Differential Impacts of Climate Changeon 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 (1948-1953) 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.

Recruitment Dynamics• 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.

ASpawning

area

BNursery

area

Adult stock

C

Denatant

Recruitm

entDen

atan

tC

ontra

nata

nt

ASpawning

area

BNursery

area

Adult stock

C

Denatant

Recruitm

entDen

atan

tC

ontra

nata

nt

Environmental Variability• Simulation is now

used to incorporate environmental variability in the traditional demographic stock assessments (Mace 2001)

MAR545 22-Ecosystems 8

Environmental Change• Environmental factors can modify the Stock-

Recruitment relationship.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0 1 2 3 4

Spawning Stock

FavorableEnvironment

UnfavorableEnvironment

High F Low F

Rec

ruit

men

t

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.

Spatial Complexity• Fishery management units were

based on fishing grounds.• Genetics, movement, growth, etc.

indicate more complex structure.• Spatial complexity confers greater

productivity and resilience than the management unit perception.

Georges Bank

Gulf of Maine

NorthernSpawningComplex

EasternGeorges

BankSouthernSpawningComplex

0

100

200

300

400

0 0.2 0.4 0.60 0.80 1

Yield (k

mT)

Fishing MortalityManagement Units Spawning Groups

Spawning Groups

Management Units

Fishing Mortality

Fish

ery

Yiel

d (k

t)

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):

– Size at age (wa) is positively affected by warming (Brander 1995):

– Fishery production decreases with warming.

TSSeR

)(1 aThga e

Ww

Fishing Mortality

Fish

ery

Yiel

d (M

il t)

1982-2003 mean T

+1oC

+2oC

0

50000

100000

150000

200000

250000

0 0.2 0.4 0.6 0.8 1

SSB

(mT)

Fishing Mortality

Baseline ModelClimate Change (+ 1 degree)Climate change (+ 2 degrees)

0

50000

100000

150000

200000

250000

0 0.2 0.4 0.6 0.8 1

SSB

(mT)

Fishing Mortality

Baseline Model

Climate Change (+ 1 degree)

Climate change (+ 2 degrees)

0

50000

100000

150000

200000

250000

0 0.2 0.4 0.6 0.8 1

SSB

(mT)

Fishing Mortality

Baseline ModelClimate Change (+ 1 degree)Climate change (+ 2 degrees)

ProductivityNorthern Spawning Complex SSB as Temperature

Southern Spawning Complex SSB as Temperature

Eastern Georges Bank SSB as Temperature

0

5000

10000

15000

20000

25000

30000

0 0.2 0.4 0.6 0.8 1

Catc

h (m

T)

Fishing Mortality

Baseline modelClimate change (+ 1 degree)Climate change (+ 2 degree)

0

5000

10000

15000

20000

25000

30000

0 0.2 0.4 0.6 0.8 1

Cat

ch (

mT)

Fishing Mortality

Baseline modelClimate change (+1 degree)Climate change (+ 2 degrees)

0

5000

10000

15000

20000

25000

30000

0 0.2 0.4 0.6 0.8 1

Catc

h (m

T)

Fishing Mortality

Baseline modelClimate change (+ 1 degree)Climate change (+ 2 degree)

Sustainable YieldNorthern Spawning Complex MSY as Temperature

Southern Spawning Complex MSY as Temperature

Eastern Georges Bank MSY as Temperature

StabilityNorthern Spawning Complex CV as Temperature

Southern Spawning Complex CV as Temperature

Eastern Georges Bank CV as Temperature

MetapopulationResponse

0

200000

400000

600000

800000

0 0.2 0.4 0.6 0.8 1

SSB

(mT)

Fishing Mortality

Baseline

Climate Change (+1 degree)

Climate Change (+2 degree)

0

20000

40000

60000

80000

0 0.2 0.4 0.6 0.8 1

Cat

ch (

mT)

Fishing Mortality

Baseline modelClimate change (1 degree)Climate change (2 degrees)

Productivity SSB as Temperature

Yield MSY as Temperature

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.