adult biomass Larval density 2050 2050 good fishing grounds could be displaced further eastward & Reduced biomass in western Pacific

  12. Albacore projection 2000 2000 Adult biomass Larval density 2050 2050 No change in O2 Sensative to O2 hence distribution changes WithmodelledO2

  13. Total Fishery catch 2035 2050 2100 2035 2050 2100 Change in % relative to average catch 1980-2000

  14. Total Fishery FIJI

  15. Total Catch Whatwillbe the future trend of fishing effort?

  16. Status of Stocks Last place to be Climate change ?

  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 stateto 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. Priority adaptations • 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 • Eg. Productivity associated with the Sepik-Ramu Rivers in PNG currently provide optimal habitat

  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

  21. Resolution 2° Conclusions • 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 Resolution 1° Resolution 0.25 °

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