© 2004 by ICES/CIEM International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer
A temperature-dependent reproductive model for spotted seatrout (Cynoscion nebulosus) explaining spatio-temporal variations in reproduction and young-of-the-year recruitment in Florida estuaries
Fish and Wildlife Conservation Commission, Florida Marine Research Institute 100 8th Avenue SE St. Petersburg, FL 33710, USA
*Current address: Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory, Pakefield Road, Lowestoft, Suffolk NR33 0HT, UK. e-mail: S.Kupschus{at}cefas.co.uk.
Spotted seatrout (Cynoscion nebulosus) exhibit various seasonal patterns of reproduction and juvenile recruitment in estuaries across their range. To explain this variability, data on the reproductive state of 1674 individual females from the Indian River Lagoon were used to develop a generalized additive model (GAM) describing the relationship between reproduction and local environmental conditions. The model predicted that optimum spawning conditions exist at a water temperature of 29°C, indicating that if this temperature was exceeded during the spawning season, spawning activity would be temporarily curtailed, which would lead to a bimodal recruitment curve. In contrast, daily mean water temperatures below the optimum condition would result in a single recruitment peak. The reproductive model was largely consistent with historical information on spotted seatrout spawning seasonality along the gulf and Atlantic coasts of the US. Factors other than temperature (i.e., hours after sunset, lunar period and size and condition factor of females) were also found to regulate reproductive activity. Model predictions of the number of recruits based on local temperature regimes during the spawning season were compared to actual catches of juvenile spotted seatrout in three Florida estuaries. The reproductive model was able to predict the timing and modality of recruitment, but the relative amplitude of the fluctuations in abundance was dampened considerably compared to the observed variation.
Keywords: Cynoscion nebulosus, seasonal recruitment patterns, spatial variation in reproduction, temperature-dependent reproduction
Received 17 February 2003; accepted 3 October 2003.
 |
1 Introduction |
|---|
 Top 1 Introduction 2 Materials and methods3 Results4 DiscussionReferences |
|---|
Spotted seatrout (Cynoscion nebulosus Cuvier 1830) range along the east coast of the US from Virginia south to Florida and along the gulf coast up to Mexico, where they are exploited both as a recreationally targeted sport fish and as a commercially exploited food fish. In Florida, conservation measures to protect the species have largely focused on catch-at-age analysis, but an important and yet poorly understood component of the stock dynamics are the factors driving recruitment to the fished stock. The stock–recruit relationship is poorly defined suggesting that environmental factors play an important part in the recruitment process.
Reproduction, as part of the recruitment process, has been documented to be highly variable, temporally and spatially. Texas populations have been characterized as having two spawning peaks based on histological examination of ovarian tissue (Brown-Petersen et al., 1988) and gonadosomatic indices (GSI; Maceina et al., 1987; Colura et al., 1988). Bimodal reproduction patterns were also indicated for Louisiana populations by GSI (Hein and Shepard, 1979; Helser et al., 1993) and by hydrophone investigations of spawning aggregations (Saucier and Baltz, 1993). In contrast, a unimodal reproductive pattern was evident in a hydrophone study of a South Carolina population (Saucier and Baltz, 1992) and in a combined histological/hydrophone study of a Georgia population (Lowerre-Barbieri et al., 1999). In addition to differences in reproductive modality, distinct differences in the length of the spawning season were also apparent, with the length of the spawning period generally inversely related to latitude (Hein and Shepard, 1979).
Both unimodal and bimodal reproductive patterns have been documented for Florida populations. Nelson and Leffler (2001) inferred two spawning peaks from juvenile abundances in Charlotte Harbor (CH) and Tampa Bay (TB), whilst they suggested unimodal reproduction for Choctawatchee Bay. Similarly, Tucker and Faulkner (1987) found unimodal and bimodal reproduction in pond experiments under ambient conditions in the Indian River Lagoon (IRL) on two consecutive years. GSI values of spotted seatrout populations in Florida's Panhandle region (DeVries et al., 1997) and in Cedar Key (Moody, 1950) as well as juvenile abundances in Naples Bay (Peebles and Tolley, 1988) indicated only a single spawning peak.
