Acidification has historically impaired Cheat Lake's fish community, but recent mitigation efforts within the Cheat River watershed have improved water quality and species richness. Presently, channel catfish Ictalurus punctatus are abundant and attain desirable sizes for anglers. We evaluated the age, growth, and fall diet of the population. We collected a sample of 155 channel catfish from Cheat Lake from 5 August to 4 December 2014, a subset of which we aged (n = 148) using lapillus otoliths. We fit four growth models (von Bertalanffy, logistic, Gompertz, and power) to length-at-age data and compared models using an information theoretic approach. We collected fall diets from 55 fish sampled from 13 October to 4 December 2014. Total lengths of individuals in the sample ranged from 154 to 721 mm and ages ranged from 2 to 19 y. We AICc-selected the von Bertalanffy growth model as the best approximating model, and the power and Gompertz models also had considerable support. Diets were numerically dominated by Diptera larvae, specifically Chironomidae and Chaoboridae, while 39% of stomachs contained terrestrial food items. This study provides baseline data for management of Cheat Lake's channel catfish population. Further, this study fills a knowledge gap in the scientific literature on channel catfish, because few previously published studies have examined the population ecology of channel catfish in the Central Appalachian region.

The channel catfish Ictalurus punctatus (Figure 1) is an economically important species in North America because of its popularity among recreational and commercial fishermen, as well as aquaculturalists. Channel catfish are native to the central drainages of North America (Etnier and Starnes 1993), and have been extensively introduced elsewhere to enhance sport fisheries (Marsh 1981; Tyus and Nikirk 1990; Bonar et al. 1997). Presently, the range of channel catfish extends throughout much of the United States (Hubert 1999a). On account of its importance to humans and extensive range, channel catfish have been studied extensively. However, few studies have been published on channel catfish populations in the Central Appalachians, presenting a gap in the knowledge base on the species. Given the extensive variability among populations, filling in gaps may help elucidate factors influencing channel catfish population dynamics.

Figure 1.

A channel catfish Ictalurus punctatus collected from Cheat Lake, West Virginia, during a night-time electrofishing survey in 2013. Photo by D. M. Smith.

Figure 1.

A channel catfish Ictalurus punctatus collected from Cheat Lake, West Virginia, during a night-time electrofishing survey in 2013. Photo by D. M. Smith.

Close modal

Cheat Lake has one of the more prolific channel catfish populations of West Virginia's reservoirs. Currently, no management practices are in place to maximize channel catfish production in Cheat Lake, and limited data exist on the population. This study focuses on estimation of population characteristics of Cheat Lake channel catfish and evaluation of fall diets. Our objectives were to estimate size structure, age structure, mortality, condition, growth, and fall diets for Cheat Lake's channel catfish population, thus providing a baseline for future management decisions and filling a regional knowledge gap in the population ecology of channel catfish.

Cheat Lake (also referred to as Lake Lynn) is a 700.4-ha hydropower reservoir on the Cheat River near Morgantown, West Virginia (Figure 2). The reservoir flows 20.9 km from the head of the lake to the Lake Lynn Hydropower Dam. Acid precipitation (Welsh and Perry 1997) and acid mine drainage (Freund and Petty 2007; Merovich and Petty 2007; Merovich et al. 2007) within the Cheat River Watershed have affected downstream sections, including Cheat Lake. Fish survey reports from Cheat Lake during the 1950s documented 14 total species, predominately from the families Catostomidae and Ictaluridae (Core et al. 1959). However, mitigation efforts throughout the watershed have led to improved pH (D. M. Smith, West Virginia Division of Natural Resources, unpublished data) within Cheat Lake and a resurgence of fish species richness. Since 1997, 44 species (11 families) have been collected from Cheat Lake (D. M. Smith, unpublished data). Presently, channel catfish are abundant in Cheat Lake, making up a large proportion of the catch in gill-net surveys (D.M. Smith, unpublished data).

Figure 2.

Map of Cheat Lake in relation to the nearest city (Morgantown) and West Virginia–Pennsylvania state line. Sites sampled for channel catfish Ictalurus punctatus (from 5 August to 4 December 2014) are indicated with filled in circles.

Figure 2.

Map of Cheat Lake in relation to the nearest city (Morgantown) and West Virginia–Pennsylvania state line. Sites sampled for channel catfish Ictalurus punctatus (from 5 August to 4 December 2014) are indicated with filled in circles.

Close modal

Fish collection

We collected channel catfish from Cheat Lake from 5 August 2014 to 4 December 2014 using gill nets, boat electrofishing, and baited hoop nets. We collected fish during this period to ensure spawning had been completed, which reduced sex-related bias in condition estimates. We strategically selected sampling sites in areas with historical success of channel catfish collection or favorable habitat. We also modified spatial sampling arrays to collect channel catfish as they moved between seasonal habitats and to avoid areas fish were no longer utilizing. We avoided areas with submerged woody debris in gill-net and hoop-net sampling to minimize the likelihood of net entanglement. We calculated mean catch per unit effort for all sampling gears and measured it as fish per net-night, fish per hour, and fish per net-night for gill nets, boat electrofishing, and baited hoop nets, respectively. We have provided catch per unit effort and water temperatures for sampling events in Table S1.

We primarily used gill nets because of prior success capturing channel catfish in a separate study in Cheat Lake (D. M. Smith, unpublished data). We fished with two different types of monofilament nets, including nets of dimensions 38.1 m × 1.8 m (consisting of five 7.6-m panels of bar mesh sizes 1.9-, 2.5-, 3.8-, 5.1- and 6.4-cm) and 45.7 m × 1.8 m (consisting of six 7.6-m panels of bar mesh sizes 3.8-, 4.4-, 5.1-, 3.8-, 4.4- and 5.1-cm). We initially used the shorter 38-m experimental gill nets to avoid exclusion of smaller channel catfish, but we discontinued their use when we collected few small individuals (five fish shorter than stock length [280 mm] in 47 net-nights). We subsequently used the 46-m gill nets in an effort to maximize catch rates. We tied gill nets to woody debris on shore and set them perpendicular to the shoreline. We anchored nets to the lake bottom using cinder blocks adjoined to the sinking line of the gill net. We fished nets overnight and pulled nets in the order they were set.

