Evaluation of Precision and Sample Sizes Using Standardized Sampling in Kansas Reservoirs

Transcription

1 K156: {Koch, 214 #4834} North American Journal of Fisheries Management 34: , 214 Ó American Fisheries Society 214 ISSN: print / online DOI: 1.18/ ARTICLE Evaluation of Precision and Sample Sizes Using Standardized Sampling in Kansas Reservoirs Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Jeff D. Koch* Kansas Department of Wildlife, Parks, and Tourism, South Yoder Road, Pretty Prairie, Kansas 6757, USA Ben C. Neely Kansas Department of Wildlife, Parks, and Tourism, 589 Road 2925, Independence, Kansas 6731, USA Michael E. Colvin Oregon Cooperative Fish and Wildlife Research Unit, Department of Fisheries and Wildlife, Oregon State University, 14 Nash Hall, Corvallis, Oregon 97331, USA Abstract We evaluated the precision of samples and the number of stock-length fish collected by means of standard methods used for sampling North American freshwater fishes from 21 to 213 in Kansas. Additionally, we used resampling procedures to determine the number of gear deployments needed to achieve a relative standard error (RSE) of 25% for the CPUE and collect 1 stock-length individuals. Median RSE of electrofishing samples was generally less than 25% for Largemouth Bass Micropterus salmoides in all sizes of reservoirs and for Channel Catfish Ictalurus punctatus in medium (251 1, acres) and large reservoirs (greater than 1, acres). The RSE estimates were generally >25% for Bluegill Lepomis macrochirus and crappies Pomoxis spp. collected in trap nets and palmetto bass (female Striped Bass Morone saxatilis male White Bass M. chrysops) and Walleye Sander vitreus sampled in gill nets. With few exceptions, 1 stock-length individuals of all target species (e.g., Largemouth Bass, Bluegill, crappies, palmetto bass, Channel Catfish, Walleye) were not sampled at current levels of effort. Resampling procedures indicated that fewer than 2 deployments were usually needed to obtain an RSE 25% and 1 stock-length fish for Largemouth Bass in smaller impoundments (i.e., <25 acres); however, more than 2 deployments were needed in larger impoundments. The median effort needed to achieve an RSE 25% for Bluegills and crappies in trap nets varied and may exceed what some biologists find practical. Fewer gill-net deployments were needed to reach an RSE 25% for palmetto bass and Walleyes than to collect 1 stock-length fish. Our results indicate that more samples than are currently prescribed are generally needed to precisely sample sport fishes by means of standardized protocols in Kansas reservoirs. In some instances, obtaining precise samples may not be logistically feasible. In these situations, biologists should be aware of the potential shortcomings of sampling protocols and set objectives accordingly. Fish sample data should be collected using protocols designed to allow rigorous statistical comparisons (Willis and Murphy 1996). As such, biologists must consider whether collected data will allow a proper evaluation of research or management questions (Brown and Austen 1996). Additionally, data must be collected using standard methods that allow for spatial and temporal comparisons (Bonar et al. 29a). Two important characteristics of fish sample data are accuracy and precision. Accuracy refers to the closeness of a metric to its true value, and precision refers to how well test results can be reproduced. Because determining accuracy of fisheries samples is generally not feasible, precision is most often used *Corresponding author: jeff.koch@ksoutdoors.com Received May 12, 214; accepted August 23,

2 K156: {Koch, 214 #4834} 1212 KOCH ET AL. Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 to provide assurance that no unsuspected bias exists in the measure (Brown and Austen 1996). If data are imprecise inferences about metrics describing fish assemblages and populations may be limited (Brown and Austen 1996; Quist et al. 29). Although the number of gear deployments is directly related to precision (Wilde 1995; Wilde and Fisher 1996; Dumont and Schlechte 24), few recommendations are available to guide the number of gear deployments for standardized fish sampling. Quist et al. (29) suggested that existing data be used to determine the number of gear deployments needed to meet desired sampling objectives. This approach should be considered when developing standardized sampling protocols (Noble et al. 27; Quist et al. 29). Additionally, gear deployment estimators provide biologists with realistic expectations of conclusions that can be drawn from fish sampling data. The Kansas Department of Wildlife,Parks,andTourism (KDWPT) adopted standard methods for sampling North American freshwater fishes in 21 following recommendations from Bonar et al. (29b). Kansas biologists standardized gears, seasons and times of sampling, and the manner in which sampling sites were chosen. As no sample size criteria are provided in the methods proposed by Bonar et al. (29b), the number of deployments per impoundment were chosen based on logistical restraints associated with reservoir size (i.e., sample size increases with reservoir size; Table 1). Currently, the main objective of KDWPT sampling is to achieve these minimum sampling efforts; however, obtaining precise data in regard to relative abundance metrics (i.e., CPUE) should also be considered. Several studies have recommended target precision levels of a relative standard error (RSE) of at least 25% for