Simms et al.: Distribution, growth, and mortality of larval Istiophorus platypterus in the northern Gulf of Mexico 
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Table 1 
Mean environmental conditions (± standard deviation [SD] ) by oceanographic feature for ichthyoplankton collections in the 
northern Gulf of Mexico in 2005 and 2006. Environmental parameters were recorded at the surface at each sampling station. 
Feature 
Temperature (°C) 
Salinity (ppt) 
Dissolved oxygen (mg/L) 
Anticyclone 
29.1 (1.6) 
36.1 (0.4) 
6.8 (0.8) 
Front 
28.9(1.4) 
36.1 (0.4) 
6.6 (0.5) 
Open ocean 
29.3 (1.6) 
35.5(1.2) 
6.7 (0.8) 
Cyclone 
28.2 (2.0) 
35.6(0.6) 
7.2 (1.3) 
N t = N 0 e- Zt , (4) 
where N t - abundance at time t\ 
N 0 = estimated abundance at hatching; 
Z = instantaneous mortality coefficient (d); and 
t = otolith-derived age. 
Dry weight (mg) was calculated for all larvae with a 
measured length by using the length-weight relationship 
for sailfish larvae by Luthy et al. (2005): weight (mg) = 
0.002(SL[mm] ) 3012 . Weight-at-age data were fitted with 
exponential growth models to determine instantaneous 
weight-specific growth coefficients (G) for each survey 
by using the equation 
W t = W 0 e Gt , (5) 
where W t = dry weight (mg) at time t ; 
W 0 = estimated weight at hatching; 
G = instantaneous weight-specific growth coef- 
ficient (d); and 
t - otolith-derived age. 
Indices of stage-specific production potential were 
assessed for each cohort by examining the ratio of 
instantaneous weight-specific growth to daily mortal- 
ity ( G:Z ). This ratio incorporates growth and mortality 
and was used as an index of stage-specific production 
of larval cohorts (Rilling and Houde, 1999; Rooker et 
al., 1999; Wells et al., 2008). A cohort with a G.Z>1.0 
was considered to be gaining biomass, which indicates 
that individuals had increased survival and production 
potential (Houde and Zastrow, 1993; Wells et al., 2008). 
Hatch dates for larvae were determined by sub- 
tracting age from date of collection. Otolith-derived 
ages were used when available, and remaining ages 
were predicted by applying cohort-specific age-length 
keys. Given that larger, older larvae in our collections 
hatched earlier and experienced greater cumulative 
mortality than larvae that hatched later, adjustments 
for mortality were made to more effectively represent 
the hatch dates of survivors in our collections by using 
the equation 
N 0 = N t / e~ Zt , (Powell et al., 2004), (6) 
where N 0 = estimated number of larvae at hatching; 
N t = number of larvae at time t (N t = 1 because N 0 was 
calculated for each individual larva); 
Z = cohort-specific daily instantaneous mortality 
rate; and 
t = age of larva in days. 
Data analysis 
Spatial and temporal variation in environmental condi- 
tions and density of sailfish larvae was examined with a 
two-way analysis of variance (ANOVA) (factors: oceano- 
graphic feature and survey). Because of uneven repli- 
cates in 2005 and 2006, separate one-way ANOVAs were 
conducted to assess inter- and intra-annual variation in 
length and age of sailfish with year or survey as a fixed 
factor. In order to minimize heteroscedasticity, estimates 
of density were log^+1 transformed, whereas standard 
length and age data were log e transformed. In cases 
where variances were unequal, nonparametric analyses 
(Brown-Forsythe F-Test; Brown and Forsythe, 1974) were 
performed; however, results were consistent with para- 
metric tests (ANOVA) and thus only parametric analyses 
are presented. Post-hoc differences among levels of the 
main effect) s) were examined with Tukey’s honestly 
significant difference (HSD) test when variances were 
equal and with a Dunnett’s T3 test when variances were 
unequal (Zar, 1996). Analysis of covariance (ANCOVA) 
was used to test for spatial and temporal variations in 
growth and mortality (covariate: age) with models to 
determine if the slopes of the regression lines differed 
(slopes test). All data analyses were performed with 
SPSS, vers. 15.0 (SPSS Inc., Chicago, IL) with a=0.05. 
Results 
Environmental conditions 
Spatial and temporal variations in environmen- 
tal conditions were observed during Gulf collections. 
Temperatures were not significantly different among 
oceanographic features (ANOVA, F (3 270) = 2.2, P=0.09), 
albeit temperature was lowest within cyclones (28.2°C) 
compared with other oceanographic features (28.9- 
29.3°C) (Table 1). Mean temperature was 28.8°C and 
29.4°C in 2005 and 2006, respectively, and varied signifi- 
cantly among the five surveys (ANOVA, F {4 270) =354.0, 