The estuary-specific pattern and lengths of the spawning season might suggest that reproduction locally is governed by genetic differences and that endogenous reproductive rhythms evolved to maximize survival and growth of juveniles under long-term average environmental conditions (Bye, 1990). However, observed differences may equally well be explained by the direct influence of variable environmental conditions on reproductive activity, allowing for a single model to describe reproductive timing for the species.
This study sets out to examine the effects of temperature on reproduction, and to investigate if predicted egg production from such a model projected forward can explain regionally highly variable temporal trends in recruitment.
|
2 Materials and methods |
|---|
|
Top1 Introduction2 Materials and methods3 Results4 DiscussionReferences |
|---|
2.1 Sampling
Mature females were sampled at four documented spawning sites in the IRL (Fort Pierce, Longpoint Park, the northern Banana River and Black Point) on the east coast of central Florida (Figure 1) from January 1996 to December 1997. Sampling consisted of three to five dedicated gillnet trips per month during the spawning season (April–October) and fewer trips during the rest of the year (November–March). Nets used were one or more of the following: (a) 550 m x 2.4 m monofilament net with equal sections of 76, 98, and 101 mm stretch mesh, (b) 550 m x 2.4 m monofilament net with equal sections of 76, 89, and 101 mm stretch mesh, and (c) 274 m x 1.8 m monofilament net constructed entirely of 114 mm stretch mesh. Deployment was predominantly around dusk (the reported time of maximum spawning; Saucier and Baltz, 1992; Lowerre-Barbieri et al., 1999) over areas of seagrass-covered shoals in the proximity of topical relief and retrieval occurred between 1 and 3 h later. Samples not collected at dusk were used to estimate the daily periodicity of reproductive activity and were largely derived from two 24-h sampling events in the Banana River, with gear being retrieved and rest every 2 h. Additionally, samples collected by other methods and during other studies were incorporated into the analysis.
|
Date, time of day (recorded in Eastern Standard Time – EST), location, and surface water temperature (°C) were recorded for catches of mature females. If suitable temperature data were unavailable, samples were eliminated from the analysis. Photoperiod (day length in h) and hours after sunset were calculated from information on latitude, longitude, and EST.
Females caught were placed on ice and returned to the laboratory, where total weight (g), gonad weight (g), and total length (TL in mm) were measured. To provide a measure of the energy reserves, a gonad-free-weight (W–g) condition factor (C) was calculated as
|
|
Sections from the right ovary were fixed in 10% buffered formalin, soaked in water, and stored in 70% ethanol prior to histological preparation. Subsequently, glycol-methacrylate-stained histology sections were prepared by using a modified periodic-acid-Schiff's technique, with Weigert's iron hematoxylin as nuclear stain and metanil yellow as counterstain (Quintero-Hunter et al., 1991).
The ovarian tissue was microscopically examined and samples were sorted in eight reproductive stages in accordance with the classification used by Lowerre-Barbieri et al. (1996). Only females with hydrated oocytes (Stage 4) were classified as spawning on the day of capture and all others as not spawning.
Juvenile collections were made from January 1996 to December 1999 by the Fisheries-Independent Monitoring (FIM) Program in three estuaries (TB, CH and IRL; Figure 1). Because of its latitudinal expanse (120 km), IRL was split into a northern (IRN) and a southern region (IRS) at Cape Malabar, coincident with the reported temperature-induced zoogeographic boundary (Gilmore, 1995; Kupschus and Tremain, 2001). Sampling for juveniles did not commence in IRS until 1999.
