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.
Table 1.
4x4x4x4 scenario hypercube framework.
Climate scenarios incorporate changes in fuel costs associated with carbon taxation as well as economic development used in the GCAM projections. Total fuel price is calculated as the sum of the base price, determined from the growth rate, and the carbon tax. Ocean (OA) acidification impacts include either no impact, or combinations of increasing larval mortality (Larvae), reduced growth rates (Growth), and increased mortality of small scallops due to predation (Predation). Management impacts include either no set catch limits, or combinations of maximum allowable biological catch (ABC), varying reference points due to changing growth rates (FMSY), and closed areas (10% closure).
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+FMSY), and area closures (ABC+FMSY+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+FMSY), and area closures (ABC+FMSY+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).