Management agencies often estimate the ages of Largemouth Bass Micropterus salmoides based on the examination of scales—a structure that is known to produce biased estimates—without knowing how the associated bias affects management decisions. We sought to understand the effects of this bias by comparing population metrics that were predicted using scale‐derived and otolith‐derived age data. We collected scales and otoliths from Largemouth Bass that were sampled during standard electrofishing surveys. The age of each fish was estimated independently by three separate readers using both scales and otoliths. We assessed the average coefficient of variation for scale‐derived and otolith‐derived age estimates, examined the bias of scale‐derived age estimates, and estimated von Bertalanffy growth model parameters by using ages estimated from scales and otoliths. These parameter estimates were used in yield‐per‐recruit simulations that predicted yield and the percentage of individuals in the cohort surviving to 380 mm (proportional size distribution [PSD] 380) or to 470 mm (PSD 470) at several levels of natural mortality and fishing mortality. Otolith‐derived age estimates were more precise; scale‐derived age estimates showed significant positive bias for fish younger than age 6 and significant negative bias for fish older than age 6. Von Bertalanffy parameter estimates were significantly different when using ages estimated from scales and those estimated from otoliths. Modeling indicated that estimates of yield and PSD 380 resulting from the two structures were similar. However, the use of scale‐derived ages resulted in underestimating the impact of fishing mortality on PSD 470 by as much as five times at low levels of natural mortality and fishing mortality. Our estimates of precision and bias were similar to other comparisons of scales and otoliths, and the results of our yield‐per‐recruit simulations are likely generally applicable for Largemouth Bass management. Trophy fishing is a common management objective, and managers relying on scale‐based age data could be less likely to adopt the restrictive harvest regulations that are critical for producing trophy Largemouth Bass. Received November 17, 2016; accepted June 22, 2017 Published online August 22, 2017

Understanding catchability—the fraction of a stock caught by a defined unit of effort—is crucial to using fisheries assessment data to index abundance. We conducted mark–recapture experiments to estimate catchability and evaluate standard boat electrofishing methods for assessing populations of Largemouth Bass Micropterus salmoides. We then used a resampling analysis to test for differences in bass CPUE (fish/h and fish/km) between two high‐density reservoirs and one low‐density reservoir and among surveys within each reservoir. We compared scenarios using surveys conducted only during (1) the standard time period (mid‐April to mid‐May) and (2) the entire assessment period (early April to mid‐June). We considered the percentage of significant differences in CPUE between the high‐density and low‐density reservoirs to represent statistical power (i.e., the ability to detect a difference in CPUE when a difference actually exists) and the percentage of significant differences in CPUE between surveys in the same reservoir to represent the false‐positive rate (i.e., the detection of a difference in CPUE when no difference in density exists). Catchability and CPUE were greatest and least variable during recapture events conducted during the standard period. The mean catchability of sub–stock length Largemouth Bass (150–200 mm) and memorable‐length bass (≥510 mm) was significantly less than those for other length categories. Statistical power exceeded 80%, and the false‐positive rate was generally less than 10% for sampling during the standard period at as few as six electrofishing sites. When including samples from outside the standard period, power was lower and the false‐positive rate was as high as 60%. Power and false‐positive rate were similar whether effort was measured in time or distance. Our results emphasize that standardized springtime boat electrofishing assessments validly index Largemouth Bass density and size structure. Received October 7, 2016; accepted February 2, 2017 Published online April 24, 2017

Fisheries managers implement minimum length limits (MLLs) to improve the size structure of populations of crappie Pomoxis spp. throughout Midwestern and southeastern U.S. reservoirs. The success of these regulations has been mixed, with several implementations resulting in undesirable outcomes, including slow growth and stunting of crappies, and ultimately regulation removal. Consequently, it is unclear whether and where MLLs should be used to improve crappie size structure. Beginning in 2003, Ohio instituted a statewide standard sampling protocol to monitor reservoir crappie populations, and between 2003 and 2010 a 229‐mm MLL was implemented at over 40 reservoirs throughout the state. Using these spatially and temporally extensive crappie population data, we sought to (1) test for the response of crappie population adult abundance, growth, and size structure to the MLL, (2) test whether reservoir surface area and/or productivity mediated this response, and (3) model fisheries outcomes at different reservoir sizes and productivities to predict where application of a MLL would be most appropriate. Using linear mixed‐effects models and an information theoretic approach, we found that crappie population abundances generally increased, whereas growth decreased in small, unproductive reservoirs but increased in large, productive reservoirs. Overall, the MLL failed to produce increases in size structure, except in large reservoirs. Yield‐per‐recruit models predicted a decrease in angler yield in response to a 229‐mm MLL in small reservoirs, whereas in large, productive reservoirs this regulation was predicted to increase angler yield. Consequently, the MLL could improve crappie fisheries in reservoirs larger than 1,000 ha with high productivity (total phosphorus concentrations > 50 μg/L) but could be counterproductive in small, unproductive reservoirs. Finally, our approach highlights the benefits of standard sampling as we were able to integrate data across years and reservoirs to make comparisons on a statewide scale.

