Gannon and Gannon: Passive acoustic assessment of soniferous fish density 
113 
Table 3 
Covariate parameter estimates from a multivariate analysis of covariance (MANCOVA) to investigate the relationships among 
the dependent variables received sound level (Level) and peak acoustic frequency (Frequency) of Atlantic croaker (Micropo- 
gonias undulatus) calls; the covariates dissolved oxygen concentration (DO), temperature (Temp), and trawl catch per unit 
effort of Atlantic croaker (CPUE); and fixed factors of month and habitat, and their interaction in North Carolina’s Neuse 
River estuary. 
95% Confidence interval for B 
Dependent variable 
Covariate 
B 
Standard error of B 
t 
P 
Lower 
bound 
Upper 
bound 
Level 
Intercept 
79.94 
10.33 
7.74 
<0.001 
59.49 
100.39 
DO 
0.87 
0.31 
2.77 
0.006 
0.25 
1.49 
Temp 
1.01 
0.40 
2.51 
0.013 
0.21 
1.80 
CPUE 
0.94 
0.59 
1.60 
0.113 
-0.23 
2.10 
Frequency 
Intercept 
561.36 
157.92 
3.56 
0.001 
248.85 
873.87 
DO 
-8.88 
4.79 
-1.86 
0.066 
-18.36 
0.59 
Temp 
11.41 
6.12 
1.87 
0.064 
-0.69 
23.52 
CPUE 
10.83 
8.96 
1.21 
0.229 
-6.90 
28.57 
level for Atlantic croaker calls, which may have been due 
to low statistical power (power=0.35; Table 2). There was 
a high degree of spatial overlap between measures of 
Atlantic croaker density derived from trawl CPUEs and 
calling index, especially in the mid-river habitat during 
August. With CART analysis we identified a significant 
relationship between calling index and CPUE (Fig. 3). 
Taken together, these data indicate that passive acoustic 
techniques have the potential to be a means of assessing 
trends in abundance and habitat selection for soniferous 
fishes. However, the relationships between data derived 
from passive acoustics and those from traditional cap- 
ture methods are not simple. Further development of 
analytical methods may clarify these relationships. Use 
of a calling index with a resolution greater than four 
levels; the ability to quantify the Atlantic croakers’ con- 
tribution to ambient noise levels with greater precision; 
and a better understanding of how the acoustic source 
levels of individual fish are affected by dissolved oxygen 
concentration, temperature, and body size may result in 
an improved ability to estimate Atlantic croaker density 
based on passive acoustic data. 
An important result of this study is the demonstra- 
tion that environmental factors (e.g., dissolved oxygen, 
temperature, and habitat) appear to influence the rela- 
tionship between acoustically derived indices of Atlantic 
croaker density and trawl CPUE. Many factors can in- 
fluence calling behavior, spectral qualities of calls, and 
distance over which calls transmit. For example, Con- 
naughton et al. (2000) showed that the sound pressure 
level, pulse repetition rate, and dominant frequency of 
disturbance calls made by weakfish ( Cynoscion regalis) 
increased with increasing temperature and that domi- 
nant frequency varied inversely with fish size. Thus, 
temporal trends in peak frequency of Atlantic croaker 
calls likely resulted from changes in temperature and 
growth of the juvenile fish (Fig 2, A and E). Changes in 
Table 4 
Williamson’s index of spatial overlap between trawl 
catch per unit of effort of Atlantic croaker ( CPUE ) and two 
passive acoustic measures of Atlantic croaker ( Micropogo - 
nias undulatus) density, calling index (Cl) and received 
sound level of calls (RL), in the Neuse River estuary from 
June to October of 2000 (* indicates P<0.01). 
Cl and CPUE 
RL and CPUE 
Jun-Oct 
1.150* 
1.002 
Jun 
1.083 
1.036 
Aug 
1.264* 
0.959 
Oct 
1.092 
1.012 
Creeks 
1.019 
1.018 
River edge 
1.132* 
0.989 
Mid-river 
1.478* 
1.061 
dissolved oxygen concentration may have also affected 
calling behavior, but this topic has not been well stud- 
ied in sciaenids. 
Propagation of sound is affected by absorption, spread- 
ing loss, and scattering (reflection and refraction) (Rich- 
ardson et al., 1995, p. 27-30); therefore, factors such as 
water depth, temperature gradients, density gradients, 
turbulence, suspended particles, bottom topography, 
and substrate type affect how sound travels and how 
efficiently sound is detected. That the highest spatial 
overlap values between CPUE and calling index (up to 
1.48) occurred during August in the mid-river habitat 
likely reflects the high degree of patchiness in Atlantic 
croaker distribution related to the patchiness of hypoxia 
in this habitat. Also, the mid-river habitat was deeper 
and had smoother bathymetry than the other habitats, 
which may have resulted in a more uniform transmis- 
