Workshop Proceedings: Short Papers

Applications of underwater acoustics data in fisheries management for spotted seatrout, Cynoscion nebulosus, in estuaries of South Carolina

Bill Roumillat1, Myra Brouwer2

Marine Resources Research Institute, South Carolina Department of Natural Resources, 217 Ft. Johnson Rd., Charleston, SC 29412.



The spotted seatrout, Cynoscion nebulosus, is an estuarine-dependent member of the family Sciaenidae. Spotted seatrout are year-round residents of estuaries along the South Atlantic coast and spawning takes place inshore and in coastal areas (McMichael and Peters, 1989; Luczkovich et. al., 1999). During summer months, male spotted seatrout produce "drumming" sounds, this resulting from the contraction of the swimbladder by specialized muscles which are seasonally hypertrophied from the abdominal hypaxialis muscle mass (Fish and Mowbray, 1970; Mok and Gilmore, 1983). Direct involvement of sound production with spawning has been shown for this and other sciaenids (Mok and Gilmore, 1983; Saucier et al., 1992; Saucier and Baltz, 1993; Luczkovich et al., 1999). By listening to these sounds during evening hours (Holt et al. 1985) using hydrophone equipment we determined the locations, seasonality and diurnal periodicity of spawning aggregations in Charleston Harbor (Saucier et al., 1992; Riekerk et al., unpublished data).

Spotted seatrout are group-synchronous spawners with indeterminate fecundity. As such, they release gametes in several batches over a protracted spawning season and total fecundity is not fixed prior to the onset of spawning (Wallace and Selman, 1981). The spawning season extends from April through September along the South Atlantic and Gulf of Mexico coasts (Overstreet, 1983; Brown-Peterson et al., 1988; McMichael and Peters, 1989; Wenner et al., 1990; Saucier and Baltz, 1993). As in other indeterminate spawning fish, annual fecundity in this species is dictated by the number of oocytes released during each spawning event (batch fecundity, BF) and the number of such spawning events during the course of the season (spawning frequency, SF). Estimation of annual fecundity (AF) is intuitively necessary to determine the contribution of an entire spawning season, and is made even more useful for fisheries management purposes if separated by size class or age cohort within a population (Prager et al., 1987; Zhao and Wenner, 1995).

Behavior patterns based on acoustic data enabled us to target females in imminent spawning condition, then carry out oocyte counts for batch fecundity estimation. Additional random sampling in other estuarine areas of the SC coast provided the data necessary to estimate spawning frequency for each of the three dominant age classes (ages 1—3) in our waters. Ultimately, our annual fecundity estimates for each age class will facilitate management of this species in South Carolina.

Estimation of batch fecundity

We conducted sampling for batch fecundity studies during two consecutive afternoons fortnightly from the middle of April through the first week of September 1998, 1999 and 2000. We deployed a trammel net from a shallow water boat at pre-selected sites in Charleston Harbor. Sites were chosen based on proximity to known spawning locales established through hydrophone work. Water depth at the sampling sites ranged from 0.3 to 1.5 meters and sampling was conducted during the afternoon (1400-1800h) high tide. Male spotted seatrout, identified by their drumming sounds, were measured and released on site. Females were brought back to the laboratory for processing. We recorded standard life-history parameters for each specimen, preserved sagittal otoliths for aging and removed sections of the posterior portion of each ovary for histological work. In addition, whole ovaries that evidenced oocyte maturation were fixed in 10% buffered seawater formalin for enumeration of hydrated oocytes (Hunter and Macewicz, 1985).

One hundred and thirty-five ovaries were used to estimate batch fecundity of spotted seatrout aged 1-3. We re-weighed preserved ovaries to the nearest 0.01 g and randomly extracted 130-150 mg aliquots from three of eight possible regions in the ovary (four per lobe). We counted hydrated oocytes and used their mean number per subsample to estimate the total number of oocytes in the ovary. To investigate the relationships between batch fecundity and length, somatic weight (ovary-free body weight), and age we used linear regression on log-transformed data. We used ANOVA on ranked data for comparisons of mean batch fecundity among ages, months and years.