We conducted high-frequency (60 pps) boat electrofishing using a Smith-Root boat-mounted electrofisher (5.0 GPP) with a typical output of 4–6 amps. Sampling took place from dusk to 2400 hours in shallow areas (<2.5 m) with suitable water clarity. On some occasions, we deployed bait to lure channel catfish into shallow areas to improve their susceptibility to electrofishing. We attached to a carabineer cheese trimmings (Memphis Net & Twine) or Charlie Blood B Dough Bait (Catfish Charlie Bait Co. Inc.) contained in a mesh bag, and we clipped the carabineer to a rope connecting an anchor to a buoy. We used buoys to mark the exact site of bait deployment. We electrofished in areas adjacent to buoys approximately 30–60 min after buoy deployment. We used electrofishing to target small individuals not recruited to other gears.

Several studies have suggested baited tandem hoop nets as the most effective gear for sampling channel catfish in lentic systems (Sullivan and Gale 1999; Michaletz and Sullivan 2002; Flammang and Schultz 2007; Richters and Pope 2011). Suitable sites for tandem hoop nets in Cheat Lake were limited on account of steep banks and submerged woody debris. As a result, we set single hoop nets in coves and mouths of tributaries where depths were shallow (<3 m) and bathymetry was relatively low gradient. Hoop nets consisted of seven 1.2-m fiberglass hoops with 3.8-cm mesh with restrictive throats on the second and fourth hoops. We placed cheese trimmings or Blood Dough Bait contained in mesh bags in the cod end of the hoop net. Neely and Dumont (2011) suggested baited, tandem hoop net sets were most effective if set for 2–3 d. In Cheat Lake, intense recreational boating prevented long-term sets and we set hoop nets over-night. After low success rates during pilot sampling, we used hoop nets sparingly.

Specimen processing

We immediately placed collected channel catfish on ice to preserve specimen integrity and slow digestion of stomach contents. We measured channel catfish total length (TL) to the nearest mm and weighed them to the nearest g using a battery-operated digital scale (Ohaus® Valor 2000 Series - Model V21PW6). We extracted lapillus otoliths (lapilli, hereafter) for age analysis. We cleaned lapilli of all soft tissue and allowed them to dry in coin envelopes.

Annulus interpretation on whole channel catfish lapilli is difficult because of opaqueness. To gain a view of the transverse plane, we used the protocol described by Buckmeier et al. (2002). In accordance with this technique, we burnt lapilli on a Carolina™ Hot Plate/Stirrer to produce a dark amber color. We mounted burnt lapilli to a glass microscope slide using Crystalbond™ 509 (Electron Microscopy Sciences). We sanded lapilli using 400- or 600-grit wet/dry sandpaper to remove the top third of the otolith. We polished the transverse plane using 1,200- and 2,500-grit automotive-grade sandpaper to improve clarity of annuli. We immersed mounted lapilli in water to reduce glare and viewed them under a dissecting microscope (20–40× magnification). Two independent readers counted annuli and discrepancies were resolved by mutual examination.

We included in diet analysis fish collected from 13 October 2014 to 4 December 2014. We used gill nets exclusively to sample fish for diet analyses. We excised a sample of 55 stomachs and preserved them in a 95% ethanol solution (Dagel et al. 2010). We removed stomach contents in the laboratory and identified them to family or the lowest practical taxonomic level. We counted prey items with the exception of detritus, which we noted as present or absent. We labeled counted prey items as either aquatic or terrestrial in origin. We noted empty stomachs as such and excluded them from further analysis.

Analyses

To estimate the size structure of the Cheat Lake channel catfish population, we constructed a length-frequency histogram and calculated proportional size distributions (PSDs). We constructed the length-frequency histogram using length–group interval guidelines presented in Neumann et al. (2012). We estimated proportional size distributions (Gabelhouse 1984; Neumann et al. 2012) using the following length categories presented by Gabelhouse (1984); stock (280–409 mm), quality (410–609 mm), preferred (610–709 mm), memorable (710–909 mm), and trophy (≥910 mm). We estimated confidence intervals (95%) on PSDs using the equation presented by Gustafson (1988).

We used a relative weight index to estimate condition of Cheat Lake's channel catfish population. Relative weight (Wr) is calculated as Wr = (W/Ws) × 100, where W is the weight of an individual fish in g and Ws is the standard weight (Wege and Anderson 1978). Standard weight of channel catfish is calculated as log10 (Ws) = −5.800 + 3.294 log10 (L), where L is the TL of an individual fish in mm (Brown et al. 1995). We summarized relative weights using the length categories presented by Gabelhouse (1984) with the addition of a sixth category (substock) to encompass small fish not represented in the other categories (Shuman et al. 2011).

We used age-class data and catch-curve linear regression (Ricker 1975) in R version 3.1.3 (R Core Team 2015) to estimate an instantaneous mortality rate (Z) of channel catfish. We used weighted linear regression to lessen the influence of older, less common age classes (Maceina 1997). We subsequently calculated the annual mortality (A) rate as A = 1 − e Z (Miranda and Bettoli 2007). Hubert (1999b) stated in a meta-analysis of 102 channel catfish age studies that most studies had few fish <3 y old, indicating channel catfish may not fully recruit to sampling gears until age 3. As a result, we excluded fish younger than age 3 from catch-curve analysis. Catch-curve analysis assumes no age estimation error, as well as constant recruitment, mortality, and catchability over all age classes considered (Miranda and Bettoli 2007; Smith et al. 2012).

We used mean length-at-age data to compare Cheat Lake channel catfish growth to standards presented by Hubert (1999b) and Jackson et al. (2008). Hubert (1999b) provided growth standards for channel catfish from age 3–10, allowing assignment of percentiles to mean length-at-age data. We also compared Cheat Lake channel catfish growth using the relative growth index (RGI) to the standard length (Ls) equation presented by Jackson et al. (2008), where . We calculated relative growth index values as RGI = (Lt/Ls) × 100, where Lt was the observed length-at-age and Ls was the predicted age-specific total length from the standard length equation (Quist et al. 2003). We calculated relative growth index values for all aged fish and averaged them by age class. We compared mean RGI values to an average value of 100, where RGI values >100 indicate fast growth, while RGI values <100 indicate slow growth (Quist et al. 2003). We presented mean RGI values from ages 3 to 10 because Hubert (1999b) indicated most studies lack adequate sample sizes outside this range.