A monthly multigear (trawls sampling depths >1.8 m; seines depths <1.5 m), stratified-random sampling design, proportionally stratified by the presence or absence of bottom and shore vegetation and logistically implemented zones, was used to establish relative abundances of juvenile fish. Seines were deployed in one of three different ways: boat sets, beach sets, and offshore sets (Nelson, 1998). From each randomly collected sample, spotted seatrout >15 mm and 
50 mm standard length (SL) were used in the analysis. Catches from both types of gear were summed over each calendar month for each estuary or estuarine region distinguished. Changes to spatial and gear effort allocations have been implemented in all three estuaries, invalidating absolute interannual comparisons of juvenile abundances. However, effort was constant within any one year, so that intra-annual abundances relative to total annual catches for each estuary can be used to reflect relative seasonal dynamics of juveniles. Impartial measures of the surface temperature regime in each estuarine region were developed to independently predict its relative reproductive output. The average daily surface temperature was estimated using a cubic spline smoother with 15 degrees of freedom from all stratified-random samples collected by the FIM Program over the January 1996 (January 1997 for IRS) to December 1999 period.
2.2 Models
The probability of a female being in spawning condition (p) was modelled as a generalized additive model (GAM) using a logit link function. This allowed for the examination of the binomial response variable (spawning or not spawning on the day of capture), whilst at the same time allowing for multiple relationships with non-linearly related independent variables (Hastie and Tibshirani, 1990). The general form of the GAM was
|
|
|
|
is the intercept of the additive predictor, f is the spline function of the ith smoothed-dependent variable (X) and 
is a Gaussian error term. Surface temperature, days past the full moon, photoperiod, time after sunset, TL, and gonad-free-weight condition factor were included as independent variables in the initial model. The final form of the model was selected by increasing and decreasing the degrees of freedom of the spline functions in a bi-directional manner, using the Akaike information criterion (AIC) to determine the most parsimonious model (McCullagh and Nelder, 1989). The model selected was then used to predict temporal changes in the reproductive potential of an average female (398 mm SL, condition factor = 0.892) in each estuarine region at the peak daily spawning time based on the interpolated regional temperature for that day.
Comparing predicted reproductive output with observed abundances of juveniles of a certain size requires an adjustment for the growth experienced between spawning and sampling. To this aim, a temperature-dependent growth model was developed from data published in Alshuth and Gilmore (1994). Growth was modelled as a GAM describing TL as a function of age in days (a) and water temperature (T) using an identity link function (assuming a normal error distribution)
|
|
From the model, a matrix of daily growth increments was created, starting with an initial length of 1.5 mm at the day of hatching, which occurs on the day following spawning (Alshuth and Gilmore, 1993). The growth of individual daily cohorts of juveniles was then simulated in each estuarine region based on the smoothed temperature estimates for each day. For comparison to juvenile catches, predicted TL was converted to SL using the formula provided in Hein et al. (1980).
Simulated relative reproductive output and juvenile growth were combined to predict relative intra-annual dynamics in spotted seatrout abundances in each region, assuming a fixed natural mortality over all months and in all regions. The daily spawning probability was calculated to cover the entire period during which juveniles were predicted to be available to the gear (15 mm < SL 
50 mm). Each daily cohort was then discounted by the mortality rate (M=5.11 yr–1; monthly mortality of 34.7%) taken from an Everglades National Park study (Rutherford et al., 1989). The resulting daily measure of juvenile abundance was summed by month and expressed as a percentage of the total abundance over all months. To compare predicted and observed relative abundance, monthly catches were analogously expressed as a percentage of total annual catches. Significance of the correlation between observed and predicted values were tested by Spearman rank correlation.
|
3 Results |
|---|
|
Top1 Introduction2 Materials and methods3 Results4 DiscussionReferences |
|---|
3.1 Reproduction
A total of 1674 female spotted seatrout, collected on 133 successful sampling days, were sacrificed for histological examination. All females were found to be mature, and the 195 reproductively active females (8.6% of all females and 18.4% of the females caught between April and September) were caught between April and September in water temperatures ranging from 24.0 to 32.5°C.
