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: – Huxleys (1883) affirmation that the cod, herring and mackerel fisheries were inexhaustible. – Thompson-Burkenroad debates ( ) 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.

Environmental Variability Simulation is now used to incorporate environmental variability in the traditional demographic stock assessments (Mace 2001)

MAR54522-Ecosystems8 Environmental Change Environmental factors can modify the Stock- Recruitment relationship. Recruitment

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 Northern Spawning Complex Eastern Georges Bank Southern Spawning Complex Management Units Spawning Groups Spawning Groups Management Units Fishing Mortality Fishery Yield (kt)

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 CO 2 emissions scenario: Mean & Std.dev. + 1°C – High CO 2 emissions scenario: Mean & Std.dev. + 2°C Response metrics: – Productivity: spawning stock biomass (SSB) – Sustainable yield: maximum sustainable yield (MSY) and F MSY – 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 (w a ) is positively affected by warming (Brander 1995): – Fishery production decreases with warming mean T +1 o C +2 o C

Productivity Northern Spawning Complex SSB as Temperature Southern Spawning Complex SSB as Temperature Eastern Georges Bank SSB as Temperature

Sustainable Yield Northern Spawning Complex MSY as Temperature Southern Spawning Complex MSY as Temperature Eastern Georges Bank MSY as Temperature

Stability Northern Spawning Complex CV as Temperature Southern Spawning Complex CV as Temperature Eastern Georges Bank CV as Temperature

Metapopulation Response 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.