We fit four growth models to channel catfish length-at-age data using a Gauss–Newton algorithm in Program R. The four candidate models were the von Bertalanffy (VBGM), logistic, Gompertz, and power models:

formula
formula
formula
formula

All candidate models, except the power model, include a maximum length term (L), indicative of asymptotic growth. However, the power model assumes indeterminate growth. The VBGM assumes the growth rate decreases linearly with size (Katsanevakis 2006; Katsanevakis and Maravelias 2008). In the VBGM, k describes how quickly L is reached and t0 is the theoretical age when length equals zero (Quist et al. 2012). The Gompertz and logistic models approximate sigmoidal curves. The Gompertz model assumes an exponential decrease in growth rate with age (Katsanevakis 2006), whereas the logistic model is symmetrical about an inflection point (Quist et al. 2012). In the Gompertz model, t0 is the inflection point of the curve and G is the instantaneous growth rate at age t0 (Quist et al. 2012). The parameters G and t0 in the logistic model are the instantaneous growth rate at the origin of the curve and the theoretical age when length is zero, respectively (Quist et al. 2012).

We compared the four candidate growth models for goodness-of-fit using an information theoretic approach. We used Akaike's Information Criterion with a small-sample bias correction (AICc) to rank models in order of decreasing fit (Anderson 2008; Katsanevakis and Maravelias 2008; Burnham et al. 2011). We considered the model with the lowest AICc value to be the “best” approximating model (Burnham et al. 2011). We calculated AICc weights (wi) for each model and used them as relative measures of evidence for each model (Akaike 1983; Burnham and Anderson 2002). We completed all AICc calculations in R using the AICcmodavg package (Mazerolle 2015). We used multimodel inference to reduce uncertainty associated with using a single model (Buckland et al. 1997; Burnham et al. 2011). We used estimates of L from the VBGM, Gompertz, and logistic models to find the model average asymptotic length (; Katsanevakis and Maravelias 2008; Yin and Tzeng 2009). We calculated standard error on the estimate using an equation presented by Katsanevakis (2006).

We summarized diets (n = 55) using percent frequency of occurrence (Oi), mean percent frequency by number (MNi), and prey-specific abundance (Pi). We calculated frequency of occurrence as Oi = Ji P−1 × 100, where Ji was the number of stomachs containing a particular food item and P was the total number of stomachs containing food (Chipps and Garvey 2007). We calculated mean percent composition by number as below, where P was the total number of stomachs containing food, Q was the number of prey item categories, and Nij, was the number of food category i in fish j (Chipps and Garvey 2007).

formula

We calculated prey-specific abundance (Pi) for each food item i as Pi = (ΣSiSt), where ΣSi was the total number of food item i observed and ΣSt was the total number of prey items in stomachs with food item i in them (Amundsen et al. 1996).

We collected 155 channel catfish during the sampling period, most of which we collected using gill nets (n = 136). We collected a smaller proportion of fish using boat electrofishing (n = 17) and baited hoop nets (n = 2). Sampling efforts of gill nets, boat electrofishing, and hoop nets were 85 net-nights, 3.9 h, and 4 net-nights, respectively. We calculated mean catch per unit effort estimates of gill nets, boat electrofishing, and baited hoop nets as 1.6 fish/net-night, 4.4 fish/h, and 0.5 fish/net-night, respectively. We have provided catch per unit effort and water temperatures for sampling events in Table S1. The mean TL of the sample was 466 mm (SD = 117 mm), and the length-frequency distribution (Figure 3) indicates a majority of fish collected were >400 mm in length.

Figure 3.

Length frequency distribution (25-mm bins) of Cheat Lake, West Virginia, channel catfish Ictalurus punctatus (n = 155) collected from 5 August to 4 December 2014. Length was measured as total length.

Figure 3.

Length frequency distribution (25-mm bins) of Cheat Lake, West Virginia, channel catfish Ictalurus punctatus (n = 155) collected from 5 August to 4 December 2014. Length was measured as total length.

Close modal

We summarized length and relative weight data using the Gabelhouse (1984) five-category system. The number of individuals in the Gabelhouse (1984) categories of stock (S), quality (Q), preferred (P), memorable (M), and trophy (T) were 34, 94, 16, 1, and 0, respectively. Ten fish were shorter than the minimum stock length (280 mm). We estimated proportional size distributions with 95% confidence intervals as follows: PSD = 77 ± 8, PSD-P = 12 ± 6, PSD-M = 1 ± 2, and PSD-T = 0. We estimated incremental PSDs with 95% confidence intervals as follows: PSD S-Q = 23 ± 8, PSD Q-P = 65 ± 9, PSD P-M = 11 ± 6, and PSD M-T = 1 ± 2. We calculated relative weight (Wr) for all channel catfish collected (n = 155; Table 1). Mean Wr of the substock, stock, quality, and preferred categories were 98, 93, 93, and 91, respectively.

Table 1.

Mean relative weights (Wr) of channel catfish Ictalurus punctatus (n = 155) collected from Cheat Lake, West Virginia (5 August–4 December 2014). Wr is summarized by Gabelhouse (1984) length categories, where length was measured as total length (TL) in mm. Percentile values were determined from Brown et al. (1995) using distributions of Wr by length category. NA indicates an insufficient sample size for calculation.

Mean relative weights (Wr) of channel catfish Ictalurus punctatus (n = 155) collected from Cheat Lake, West Virginia (5 August–4 December 2014). Wr is summarized by Gabelhouse (1984) length categories, where length was measured as total length (TL) in mm. Percentile values were determined from Brown et al. (1995) using distributions of Wr by length category. NA indicates an insufficient sample size for calculation.
Mean relative weights (Wr) of channel catfish Ictalurus punctatus (n = 155) collected from Cheat Lake, West Virginia (5 August–4 December 2014). Wr is summarized by Gabelhouse (1984) length categories, where length was measured as total length (TL) in mm. Percentile values were determined from Brown et al. (1995) using distributions of Wr by length category. NA indicates an insufficient sample size for calculation.

