Transcript Complexity - IEO Santander

Differential Impacts of Climate Change
on Spawning Populations of Atlantic cod
in U.S. Waters
Lisa Kerr, Steve Cadrin
(UMass School for Marine Science & Technology),
Mike Fogarty
(NOAA Northeast Fisheries Science Center),
and Jim Churchill
(Woods Hole Oceanographic Institution)
Outline
• History of fisheries oceanography
– Oceanographic foundations of
fisheries science
– Single-species demographic
conventions
– Recruitment studies
– Incorporating environmental factors
in fishery stock assessment
– An emerging role for simulation
• Case study: cod and climate off
New England.
Formative Years of Fisheries Oceanography
• Northeast Atlantic:
– ICES was formed in 1902
primarily to explain
fluctuations in fishery yields,
and adopted an oceanographic
approach to studying fisheries.
• Northwest Atlantic:
– Early fisheries science was
largely influenced by
oceanography (e.g., Henry
Bigelow, 1879–1967).
Fishing and the Environment
• Several scientific debates and initiatives
focused on the relative effects of fishing
and the environment:
– Huxley’s (1883) affirmation that the cod,
herring and mackerel fisheries were
inexhaustible.
– Thompson-Burkenroad debates (19481953) on the overfishing vs. environmental
factors as the cause of decline in the Pacific
halibut stock.
– California Cooperative Oceanic Fisheries
Investigations (CalCOFI) was formed to
study the ecological aspects of the collapse
of the sardine populations off California.
Single-Species Stock Assessment
• A convention for fishery science based on demographics
was formed in the 1950s (Ricker 1955, Beverton & Holt
1957;) in which overfishing and Maximum Sustainable Yield
(MSY) were estimated through age-based models.
Adult stock
C
Spawning
area
Denatant
t
en
A
itm
cru
Re
• Cushing (1982) illustrated the
importance of climate, primary &
secondary production as factors
explaining recruitment variability.
• Sinclair (1988) demonstrated the
importance of hydrographic
processes in larval retention.
• Rothschild (1988, etc.) recognized
the decadal scale of recruitment
variability.
De
na
ta n
Co
t
ntr
an
ata
nt
Recruitment Dynamics
B
Nursery
area
Environmental Variability
• Simulation is now
used to incorporate
environmental
variability in the
traditional
demographic stock
assessments (Mace
2001)
Environmental Change
• Environmental factors can modify the StockRecruitment relationship.
1.4
High F
Recruitment
1.2
Low F
Favorable
Environment
1.0
0.8
Unfavorable
Environment
0.6
0.4
0.2
0.0
0
1
2
3
4
Spawning Stock
MAR545
22-Ecosystems
8
Challenges for Fisheries Management
• Predictability of future environments
– If the environment strongly influences fish productivity and can
be reliably projected, fisheries can be managed accordingly (e.g.,
Pacific sardine; MacCall 1995, Hill et al. 2007).
– When the environment cannot be reliably projected, we only have
a retrospective understanding of fishery variability.
• A new form of understanding through simulation
– Operating models can be used to represent biological and
environmental realism.
– Simple stock assessment models can be evaluated in the context
of a more complex world.
– Fishery management strategies can be designed to take advantage
of favorable environments while being robust to variability.
Cod, Climate and Complexity
• Objective: examine the impacts of climate change on the
productivity, stability, and sustainable yield of U.S. cod
populations.
– Complexity: recent genetic data shows that population structure is
composed of three primary spawning components.
– Climate Change: increased water temperature and storms
influence recruitment and growth of each spawning component.
400
Spatial Complexity
Management Units
Fishery Yield (kt)
Yield (k mT)
• Fishery management units were
300
based on fishing grounds.
• Genetics, movement, growth, etc. 200
indicate more complex structure.
100
• Spatial complexity confers greater
productivity and resilience than the 0
management unit perception.
