Body size governs predator-prey interactions, which in turn structure populations, communities, and food webs. Understanding predator-prey size relationships is valuable from a theoretical perspective, in basic research, and for management applications. However, predator-prey size data are limited and costly to acquire. We quantified predator-prey total length and mass relationships for several freshwater piscivorous taxa: crappie (Pomoxis spp.), largemouth bass (Micropterus salmoides), muskellunge (Esox masquinongy), northern pike (Esox lucius), rock bass (Ambloplites rupestris), smallmouth bass (Micropterus dolomieu), and walleye (Sander vitreus). The range of prey total lengths increased with predator total length. The median and maximum ingested prey total length varied with predator taxon and length, but generally ranged from 10–20% and 32–46% of predator total length, respectively. Predators tended to consume larger fusiform prey than laterally compressed prey. With the exception of large muskellunge, predators most commonly consumed prey between 16 and 73 mm. A sensitivity analysis indicated estimates can be very accurate at sample sizes greater than 1,000 diet items and fairly accurate at sample sizes greater than 100. However, sample sizes less than 50 should be evaluated with caution. Furthermore, median log10 predator-prey body mass ratios ranged from 1.9–2.5, nearly 50% lower than values previously reported for freshwater fishes. Managers, researchers, and modelers could use our findings as a tool for numerous predator-prey evaluations from stocking size optimization to individual-based bioenergetics analyses identifying prey size structure. To this end, we have developed a web-based user interface to maximize the utility of our models that can be found at www.LakeEcologyLab.org/pred_prey.

Effects of sampling time (day or night and fall or spring), target fish density, water clarity, water temperature, water conductivity, and lake morphometry on electrofishing catch per effort (CPUE) of largemouth bass Micropterus salmoides 200 mm total length (TL) and longer were determined. Electrofishing catch per hour (CPH) and catch per kilometer (CPK) were also compared to determine if each expression provided similar trends in CPUE. Correlations between day CPH and day CPK (r = 0.99; P < 0.0001) and night CPH and night CPK (r = 0.97; P < 0.0001) suggested that both measures provided similar trends in CPUE. Night CPH significantly exceeded day CPH, and spring CPH significantly exceeded fall CPH. Catchability (q) decreased with increasing density; therefore, CPH increased nonlinearly with density. Day CPH in fall decreased with increasing Secchi depth and water temperature but was unrelated to largemouth bass density. Day CPH in spring decreased with increasing Secchi depth and water temperature and increased with increasing density of largemouth bass and water conductivity. Night CPH in fall increased with increasing density and decreased with decreasing water conductivity, and night CPH in spring increased with increasing density and decreasing percent littoral area (percent of lake with depth less than 4.6 m) among lakes. These variables explained 44% of day CPH in fall, 75% of day CPH in spring, 28% of night CPH in fall, and 59% of night CPH in spring. Effects of density on q must be determined and environmental conditions must be similar before CPUE can be a useful index of largemouth bass density.

We assessed the seasonal variation of trap‐net catches of bluegill Lepoomis macrochirus in Minnesota lakes. Size and catch per unit effort (CPUE) of bluegill declined from June through August. The highest CPUE of bluegills longer than 149 mm total length occurred when gonads were most developed. Regression models indicated day of year explained 66% of the variation in biomass per lift, 63% of the variation in CPUE of bluegills longer than 149 mm, and 40% of the variation in CPUE for all sizes of bluegill. Similar trends in temporal variation of biomass per lift and CPUE were seen in the statewide data set of Minnesota surveys. Seasonal variation should be accounted for when data on trap‐net catches of bluegill are used for management decisions.

We quantified the effects of length‐group (150–199, 200–249, and 250–299 mm), sampling period (September, October, early spring, and late spring), lake, and intraspecific density on catchability q of black crappies Pomoxis nigromaculatus in trap nets (modified fyke nets) set in eight natural Minnesota lakes during 1996–2001. The catchability of the two larger length‐groups exceeded that of the smallest length‐group in all lakes. Catchability in early and late spring exceeded that in September or October in most lakes; otherwise, q did not differ among sampling periods. Catchability differed among lakes during September, October, and early‐spring sampling periods but did not differ among lakes in late spring. For 150–199‐mm fish, q increased with increasing lake surface area during all sampling periods, decreased with increasing shoreline development ratio during all periods, decreased with increasing maximum depth during fall sampling periods, and was unrelated to the percentage of surface area of lakes less than 4.6 m deep. Catchability of the larger length‐groups was unrelated to any of these lake morphometric variables. Catchability of 150–199‐mm black crappies decreased with increasing density during all sampling periods. However, the q of 200–249‐mm black crappies was density independent during early spring and September, decreased with increasing density in October, and may have been density dependent in late spring. For 250–299‐mm black crappies, the q in early spring decreased with increasing density, and the q in late spring was density independent. Trap‐net catch per unit effort (CPUE) provides more meaningful data on the relative abundance of 200‐mm and longer black crappies than it does for smaller black crappies. Comparisons of trap‐net CPUE and length‐frequency distributions are most meaningful if trap‐net samples are collected during the same sampling period and within the same lake.

A holistic approach to fisheries management requires an understanding of factors related to fish abundance over several spatial scales. We used geographic information systems to extract data describing habitat influences across three different spatial scales for a selected ecological class of Minnesota bass-panfish lakes (n ϭ 113). These data were then analyzed by regression tree analysis to describe relationships between habitat and trap-net catch per effort (CPE) of bluegills Lepomis macrochirus. At the landscape scale of analysis, bluegill CPE increased among lakes with decreases in hydrologic connectivity (landscape position) and increases in geographic northing and easting gradients that corresponded to regional differences in geomorphology and edaphic characteristics. At the watershed-lake scale of analysis, a regression tree model with variables describing watershed area, cultivated land cover, forested land cover, and lake area explained 55% of the variation in bluegill CPE among lakes. At the site scale, a regression tree model with variables describing submerged plant cover and detritus substrates explained 57% of the variation in bluegill CPE among 72 sites spread among six lakes. However, much of the sitescale habitat influences on bluegill abundance was explained by broader landscape-and watershedscale factors that influence the plant and bottom substrates in lakes. This study reinforces the importance of identifying habitat limitations and the influences of human activities at the landscape and watershed scales in addition to more commonly addressed site-scale habitat deficiencies.