developing a model for the us sea scallop fishery that ...cmip5.whoi.edu/doc/rheuban et al. cmip...
TRANSCRIPT
Future Scenarios
Developing a model for the US Sea Scallop fishery that incorporates ocean acidification and warming
References Cooley, S. R., J. E. Rheuban, D. Hart, V. Luu, D. Glover, J. A. Hare, and S. C. Doney. 2015. An integrated assessment model for helping the United States sea scallop (P. magellanicus) fishery plan ahead for ocean acidification and warming. PLoS ONE. Hart, D. R., and A. S. Chute. 2004. Essential fish habitat source document: Sea scallop. Placopecten magellanicus, life history and habitat characteristics. Northeast Fisheries Science Center.
Jennie E. Rheuban1, Sarah R. Cooley2, Deborah Hart3, Victoria Luu4, David M. Glover1, Jonathan A. Hare3, and Scott C. Doney1 1. Woods Hole Oceanographic Institution, Woods Hole, MA 2. Ocean Conservancy, 3. NOAA NMFS NEFSC, 4. Boston University [email protected]
Atlantic Sea Scallop Placopecten magellanicus
• High value wild-caught fishery (500 million USD ex-vessel revenue, Fig. 1) • Spatially separate populations (Mid-Atlantic Bight and Georges Bank)
Overfished
• Management successful in improving fishery but does not account for potential long term change
Climate Impacts
10 year
•Ocean Acidification (OA): reduction in ocean pH and CaCO3 saturation state caused by increased atmospheric carbon dioxide (Fig. 3). •Mollusk growth (Fig. 4) and reproduction more difficult •Warming can alter species distribution, growth rates, and mortality.
Influence of OA on Scallops
Fig. 5. From 8 species in 6 studies (Cooley et al. 2015).
* *
*
*
*
*Likely Influenced by OA
Pelagic
Benthic
Fig. 5. Life cycle of sea scallop. (Adapted from Hart and Chute 2004).
Model
Links 3 submodels (Fig. 5) through relationships from other mollusk species (e.g. Fig. 4), IPCC future scenarios, and management decisions.
Size based population
dynamics from NOAA NMFS management
models
Two-box biogeochemical model, driven by seasonal thermal stratification
Economic decision-making and NOAA
NMFS Economics data
Fig. 5. Model schematic (Cooley et al. 2015)
Model Fit
Size-specific abundances (Fig. 6), landings, revenue (Fig. 7), and biomass (not shown) match historical data well
Fig. 6 (left). (A) actual and (B) modeled size-
specific abundance
Fig. 7. Revenue (A) and landings (B).
Scenario/Driver Pressures
Climate (T, CO2) RCP2.6 RCP4.5 RCP6 RCP8.5
Fuel
Base growth rate (%) 0 0.35 0.7 1.4
Tax Carbon tax $/ton/100
Price Base fuel price + Fuel tax
OA Impacts None L G+L G+L+P
Management None ABC ABC + Fmsy
ABC +
Fmsy +
Closure
Exploring the impacts of possible futures in a 4x4x4x4 scenario framework with differing degrees of OA impacts, management levels, fuel costs, and future climate scenarios (Table 1) (256 possible futures!)
Table 1. Possible driver choices for future scenario framework. L = larval impacts, G = growth rate impacts, P = predation impacts, ABC = management set allowable biological catch, Fmsy = variable Fmsy, Closure = 10% biomass in areas closed to fishing
2010 2040 2070 2100
0
1
2
3
4
5 ΔT (°C from 2006-2010 mean)
300
400
500
600
700
800
900
1000
20
00
20
10
20
30
20
50
20
70
20
90
Atmospheric CO2 (IPCC RCP pathways)
Future trajectories vary considerably based on climate pathways, impacts, and degrees of management. Outcomes from this model will be used to inform management and leaders of the industry of possible futures.
Results
RCP 8.5 High Management RCP 2.6 High Management RCP 8.5 No Management RCP 2.6 No Management