a mean CPUE (hereafter RSE25) in fisheries management surveys (Robson and Regier 1964; Hardin and Conner 1992; Wilde and Fisher 1996; Dumont and Schlechte 24). Additional sampling objectives may include description of population size structure. Researchers have suggested a minimum sample size of 1 stocklength individuals to adequately describe size structure (Anderson and Neumann 1996), although specific sample sizes vary with survey objectives (Gustafson 1988; Miranda 1993, 27; Vokoun et al. 21; Quist et al. 29). Regardless, variability of samples and number of fish collected are important to consider when establishing or evaluating a sampling protocol. Evaluation of KDWPT fish sample data can provide insight into the quality of existing data and help guide future sampling efforts. Further, this evaluation provides an examination of the influence of fish sampling standardization as recommended by Bonar et al. (29b). As such, our objectives were to (1) evaluate the precision of catch estimates and the number of stock-length individuals collected from standard sampling gears (i.e., electrofishing, trap-netting, gill netting) after implementation of standard methods used for sampling North American freshwater fishes and (2) use resampling procedures to develop guidelines for the number of gear deployments required to obtain an RSE25 and 1 stock-length fish. TABLE 1. Prescribed minimum effort and median actual number of gear deployments (minimum and maximum actual effort in parentheses) expended by KDWPT using standard methods for sampling North American freshwater fishes from 21 to 213. Gill-net and trap-net effort was defined as the number of net-nights. Electrofishing effort was defined as the number of 1-min stations. Gear Reservoir size (acres) Prescribed minimum effort Actual effort Experimental gill net <5 3 3 (1 5) (2 8) (2 12) (3 1) 1, 2, (1 11) 2,5 4, (6 19) 5, 8, (9 16) 9, 2 2 (6 27) Trap net <1 2 2 (1 8) (1 1) (2 8) 1, 1, (9 12) 1,5 1, (8 8) 2, (2 24) Electrofishing <25 6 a 6 (1 15) (1 65) a Or a complete shoreline circuit if six stations cannot be completed.

3 K156: {Koch, 214 #4834} EVALUATION OF STANDARDIZED SAMPLING TECHNIQUES 1213 Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 METHODS Fish Collection Data collected during were analyzed from 184 Kansas reservoirs varying in size from 1 to 16,2 acres. Although physical and chemical characteristics of Kansas reservoirs are diverse, most are relatively shallow, turbid, and do not stratify due to persistent winds (Dodds et al. 26). The watersheds of most study reservoirs are dominated by either row crop or grassland. More detailed descriptions of Kansas impoundments are given in Dodds et al. (26). Target species for this project included Largemouth Bass Micropterus salmoides, Bluegill Lepomis macrochirus, crappies Pomoxis spp., Channel Catfish Ictalurus punctatus, palmetto bass (female Striped Bass Morone saxatilis male White Bass M. chrysops), and Walleye Sander vitreus and were chosen for their popularity with anglers, status of concern for managers, and widespread distribution in Kansas. For each target species, data were included in the analysis when at least one individual of that species was sampled from the respective impoundment during the study years. The number of reservoirs included for each target species varied from 157 to 164 for Bluegill, Channel Catfish, crappies, and Largemouth Bass, while 55 reservoirs were included in the analysis for both palmetto bass and Walleye. Discrepancies in these numbers and total number of reservoirs included in the analysis were due to the absence of species or gears in some sampling events. Largemouth Bass were sampled by KDWPT in spring using daytime boat electrofishing. Electrofishing equipment (e.g., Smith Root, Coffelt, Midwest Lake Electrofishing Systems) was variable among Kansas biologists; however, target power outputs of 2,75 3,25 W were used to achieve the desired fish response (Miranda 29). Electrofishing surveys were conducted at randomly selected shoreline stations for 1 min. Reservoir maps with numbered-grid overlays were produced to assist in the selection of randomized sampling sites. Each grid was ft for impoundments smaller than 1,2 acres and 1,1 1,1 ft for impoundments larger than 1,2 acres. Prior to fish sampling each year, grids were randomly chosen for all gears from appropriate sampling locations (Bonar et al. 29b). A minimum of 1 electrofishing stations were sampled in reservoirs greater than 25 acres, and a minimum of six stations or one complete lap of the shoreline were sampled in reservoirs less than 25 acres (Table 1). Largemouth Bass were sampled during their spawning period when water temperatures were 6 7 F. For this analysis, only electrofishing samples collected between April 1 and May 31 were used. Bluegills and crappies were collected with trap nets from October 1 to November 3 when water temperatures were 68 F or below. Trap nets consisted of two rectangular 3 6-ft frames, a 4-in opening in the frame, and four 2.5-ft-diameter hoops with a funnel attached to the first and third hoops (Pope et al. 29). The leads were 1 ft long and were constructed of.5-in bar mesh. Trap nets were deployed in randomly selected locations in water 3 16 ft deep in the afternoon and retrieved the following morning, so sample periods encompassed two crepuscular periods (Pope et al. 29). Black Crappie P. nigromaculatus and White Crappie P. annularis were combined because they are