As expected, we found a significant difference in mean batch fecundity among age classes (Kruskal-Wallis test, P< 0.05). Age 1 spotted seatrout, produced an average of 145,452 oocytes per spawn. Fish aged 2 and 3 spawned an average of 291,123 and 529,976 oocytes per batch, respectively. Therefore, mean batch fecundity was compared among months and years for each age class separately. There were no significant inter-annual or monthly variations in mean batch fecundity for any of the three age classes.

Pooling data across years, total length explained 69% of the variability in spotted seatrout batch fecundity. Batch fecundity showed a similarly strong relationship to female somatic (ovary-free) weight but did not relate quite as strongly to age. The equations below describe these relationships:

Log BF = 3.134(Log TL) — 2.653 (r2 = 0.686) P<0.05

Log BF = 1.011(Log OFWT) + 2.709 (r2 = 0.675) P<0.05

Log BF = 0.288(Age) + 4.844 (r2 = 0.586) P<0.05

Calculation of spawning frequency

We obtained samples for spawning frequency determination during the course of stratified random trammel net sampling in several estuaries along the SC coast. Each stratum was sampled once a month throughout the year during ebbing tide. However, we only used spotted seatrout samples obtained during summer months (1 May through 31 August) for this study.

We calculated monthly spawning frequencies for age classes 1-3 using the postovulatory follicle method of Hunter and Macewicz (1985) where spawning frequency is the inverse of the proportion of ovaries with postovulatory follicles (POF) < 24 h old among mature and developing females.

Over a decade of sampling the Charleston Harbor estuarine system we have observed that, among females captured in shallow water during the spawning season, oocyte maturation begins at about 1200h. From mid to late afternoon these females leave the marsh edge for deeper water to spawn. Our hydrophone surveys have indicated that spawning typically begins around 1800h and ceases around 2200h. Females then return to feeding grounds near the marsh where they are available to our sampling gear. Knowledge of this reproductive behavior enabled us to target spotted seatrout in the mid-late afternoon specifically to capture fish with late-maturing oocytes for batch fecundity estimation. Females that were back in the shallows after having spawned the previous evening were available for capture during daytime sampling. In addition, we carried out round-the clock sampling on two occasions during the 2000-spawning season. Samples from this effort allowed for the calibration of criteria used to age POFs.

A total of 941 female spotted seatrout, captured during the spawning seasons of 1998,1999 and 2000 was examined to determine spawning frequency. Females used to determine SF ranged in length from 240 mm to 542 mm (mean 340 mm) and in age from 1 to 5. However, 97% of the specimens belonged to age classes 1-3. Thus, reproductive parameters are presented only for these age classes.

Small sample sizes prevented calculation of monthly spawning frequencies for each age class by year. Thus, data for all three years were pooled to obtain a single monthly spawning frequency estimate by age class (Table 1). Overall, spotted seatrout ages 1-3 in South Carolina spawned every 4.4 days or roughly 28 times during the reproductive season.

Estimation of annual fecundity

We calculated monthly egg production (MEP) by multiplying the monthly spawning frequency by the mean monthly batch fecundity for each specimen. Because not all age-1 female trout were mature at the beginning of the spawning season, the fraction of mature age-1 females obtained from a previous study (Wenner, unpublished data) was used to refine the MEP estimate. MEP estimates were then summed to arrive at an annual fecundity estimate for each age class (Table 1). We used linear regression on log-transformed data to investigate the relationship between annual fecundity and age and thus predict annual fecundity for spotted seatrout aged 4 and 5. Age explained 98% of the variability in annual fecundity for age classes 1—3. From this relationship, the predicted annual fecundities for age classes 4 and 5 were 43,752,211 and 101,157,945, respectively.


Table 1. Fecundity parameters for C. nebulosus ages 1 — 3 from South Carolina estuaries. BF= batch fecundity in numbers of oocytes; SF= spawning frequency expressed as the number of spawns per month; MEP= monthly egg production= (BF*SF)%mature. Annual fecundity is the sum of mean monthly MEP values for each year class and represents the total number of oocytes produced by any given female from 1 May to 31 August. Numbers in parentheses indicate sample size.