The most parsimonious GAM model, as selected by the AIC, explained 38.2% of the total deviance with 15.8 model degrees of freedom. Dependent variables included in the model in decreasing order of importance were water temperature, hours after sunset, condition factor, TL, and days past the full moon (Figure 2). The model reached a maximum spawning probability of 0.42, suggesting that during optimum spawning conditions, females on average spawn every 2.38 days. The temperature partial reached a maximum at 29°C, declining at both higher and lower temperatures, indicating spawning probability peaks at 29°C. The partial effect of hours after sunset was also unimodal, reaching a peak about 2 h before sunset. The gonad-free-weight condition factor and TL partial effects indicated that fish with a high weight-to-length ratio, as well as larger fish in general, were more likely to spawn on a given date than more poorly conditioned or smaller females were. The model also indicated an almost linear decline in the propensity to spawn during the entire lunar cycle following the full moon, a result supported in the raw data.
|
Photoperiod, in the absence of temperature, explained a significant portion of the total deviance in the model, but it was dropped by the selection procedure when temperature was included. Temperature, rather than photoperiod, was included in the final model because it explained a larger portion of the deviance, suggesting that there was an effect of temperature beyond the component shared by the two correlated variables.
3.2 Predicted seasonal patterns of juvenile abundance
The model clearly predicted seasonally bimodal reproduction in CH and IRS, with the temporary decrease in reproductive activity corresponding to the hottest months (July and August) of the year (Figure 3). In IRN and TB, the predicted summer reproductive hiatus was generally much less pronounced in all years, and it was completely absent in cooler summers (IRN: 1999; TB: 1996, 1999; Figures 3 and 4). Temperature data for the four estuarine regions examined in this analysis indicated that CH and IRS generally had higher temperatures than TB and IRN did. However, local estuarine conditions do not necessarily follow the overall regional trend, which in itself is variable over time. All regions in all years experienced temperatures in excess of the predicted optimum reproductive conditions during the summer months (Figure 4).
|
|
3.3 Comparison of observed and predicted juvenile abundance
During stratified-random sampling 1994 (CH), 1685 (IRN), 265 (IRS), and 3450 (TB) juvenile spotted seatrout 15 mm < SL
50 mm were collected over the study period 1996–1999. The highest monthly juvenile spotted seatrout abundances were reported roughly one month after the highest predicted relative reproductive effort (Figure 3), with juveniles being available to the gear between 43 and 69 days, dependent on temperature.
The period during which juvenile spotted seatrout 50 mm SL were predicted to occur in each estuary coincided well with the period during which catches of juveniles were made, suggesting that the model predicted the spawning season accurately (all Spearman rank correlation coefficients significant at P=0.05: 0.82, 0.82, 0.62 and 0.83 for CH, IRN, IRS and TB, respectively). Additionally, the juvenile abundances predicted from the model overall resembled the types of temporal recruitment patterns observed in the three estuaries. Within the spawning season, the timing of increases and decreases in reproductive activity appeared to be predicted well particularly in TB and CH, although the amplitude of the fluctuations during the spawning season was underestimated.
|
4 Discussion |
|---|
|
Top1 Introduction2 Materials and methods3 Results4 DiscussionReferences |
|---|
Temperature was the most important predictor of spotted seatrout reproductive activity in the IRL, as reported for other species, particularly those occurring in low latitudes (Taylor, 1990; Wieland et al., 2000). However, unlike the linear relationship hypothesized for spotted seatrout by Brown-Petersen and Thomas (1988), temperature was unimodally related to reproductive activity. The likelihood of encountering reproductively active females increased until the optimum water temperature of 29°C was reached and then declined at higher temperatures. Consequently, the model implied that spotted seatrout populations in estuaries with daily mean summer temperatures below the optimum would have only one spawning peak and that those populations experiencing water temperatures consistently above the optimum would exhibit a temporary decline in reproductive effort during the hottest months of the spawning season. In addition, conditions suitable for spawning should be reached earlier in the year and be maintained longer in warmer estuaries or during warmer years leading to a generally more protracted spawning season in the southern part of the species' range (Bye, 1990).