grouped for management activities in Kansas (e.g., length limits, creel limits). Trap-net effort varied by reservoir size from 2 to 16 net-nights (Table 1). Channel Catfish, palmetto bass, and Walleyes were sampled during autumn with gill nets that were generally fished concurrently with trap nets. Experimental sinking gill nets were 8 ft long, 6 ft deep, and constructed of eight randomly ordered 1-ft panels of in bar measure monofilament mesh in.25-in increments (Pope et al. 29). Similar to trap nets, gill nets were deployed in the afternoon and retrieved the next morning. Gill nets were set perpendicular to the shoreline in 6 16 ft of water with the orientation of nets randomly assigned for each deployment. Prescribed gill-net deployments varied from 3 to 2 net-nights depending on reservoir size. Trap nets and gill nets that were fished for h were included in the analysis and corresponding effort was considered as one net-night. Because of variation in fish assemblages and reservoir characteristics, study reservoirs were grouped by surface area. Ponds were classified as those 2 surface acres. Most of these impoundments were small urban and municipal ponds. Reservoirs from 21 to 25 acres were classified as small, and encompassed state-owned Kansas State Fishing Reservoirs. Medium impoundments varied from 251 to 1, acres and generally represented larger municipal and county reservoirs. Lastly, reservoirs larger than 1, acres were classified as large, which represented federal flood control reservoirs and power plant cooling supplies. Data Analysis Observed data. The precision of catch rates for stocklength fish (Gabelhouse 1984; Dumont and Neely 211) was quantified by calculating the RSE for each combination of reservoir, target species, and sample year. As such, depending on how many years an impoundment was sampled, up to four RSE estimates were calculated for each reservoir and species. Similarly, the number of fish collected per sample was calculated as the sum of all stock-length individuals collected per year in each reservoir with each gear (e.g., number of stocklength Bluegills captured in trap nets at one reservoir in a given year). Stock-length fish were used in this analysis to mitigate potential effects of large and variable catches of age- individuals. Resampling analysis. Data for resampling techniques consisted of the number of stock-length fish of each target species captured during each gear deployment in each impoundment. For electrofishing, one 1-min station was considered as

4 K156: {Koch, 214 #4834} 1214 KOCH ET AL. Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 one deployment, and for gill and trap nets, one net-night was considered as one deployment. Catch data for each target species and reservoir combination were pooled among years to avoid potential effects of small sample sizes, as some impoundments had few sample deployments (e.g., <5) annually. This resulted in each target species and reservoir combination having an array of numbers that represented catch per gear deployment during the entire study period. The resampling approach (i.e., stochastic resampling procedure; Dumont and Schlechte 24) began by randomly resampling (with replacement) two numbers (i.e., two gear deployments) 2, times and calculating the RSE for each of the 2, resamples. The proportion of 2, resamples achieving an RSE 25 was then calculated. If the proportion was <.8, then three deployments were evaluated. The threshold of.8 was used in a similar analysis by Dumont and Schlechte (24) as they indicated that 8% certainty in estimates was sufficient for these analyses. This process continued iteratively in increments of one deployment until the proportion of resampling events achieving precision (RSE25) objectives was.8. This process was repeated to evaluate gear deployments needed to sample 1 stock-length fish. A minimum of two and a maximum of 1 deployments were set as the lower and upper boundaries to reflect the practical amounts of effort (Dumont and Schlechte 24). Resampling analysis was conducted using the program R (R Core Development Team 213). RESULTS Electrofishing Observed precision of Largemouth Bass CPUE from 21 to 213 was relatively high, as RSE was often below 25% (Figure 1). Largemouth Bass catch precision appeared more variable in larger waters, although median RSE was below 25% for all reservoir sizes. With the exception of small reservoirs, the target of 1 stock-length Largemouth Bass was rarely achieved in annual samples (Figure 2). Resampling analyses indicated less than 1 deployments were needed to reach RSE25 for ponds and small impoundments (Figure 3). As reservoir size increased, more samples were needed to achieve an RSE25 for Largemouth Bass. In large reservoirs, the median number of samples needed to reach RSE25 was approximately 23; however, to achieve an RSE25 in 75% of surveys, over 5 electrofishing stations would be needed. Fewer samples were needed to collect 1 stock-length Largemouth Bass in ponds and small reservoirs compared with larger reservoirs (Figure 4), where the number of samples needed to collect 1 fish was highly variable. This was evidenced by interquartile ranges for medium and large reservoirs of 88 and 64 samples, respectively. In medium and large reservoirs, approximately 2 45 stations were needed to collect 1 stock-length fish in 5% of surveys. Additionally, 8 to over 1 surveys were needed to achieve this objective in 75% of surveys. Trap-Netting Catch rates