Natural resource monitoring programs benefit from routine evaluation. Here, Florida’s statewide Freshwater Fisheries Long-Term Monitoring (LTM) program is used to show how stakeholder surveys can be integral to this process. In 2022, an online questionnaire was sent to internal stakeholders, i.e., state agency personnel who collect, enter, or use freshwater fisheries data for fisheries and habitat management purposes. The survey’s primary objective was to evaluate the program at its 15-year mark; secondary objectives were to compare results with a similar survey conducted at the 4-year mark, compare results among respondents based on experience and functional role, and develop recommendations for strategic initiatives to further improve the program. The survey consisted of 43 questions across six sections of program evaluation: demographics; field sampling; data entry, summary, and reporting; management decision support; programmatic views; and additional input. Respondents generally had positive views of the LTM program, but the survey revealed differences among respondents with different functional roles (e.g., fisheries researchers and managers viewed the decisional value, priority, and sample sizes of LTM data more favorably than habitat managers) while highlighting high-priority future initiatives (e.g., database development). Our results demonstrate the utility of stakeholder surveys as an important step in evaluating monitoring programs.

Objective: Florida’s Freshwater Fisheries Long-Term Monitoring Program was implemented in 2006 to track changes in freshwater fish populations and communities. As part of an evaluation of the program, this study used a simulation framework to assess trend detection for fish abundance and biomass indices and how sampling intensity (number of samples per year) and frequency (number of years) can influence detection of these trends. Methods: Using count and weight data from fall electrofishing samples collected between 2006 and 2021 from 21 lakes, trends were simulated for annual mean count and weight over a 10-year period that ranged from −70% to +200%. In all, simulations were performed for seven game fish species and three management-relevant groups (large nongame, nonnative, and prey species). For sampling intensity, data were simulated with a range of sample sizes, from 10 to 40 electrofishing transects or the maximum number available for a given lake. For sampling frequency, data were simulated for different sampling schedules that included sampling 1 year followed by 1- or 2-year breaks (4–5 years of sampling in a 10-year period), sampling two consecutive years followed by 1- or 2-year breaks (6–7 years of sampling in a 10-year period), and sampling the first 5 years only. Results: Simulations based on weight and count data yielded similar results, but the effect of sampling frequency and sampling schedule varied by species, management group, and lake. Trend detection was lower and more variable when mean counts and weights of fish in electrofishing samples were low. Overall, at least a 60% increase or 40% decrease over a 10-year period was typically needed for trends in mean weight and count to be detected at least 80% of the time in at least half of the lakes. Increasing sampling intensity did not substantially improve trend detection for lower-magnitude changes, but reducing sample intensity to a minimum of 10 electrofishing transects per year would have a large negative effect on trend detection in almost all lakes. Detection of trends improved as the number of years sampled increased, but ideally, sampling should be spaced throughout the entire 10-year period to capture the full magnitude of change. Sampling every year generally resulted in better trend detection and for many species and groups was the only sampling schedule that resulted in all study lakes achieving the 80% target detection level. Of the alternative schedules considered, those involving 2 years of consecutive sampling outperformed those with only 1 year of sampling followed by a 1- or 2-year break. Conclusions: Relatively large changes in mean count and weight were required to detect trends over a 10-year period, but there was no clear advantage of using count or weight data for monitoring purposes. Further, study results support the current sampling intensity, but trend detection is optimized at higher mean catch and weight values. Although sampling every year is ideal, an alternative schedule involving sampling two consecutive years with 1- or 2-year breaks could be considered in certain situations. These results will be important for informing future decisions regarding Florida’s Freshwater Fisheries Long-Term Monitoring Program and other monitoring initiatives.

Objective: Standard weight (Ws) and standard length categories have not been established for the Longear Sunfish Lepomis megalotis. Therefore, fisheries managers have been unable to evaluate condition and size structure of various populations across the species’ range. Our objectives were to develop and assess Ws equations using three different techniques and to propose standard length categories for Longear Sunfish. Methods: Length and weight data were collected for Longear Sunfish from 17 states across the species’ native and introduced range. Data from 54,106 fish across 512 populations were used to develop Ws equations for Longear Sunfish by using the regression line percentile, linear empirical percentile, and quadratic empirical percentile techniques. Standard length categories for Longear Sunfish were developed using the length from the International Game Fish Association’s all-tackle world record. Results: We propose the regression line percentile equations as log10W = 3.3127·log10L − 5.2861, where W is weight (g) and L is total length (mm) for metric units, and log10W = 3.3114·log10L − 3.2887, where W is weight (lb) and L is TL (inches) for English units. We also developed proportional size distribution length categories of 60, 100, 130, 170, and 210 mm TL, representing stock, quality, preferred, memorable, and trophy categories, respectively. Conclusions: Our Ws equations and standard length categories will allow fisheries biologists to better understand and manage Longear Sunfish populations across their native and introduced range.

Objective: To date, no standard weight equation has been developed to assess the condition of Flier Centrarchus macropterus across its range. Additionally, the current standard-length categories needed to be revised based on the more comprehensive data set that was obtained for this study. Thus, the primary objectives of this study were to (1) gather weight and length data sets for Flier throughout their native and introduced ranges and use them to develop a standard weight equation and (2) propose updated standard-length categories. Methods: We developed a standard weight equation for the Flier using the regression-line-percentile (RLP) technique and the empirical-percentile-linear and the empirical-percentile-quadratic methods. Individual length and weight data for 8,192 fish from 58 populations and ranging in size from 80 to 305 mm total length (TL) were used in the analysis. The fish were collected from 1949 to 2024 from known populations across the species’ native and introduced ranges in North America. Results: The results were nearly identical among the three methods; thus, we recommend the RLP-derived equation for describing this species for individuals from 80 to 240 mm TL. The resulting equation is log10W = 3.141 * log10L − 5.013 (RLP), where W is weight (g) and L is TL (mm). Although fish that were as large as 305 mm TL were included in our data set, bias was found at the upper end of the length spectrum due to low sample sizes. As a result, we caution using any of the equations for Flier ≥25 cm TL. We also developed standard-length categories for Flier with minimum lengths for five standard-length categories of 8, 13, 15, 18, and 23 cm TL for stock, quality, preferred, memorable, and trophy sizes, respectively. Conclusions: The development of a standard weight equation and standard-length categories will aid biologists in assessing the condition and size structure of wild Flier populations and those being potentially propagated for supplemental stocking into areas with depressed populations across its native range. This information will be valuable for the future management and conservation of this valuable sunfish species.