These findings are generally consistent with the documented patterns of reproduction in Florida spotted seatrout (Moody, 1950; Tabb, 1958; Stewart, 1961; Janke, 1971; Tucker and Faulkner, 1987; Peebles and Tolley, 1988; DeVries et al., 1997; Nelson and Leffler, 2001) and were also largely in agreement with the reproductive patterns of spotted seatrout populations throughout the range of the species (Hein and Shepard, 1979; Maceina et al., 1987; Brown-Petersen et al., 1988; Colura et al., 1988; Saucier and Baltz, 1992; Lowerre-Barbieri et al., 1999). Tucker and Faulkner (1987) and Nelson and Leffler (2001) found differences in the seasonal reproductive trends within populations that supported the idea that genetic differences cannot be solely responsible for the observed regional differences in spotted seatrout reproduction. Therefore, as was concluded by Tabb (1966) and Beaumarige (1969), environmental conditions, at least in part, regulate spotted seatrout reproduction.
The predicted optimum reproductive temperature of 29°C was also in general agreement with the temperature reported for optimum hatch rates (Gray et al., 1991; 25–30°C), highest larval survival (Taniguchi, 1981; 28°C; Alshuth and Gilmore, 1994; 25–30°C), and juvenile habitat preference (Kupschus, in press).
The principal diel spawning period of seatrout extends from 2 h before to 1 h after sunset as indicated by the maximum rate of decrease in the partial effect of hours after sunset. This is consistent with the estimates by Brown-Petersen et al. (1988) who reported a peak in spawning activity from 1 h before to 2 h after sunset. Tucker and Faulkner (1987) and Saucier and Baltz (1992) reported probable peak spawning times from 2100 to 2230 and 2002 to 2331 local time, respectively. Other studies reported spawning of specific events within a longer time frame: Lowerre-Barbieri et al. (1999) described male spawning sonifications lasting from 1830 to 2300 hours. Saucier and Baltz (1993) recorded a spawning event as lasting from 1630 to 2330, with spawning more generally occurring between 1700 and 0100. Therefore, the model is very much consistent with the reported times of the diel spawning period reported in seatrout studies along the Gulf and Atlantic coasts.
The model indicated strongest spawning during the first few days following the full moon with a decline in activity towards the following full moon. This slightly unusual cyclical pattern has been reported anecdotally by fishermen as a response to a combination of specific light and current requirements, and has been observed by Tucker and Faulkner (1987) and McMichael and Peters (1989).
Expected effects of condition and length of individual were produced by the model. Although these variables were largely included as covariables to account for differences in sampling gear, it was clearly indicated that larger fish and those in better condition are more likely to spawn (and thus more frequently) than smaller fish or those in poorer condition.
Photoperiod was not a significant predictor in the model in addition to temperature. In contrast, laboratory-based reproductive studies have relied on a combination of temperature and photoperiod manipulation to induce spawning of seatrout (Capo et al., 1997) or to correlate spawning events to environmental conditions (Tucker and Faulkner, 1987). Bye (1990) suggested that under natural conditions, photoperiod might not be an important cue to reproduction, but photoperiod may just be too strongly correlated with temperature to see the effect.
In general, much of the current knowledge on reproduction could be combined into a single quantitative model that explained a significant portion (38.2%) of the deviance in the reproductive status of IRL spotted seatrout. In addition, the results were largely consistent with the regional differences observed in reproductive timing throughout the species' range.