of Bluegills and crappies in trap nets were highly variable among years and reservoirs. Among species and reservoir sizes, the median RSE of stock CPUE was less than 25% for crappies only in large reservoirs. Among reservoir sizes, the RSE25 for Bluegills was only reached in at least 25% of samples in ponds (Figure 1). In larger impoundments, very few Bluegill CPUE estimates exhibited an RSE25. Excluding crappies in large reservoirs, 1 stock-length individuals were not typically captured in trap-net samples (Figure 2). Fewer trap nets were usually needed to precisely estimate the CPUE for crappies than for Bluegills. In many instances, 2 or more trap nets were needed to reach an RSE25 for Bluegills regardless of reservoir size (Figure 3). Similarly, 2 trap nets were required to reach an RSE25 for crappies 5% of the time in all sizes of reservoirs except ponds. Fewer gear deployments were generally required to capture 1 stock-length Bluegills and crappies than to reach the RSE25 (Figure 4). Gill Netting Relative standard errors of gill-net catch rates were generally lower in larger reservoirs where more effort was expended. The median RSE for CPUE of Channel Catfish exceeded 25% in ponds and small reservoirs (Figure 1). Rarely were 1 stock-length Channel Catfish collected in any sampling event. The 9th percentile of Channel Catfish catch was greater than 1 fish only in large reservoirs (Figure 2). Palmetto bass and Walleyes were mostly absent from pond samples and catch rates were highly variable. The median RSE was below 25% for Walleyes only in large reservoirs; whereas, the median RSE for palmetto bass varied from 3% to 5% (Figure 1). One hundred stock-length palmetto bass or Walleyes were rarely collected in sampling events. Approximately 25% of samples from large reservoirs contained 1 palmetto bass, and only around 1% of samples contained 1 Walleyes (Figure 2). The number of gill nets needed to catch 1 stock-sized palmetto bass and Walleyes was generally high, often approaching or exceeding 5 samples at the 5th percentile (Figure 4). Generally, fewer than 2 gill nets were needed to reach an RSE25 for Channel Catfish in most samples in medium and large reservoirs. Similarly, 1 15 gill nets were needed to obtain an RSE25 for half the time in ponds and small reservoirs. About 2 4 gill nets were needed to collect 1 stock-sized Channel Catfish, regardless of reservoir size, in at least 5% of samples (Figure 4). More than 2 samples were usually needed to achieve an acceptable precision of catch rates for palmetto bass in any size of reservoir at the

5 K156: {Koch, 214 #4834} EVALUATION OF STANDARDIZED SAMPLING TECHNIQUES Ponds 1 Small Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Relative standard error Medium 5th percentile (Figure 3). Further, at the 75th percentile, over 4 gill-net deployments were needed to achieve an RSE25 for palmetto bass. The number of samples needed to precisely sample Walleyes varied widely, but in large reservoirs, around 2 gill nets were needed to reach an RSE25 in 5% of samples. DISCUSSION With the exception of Channel Catfish in medium reservoirs and Largemouth Bass in all reservoir sizes, an RSE25 was not achieved at the 5th percentile for target fishes with the current number of samples in ponds and small and large Kansas reservoirs from 21 to 213. In large reservoirs, which received more sampling effort, the median RSE of CPUE was below 25% for Largemouth Bass, crappies, Channel Catfish, and Walleye. However, reaching an acceptable level of precision 5% of the time for these target species may not be acceptable to fisheries managers. Additionally, minimum recommended sample sizes for adequately describing size structure were rarely collected using current sampling protocols Large FIGURE 1. Box plots of RSE of CPUE estimates for Largemouth Bass, Bluegills, crappies, Channel Catfish, palmetto bass, and Walleyes from ponds ( 2 acres) and small (21 25 acres), medium (251 1, acres), and large reservoirs (>1, acres) in Kansas, Each data point represents an RSE of the sample for a species in a given year. Lower and upper fences are 25th and 75th percentiles, and the median is in between. Bars represent 1th and 9th percentiles. Horizontal reference line represents RSE25. Our results are similar to those reported in a study examining sampling precision and sample size requirements in Texas reservoirs (Dumont and Schlechte 24). In that study, the only target species that exhibited a median RSE of 25% for the CPUE of stock-length fish was Largemouth Bass. Although median Largemouth Bass RSE was below 25% for all sizes of Kansas reservoirs, substantial variation in CPUE was exhibited in medium and large reservoirs. Electrofishing data used for this study were collected during the day, and research has suggested that night electrofishing catch rates and precision are higher than those collected during the day (Paragamian 1989; Dumont and Dennis 1997). If biologists using day electrofishing wish to improve data quality, night electrofishing may be used. Additionally, in situations where collecting precise Largemouth Bass samples is important, decreasing electrofishing segment length (e.g., 5 min) may increase the number of gear deployments and improve sample precision, especially in instances where shoreline length may preclude large sample segments. Although Miranda et al. (1996) indicated that sample duration is inversely related to the variability of CPUE, given a fixed time allocation, more small samples

