Spatial and Temporal Variability in a Large‐Reservoir Fish Assessment and Application of a Stratified Random Sampling Approach

Abstract

Sampling is often standardized with regard to time and space to monitor population characteristics. Effective sampling of large reservoirs can be complicated by the inherit bias of habitat variability along the reservoir gradient. Our objective was to assess spatial and seasonal distribution patterns of target and nontarget fish species in a large reservoir to identify potential sources of bias. A multitude of fish community and habitat characteristics were measured during seasonal (spring, summer, and fall) gill‐net surveys in 2015 and 2016 at Lake McConaughy, Nebraska. Spatial assessments along the longitudinal gradient (up‐reservoir to down‐reservoir) and between opposing shorelines were made for fish metrics from the seven most common species, and associations between species‐specific relative abundance and habitat data were examined. Spatial differences in relative abundance and size structure occurred for nearly all species, with the greatest spatial variability occurring between the upper and lower reservoir zones, but few strong correlations were observed between species‐specific relative abundances and habitat data. Seasonal differences occurred in relative abundance and size structure for most species, and size structure was lowest in the fall for most species. To reduce the impact of spatial variability, we determined the minimum required sampling effort to achieve precise estimates of mean catch per net‐night using two resampling strategies, with 16 or fewer gill‐net sets required for five of seven species and 14 or fewer required if a stratified random approach is utilized. This research quantifies the extent of spatial and temporal variability in standardized sampling on a large reservoir and provides novel insight for managers of similar systems considering a stratified random approach to reduce sampling effort while maintaining desired levels of precision.

Development and Application of a Size Structure Index for Blue Sucker

“…Different electrofishing settings (pulse rate, frequency, and amperage) can also bias the size of fish that are captured (Dolan et al 2002). Seasonal differences in the catchability of various fish sizes can cause variation in the PSD values for a population (Pope and Willis 1996;Schall et al 2019). For example, fish that are substock early in the growing season may be recruited to the stock-length category later in the growing season, causing PSD values to shift downward.…”

Seasonal Sampling Influence on Population Dynamics and Yield of Channel Catfish and Walleye in a Large Great Plains Reservoir

“…However, fish sampling is inherently biased, and the time of year samples are collected can influence sampling results. A multitude of fish metrics have been shown to vary between seasons, including fish condition (Blackwell et al 2000;Hansen and Nate 2005), size structure (Pope and Willis 1996;Fischer and Quist 2014;Schall et al 2019a), catchability (Schoenebeck and Hansen 2005), catch rate (Schall et al 2019a), and age structure (Hofmann and Fischer 2001). However, seasonal trends are not consistent among species.…”

“…However, Channel Catfish sampling continues to require further study, including consistency between seasonal sampling events (Bodine et al 2013), and Walleye population dynamics trends have been evaluated using spring samples in other areas (Kocovsky and Carline 2001;Pedersen et al 2018). Additionally, size structure of Channel Catfish and Walleye from fall samples has been documented to be smaller than from spring samples (Schall et al 2019a), which could have implications for estimating population dynamics. Therefore, the similarity of spring and fall population dynamics estimates of Channel Catfish and Walleye in large reservoirs warrants further examination.…”