We estimated age for 148 channel catfish using lapilli and included 143 total fish from age 3 to age 19 in catch-curve analysis. Independent readers agreed on 87% of assigned ages and agreement within 1 y was 96%. An age was agreed upon for all individuals after mutual examination. Estimated ages ranged from age 2 (n = 5) to age 19 (n = 1). Age-0 (young-of-the-year) and age-1 fish were absent from the sample. The age-frequency plot (Figure 4) showed the largest age classes in the sample were age-3, −4, and −7 fish, while other age classes were less common. We excluded age-2 fish from catch-curve analysis because we suspect they were not sampled effectively. We estimated instantaneous mortality as Z = 0.163 ± 0.079 (95% CI) using weighted linear regression. We calculated annual total mortality (A = 17.8% ± 9.4 [95% CI]) from instantaneous mortality.

Figure 4.

Age structure of channel catfish Ictalurus punctatus (n = 148) from Cheat Lake, West Virginia, collected from 5 August to 4 December 2014. Ages were estimated using lapillar otoliths using the protocol described by Buckmeier et al. (2002).

Figure 4.

Age structure of channel catfish Ictalurus punctatus (n = 148) from Cheat Lake, West Virginia, collected from 5 August to 4 December 2014. Ages were estimated using lapillar otoliths using the protocol described by Buckmeier et al. (2002).

Close modal

We fit four candidate growth models to length-at-age data from 148 channel catfish (ages 2–19, length 154–721 mm; Figure 5). The VBGM was selected by AICc as the best approximating model of Cheat Lake channel catfish growth (wi = 0.39), whereas the power (wi = 0.38, ΔAICc = 0.02) and Gompertz (wi = 0.17, ΔAICc = 1.65) models were also supported (Table 2). The logistic model was the least supported model (wi = 0.06, ΔAICc = 3.74). Using model-averaging of the parameter estimates from the three asymptotic models (Table 3), we estimated as 589.767 mm (SE = 16.772).

Figure 5.

Four candidate growth models fit to length-at-age data of 148 channel catfish Ictalurus punctatus (ages 2–19) collected from Cheat Lake, West Virginia, from 5 August to 4 December 2014. Length was measured as total length.

Figure 5.

Four candidate growth models fit to length-at-age data of 148 channel catfish Ictalurus punctatus (ages 2–19) collected from Cheat Lake, West Virginia, from 5 August to 4 December 2014. Length was measured as total length.

Close modal
Table 2.

Results of model selection using Akaike's Information Criterion with small sample size correction (AICc) for the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).

Results of model selection using Akaike's Information Criterion with small sample size correction (AICc) for the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).
Results of model selection using Akaike's Information Criterion with small sample size correction (AICc) for the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).
Table 3.

Parameter estimates from fitting the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).

Parameter estimates from fitting the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).
Parameter estimates from fitting the Gompertz, Logistic, Power, and von Bertalanffy (VBGM) growth models for channel catfish Ictalurus punctatus (n = 148) collected from Cheat Lake, West Virginia (5 August–4 December 2014).

We compared Cheat Lake channel catfish growth to growth standards produced from populations throughout the species' range (Table 4). Using the Hubert (1999b) growth standards, Cheat Lake channel catfish mean lengths at age were at the 75th percentile or above for ages 3–8. Age-9 fish were between the 50th and 75th percentile, whereas age-10 fish were between the 25th and 50th percentile. We found similar results using the Relative Growth Index. Fish of ages 3–9 exhibited a mean RGI value >100, whereas the mean RGI value of age-10 fish was 94.85 (SD = 18.17).

Table 4.

Description of channel catfish Ictalurus punctatus growth collected from Cheat Lake, West Virginia (n = 148; 5 August–4 December 2014). Mean relative growth index (RGI) values and Hubert (1999b) percentiles are provided to compare Cheat Lake channel catfish growth to populations throughout the species' range. TL is total length (mm).

Description of channel catfish Ictalurus punctatus growth collected from Cheat Lake, West Virginia (n = 148; 5 August–4 December 2014). Mean relative growth index (RGI) values and Hubert (1999b) percentiles are provided to compare Cheat Lake channel catfish growth to populations throughout the species' range. TL is total length (mm).
Description of channel catfish Ictalurus punctatus growth collected from Cheat Lake, West Virginia (n = 148; 5 August–4 December 2014). Mean relative growth index (RGI) values and Hubert (1999b) percentiles are provided to compare Cheat Lake channel catfish growth to populations throughout the species' range. TL is total length (mm).

We quantified stomach contents for 55 channel catfish ranging from 274 to 606 mm TL (mean = 458.2, SD = 73.0) and the fish contained food items 74.5% of the time. Of the stomachs containing food items, 31.7% contained detritus and 2.4% contained detritus only. Fall diets were numerically dominated by aquatic invertebrates (Table 5). Chironomidae and Chaoboridae larvae were the most common prey items, whereas Ephemeroptera and Sialidae larvae were also frequently present (Table 5). Piscivory was observed—fish remains were present in 9.8% of stomachs with food items.

Table 5.

Diet contents of channel catfish Ictalurus punctatus (n = 41) collected from Cheat Lake, West Virginia (13 October–4 December 2014). Percent frequency of occurrence (Oi), mean percent frequency by number (MNi) and prey-specific abundance (Pi) were calculated. The symbol (-) indicates food item type was not enumerated. Bolded food item categories are aggregates of all food items from these sources.

Diet contents of channel catfish Ictalurus punctatus (n = 41) collected from Cheat Lake, West Virginia (13 October–4 December 2014). Percent frequency of occurrence (Oi), mean percent frequency by number (MNi) and prey-specific abundance (Pi) were calculated. The symbol (-) indicates food item type was not enumerated. Bolded food item categories are aggregates of all food items from these sources.
Diet contents of channel catfish Ictalurus punctatus (n = 41) collected from Cheat Lake, West Virginia (13 October–4 December 2014). Percent frequency of occurrence (Oi), mean percent frequency by number (MNi) and prey-specific abundance (Pi) were calculated. The symbol (-) indicates food item type was not enumerated. Bolded food item categories are aggregates of all food items from these sources.