6 K156: {Koch, 214 #4834} 1216 KOCH ET AL. 3 Ponds 3 Small Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Number of fish collected Medium are better than a few large ones (Miranda and Boxrucker 29). Similar to our study, Dumont and Schlechte (24) indicated the precision of catch rates for target species collected in gill and trap nets generally did not meet precision objectives. Additionally, catches of target species in that study did not generally meet thresholds for the minimum number of fish in Texas. Dumont and Schlechte (24) reported that Texas also used reservoir size to determine the number of gear deployments. Currently in Kansas, 2 gill nets are prescribed as a minimum effort for the largest reservoirs. Our results indicated that 2 nets will generally precisely sample Channel Catfish and Walleyes in large reservoirs; although, more are required for palmetto bass. As many as 25 gill-net samples are needed to precisely sample palmetto bass in large reservoirs 5% of the time; although, 8 may be needed in smaller impoundments. Several studies suggest difficulty in precisely sampling Morone spp. Wilde (1995) indicated that as many as 5 gill nets were needed to precisely sample temperate basses in Texas reservoirs. Additionally, Neumann et al. (1995) reported difficulty obtaining precise samples of Morone spp Large FIGURE 2. Box plots of the number of stock-length fish collected per sampling event for Largemouth Bass, Bluegills, crappies, Channel Catfish, palmetto bass, and Walleyes from ponds ( 2 acres) and small (21 25 acres), medium (251 1, acres), and large reservoirs (>1, acres) in Kansas, Each data point represents stock-length catch of the sample for a species in a given year. Lower and upper fences are 25th and 75th percentiles, and the median isin between. Bars represent 1th and 9th percentiles. Horizontal reference line represents 1 stock-length fish. with multiple gear types. These corroborating findings suggest that refinement of sampling strategies is needed for Morone spp. Until then, fisheries managers should be aware of potential shortcomings of temperate bass catch data and make decisions accordingly. Channel Catfish catch rates were estimated with relatively high precision in our study regardless of reservoir size. However, our objective for catching 1 stock-length Channel Catfish was rarely met using standard protocols. Substantial sampling effort, beyond what is practical, would be required to meet this objective. In situations where large numbers of Channel Catfish are difficult to obtain with gill nets, biologists might consider the use of baited, tandem hoop nets. Studies indicate that catch rates of hoop nets in lentic environments can be high (Michaletz and Sullivan 22; Neely and Dumont 211; Stewart and Long 212). Sullivan and Gale (1999) indicated baited hoop nets caught more Channel Catfish per personnel-hour than did gill nets. Although collecting large numbers of Channel Catfish with hoop nets may achieve some objectives, Michaletz and Sullivan (22) indicated that obtaining precise measures of CPUE using baited, tandem

7 K156: {Koch, 214 #4834} EVALUATION OF STANDARDIZED SAMPLING TECHNIQUES Ponds 1 Small Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Number of samples needed to reach RSE Medium hoop nets was difficult and that from 12 to 5 series deployments were required to reach acceptable levels of precision. Neely and Dumont (211) reported that 5 18 series were required to reach an RSE25 with baited, tandem hoop nets. Buckmeier and Schlechte (29) reported that hoop net series provided accurate size structure data and consistent relative abundance estimates for adult Channel Catfish. These findings suggest that in instances where gill nets are not providing fisheries scientists with sufficient data, a hoop net series may provide an alternative Channel Catfish sampling method. Precision of Walleye CPUE was less than RSE25 more than 5% of the time in large reservoirs, where most quality Walleye populations occur in Kansas. Low catch rates and high variability likely limit the value of information obtained regarding Walleyes in smaller reservoirs in Kansas. In most instances, more samples were required to obtain an RSE25 than to collect 1 stock-length Walleyes. These results suggest that in cases where sampling time and resources are limited, biologists should consider collecting precise catch data rather than capturing large numbers of Walleyes for Large FIGURE 3. Box plots of sampling effort needed to achieve an RSE25 of CPUE effort for Largemouth Bass, Bluegills, crappies, Channel Catfish, palmetto bass, and Walleyes in ponds ( 2 acres) and small (21 25 acres), medium (251 1, acres), and large reservoirs (>1, acres) in Kansas. Each data point represents the number of deployments needed to achieve an RSE25. Units of effort are 1-min electrofishing stations for Largemouth Bass, one trap-net-night for Bluegills and crappies, and one gill-net-night for Channel Catfish, palmetto bass, and Walleyes. Lower and upper fences are 25th and 75th percentiles, and the median is in between. Bars represent the 1th and 9th percentiles. examination of size structure. If collecting large numbers of Walleyes is important to managers, other sampling methods (Isermann and Parsons 211) should be considered. For instance, surface gill nets resulted in higher CPUE of Walleyes compared with benthic gill-net sets in Lake Erie (Isbell and Rawson 1989). Additionally, researchers