0
Spawning Groups
Northern
Spawning
Complex
Gulf of Maine
Georges Bank
Southern
Spawning
Complex
Spawning Groups
Eastern
Georges
Bank
Management Units
0.2
0.4 0.60 0.80
Fishing
Mortality
Fishing Mortality
1
Climate Change
• Environmental effects on recruitment:
– Retention of larval cod is strongly correlated to mean
northward wind velocity (Churchill et al. 2011).
– Winter storms are strongly associated with temperature
(e.g., Emanuel 2005).
Complexity and Climate Simulations of Cod
• We estimated spawning group-specific temperature effects.
• We simulated response of cod populations to sea surface
temperature (SST) across a range of fishing mortality (F)
– Baseline model: Mean and standard deviation of SST
– Low CO2 emissions scenario: Mean & Std.dev. + 1°C
– High CO2 emissions scenario: Mean & Std.dev. + 2°C
• Response metrics:
– Productivity: spawning stock biomass (SSB)
– Sustainable yield: maximum sustainable yield (MSY) and FMSY
– Stability: coefficient of variation (CV) in SSB
Climate Change
• Temperature (T) effects on cod production:
– Recruitment (R) as a function of spawning biomass (S) is
negatively affected by warming (Fogarty et al. 2008):
R  Se  S T
– Size at age (wa) is positively affected by warming
W
(Brander 1995): w 
1  e g ( h T a )
– Fishery production
decreases with warming.
Fishery Yield (Mil t)
a
1982-2003 mean T
+1oC
+2oC
Fishing Mortality
250000
Baseline Model
Climate Change (+ 1 degree)
Climate change (+ 2 degrees)
Productivity
SSB (mT)
200000
150000
Northern Spawning Complex
SSB
as Temperature
100000
50000
0
250000
0
SSB (mT)
200000
0.2
0.4
Baseline Model
0.6
0.8
1
Climate Change (+ 1 degree)
Climate change (+ 2 degrees)
Fishing Mortality
Southern Spawning Complex
SSB
as Temperature
150000
100000
50000
0
250000
0
SSB (mT)
200000
0.2
0.4
Baseline Model
0.6Climate
0.8Change1(+ 1 degree)
Eastern Georges Bank
SSB
as Temperature
Climate change (+ 2 degrees)
Fishing Mortality
150000
100000
50000
0
0
0.2
0.4
0.6
0.8
Fishing Mortality
1
30000
Sustainable Yield
Catch (mT)
25000
20000
15000
Baseline model
Climate change (+ 1 degree)
Climate change (+ 2 degree)
Northern Spawning Complex
MSY
as Temperature
10000
5000
0
30000
0
0.2
Catch (mT)
25000
20000
0.4
0.6
0.8
1
Baseline model
Climate change (+1 degree)
Fishing Mortality
Climate change (+ 2 degrees)
Southern Spawning Complex
MSY
as Temperature
15000
10000
5000
0
30000
Catch (mT)
25000
0
0.2
0.4
0.6
0.8
Eastern Georges Bank
MSY
as Temperature
Fishing Mortality
20000
15000
1
Baseline model
Climate change (+ 1 degree)
Climate change (+ 2 degree)
10000
5000
0
0
0.2
0.4
0.6
Fishing Mortality
0.8
1
Stability
Northern Spawning Complex
CV
as Temperature
Southern Spawning Complex
CV
as Temperature
Eastern Georges Bank
CV
as Temperature
800000
Baseline
Climate Change (+1 degree)
SSB (mT)
600000
Climate Change (+2 degree)
400000
Productivity
SSB
as
200000
Catch (mT)
0
80000
Metapopulation
Response
0
0.2
0.4
0.6
0.8
Temperature
1
Fishing Mortality
60000
Yield
MSY
40000
Baseline model
Climate change (1 degree)
Climate change (2 degrees)
20000
as
Temperature
0
0
0.2
0.4
0.6
Fishing Mortality
0.8
1
Stability
CV
as
Temperature
Conclusions
• Climate change differentially influences cod
spawning groups based on the timing and location
of spawning and different growth environments of
each population.
• Spatio-temporal population structure is important
for determining sensitivity to climate change.
• Simulation, the operating model concept, and
management strategy evaluation offer new tools for
fisheries oceanography.