Terrestrial food items were present in 39.0% of stomachs. A wide diversity of terrestrial invertebrate taxa were consumed, with Lepidoptera being the most common (Table 5). Adult terrestrial insects were commonly identified in stomach contents. Mammalian remains were also present in channel catfish diets—Rodentia were found in 4.9% of stomachs and were the only prey items present in those stomachs. Channel catfish stomachs also contained seasonally available fruits and acorns 14.6 % of the time. Acorns Quercus spp., grapes Vitis spp., and paw-paw Asimina triloba seeds were identified in stomach contents.

Given the lack of regional published data on channel catfish growth, the robust population in Cheat Lake provided an opportunity to gather data on age, growth, and diet within a West Virginia hydropower reservoir. Channel catfish in Cheat Lake exhibited faster than average growth (Hubert 1999b; Jackson et al. 2008). Low exploitation may contribute to fish reaching relatively old ages compared with other populations. Fall diet was also comparable to other studies. However, the high incidence of terrestrial items possibly suggests increased availability related to constant, small water-level fluctuations typical of hydropower operations. These data provided valuable information for potential future management of the population and for comparison with other populations in the region.

Cheat Lake's channel catfish population included an abundance of quality-length fish (>410 mm; Gabelhouse 1984). However, size structure estimated above could be biased because of selectivity of sampling gears (Colombo et al. 2008). Colombo et al. (2008) found channel catfish PSD in the Wabash River, Indiana, differed by >40 when comparing samples collected with hoop nets versus alternating-current electrofishing. In a Missouri impoundment, Sullivan and Gale (1999) found similar PSDs from hoop-net and gill-net samples. Using multiple gears in this study could have reduced biases associated with a single sampling gear, but a vast majority of fish were collected using gill nets because of low catch rates using other gears. Use of gill nets as the primary sampling gear likely excluded small channel catfish. Future studies could incorporate trawls (Phelps et al. 2011) and wooden slat traps, angling, or trotlines (Santucci et al. 1999) to improve catch rates of small and exceptionally large fish, respectively.

The catch numbers from baited electrofishing were similar to nonbaited electrofishing, but baited electrofishing required less time investment (∼120 s/site). The method appeared to concentrate local fish around the bait, but did not appear to draw additional fish from other areas. We noted presence of cheese trimmings in the stomachs of collected fish during dissection. This method may be more effective in lotic systems where flows carry scent of baits downstream or smaller impoundments. Further study is required to determine whether using bait during electrofishing can actually increase catch rates.

Cheat Lake channel catfish Wr was >90 for all length categories. Condition appeared to be similar to six Missouri River reservoirs, where Wr estimates ranged from 89 to 93, with a single reservoir estimated as 81 (Bouska et al. 2011). Barada and Pegg (2011) found channel catfish condition declined below average as fish grew longer, attributing this trend to differences in food availability for length categories. However, Cheat Lake has a large forage base, dominated by gizzard shad Dorosoma cepedianum, emerald shiner Notropis atherinoides, and three Lepomis species (D. M. Smith, unpublished data). Cheat Lake channel catfish Wr may decline below average on account of intraspecific competition, resulting from large numbers of quality-length (>410 mm) fish. Another possible explanation may be due to seasonal differences in Wr (Blackwell et al. 2000). We collected fish in late summer and fall after spawning had taken place.

We estimated Cheat Lake channel catfish annual total mortality as A = 17.8% using catch-curve analysis. Hubert (1999a) reported annual mortalities ranging from 13% to 88% from >50 channel catfish populations. The annual mortality estimate presented above is relatively low compared with the range of estimates in other populations. We speculate low mortality rates could be related to low exploitation. Haxton and Punt (2004) estimated annual mortality as 15.7% in the Ottawa River, while claiming there is little fishing pressure for the species. Low mortality rates may allow fish to reach relatively old ages. A maximum observed age in Cheat Lake, of 19 y, is relatively old compared with most populations. Bouska et al. (2011) also noted low mortality rates (12–25%) and long-lived fish with maximum ages ranging from 14 to 28 y, suggesting 28 y was the oldest wild channel catfish on record. Hubert (1999a) observed a most frequent maximum age of 8 y and noted few bodies of water produce fish older than 15 y.

Cheat Lake channel catfish experience rapid growth based on the standards presented by Hubert (1999b) and Jackson et al. (2008). Channel catfish growth has been correlated with a number of factors, including forage abundance, latitude, and limnological variables (Shoup et al. 2007; Rypel 2011). Abundant gizzard shad, emerald shiners, and Lepomis spp. in Cheat Lake may provide a forage base conducive to rapid channel catfish growth. Rypel (2011) described a latitudinal countergradient when normalizing for mean annual temperature. Cheat Lake is located just south of the West Virginia–Pennsylvania state line (Figure 2) and may experience fast growth rates due to moderate latitudinal and thermal influences. Meta-analysis of growth data from both lentic and lotic systems found growth positively correlated with lentic habitats (Rypel 2011). The shallow transitional section, coves, and upper riverine section of Cheat Lake may promote fast growth rates. Shoup et al. (2007) found a positive correlation with channel catfish growth and littoral area in 11 Illinois reservoirs.

Frequently in fisheries science, somatic growth is described using a single model selected a priori (generally the VBGM; Katsanevakis 2006; Katsanevakis and Maravelias 2008). Katsanevakis and Maravelias (2008) noted the VBGM often had the highest L estimate. This trend was also noted in the present study. Selecting the VBGM a priori could lead to overestimates of L. Future growth modeling efforts should use an information theoretic approach comparing multiple models to minimize biases associated with use of a single model.

Diets of Cheat Lake channel catfish are consistent with results of other diet studies. Numerous studies observed extensive use of macroinvertebrates and a large presence of dipterans in channel catfish diets (Griswold and Tubb 1977; Weisberg and Janicki 1990; Michaletz 2006). Piscivory appeared to be infrequent, as was observed by Crumpton (1999). Infrequent encounters of fish in channel catfish stomachs could be the result of selection of prey items requiring less energy expenditure or handling time. Also, fish could have been lost via regurgitation due to sampling stress. Sutton et al. (2004) reported large piscivorous fish have higher regurgitation rates than small nonpiscivorous fish. Stomach content retention by gill-net collected channel catfish may be high because they are primarily caught by entanglement of spines, not wedging (Sutton et al. 2004).

