Nelson: Abundance, growth, and mortality of young-of-the-year Lagodon rhomboides 
317 
trawl made at each random site were used to ensure 
independence of observations. Data from 1989-94 
were combined to examine within-year trends rather 
than year-to-year variability. 
Factors influencing spatial YOY abundance 
I examined variation in YOY pinfish abundance in 
shallow-water areas for year, deployment technique, 
month, zone, sediment type (mud or sand), absence 
or presence of bottom vegetation (mostly seagrasses), 
temperature, and salinity effects by bay. Spring catch 
data (transformed by using ln(x+l) prior to analy- 
sis) from the first seine haul at each randomly se- 
lected site were analyzed with general linear models 
(GLM; Hilborn and Walters, 1992) and PROC GLM 
(SAS Institute, 1988). Year, month, deployment tech- 
nique, zone, sediment type, and bottom vegetation 
were treated as main effects, and temperature and 
salinity (transformed by using In (x+ 1 ) prior to analy- 
sis) as covariates. All first-order interactions of the 
main effects were also tested. Any variable or first 
order interaction not significant at a = 0.05 with type- 
III (partial) sum of squares was dropped from the 
initial GLM model and the analysis was repeated. 
In addition, least squares means and their 95% con- 
fidence intervals (Searle et al., 1980; SAS Institute, 
1988) from the GLM’s were back-transformed (Sokal 
and Rohlf, 1981) to examine significant abundance 
and main effect relationships. 
Initial analyses revealed that the only significant 
first-order interactions were related to the random 
selection of zones for sampling. Because these inter- 
actions were not considered relevant to this study, 
they were absorbed in the error term, and the main 
effects and covariates were retested. 
Factors influencing YOY annual abundance 
To determine if annual variations in YOY abundance 
were correlated with variations in temperature, I 
compared annual relative abundance indices (least 
squares means for the effect of year) to monthly 
means of sea-surface temperature before and dur- 
ing the first appearance of YOY pinfish, using 
Pearson product moment correlation (Sokal and 
Rohlf, 1981; Tyler, 1992). Temperature data were 
obtained from the National Oceanic and Atmospheric 
Administration’s (NOAA) oceanographic monthly 
summary series. 
I also used Pearson product moment correlation 
to determine if annual variations in YOY relative 
abundance were correlated with variations in adult 
abundance. Adult (>80 mm SL) pinfish abundance 
indices were derived from data collected in the Ma- 
rine Recreational Fisheries Statistics Survey 
(MRFSS on Florida’s west coast in 1988-93 )(U.S. 
Dep. Commer., 1990; 1992). The GLM approach was 
used only to derive annual least-squares mean catch- 
per-intercept estimates (relative abundance) by ad- 
justing the total number of fish caught per intercept 
for the classification variables of two-month sampling 
wave, fishing mode (party or charter boat, private or 
rental boat, or shore-based fishing boat), area fished, 
counties where interviews were conducted, and for 
the covariates of number of anglers per intercept and 
hours fished by anglers. All variables were signifi- 
cant contributors to the overall variation in catch 
rates in Tampa Bay (model: F | 28 3853] =11.55, P<0.001, 
r 2 =0.08), but only year, sampling wave, county, and 
hours fished by anglers were significant for Char- 
lotte Harbor (Model: F [20 10601 =5.74,P<0.001, r 2 =0.10). 
Growth 
I examined annual growth of YOY by estimating in- 
stantaneous growth rates ( G ) using mean lengths for 
each bay and year. Growth was estimated with the 
following model: 
In L, = In L 0 +Gxt , 
where G = the instantaneous growth rate (per 
month); 
L f = monthly mean length (mm); 
L 0 = the theoretical length at which pinfishes 
recruit to each bay; and 
t = time in months (Ricker, 1975; DeAngelis 
et al., 1980). 
Mortality 
Daily instantaneous total mortality rates were esti- 
mated for each bay population of pinfish by means 
of the relationship 
where Z = the daily instantaneous total mortality; 
and 
N = the index of relative abundance at months 
t and t + 1 (Ricker, 1975). 
Monthly indices of relative abundance from fixed 
seine stations were used in the equation. Although 
immigration and emigration in the shallow-water 
areas can bias the rate of decline in abundance used 
