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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 jrheuban@whoi.edu

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