Cheat Lake channel catfish were found to use terrestrial food items between 13 October and 4 December 2014. Use of terrestrial food items has been documented in other systems (Bailey and Harrison 1948; Hill et al. 1995; Edds et al. 2002). Inclusion of terrestrial food items in fall diets may supplement growth or may simply be the result of opportunistic foraging. Sweka and Hartman (2008) used bioenergetics modeling to determine that inclusion of terrestrial invertebrates in diets improved brook trout Salvelinus fontinalis growth in two West Virginia streams. Although trophic dynamics in small streams and reservoirs are quite different, consumption of vulnerable terrestrial organisms could provide calories with small energetic investment. Channel catfish have been described as opportunistic foragers (Bailey and Harrison 1948; Lewis 1976). Use of terrestrial prey items may be due to increased availability of terrestrial insects and tree fruits. Water-level fluctuations as a result of hydropower operations could have led to displacement of terrestrial food items through inundation of previously exposed substrate.

Our data on size structure, age structure, mortality, condition, growth, and fall diets of the channel catfish population in Cheat Lake will inform future management decisions. Additionally, this information may be applicable to the management of other Central Appalachian channel catfish populations because existing scientific literature on the population dynamics of channel catfish is limited for this geographic region. Based on the fast growth and abundance of quality-length (>410 mm; Gabelhouse 1984) channel catfish in Cheat Lake, further management may not be needed at this time. Presently, angling effort for channel catfish in Cheat Lake is unknown. Conducting an angler survey would allow fisheries managers to quantify angling effort and harvest rates for channel catfish on Cheat Lake and also determine angler attitudes about size structure and abundance.

Please note: The Journal of Fish and Wildlife Management is not responsible for the content or functionality of any supplemental material. Queries should be directed to the corresponding author for the article.

Table S1. Details on individual sampling events for channel catfish Ictalurus punctatus in Cheat Lake, West Virginia. Dates provided were from the year 2014. Water temperatures presented were measured by the U.S. Geological Survey water gauge on the Cheat River at Albright, West Virginia, at 2400 hours. Gear was denoted as EGN (experimental gill nets), HN (hoop nets), GN (46-m gill nets), and BEF (boat electrofishing). See text for thorough explanations of net dimensions.

Found at DOI: 10.3996/092015-JFWM-091.s1; (13 KB DOCX).

Please note: The Journal of Fish and Wildlife Management is not responsible for the content or functionality of any archived material. Queries should be directed to the corresponding author for the article.

To cite this archived material, please cite both the journal article (formatting found in the Abstract section of this article) and the following recommended format for the archived material.

Data A1. Hilling CD, Welsh SA, Smith DM. Data from: Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia. Journal of Fish and Wildlife Management, 7(2):xx–xx. Archived in Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.8583t