have reported successfully capturing Walleyes in trap nets, especially in shallow water during spawning periods (Beard et al. 1997; Kocovsky and Carline 21). Regardless of the sampling method, biologists should be aware of the biases of each sampling method. In most cases, trap-netting protocols did not allow biologists to collect precise catch data or collect enough fish for meaningful size structure analysis for Bluegills and crappies in Kansas reservoirs without considerably more sampling effort per impoundment. Due to logistic limitations for most Kansas biologists, this represents at least 3 4 d of sampling effort. Such a time investment is likely more than most biologists would find acceptable for most ponds and small reservoirs. Additionally, relatively few samples collected at least 1 stock-length Bluegills or crappies; although, fewer

8 K156: {Koch, 214 #4834} 1218 KOCH ET AL. 1 Ponds 1 Small 8 8 Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Number of samples needed to collect 1 stock-sized fish Medium samples were generally required to do so compared with those required to reach acceptable levels of precision. Biologists should determine which objectives (i.e., precision of CPUE estimates or number of fish for size structure representation) are most important for a given impoundment. If high precision of catch rates is important to biologists, the use of other methods for sampling Bluegills may be appropriate; however, Hardin and Conner (1992) indicated difficulty in obtaining precise catches of Bluegills via electrofishing in Florida. Additionally, Schultz and Haines (25) suggested that fall trap-netting provided more accurate information about harvestable-length Bluegills than did electrofishing in a large Kansas impoundment. For crappies, otter trawls can provide higher catch rates and precision than trap nets in Florida lakes (Allen et al. 1999). In Tennessee reservoirs, electrofishing collected larger crappies than did trap-netting; however, fall trap nets were recommended by those investigators for examination of yearclass strength (Sammons et al. 22). In an Oklahoma reservoir, hoop nets and trap nets had similar catch rates, except in Large FIGURE 4. Box plots of sampling effort needed to collect 1 stock-length individuals of Largemouth Bass, Bluegills, crappies, Channel Catfish, palmetto bass, and Walleyes in ponds ( 2 acres) and small (21 25 acres), medium (251 1, acres), and large reservoirs (>1, acres) in Kansas. Each data point represents the number of deployments needed to collect 1 stock-length individuals. Units of effort are 1-min electrofishing stations for Largemouth Bass, one trap-net-night for Bluegills and crappies, and one gill-net-night for Channel Catfish, palmetto bass, and Walleyes. Lower and upper fences are 25th and 75th percentiles, and the median is in between. Bars represent the 1th and 9th percentiles. summer when hoop nets captured more White Crappies than did trap nets (Muoneke et al. 1993). Similarly, unbaited, tandem hoop nets provided higher catch rates of Bluegills and crappies than standard trap nets in Iowa; however, catch rate precision of the gears were similar (M. Flammang, Iowa Department of Natural Resources, unpublished data). Although standard protocols did not generally meet precision and total catch goals for Bluegills and crappies in Kansas, fisheries managers should set sampling objectives and consider using alternative sampling methods (e.g., multigear approaches) that meet specific objectives. Our results indicate that current sampling effort expended by KDWPT with standard methods for sampling North American freshwater fishes is generally not providing precise estimates of CPUE for stock-length fish. Additionally, the minimum numbers of fish recommended to adequately describe size structure were usually not collected. Kansas Department of Wildlife, Parks, and Tourism is aware of the shortcomings of some sampling procedures and is making

9 K156: {Koch, 214 #4834} EVALUATION OF STANDARDIZED SAMPLING TECHNIQUES 1219 Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 efforts to improve the quality of future data. For example, effort in smaller Kansas reservoirs should be increased if objectives of fisheries managers include obtaining precise catch rates and adequate descriptions of size structure. Objective-based sampling should also be considered instead of the current protocol of determining minimum sampling efforts based on reservoir size. Along similar lines, KDWPT should also consider basing minimum sampling effort on historical catch data (Quist et al. 29) rather than on reservoir size. Because our results indicate that data obtained from some sampling protocols are often too variable to obtain precise estimates of CPUE, biologists should focus on collecting numbers of fish needed to adequately describe size structure, as samples that do not reach an RSE25 may only be useful for assessing large changes in relative abundance (Dumont and Schlechte 24). If precise estimates of CPUE are desired, more effort should be expended on fewer reservoirs, which may represent a shift from the paradigm of sampling each reservoir annually. Managers may be better served if they collect a large number of statistically powerful samples from reservoirs on a 2- or 3- year cycle instead of obtaining marginal data every year. Finally, protocols for the use of supplemental, nonstandard gears are in place in Kansas (Marteney et al. 21), and