North American fisheries management agencies commit considerable resources to managing reservoir fisheries for Channel Catfish Ictalurus punctatus, which often includes stocking. However, Channel Catfish population characteristics often vary greatly among reservoirs, resulting in variable and unpredictable fishery quality. We sampled Channel Catfish populations in 44 Ohio reservoirs with tandem, baited hoop nets to understand relationships among population characteristics (density, as CPUE from hoop nets; growth, as mean length at age 7; mortality, as total annual mortality from catch‐curve analysis; and size structure, as proportional size distribution), stocking, and the relationships between these characteristics and reservoir size (as surface area), predator density (as Largemouth Bass Micropterus salmoides electrofishing CPUE), and productivity (as chlorophyll‐a concentration). We used multiple linear regression and an information theoretic approach to select the most parsimonious models for explaining observed variation in Channel Catfish density, growth, mortality, and size structure. We found that population density varied greatly among our study reservoirs, and none of our models sufficiently explained variation in density. Reservoir size and the interaction between reservoir size and population density explained the most variation in Channel Catfish growth, but productivity was also important. Small reservoirs (≤101 ha) had low to moderate densities and growth was uniformly slow; however, in larger reservoirs, lower densities resulted in faster growth. Growth increased as productivity increased. Total annual mortality was uniformly low (<0.26) but increased with density. Faster growth led to populations with larger size structures. These outcomes show that the largest Ohio reservoirs (≥406 ha) are the most suitable for supporting populations with fast growth and large size structures. Dense populations (CPUE > 50 Channel Catfish/net set) resulted in slower growth, greater mortality, and poor size structure. Future research to understand natural recruitment in reservoir Channel Catfish populations could be important for explaining variation in density.

Fisheries managers efficiently sample reservoir Channel Catfish Ictalurus punctatus populations with tandem, baited hoop nets. However, catchability (the fraction of a fish stock caught with a defined unit of effort) of Channel Catfish with this gear and the size selectivity of this gear are not fully known. Furthermore, scientists have not identified a standard sampling period that maximizes catches while minimizing variation in catchability. Here, we estimated Channel Catfish population density (number/ha) and catchability with tandem, baited hoop nets using mark–recapture methods in three Ohio reservoirs during May–July 2016–2018. We tested for differences in catchability (1) among reservoirs; (2) among 50‐mm length categories; and (3) by week. We then tested CPUE as an index of density by simulating the sampling of populations with different densities based on observed variation in catchability and estimating the statistical power to detect density differences. We found that total catchability differed among study reservoirs, among length categories, and among sampling events but did not consistently change during the May–July sampling period. Catchability of 50‐mm length categories did not differ among reservoirs. The greatest catchability was observed for 400–649‐mm Channel Catfish. Our power analysis showed that we could detect a large (>2:1 effect sizes) difference in density with 80% power by using 20 or more sample sites. Furthermore, our length‐category‐specific catchability estimates provide information to reduce bias in size structure, growth, and mortality estimates derived from Channel Catfish samples collected with tandem, baited hoop nets. We encourage further development, validation, and application of tandem, baited hoop nets to better understand differences in reservoir Channel Catfish densities and size structures.

Management agencies commonly stock Channel Catfish Ictalurus punctatus as advanced yearlings instead of fingerlings (age 0) to help reduce potential predation mortality despite uncertainty regarding the degree to which predation limits fingerling poststocking survival. To better understand whether fingerling survival during the first 7 d after stocking—when predation risk is likely greatest—could benefit from the presence of alternative prey fish, we conducted an experiment in 0.4‐ha ponds (N = 18; 6 ponds/treatment) that measured fingerling (TL range = 56–186 mm) survival in ponds with predators only (adult Largemouth Bass Micropterus salmoides; mean TL = 327 mm; SE = 21), with predators and alternative prey fishes (Bluegill Lepomis macrochirus and Goldfish Carassius auratus), or with neither (i.e., control ponds). Without alternative prey, fingerling Channel Catfish survival 1 week after stocking was significantly (P < 0.01) lower (89%) than in the ponds with alternative prey (98%) or in the control treatment with no predators (97%). Our experiment also indicated the potential for alternative prey to promote fingerling survival by reducing water clarity, not just by serving as a buffer from predation. Further research, however, is needed to determine the degree to which our findings apply to larger ecosystems and to learn whether stocked fingerlings survive well enough after the initial stocking period to achieve desired management goals. Even so, our results suggest that alternative prey can reduce Largemouth Bass predation mortality on fingerlings immediately after stocking, which could influence Channel Catfish stocking approaches in some managed systems.