G. Merovich and D. Wellman provided constructive comments that improved previous versions of this manuscript. We thank E. Irwin and an anonymous reviewer for comments that further improved the manuscript. We also thank J. Aldinger, E. Miller, A. Rizzo, and P. Thompson for their assistance in collection and processing of samples. Funding for this project was provided by Harbor Hydro Holdings, LLC., and West Virginia Division of Natural Resources. This study was performed under the auspices of West Virginia University IACUC protocol 11-0403.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Akaike
H.
1983
.
Information measures and model selection
.
International Statistical Institute
44
:
277
291
.
Amundsen
PA,
Gabler
HM,
Staldvik
FJ.
1996
.
A new approach to graphical analysis of feeding strategy from stomach contents data-modification of the Costello (1990) method
.
Journal of Fish Biology
48
:
607
614
.
Anderson
DR.
2008
.
Model based inference in the life sciences: a primer on evidence
.
New York
:
Springer
.
Bailey
RM,
Harrison
HM.
1948
.
Food habits of the southern channel catfish (Ictalurus lacustrus punctatus) in the Des Moines River, Iowa
.
Transactions of the American Fisheries Society
75
:
110
138
.
Barada
TJ,
Pegg
MA.
2011
.
Population characteristics of channel catfish in the Platte River, Nebraska
.
Pages
81
94
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Blackwell
BG,
Brown
ML,
Willis
DW.
2000
.
Relative weight (Wr) status and current use in fisheries assessment and management
.
Reviews in Fisheries Science
8
:
1
44
.
Bonar
SA,
Pahutski
J,
Bolding
BD,
Fletcher
D,
Divens
M.
1997
.
Survival and growth of channel catfish stocked in Washington lakes
.
North American Journal of Fisheries Management
17
:
773
778
.
Bouska,
WW,
Longhenry
C,
Bailey
P,
Fryda
D,
Headley
H.
2011
.
Channel catfish populations, management, and angler use in the Main–Stem Missouri River reservoirs
.
Pages
167
176
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Brown
ML,
Jaramillo
F,
Gatlin
DM,
Murphy
BR.
1995
.
A revised standard weight (Ws) equation for channel catfish
.
Journal of Freshwater Ecology
10
:
295
302
.
Buckland
ST,
Burnham
KP,
Augustin
NH.
1997
.
Model selection: an integral part of inference
.
Biometrics
53
:
603
618
.
Buckmeier
DL,
Irwin
ER,
Betsill
RK,
Prentice
JA.
2002
.
Validity of otolith and pectoral spines for estimating ages of channel catfish
.
North American Journal of Fisheries Management
22
:
934
943
.
Burnham
KP,
Anderson
DR.
2002
.
Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition
.
New York
:
Springer
.
Burnham
KP,
Anderson
DR,
Huyvaert
KP.
2011
.
AIC model selection and multimodel inference in behavioral ecology: some background, observation, and comparisons
.
Behavioral Ecology and Sociobiology
65
:
23
35
.
Chipps
SR,
Garvey
JE.
2007
.
Assessment of diets and feeding patterns
.
Pages
473
514
in
Guy
CS,
Brown
ML,
editors
.
Analysis and interpretation of freshwater fisheries data
.
Bethesda, Maryland
:
American Fisheries Society
.
Colombo
RE,
Phelps
QE,
Garvey
JE,
Heidinger
RC,
Stefanavage
T.
2008
.
Gear-specific population demographics of channel catfish in a large midwestern river
.
North American Journal of Fisheries Management
28
:
241
246
.
Core
EL,
Anderson
BG,
Taylor
LH,
Boer
GH,
Birch
RL,
Norman
C,
Schwartz
FJ,
Basnett
FD,
Rohr
HJ,
Burley
IWA,
Gorman
JW,
Hamilton
R,
Hatfield
K,
Meredith
W,
Sawyer
J,
Struthers
G.
1959
.
Biological investigations of Cheat Lake: summary
.
Morgantown
:
West Virginia University
.
Crumpton
JE.
1999
.
Relative abundance, age, growth and food habits of channel and white catfish from the Clermont Chain of Lakes, Florida
.
Pages
115
119
in
Irwin ER, Hubert WA, Rabeni CF, Schramm
HL
Jr,
Coon
T,
editors
.
Catfish 2000: proceedings of the international ictalurid symposium
. Bethesda, Maryland: American Fisheries Society. Symposium 24.
Dagel
JD,
Wuellner
MR,
Willis
DW.
2010
.
Channel catfish diets include substantial vegetation in a Missouri River reservoir
.
The Prairie Naturalist
42
:
1
7
.
Edds
DR,
Matthews
WJ,
Gelwick
FP.
2002
.
Resource use by large catfishes in a reservoir: is there evidence for interactive segregation and innate differences?
Journal of Fish Biology
60
:
739
750
.
Etnier
DA,
Starnes
WC.
1993
.
Fishes of Tennessee
.
Knoxville
:
University of Tennessee Press
.
Flammang
MK,
Schultz
RD.
2007
.
Evaluation of hoop-net size and bait selection for sampling channel catfish in Iowa impoundments
.
North American Journal of Fisheries Management
27
:
512
518
.
Freund
JG,
Petty
JT.
2007
.
Response of fish and macroinvertebrate bioassessment indices of water quality in a mined Appalachian watershed
.
Environmental Management
39
:
707
720
.
Gabelhouse
DW.
1984
.
A length-categorization system to assess fish stocks
.
North American Journal of Fisheries Management
4
:
273
285
.
Griswold
BL,
Tubb
RA.
1977
.
Food of yellow perch, white bass, freshwater drum, and channel catfish in Sandusky Bay, Lake Erie
.
The Ohio Journal of Science
77
:
43
47
.
Gustafson
KA.
1988
.
Management briefs: approximating confidence intervals for indices of fish population size structure
.
North American Journal of Fisheries Management
8
:
139
141
.
Haxton
T,
Punt
K.
2004
.
Abundance and demography of channel catfish in a large northern river
.
North American Journal of Fisheries Management
24
:
1440
1446
.
Hill
TD,
Duffy
WG,
Thompson
MR.
1995
.
Food habits of channel catfish in Lake Oahe, South Dakota
.
Journal of Freshwater Ecology
10
:
319
323
.
Hilling
CD,
Welsh
SA,
Smith
DM.
2016
.
Data from: Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia
.
(see Archived Material, Data A1, Archived in Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.8583t
Hubert
WA.
1999
a
.
Biology and management of channel catfish
.
Pages
3
22
in
Irwin ER, Hubert WA, Rabeni CF, Schramm
HL
Jr,
Coon
T,
editors
.
Catfish 2000: proceedings of the international ictalurid symposium
. Bethesda, Maryland: American Fisheries Society. Symposium 24.
Hubert
WA.
1999
b
.
Standards for assessment of age and growth data for channel catfish
.
Journal of Freshwater Ecology
14
:
313
326
.
Jackson
ZJ,
Quist
MC,
Larscheid
JG.
2008
.
Growth standards for nine North American fish
.
Fisheries Management and Ecology
15
:
107
118
.
Katsanevakis
S.
2006
.
Modelling fish growth: model selection, multi-model inference and model selection uncertainty
.
Fisheries Research
81
:
229
235
.
Katsanevakis
S,
Maravelias
CD.
2008
.
Modelling fish growth: multi-model inference as a better alternative to a priori using von Bertalanffy equation
.
Fish and Fisheries
9
:
178
187
.
Lewis
GE.
1976
.
