128 
Fishery Bulletin 1 10(1 ) 
Figure 2 
(A) Marine Resource Monitoring, Assessment, 
and Prediction (MARMAP) standard sampling 
stations on Georges Bank from 1977 to 1987, 
and (B) the U.S. Global Ocean Ecosystems 
Dynamics (GLOBEC) broad scale standard 
sampling stations surveyed from 1995 to 1999. 
Depth contours are given in meters (m). 
the modeled mortality rates to estimate the 
underlying on-bank loss due to starvation and 
predation. The equations used to estimate egg 
mortality (M observed ) were as follows: 
Cod ^observed = 8 ' 59 + 150 (M modeled^ 
r 2 =0.49, n-l\\ (2) 
Haddock M observed = 5.76 + 1.06 (M modeled ), 
r 2 = 0.17, 71 = 11. (3) 
The intercepts were used as the constant on-bank 
mortality and added to the yearly off-bank modeled 
mortality for an estimate of the total yearly mortal- 
ity rate. Although the regressions were not highly 
significant, they appeared to be a reasonable adjust- 
ment. About 6-9 %/d of the total egg mortality can 
be attributed to in situ processes leaving 10-14 %/d 
due to transport loss. Mountain et al. (2008) used just 
four years from the GLOBEC data and found similar 
on-bank mortality of 8-9 %/d from the regression 
intercepts. 
Larvae 
Mountain et al. (2008) found an inverse relationship 
between early larval cod and haddock mortality and a 
Georges Bank spring salinity anomaly for the GLOBEC 
years, which also was related to larval prey abundance 
(Buckley and Durbin, 2006). Mountain et al. (2008) 
also found a positive relationship between larval mor- 
tality and Georges Bank water temperatures for the 
same years; however, there was no relationship between 
temperature and recruitment. Nevertheless, we were 
not able to find a relationship between salinity or tem- 
perature and larval mortality when they were averaged 
over a spawning season. Estimating larval mortality 
without adequate survey data is difficult because of the 
complex interaction between growth and mortality and 
the increasing ability of the larvae to limit transport, 