Reproductive investment, expressed in terms of fecundity and egg quality produced by individual female fish, varies among populations for many species, reflecting plasticity in life history strategies related to intraspecific density dependence or environmental variability. Fisheries scientists and managers have long sought to understand differences in Largemouth Bass Micropterus salmoides population dynamics, yet basic life history traits, such as variation in reproductive investment, remain largely unknown. We determined the fecundity–weight and ovary energy density–weight relationships (where fecundity indexes egg quantity and ovary energy density indexes egg quality) for Largemouth Bass populations from 19 Ohio reservoirs and examined factors that were correlated with population‐specific differences. We found that both relationships varied among reservoir populations, with some interannual variation in reservoirs sampled in multiple years. We then related fecundity and ovary energy density to (1) population characteristics, including population density (as indexed by standard shoreline boat electrofishing CPUE, fish/h) and growth (as indexed by the growth coefficient k from the von Bertalanffy growth function); and (2) reservoir characteristics, including reservoir size (as surface area) and productivity (as Secchi transparency depth). We found that populations with greater fecundity also exhibited greater ovary energy density, indicating that the quantity and quality of reproductive output were greater in some populations than in others. Populations with high reproductive investment were associated with low Largemouth Bass density, fast growth, large reservoir size, and high productivity (i.e., low Secchi transparency). The among‐population variation in reproductive investment provides evidence of density‐dependent control of fecundity and egg quality.

Fisheries managers commonly use low-frequency electrofishing to survey Flathead Catfish Pylodictis olivaris and Blue Catfish Ictalurus furcatus populations; however, inconsistent methods prohibit comparisons among studies. Here, we simultaneously sampled Flathead Catfish and Blue Catfish to compare single-and chase-boat low-frequency electrofishing configurations in five Ohio River navigational pools and inform standard sampling of these catfishes. Our objectives were to (1) compare Flathead Catfish and Blue Catfish CPUE among length categories, (2) evaluate the prevalence of high-catch samples, and (3) determine the number of 15-min electrofishing sites needed to achieve predefined precision and catch objectives between single-and chase-boat configurations. The chase-boat configuration produced greater catches of both Flathead Catfish (mean total CPUE was 44.6 fish/h for the chase-boat configuration versus 32.8 fish/h for the single-boat configuration) and Blue Catfish (mean total CPUE of 6.8 fish/h for the chaseboat configuration versus 2.8 fish/h for the single-boat configuration). Zero-inflated negative binomial models revealed that CPUE was greater with the chase boat for both Flathead Catfish and Blue Catfish across substock, stock-quality, and quality and larger length categories. High-CPUE samples (total CPUE >52 Flathead Catfish/h or >8 Blue Catfish/h) were more likely with the chase-boat configuration than the single-boat configuration. We found that a similar number of sites were needed to achieve the precision objective (relative standard error of CPUE <25%) for both configurations for Flathead Catfish; however, to achieve the precision objective for Blue Catfish, more single-boat sites/pool were needed compared to chase-boat sites/pool. To achieve the catch objective (capture 100 stock-length catfish/pool), more single-boat sites/pool were needed than chase-boat sites/pool for both species. Our results suggest that using a chase boat better indexes the abundance of Flathead and Blue catfish, particularly when high catches are possible. However, more research is needed to inform the standardization of low-frequency electrofishing for sampling catfishes in large river systems.Flathead Catfish Pylodictis olivaris and Blue Catfish Ictalurus furcatus provide popular recreational fisheries and valuable commercial fisheries throughout the Mississippi River basin (Graham 1999). Fisheries managers often rely on low-frequency electrofishing to assess Flathead Catfish and Blue Catfish populations (Bodine et al. 2013). However, low-frequency electrofishing methods vary greatly among studies (Brown 2009;Bodine et al. 2013; Montegue and Shoup 2021) and are poorly described in fisheries methodological texts (e.g., Bonar et al. 2009; Zale et al. 2012). Sampling variables such as electrofishing pulse frequency, duty cycle, power, sample duration, and the use of one or more chase boats lack recommended standards. Therefore, the effectiveness and efficiency of low-