Projecting the predicted reproductive output from the model forward to the juvenile stage resulted in temporal patterns of recruitment very similar to the types observed in Florida estuaries, confirming reproduction as one of the major determinants driving recruitment as inferred by Nelson and Leffler (2001). The model, based on temperature differences in space and time, could explain the observation of unimodal and bimodal recruitment, as well as the differences in the protraction of the recruitment period. Although the output matched the relative trends in recruitment across time reasonably, the observed fluctuations in recruitment were amplified over those predicted by the projection. This amplification may be caused by the interactions of at least three factors. First, reproductive activity itself could modulate as the number of individuals on spawning sites fluctuates. Migration in response to lunar cycles, as exploited by fishermen, may reflect a more general movement to spawning sites during favourable conditions and away from spawning sites during unfavourable conditions. Second, egg production could modulate, as both the quantity and the quality of the eggs produced vary with changes in length or condition of females spawning, as observed for other species (Santiago and Eltink, 1988; Secor, 2000; Wieland et al., 2000), or through variation in the fraction of mature females during the spawning season as seen in some species such as Cynoscion regalis (Lowerre-Barbieri et al., 1996, 1998), Engraulis encrasicolus (Santiago and Eltink, 1988), and Penaeus semisulcatus (Crocos and van der Velde, 1995). Finally, processes following egg production such as hatching rates and juvenile survival are influenced by environmental conditions (Taniguchi, 1981; Gray et al., 1991; Helser et al., 1993; Alshuth and Glimore, 1994). If the effects on these processes are similar to those on reproduction, as indicated by the effect of temperature on the survival of adults (Vetter, 1977; Wohlschlag and Wakeman, 1978), the variation in the reproductive signal would be amplified in the recruitment pattern. All three factors would have a tendency to amplify the variation in observed recruitment patterns compared to the model signal.
Reproductive output certainly is determined to a large extent by the environmental conditions, so that variability in recruitment pattern and recruitment strength between estuaries and years is to be expected. Fisheries managers must take this variability into account, particularly when employing tuning indices of recruitment based on an amalgamation of data from a combination of estuaries. To fully understand the recruitment processes, data on variations in abundance on spawning grounds, on temporal trends in size composition and condition, and on fluctuations in larval and juvenile mortality are required. Without this understanding it is doubtful whether a meaningful stock–recruitment relationship can be established for this species.
|
References |
|---|
|
Top1 Introduction2 Materials and methods3 Results4 DiscussionReferences |
|---|
-
Alshuth S. and Gilmore R. G. Jr. (1993) Egg identification, early larval development and ecology of the spotted seatrout, Cynoscion nebulosus C. (Pisces: Sciaenidae). ICES CM 1993/G: 28.
Alshuth S. and Gilmore R. G. Jr. (1994) Salinity and temperature tolerance limits for larval spotted seatrout, Cynoscion nebulosus C. (Pisces: Sciaenidae). ICES CM 1994/L: 17.
Beaumarige D.S. (1969) Returns for the 1965 Schlitz Tagging Program including a cumulative analysis of previous results. Florida Department of Natural Resources Marine Research Laboratory Technical Series 59: 38 pp.
Brown-Petersen N. and Thomas P. (1988) Differing reproductive life histories between temperate and subtropical groups of Cynoscion nebulosus. University of Texas, Contributions to Marine Science 30:71–78.
Brown-Petersen N., Thomas P., Arnold C.E. (1988) Reproductive biology of the spotted seatrout, Cynoscion nebulosus, in south Texas. U.S. Fishery Bulletin 86:373–388.
Bye V.J. (1990) Temperate marine teleosts. In Munroe A.D., Lam T.J., Scott A.P. (Eds.). Reproductive Seasonality in Teleosts: Environmental Influences(CRC Press, Boca Raton) pp. 125–143 254 pp.
Capo T. R., Wisner B. B., Serafy J. E., Boyd A. E. (1997) Short communication: extended spawning of captive spotted seatrout (Cynoscion nebulosus) under photo-thermal regulations. Proceedings Aquaculture Europe 97May 4–9, 1997Les-trois-ilets, Martinique.
Colura R.L., Maciorowski A.F., Henderson-Arapalo A. (1988) Gonadal maturation, fecundity and strip spawning of female spotted seatrout. Proceedings of the Annual Conference of the Southeast Association of Fish and Wildlife Agencies 48: pp. pp. 80–88.
Crocos P.J. and van der Velde T.D. (1995) Seasonal, spatial and interannual variability in the reproductive dynamics of the grooved tiger prawn Penaeus semisulcatus in Albatross Bay, Gulf of Carpentaria, Australia: the concept of effective spawning. Marine Biology 122:557–570.[CrossRef]
DeVries D. A., Bedde C. D., Palmer C. L., Bortone S. A. (1997) Age, growth, maturity, and size composition of spotted seatrout, Cynoscion nebulosus, in the Panhandle Region of Florida. Final Report. Florida Department of Environmental Protection, Marine Resources Grants MR019 and MR024. Tallahassee, Florida.
