Projected impacts of future climate change, ocean acidification, and management on the US Atlantic sea scallop (Placopecten magellanicus) fishery

Abstract

Ocean acidification has the potential to significantly impact both aquaculture and wild-caught mollusk fisheries around the world. In this work, we build upon a previously published integrated assessment model of the US Atlantic Sea Scallop (Placopecten magellanicus) fishery to determine the possible future of the fishery under a suite of climate, economic, biological, and management scenarios. We developed a 4x4x4x4 hypercube scenario framework that resulted in 256 possible combinations of future scenarios. The study highlights the potential impacts of ocean acidification and management for a subset of future climate scenarios, with a high CO2 emissions case (RCP8.5) and lower CO2 emissions and climate mitigation case (RCP4.5). Under RCP4.5 and the highest impact and management scenario, ocean acidification has the potential to reduce sea scallop biomass by approximately 13% by the end of century; however, the lesser impact scenarios cause very little change. Under RCP8.5, sea scallop biomass may decline by more than 50% by the end of century, leading to subsequent declines in industry landings and revenue. Management-set catch limits improve the outcomes of the fishery under both climate scenarios, and the addition of a 10% area closure increases future biomass by more than 25% under the highest ocean acidification impacts. However, increased management still does not stop the projected long-term decline of the fishery under ocean acidification scenarios. Given our incomplete understanding of acidification impacts on P. magellanicus, these declines, along with the high value of the industry, suggest population-level effects of acidification should be a clear research priority. Projections described in this manuscript illustrate both the potential impacts of ocean acidification under a business-as-usual and a moderately strong climate-policy scenario. We also illustrate the importance of fisheries management targets in improving the long-term outcome of the P. magellanicus fishery under potential global change.

Fig 1. Conceptual illustration of the integrated assessment model.

Red arrows indicate connections between submodels, black arrows indicate population submodel, green arrows indicate decision-making and socio-economic submodel. Illustrations courtesy of the Integration and Application Network, University of Maryland Center for Environmental Science (ian/umces/edu/symbols/).

Fig 2. External drivers of integrated assessment model.

A) Atmospheric CO₂ from the Representative Concentration Pathways (RCPs), B) change in sea surface temperature from 2000–2006 (mean ± SD) from 10 global earth system models in the 10x10 degree region containing the Mid-Atlantic Bight and Georges Bank scallop populations, C) US per-capita disposable income trajectories corrected to 2011 USD, and D) carbon tax converted to potential diesel fuel tax associated with each RCP.

Fig 3. Scallop whole stock biomass from RCP8.5 (top panel) and RCP4.5 (bottom panel) under the highest management strategy (catch limits, variable reference points, and 10% area closure) with varying additive ocean acidification impacts: Decreased larval survival (L), reduced growth rates (L+G), and increased predation on small scallops (L+G+P).

Bold line illustrates the mean, and shaded area is the 95% confidence interval for 100 model runs with stochastic recruitment. The 2000–2012 period is hindcast with observed recruitment.

Fig 4. Scallop fishery landings from RCP8.5 (top panel) and RCP4.5 (bottom panel) under the highest management strategy (catch limits, variable reference points, and 10% area closure) with varying ocean acidification impacts: Decreased larval survival (L), reduced growth rates (L+G), and increased predation on small scallops (L+G+P).

Bold line illustrates the mean, and shaded area is the 95% confidence interval for 100 model runs with stochastic recruitment. The 2000–2012 period is hindcast with observed recruitment.

Fig 5. Scallop biomass by size class from the Mid-Atlantic Bight (left panels) and Georges Bank (right panels) populations versus ocean acidification impact (rows).

Upper panels show larval impacts only, middle panels show larval and growth impacts, and bottom panels show larval, growth, and increased predation impacts. Dashed lines illustrate catch limit only management scenarios and solid lines illustrate the highest level of management (catch limits, varying reference points, and 10% area closures). Black lines indicate reference simulations with no ocean acidification impacts.

Fig 6. Scallop whole stock biomass from RCP8.5 (top panel) and RCP4.5 (bottom panel) under the highest ocean acidification impacts (increased larval mortality, reduced growth rates, and increased mortality due to predation) with varying management strategies: No set catch limit, maximum allowable biological catch (ABC), varying fisheries reference points (ABC+F_MSY), and area closures (ABC+F_MSY+10% closure).

The purple line/band illustrates the same dataset as in Fig 3. Bold line illustrates the mean, and shaded area is the 95% confidence interval for 100 model runs with stochastic recruitment. The 2000–2012 period is hindcast with observed recruitment.

Fig 7. Scallop fishery landings from RCP8.5 (top panel) and RCP4.5 (bottom panel) under the highest ocean acidification impacts (increased larval mortality, reduced growth rates, and increased mortality due to predation) with management strategies: No set catch limit, maximum allowable biological catch (ABC), varying fisheries reference points (ABC+F_MSY), and area closures (ABC+F_MSY+10% closure).

The purple line/band illustrates the same dataset as in Fig 4. Bold line illustrates the mean, and shaded area is the 95% confidence interval for 100 model runs with stochastic recruitment. The 2000–2012 period is hindcast with observed recruitment.

Fig 8. Contour plots of biomass at three different time points (2020, 2050, and 2100) for RCP8.5 (left panels) and RCP4.5 (right panels).

X-axes increase management levels from low to high as no set catch limit (None), allowable biological catch limits only (low), ABC and variable fishing mortality at maximum sustainable yield (YPR, medium), and ABC, YPR, and an additional 10% closed area (high). Y-axes increase ocean acidification impacts from no impact to high impacts as no ocean acidification impacts, larval impacts only (L), larvae and growth rate impacts (L+G), and larvae, growth, and predation (L+G+P). Biomass is shown in units of 1000 metric tons (mT).