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Table 8 
Evaluation of model simulations in which closure location rule 2 was used to examine the influence of increased incidental 
mortality on the Atlantic surfclam ( Spisula solidissima ) stock and commercial fishery in the Mid-Atlantic Bight. Tabulated 
are the proportion of simulations where metrics used to evaluate the Atlantic surfclam population and the effect of area 
management on the commercial industry were significantly greater under alternative management with 0% or 20% inci- 
dental mortality using closure location rule 2 with present-day abundance. Rule 2 mandates that the cell with the highest 
density of small clams (number of clams per square meter) be closed each year. Number of clams per bushel is not included 
because present-day management always has higher numbers of clams per bushel. There were 9 simulations per percentage. 
Any fraction over 0.11 (1 significant difference out of 9) is unlikely to occur by chance (exact binomial test: a=0.05; Conover, 
1980). Size of clams is given as shell length (SL) in millimeters, closure duration is measured in years, and LPUE means 
landings per unit of effort. 
Definition of a small clam 
104 mm SL 93 mm SL 80 mm SL 64 mm SL 
Closure duration (yr) 
357357357357 
Stock density 
0% incidental mortality 
0.33 
0.44 
0.56 
0.44 
0.33 
0.44 
0.44 
0.67 
0.56 
0.22 
0.56 
0.00 
20% incidental mortality 
0.22 
0.33 
0.44 
0.56 
0.22 
0.44 
0.44 
0.56 
0.56 
0.22 
0.44 
0.22 
LPUE 
0% incidental mortality 
0.56 
0.67 
0.44 
0.56 
0.44 
0.33 
0.89 
0.67 
0.67 
0.56 
0.78 
0.22 
20% incidental mortality 
0.44 
0.44 
0.33 
0.67 
0.22 
0.44 
0.67 
0.67 
0.56 
0.33 
0.56 
0.44 
Number of 10' squares fished 
0% incidental mortality 
0.67 
0.22 
0.00 
0.11 
0.00 
0.00 
0.22 
0.00 
0.00 
0.22 
0.00 
0.11 
20% incidental mortality 
0.22 
0.00 
0.00 
0.11 
0.00 
0.00 
0.22 
0.00 
0.00 
0.11 
0.11 
0.00 
Total distance traveled 
0% incidental mortality 
1.00 
1.00 
0.89 
1.00 
0.89 
0.78 
0.89 
0.89 
0.89 
0.89 
0.78 
1.00 
20% incidental mortality 
0.44 
0.67 
0.67 
0.33 
0.67 
0.56 
0.22 
0.56 
0.67 
0.67 
0.56 
0.67 
cruitment. A net downcoast drift of larvae previously 
identified in larval dispersion studies was not included 
because postsettlement mortality appears to have a 
much larger effect on patchiness (Zhang et al., 2015, 
2016): postsettlement mortality was incorporated into 
the model as patchy recruitment. Additional assump- 
tions were made regarding the influence of climate 
change on the stock and commercial fishery over the 
simulated timespan of fishing years used to compare 
performance metrics (76 years). Climate change will 
likely continue over the next 76 years (Scavia et al., 
2002; Feely et al., 2009); it follows that changes in the 
population dynamics and range of the Atlantic surfclam 
also will occur (e.g., Munroe et al., 2016). The extent to 
which climate change will influence the Atlantic surf- 
clam stock is impossible to assess; therefore, the set of 
simulations used in this study does not include antici- 
pated future conditions. Even if the geographic range 
of clams was to change over the coming 76 years, the 
outcomes of area management discussed here rely pri- 
marily on a constant ambit of physiological responses 
by the Atlantic surfclam within its habitable range and 
on the recognition that the Atlantic surfclam fishery 
has a limited ambit to adapt to changes in Atlantic 
surfclam density, whether that density increases or 
declines (Powell et al., 2016). Additionally, realistically 
predicting the improvement in vessel technology and 
its influence on a captain’s skill and vessel economics 
is totally speculative. It may be assumed that devel- 
opments will occur that increase vessel and harvest 
efficiency (i.e., become more fuel efficient, provide im- 
proved onboard refrigeration); however, unlike the gear 
of many fisheries, the efficiency of hydraulic dredges is 
already near 80% on good fishing grounds, so that sub- 
stantial improvements in catch efficiency are unlikely. 
The extent to which these developments will affect the 
stock and commercial industry over a 76-year time 
span is unquantifiable, but such changes are unlikely 
to drastically change the outcome of area management 
as simulated in this study, because these outcomes are 
primarily influenced by varying fishing pressure across 
the stock under a defined FMP quota cap. The area 
management options presented in this study could be 
implemented long before major changes in the fleet con- 
figuration could take place. For this reason, changes in 
boat characteristics and the skill of captains are held 
constant over the 76-year period of simulation. 
Influence of area management on Atlantic surfclam stock 
Performance metrics used to evaluate the influence of 
area management on the MAB Atlantic surfclam stock 