Gilmore R.G. (1995) Environmental and biogeographic factors influencing ichthyofaunal diversity in the Indian River Lagoon. Bulletin of Marine Science 57:153–170.[Web of Science]
Gray J.D., King T.L., Coulra R.L. (1991) Effects of temperature and hypersalinity on hatching success of spotted seatrout eggs. Progressive Fish-Culturist 53:81–84.[CrossRef]
Hastie T.J. and Tibshirani R.J. (1990) Generalized Additive Models(Chapman & Hall, London) 335 pp.
Hein S., Dugas C., Shepard J. (1980) Total length-standard and length–weight regressions for spotted seatrout Cynoscion nebulosus; red drum, Sciaenops ocellata; and black drum, Pogonias cromis, in south-central Louisiana. Louisiana Fish and Wildlife Marine Research Laboratory Technical Bulletin 31:41–48.
Hein S. and Shepard J. (1979) Spawning of spotted seatrout in a Louisiana estuarine ecosystem. Proceedings of the Annual Conference of the Southeast Association of Fish and Wildlife Agencies 33:451–465.
Helser T.E., Condrey R.E., Geaghan J.P. (1993) Spotted seatrout distributions in four coastal Louisiana estuaries. Transactions of the American Fisheries Society 122:99–111.[CrossRef]
Janke T.E. (1971) Abundance of young sciaenid fishes in Everglades National Park, Florida, in relation to season and other variables. University of Miami Sea Grant Program, Seagrant Technical Bulletin 11:1–128.
Kupschus S.R. Development and evaluation of statistical habitat suitability models; an example based on juvenile spotted seatrout (Cynoscion nebulosus). Marine Ecology Progress Series, in press.
Kupschus S.R. and Tremain D. (2001) Associations between fish assemblages and environmental factors in nearshore habitats of a subtropical estuary. Journal of Fish Biology 58:1383–1403.[CrossRef][Web of Science]
Lowerre-Barbieri S. K., Barbieri L. R., Alberts J. J. (1999) Reproductive parameters needed to evaluate recruitment overfishing of spotted seatrout in the Southeastern US. Final Report. Saltonstall-Kennedy Grant Program, 15USC. 713e–c.
Lowerre-Barbieri S.K., Chittenden M.E., Barbieri L.R. (1996) The multiple spawning pattern of weakfish in the Chesapeake Bay and Middle Atlantic Bight. Journal of Fish Biology 48:1139–1163.[CrossRef][Web of Science]
Lowerre-Barbieri S.K., Lowerre J.M., Barbieri L.R. (1998) Multiple spawning and the dynamics of fish populations: inferences from an individual-based simulation model. Canadian Journal of Fisheries and Aquatic Sciences 55:2244–2254.
Maceina M.J., Hata D.N., Linton T.L., Landry A.M. Jr. (1987) Age and growth analysis of spotted seatrout from Galveston Bay, Texas. Transactions of the American Fisheries Society 116:54–59.[CrossRef]
McCullagh P. and Nelder J.A. (1989) Generalized Linear Models 2nd edn (Chapman & Hall, London) 511 pp.
McMichael K.M. Jr. and Peters R.H. (1989) Early life history of spotted seatrout, Cynoscion nebulosus (Pisces: Sciaenidae) in Tampa Bay, Florida. Estuaries 12:98–110.[CrossRef][Web of Science]
Moody W.D. (1950) A study of the natural history of the spotted trout, Cynoscion nebulosus, in the Cedar Key area, Florida. Quarterly Journal of the Florida Academy of Sciences 12:147–171.