these alternative gears should be considered to supplement standard sampling procedures when objectives are not being met. Although standardized sampling often failed to achieve specified objectives, it should be noted that fisheries not specifically managed for targeted species were included in analyses (i.e., fisheries of poor quality, low density, or of little interest to managers were included). Target species were chosen in part because of their widespread range in Kansas, but small or remnant populations in some reservoirs might have influenced our findings. As such, biologists should recognize that collection of high-quality data from marginal fisheries may not be feasible and that monitoring fisheries where sampling targets can be reached or viable populations exist should be prioritized. These results highlight the inefficiency of attempting to collect precise data from low-abundance populations. One approach for limiting these inefficient samples might be to classify reservoirs by the quality of important recreational fisheries. For example, a particular impoundment might support a popular Walleye fishery but only maintains low-abundance Channel Catfish and palmetto bass populations that garner little interest. A manager could classify this reservoir as a Walleye fishery and sample until objectives were met for Walleyes but not necessarily for Channel Catfish or palmetto bass. This might result in the manager ceasing gill-net sampling effort when sample objectives for Walleyes were met even though relatively poor samples were collected for Channel Catfish and palmetto bass. Ultimately, this would lead to more appropriate sampling effort allocation but still retain sample quality for target species. Standardization of sampling methods allows easy spatial and temporal comparison, encourages data sharing and communication, and reduces bias that is inherent in biological data collection (Bonar et al. 29a). Benefits of standardization are numerous (Bonar and Hubert 22; Bonar et al. 29a), and our results by no means diminish the importance of standardization. We believe sample standardization should be continued in Kansas, and elsewhere, to promote development of long-term databases and encourage regional comparisons of fish populations. However, managers should recognize that data collected from standardized sampling regimes might not be sufficient to address particular questions. In these instances, managers might wish to supplement standardized samples with alternative gears or different strategies for deployment of standard gears (e.g., time of year, time of day, fixed stations). ACKNOWLEDGMENTS We thank K. Austin, C. Bever, J. Goeckler, S. Lynott, D. Nygren, R. Marteney, and S. Steffen for thoughtful discussions associated with this project. We also thank all KDWPT personnel that collected field data from 21 to 213. We thank S. Dumont, M. Quist, and five anonymous reviewers for reviews that greatly improved the manuscript. Funding for this study was provided by Kansas Department of Wildlife, Parks, and Tourism. Fish sampling was supported by Federal Aid grant F-22-R. REFERENCES Allen, M. S., M. M. Hale, and W. E. Pine III Comparison of trap nets and otter trawls for sampling Black Crappie in two Florida lakes. North American Journal of Fisheries Management 19: Anderson, R. O., and R. M. Neumann Length, weight, and associated structural indices. Pages in B. R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Beard, T. D. Jr., S. W. Hewett, Q. Yang, R. M. King, and S. J. Gilbert Prediction of angler catch rates based on Walleye population density. North American Journal of Fisheries Management 17: Bonar, S. A., S. Contreras-Balderas, and A. C. Iles. 29a. An introduction to standardized sampling. Pages 1 12 in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. Bonar, S. A., W. A. Hubert, and D. W. Willis, editors. 29b. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. Bonar, S. A., and W. A. Hubert. 22. Standard sampling of inland fish: benefits, challenges and a call for action. Fisheries 27(3):1 16. Brown, M. L., and D. J. Austen Data management and statistical techniques. Pages in B. R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Buckmeier, D. L., and J. W. Schlechte. 29. Capture efficiency and size selectivity of Channel Catfish and Blue Catfish sampling gears. North American Journal of Fisheries Management 29: Dodds, W. K., E. Carney, and R. T. Angelo. 26. Determining ecoregional reference conditions for nutrients, Secchi depth, and chlorophyll a in Kansas lakes and reservoirs. Lake and Reservoir Management 22:

10 K156: {Koch, 214 #4834} 122 KOCH ET AL. Downloaded by [Mississippi State University Libraries] at 6:46 26 November 214 Dumont, S. C., and J. A. Dennis Comparison of day and night electrofishing in Texas reservoirs. North American Journal of Fisheries Management 17: Dumont, S. C., and B. C. Neely A proposed change to palmetto bass proportional size distribution length categories. North American Journal of Fisheries Management 31: Dumont, S. C., and W. Schlechte. 