Mean BF


% mature

Mean MEP



117,760 (12)

4.18 (89)




135,403 (16)

9.40 (166)




141,237 (16)

6.54 (185)




176,594 (18)

4.57 (129)



Annual fecundity = 3,286,328



280,724 (34)

6.80 (114)




307,322 (10)

7.60 (79)




370,170 (1)

9.04 (48)




307,195 (7)

6.34 (44)



Annual fecundity = 9,538,533



487,475 (13)

7.42 (46)




519,630 (4)

9.12 (23)




765,911 (2)

3.1 (10)




590,994 (2)

11.61 (8)



Annual fecundity = 17,591,852

We expanded annual fecundities relative to the abundance of each age class in our samples for the three years of the study. We estimated that the overall average contribution from age 1 fish to the reproductive output for the season was approximately 25% whereas fish aged 2 and 3 contributed 34% and 19% of oocytes, respectively. Ages 4—5, which comprised less than 3% of specimens sampled, each contributed about 11% based on predicted annual fecundity values.


Attempts at estimating the spawning potential of a species have rarely incorporated spawning behavior into the methodology used in capturing the animals primarily due to limitations of the sampling gear. Moreover, estimates of fecundity (batch numbers and spawning frequencies) have relied on the assumption that the collection of a reasonable size range of adult females during established spawning periods should be sufficient to cover all phases of reproductive activities (DeMartini and Fountain,1981;Lisovenko and Adrianov, 1991). Our choice not to use the relative occurrence of hydrated oocytes to estimate spawning frequencies was based on our knowledge of the spawning behavior of this species. Previous work conducted in the study area (Riekerk et al., unpublished data) established the location and timing of spawning activities allowing us to focus our sampling efforts in shallow waters near known spawning locations to collect females with late maturing oocytes. This constant loss of late maturing females from the fish available to our nets in shallow water would have decreased the relative abundance of this maturity stage in our samples. Therefore, using the relative number of late maturing oocytes for spawning frequency calculations would have resulted in an underestimate of spotted seatrout reproductive potential.

Because obtaining representative numbers of animals with late-maturing oocytes is not often feasible, researchers have relied on the relative abundance of postovulatory follicles to calculate spawning frequencies (i.e.Hunter and Goldberg, 1980; Hunter et al.,1986; Brown-Peterson et al., 1988; Fitzhugh et al., 1993; Taylor et al., 1998; Macchi and Acha, 2000; Brown-Peterson and Warren, 2001; Nieland et al., 2002). This method has depended on the ability to time the disappearance of these structures. Our diurnal sampling of reproductively active spotted seatrout during warm water conditions allowed us to establish criteria to accurately estimate the age of POFs throughout the spawning season. Furthermore, we were able to verify our assessments by sampling around the clock on two occasions to collect fish over the time period immediately following a spawn. This would not have been possible had we failed to establish and verify the location of spawning aggregations with the use of passive acoustics.

The main impetus behind this study was to establish realistic annual fecundity estimates by age class that could be used in predictive modeling of the spotted seatrout population in coastal South Carolina. Herein we present equations relating fecundity to length and age that can be used to estimate the reproductive potential for each age class of spotted seatrout along the South Carolina coast. The average season-long oocyte output of age 1 fish was one-third that of age 2 (~3.28 M vs. 9.5 M). When analyzed in relation to the abundance of the other age classes, age 2 fish were predicted to contribute more overall fertilizable oocytes to the environment. Even though the average age 3 fish produced almost twice as many oocytes (17.5 M) than the average age 2, the abundance of age 3 trout in our estuarine samples was low enough to make their overall contribution to a season’s spawning effort only half that of 2 year-olds. This exemplifies the potential for error in estimating reproductive output based on the abundance of year classes, especially that of younger fish.


We thank members of the Inshore Fisheries Section of the South Carolina Department of Natural Resources for assisting in field data collection throughout this study (Dr. C. Wenner, J. Archambault, H. von Kolnitz, W. Hegler, E. Levesque, L. Goss, C. McDonough, C. Johnson, A. Palmer). Dr. C. Wenner, H. von Kolnitz and E. Levesque conducted age assessments. Histological processing was provided by C. McDonough, R. Evitt, A. Palmer and W. Hegler. C. McDonough, T. Piper, K. Maynard and R. Evitt assisted with oocyte counts. J. Archambault coordinated data management and Dr. C. Wenner and E. Levesque provided helpful suggestions on the manuscript. Funding for this study was provided by the National Marine Fisheries Service under MARFIN grant #NA77FF0550.


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