Nelson G.A. (1998) Abundance, growth, and mortality of young-of-the-year pinfish, Lagodon rhomboides, in three estuaries along the gulf coast of Florida. Fishery Bulletin 96:315–328.[Web of Science]
Nelson G.A. and Leffler D. (2001) Abundance, spatial distribution and mortality of young-of-the-year spotted seatrout (Cynoscion nebulosus) along the Gulf coast of Florida. Gulf of Mexico Science 2001:30–42.
Peebles E.B. and Tolley S.G. (1988) Distribution and mortality of larval spotted seatrout, Cynoscion nebulosus: a comparison between two adjacent estuarine areas of Southwest Florida. Bulletin of Marine Science 42:397–410.[Web of Science]
Quintero-Hunter I., Grier H., Muscato M. (1991) Enhancement of histological detail using metanil yellow as counterstain in periodic acid/Schiff's hematoxylin staining of glycol methacrylate tissue sections. Biotechnology and Histochemistry 66:169–172.
Rutherford E.S., Thomas W.S., Tilmant J.T. (1989) Early life history of spotted seatrout (Cynoscion nebulosus) and gray snapper (Lutjanus griseus) in Florida Bay, Everglades national park, Florida. Bulletin of Marine Science 44:49–64.[Web of Science]
Santiago J. and Eltink A. (1988) Distribution and abundance of anchovy eggs in the Bay of Biscay in 1987 in comparison with 1983 and 1986. ICES CM 1988/H: 9. 23 pp.
Saucier M.H. and Baltz D.M. (1992) Hydrophone identification of spawning sites of spotted seatrout Cynoscion nebulosus (Osteichthys: Sciaenidae) near Charlston, South Carolina. Northeast Gulf Science 12:141–145.
Saucier M.H. and Baltz D.M. (1993) Spawning site selection by spotted seatrout, Cynoscion nebulosus, and black drum, Pogonias cromis, in Louisiana. Environmental Biology of Fishes 36:257–272.[CrossRef][Web of Science]
Secor D.H. (2000) Spawning in the nick of time? Effect of adult demographics on spawning behaviour and recruitment in Chesapeake Bay striped bass. ICES Journal of Marine Science 57:403–411.
Stewart K.W. (1961) Contributions to the biology of the spotted seatrout (Cynoscion nebulosus) in the Everglades National Park, Florida. Masters thesis, University of Miami, Coral Gables, Florida.
Tabb D. C. (1958) Differences in the estuarine ecology of Florida waters and their effect on populations of spotted weakfish, Cynoscion nebulosus (Cuvier and Valenciennes). Transcripts of the 23rd North American Wildlife Conference pp. 392–401.
Tabb D.C. (1966) The estuary as a habitat for spotted seatrout (Cynoscion nebulosus). American Fisheries Society Special Publication No. 3:59–67.
Taniguchi A.K. (1981) Survival and growth of larval spotted seatrout (Cynoscion nebulosus) in relation to temperature, prey abundance and stocking densities. Rapports et Procès-verbaux des Réunions du Conseil International puor l'Exploration de la Mer 178:507–508.
Taylor M.H. (1990) Estuarine and intertidal teleosts. In Munroe A.D., Lam T.J., Scott A.P. (Eds.). Reproductive Seasonality in Teleosts: Environmental Influences(CRC Press, Boca Raton) pp. 109–125 254 pp.
Tucker B.E. Jr. and Faulkner J.W. (1987) Voluntary spawning patterns of captive spotted seatrout. Northeast Gulf Science 9:59–63.
Vetter R. D. (1977) Respiratory metabolism of, and niche separation between, two co-occurring congeneric species, Cynoscion nebulosus and Cynoscion arenarius, in a south Texas estuary. Masters thesis, University of Texas, Austin, Texas.
Wieland K., Jarre-Teichmann A., Horbowa K. (2000) Changes in the timing of spawning of Baltic cod: possible causes and implications for recruitment. ICES Journal of Marine Science 52:452–464.
Wohlschlag D.E. and Wakeman J.M. (1978) Salinity stresses, metabolic responses and distribution of the coastal spotted seatrout, Cynoscion nebulosus. University of Texas Contributions to Marine Science 21:171–185.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||