Vulnerability of oceanic fisheries to climate change

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Vulnerability of oceanic fisheries to climate
change
Presented by Sri Nandini
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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

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Outline

• Sensitivity of tuna habitats to oceanic variables
• Potential changes and impacts
• Priority adaptations
• Conclusions

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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

Range of sea surface temperature with substantial
catches
Source Sund et al. (1981)
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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

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Tuna habitat oxygen
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 50 1.23
Yellowfin 50 1.14
Bigeye 50 0.40
Most tolerant to low values
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Tuna habitat oxygen

0
0 m
100 m
Well oxygenated
Low oxygen
500 m
Typical vertical O2 profile
Change in subsurface may have more impact on low
oxygen tolerant species
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Tuna habitat ocean production
Primary production
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Better understanding of oceanography better
expected projections
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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
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Bigeye projection
2000
2000
Adult biomass
Larval density
2050
2050
good fishing grounds could be displaced further
eastward Reduced biomass in western Pacific
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Albacore projection
2000
2000
Adult biomass
Larval density
2050
2050
No change in O2
Sensative to O2 hence distribution changes
With modelled O2
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Total Fishery catch
Change in relative to average catch 1980-2000
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Total Fishery FIJI
Projected changes in biomass () of Skipjack for FIJI EEZ Projected changes in biomass () of Skipjack for FIJI EEZ Projected changes in biomass () of Skipjack for FIJI EEZ Projected changes in biomass () of Skipjack for FIJI EEZ Projected changes in biomass () of Skipjack for FIJI EEZ Projected changes in biomass () of Skipjack for FIJI EEZ
without fishing without fishing without fishing with fishing with fishing with fishing
2035 2050 2100 2035 2050 2100
3 4 -3 1 0 -7
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Total Catch
What will be the future trend of fishing effort?
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Status of Stocks
Last place to be
Climate change ?
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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

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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.
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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
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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

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Conclusions

• The model seems robust for historical period but
  its forecast skills are linked to those of the
  climate models - improved climate forcings
  (physicsbiochemistry) 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