Summer food of channel catfish in a West Virginia flood control reservoir
.
The Progressive Fish Culturist
38
:
177
178
.
Maceina
MJ.
1997
.
Simple application of using residuals from catch-curve regressions to assess year-class strength in fish
.
Fisheries Research
32
:
115
121
.
Marsh
PC.
1981
.
Food of channel catfish in the Coachella Canal, California
.
Journal of the Arizona–Nevada Academy of Science
16
:
91
95
.
Mazerolle
MJ.
2015
.
AICcmodavg: model selection and multimodel inference based on (Q)AIC(c). R package version 2.0-3
. .
Merovich
GT,
Petty
JT.
2007
.
Interactive effects of multiple stressors and restoration priorities in a mined Appalachian watershed
.
Hydrobiologia
575
:
13
31
.
Merovich
GT,
Stiles
JM,
Petty
JT,
Ziemkiewicz
PF,
Fulton
JB.
2007
.
Water chemistry-based classification of streams and implications for restoring mined Appalachian watersheds
.
Environmental Toxicology and Chemistry
26
:
1361
1369
.
Michaletz
PH.
2006
.
Prey resource by bluegill and channel catfish in small impoundments
.
Fisheries Management and Ecology
13
:
347
354
.
Michaletz
PH,
Sullivan
KP.
2002
.
Sampling channel catfish with tandem hoop nets in small impoundments
.
North American Journal of Fisheries Management
22
:
870
878
.
Miranda
LE,
Bettoli
PW.
2007
.
Mortality
.
Pages
229
277
in
Guy
CS,
Brown
ML,
editors
.
Analysis and interpretation of freshwater fisheries data
.
Bethesda, Maryland
:
American Fisheries Society
.
Neely
BC,
Dumont
SC.
2011
.
Effect of soak duration on precision on channel catfish catch with boated, tandem hoop nets
.
Pages
557
561
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Neumann
RM,
Guy
CS,
Willis
DW.
2012
.
Length, weight, and associated indices
.
Pages
637
676
in
Zale
AV,
Parrish
DL,
Sutton
TM,
editors
.
Fisheries techniques, 3rd edition
.
Bethesda, Maryland
:
American Fisheries Society
.
Phelps
QE,
Tripp
SJ,
Garvey
JE,
Herzog
DP,
Hrabik
RA,
Ostendorf
DE,
Ridings
JW,
Crites
JW.
2011
.
Juvenile channel catfish habitat use in the Middle Mississippi River
.
Pages
535
543
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Quist
MC,
Guy
CS,
Schultz
RD,
Stephen
JL.
2003
.
Latitudinal comparisons of walleye growth in North America and factors influencing growth of walleyes in Kansas reservoirs
.
North American Journal of Fisheries Management
23
:
677
692
.
Quist
MC,
Pegg
MA,
DeVries
DR.
2012
.
Age and growth
.
Pages
677
731
in
Zale
AV,
Parrish
DL,
Sutton
TM,
editors
.
Fisheries techniques, 3rd edition
.
Bethesda, Maryland
:
American Fisheries Society
.
R Core Team
.
2015
.
R: a language and environment for statistical computing
.
Vienna, Austria
:
R Foundation for Statistical Computing
.
Available: http://www.R-project.org/ (February 2015)
.
Richters
LK,
Pope
KL.
2011
.
Catch of channel catfish with tandem-set hoop nets and gill nets in lentic systems of Nebraska
.
Pages
573
580
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Ricker
WE.
1975
.
Computation and interpretation of biological statistics of fish populations
.
Ottawa, Ontario
:
Fisheries Research Board of Canada Bulletin 191
.
Rypel
AL.
2011
.
Meta-analysis of growth for five North American catfishes: effects of climate, hydrologic habitat, and latitudinal countergradients
.
Pages
661
677
in
Michaletz
PH,
Travinichek
VH,
editors
.
Conservation, ecology and management of catfish: the second international symposium
.
Bethesda, Maryland: American Fisheries Society. Symposium 77.
Santucci
Jr
VJ,
Wahl
DH,
Clapp
DF.
1999
.
Efficiency and selectivity of sampling methods used to collect channel catfish in impoundments
.
Pages
317
328
in
Irwin ER, Hubert WA, Rabeni CF, Schramm
HL
Jr,
Coon
T,
editors
.
Catfish 2000: proceedings of the international ictalurid symposium
. Bethesda, Maryland: American Fisheries Society. Symposium 24.
Shoup
DE,
Callahan
SP,
Wahl
DH,
Pierce
CL.
2007
.
Size-specific growth of bluegill, largemouth bass and channel catfish in relation to prey availability and limnological variables
.
Journal of Fish Biology
70
:
21
34
.
Shuman
DA,
Klumb
RA,
Wilson
RH,
Jaeger
ME,
Haddix
T,
Gardner
WM,
Doyle
WJ,
Horner
PT,
Ruggles
M,
Steffensen
KD,
Stukel
S,
Wanner
GA.
2011
.
Pallid sturgeon size structure, condition, and growth in the Missouri River Basin
.
Journal of Applied Ichthyology
27
:
269
281
.
Smith
MW,
Then
AY,
Wor
C,
Ralph
G,
Pollock
KH,
Hoenig
JM.
2012
.
Recommendations for catch-curve analysis
.
North American Journal of Fisheries Management
32
:
956
967
.
Sullivan
KP,
CM
Gale.
1999
.
A comparison of channel catfish catch rates, size distributions, and mortalities using three different gears in a Missouri impoundment
.
Pages
293
300
in
Irwin ER, Hubert WA, Rabeni CF, Schramm
HL
Jr,
Coon
T,
editors
.
Catfish 2000: proceedings of the international ictalurid symposium
. Bethesda, Maryland: American Fisheries Society. Symposium 24.
Sutton
TM,
Cyterski
MJ,
Ney
JJ,
Duval
MC.
2004
.
Determination of factors influencing stomach content retention by striped bass captured using gillnets
.
Journal of Fish Biology
64
:
903
910
.
Sweka
JA,
Hartman
KJ.
2008
.
Contribution of terrestrial invertebrates to yearly brook trout prey consumption and growth
.
Transactions of the American Fisheries Society
137
:
224
235
.
Tyus
HM,
Nikirk
NJ.
1990
.
Abundance, growth, and diet of channel catfish, Ictalurus punctatus, in the Green and Yampa rivers, Colorado and Utah
.
The Southwestern Naturalist
35
:
188
198
.
Wege
GJ,
Anderson
RO.
1978
.
Relative weight (Wr): a new index of condition for largemouth bass
.
Pages
79
91
in
Novinger
GD,
Dillard
JG,
editors
.
New approaches to the management of small impoundments
.
Bethesda, Maryland: American Fisheries Society, North Central Division. Special Publication 5.
Weisberg
SB,
Janicki
AJ.
1990
.
Summer feeding patterns of white perch, channel catfish, and yellow perch in the Susquehanna River, Maryland
.
Journal of Freshwater Ecology
5
:
391
405
.
Welsh
SA,
Perry
SA.
1997
.
Acidification and fish occurrence in the upper Cheat River Drainage, West Virginia
.
Journal of the American Water Resources Association
33
:
423
429
.
Yin
YJ,
Tzeng
WN.
2009
.
Modelling growth of Japanese eel Anguilla japonica in the lower reach of the Kao-Ping River, southern Taiwan: an information theory approach
.
Journal of Fish Biology
75
:
100
112
.

Author notes

Citation: Hilling CD, Welsh SA, Smith DM. 2016. Age, growth, and fall diet of channel catfish in Cheat Lake, West Virginia. Journal of Fish and Wildlife Management 7(2):304-314; e1944–687X. doi: 10.3996/092015-JFWM-091

The findings and conclusions in this article are those of the author(s) and do not necessarily represent the views of the U.S. Fish and Wildlife Service.

Supplemental Material