24. Use of resampling to evaluate a simple random sampling design for general monitoring of fishes in Texas reservoirs. North American Journal of Fisheries Management 24: Gabelhouse, D. W. Jr A length-categorization system to assess fish stocks. North American Journal of Fisheries Management 4: Gustafson, K. A Approximating confidence intervals for indices of fish population size structure. North American Journal of Fisheries Management 8: Hardin, S., and L. L. Conner Variability of electrofishing crew efficiency, and sampling requirements for estimating reliable catch rates. North American Journal of Fisheries Management 12: Isbell, G. L., and M. R. Rawson Relations of gill-net catches of Walleyes and angler catch rates in Ohio waters of western Lake Erie. North American Journal of Fisheries Management 9: Isermann, D. A., and B. G. Parsons Harvest regulations and sampling. Pages in B. A. Barton, editor. Biology, management, and culture of Walleye and Sauger. American Fisheries Society, Bethesda, Maryland. Kocovsky, P. M., and R. F. Carline. 21. Dynamics of the unexploited Walleye population of Pymatuning Sanctuary, Pennsylvania, North American Journal of Fisheries Management 21: Marteney, R., L. Aberson, C. Bever, S. Lynott, J. Reinke, and M. Shaw. 21. Standard fish survey techniques for small lakes and reservoirs, 5th edition. Kansas Department of Wildlife, Parks, and Tourism, Emporia. Michaletz, P. H., and K. P. Sullivan. 22. Sampling Channel Catfish with tandem hoop nets in small impoundments. North American Journal of Fisheries Management 22: Miranda, L. E Sample sizes for estimating and comparing proportionbased indices. North American Journal of Fisheries Management 13: Miranda, L. E. 27. Approximate sample sizes require to estimate length distributions. Transactions of the American Fisheries Society 136: Miranda, L. E. 29. Standardizing electrofishing power for boat electrofishing. Pages in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. Miranda, L. E., and J. Boxrucker. 29. Warmwater fish in large standing waters. Pages in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. Miranda, L. E., W. D. Hubbard, S. Sangare, and T. Holman Optimizing electrofishing sample duration for estimating relative abundance of Largemouth Bass in reservoirs. North American Journal of Fisheries Management 16: Muoneke, M. I., O. E. Maughan, and C. C. Henry Comparative capture efficiencies of frame and hoop nets for White Crappie (Pomoxis annularis Rafinesque). Fisheries Research 18: Neely, B. C., and S. C. Dumont Effect of soak duration on precision of Channel Catfish catch with baited, tandem hoop nets. Pages in P. H. Michaletz and V. H. Travnichek, editors. Conservation, ecology, and management of catfish: the second international symposium. American Fisheries Society, Symposium 77, Bethesda, Maryland. Neumann, R. M., C. S. Guy, and D. W. Willis Precision and size structure of juvenile percichthyid samples collected with various gears from Lake Texoma. North American Journal of Fisheries Management 15: Noble, R. L., D. J. Austen, and M. A. Pegg. 27. Fisheries management study design considerations. Pages 31 5 in C. S. Guy and M. L. Brown, editors. Analysis and interpretation of freshwater fisheries data. American Fisheries Society, Bethesda, Maryland. Paragamian, V. L A comparison of day and night electrofishing: size structure and catch per unit effort for Smallmouth Bass. North American Journal of Fisheries Management 9:5 53. Pope, K. L., R. M. Neumann, and S. D. Bryan. 29. Warmwater fish in small standing waters. Pages in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. Quist, M. C., K. I. Bonvecchio, and M. S. Allen. 29. Statistical analysis and data management. Pages in S. A. Bonar, W. A. Hubert, and D. W. Willis, editors. Standard methods for sampling North American freshwater fishes. American Fisheries Society, Bethesda, Maryland. R Core Development Team R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Robson, D. S., and H. A. Regier Sample size in Peterson mark recapture experiments. Transactions of the American Fisheries Society 93: Sammons, S. M., D. A. Isermann, and P. W. Bettoli. 22. Variation in population characteristics and gear selection between Black and White crappies in Tennessee reservoirs: potential effects on management decisions. North American Journal of Fisheries Management 22: Schultz, R. D., and D. E. Haines. 25. Comparison of seasonal Bluegill catch rates and size distributions obtained with trap nets and electrofishing in a large, heated impoundment. North American Journal of Fisheries Management 25: Stewart, D. R., and J. M. Long Precision of Channel Catfish catch estimates using hoop nets in larger Oklahoma reservoirs. North American Journal of Fisheries Management 32: Sullivan, K. P., and G. M. Gale A comparison of Channel Catfish catch rates, size distributions, and mortalities using three different gears in a Missouri impoundment. Pages in E. R. Irwin, W. A. Hubert, C. F. Rabeni, H. L. Schramm Jr., and T. Coon, editors. Catfish 2: proceedings of the international symposium. American Fisheries Society, Symposium 24, Bethesda, Maryland. Vokoun, J. C., and C. F. Rabeni, and J. S. Stanovick. 21. Sample-size requirements for evaluating population size structure. North American Journal of Fisheries Management 21: Wilde, G. R Gill net sample size requirements for temperate basses, shads, and catfishes. Proceedings of the Annual Conference of Southeastern Association of Fish and Wildlife Agencies 47(1993): Wilde, G. R., and W. L. Fisher Reservoir fisheries sampling and experimental design. Pages in L. E. Miranda and D. R. DeVries, editors. Multidimensional approaches to reservoir fisheries management. American Fisheries Society, Symposium 16, Bethesda, Maryland. Willis, D. W., and B. R. Murphy Planning for sampling. Pages 1 15 in B. R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland.