After data was collected from five anglers, the groups went back to the laboratory to examine the scale samples collected from the fishes. The scales were mounted between glass slides and looked at under projectors and microscopes to determine the fishes’ ages. This was done by looking at the groups of concentric rings (circuli) on scales that were classified into annuli and interpreted as seasonal growth marks. The location of an annulus was determined by the presence of a crossing-over between the circuli found on the scale. The crossing-over was identified by the first continuous circulus of the new growth season cutting over the last incomplete circulus of the preceding season. The fishes were then determined to be as old as the number of annuli present on their scales.
Next, all of the information collected was compiled into one data set. The data was entered into Excel. One section included the anglers’ catch rates separated by lakes and times. The other section had data on the growth of the fishes and their sex composition separated by lakes, species, lengths, and ages.
Once the data was compiled, it was analyzed. First, the catch per unit effort was computed (CPUE) for each angler interviewed using the equation CPUE = Total Catch/(Lines * Hours). Averages of the CPUEs were then computed for each lake in the morning and afternoon (Table 1). Totals for numbers of anglers, lines, hours, and the catch for each species were calculated next (Table 1).
There were also many ways the data was compared. The average size at the various ages was examined for bluegill, perch, and crappie on the various lakes (Table 2). The average CPUE using one line versus two lines versus three lines was contrasted (Table 3). Another comparison made was between the CPUEs of each species and the depths they were caught at (Figures 1 – 4).
Additionally, some frequency distributions were analyzed. These included the sizes of perch and bluegill and crappie (Figures 5 – 7), and the CPUE for each site (Figures 8 –11).
Most of the analysis presented in the Tables and Figures does not include Lake Wingra because no fishes were caught there.
RESULTS
A total of 127 anglers were surveyed, and they caught 817 fish altogether on 279 lines (Table 1). More bluegill (745.5) were caught than any other species, and more of them were caught on Lake Mendota than on any other lake. The next most abundant species was the perch, although only 25 of them were caught. The northern pike was the third most abundant fish caught, followed by the crappie and the walleye, and the least abundant fish was the largemouth bass. The crappie and walleye were the only fishes observed where most of them were not caught on Lake Mendota.
The average CPUEs were very different between the four lakes at different times (Table 1). Lake Wingra had the smallest average CPUEs because nothing was caught there. Monona Bay had the highest average CPUEs.
The sizes of the fishes seemed to correlate with the age group they were from (Table 2). The smallest fishes were generally younger than the larger fishes when divided among species. Among crappies, bluegills, and perch, bluegills had the smallest average size and perches had the largest average size.
More fishes were caught on one line, than on two or three lines (Table 3). So, the average CPUE was higher for one line, and it was lowest for three lines.
Most of the species caught were caught at very low depths (Figures 1 – 4). The only fishes caught at depths greater than five meters were perch and walleye. So, the CPUEs were greater at lower depths.
The size of fishes caught on the lakes differed among them (Figures 5 – 7). The majority of bluegills caught were between 15 and 17 centimeters in length (Figure 5). Lake Mendota had all of the largest bluegills caught, and Mud Lake had the smallest bluegills overall. Crappie size was evenly distributed at 18, 19, and 21 centimeters between all of the lakes (Figure 6). The smallest crappies were caught on Mud Lake, the largest crappie was from Lake Mendota, and Monona Bay had intermediate sized crappies. The lengths of only two perches were taken, and they were both 22 centimeters (Figure 7). Both of these two perch were from Lake Mendota.
The frequency distributions of CPUEs also varied among the lakes (Figures 8 – 11). Lake Mendota anglers had very low CPUEs overall, but their CPUEs varied from 0 to 35 (Figure 8). All anglers on Lake Wingra had a CPUE of 0 (Figure 9). The anglers on Monona Bay had fairly even distributions of their CPUEs ranging from 0 to 50 (Figure 10). Mud Lake’s CPUEs were skewed a little to the left with most anglers having a CPUE of 0 or 0.7 (Figure 11). Monona Bay had the largest CPUE at 50 (Figure 10).
DISCUSSION
Bluegills seem to be the most abundant fish species in the Madison lakes because many more bluegills were caught than any other species. Largemouth bass were found to be the least abundant species since only one of them were caught.
Sizes of the fishes did increase with age in this study. Male and female size at various ages of bluegills was somewhat different. However, they seemed to become more similar as the fish became older.
Fishing more than one line does seem to influence the CPUE. The more lines that are fished with, the lower the CPUE. So, the effort does not seem to pay off for having more than one line.
CPUE varies as factors change. As depth increases, CPUE seems to decrease. The CPUE relates to sites, too. Lake Wingra had the smallest CPUEs, whereas Monona Bay had the highest CPUEs. One other observation was that the CPUE was significantly smaller in the morning on Lake Mendota and Mendota Bay than in the afternoon, but Mud Lake had a higher CPUE in the morning than in the afternoon.
The data indicates some difference in the depth distribution among the species. Northern pikes, largemouth bass, crappies, perch and bluegills were caught at depths of less than five meters. But, some walleye and perch were caught at depths of ten or more meters.
About 28 percent of anglers had a CPUE higher than the average CPUE at their lake and time. On Lake Mendota, 25 percent in the morning and 23 percent in the afternoon were above their average CPUE. On Lake Wingra, all of the anglers were at their average CPUE because they all had 0 for their CPUE. Monona Bay’s anglers in the morning were above their average CPUE 40 percent of the time and 67 percent were above their average CPUE in the afternoon. Mud Lake’s anglers in the morning were above their average CPUE 36 percent of the time and 25 percent were above their average CPUE in the afternoon. So, Monona Bay’s anglers seemed to have done the best.
All of the data in this report was a result of a one-day census. For more conclusive results, more extensive studies would have to be undertaken with a larger sample size of anglers over a longer period of time.
Overall, it seems that the highest CPUEs were on Monona Bay. So, if an angler wants the best CPUE, he or she should go fishing on Monona Bay in the afternoon with one line. Anglers should probably not fish on Lake Wingra because our study showed no fish being caught there. If an angler wants to catch many fish species, then they should go fishing on Lake Mendota because the widest range of species were caught there.
Table 1. Census Data by Site and Time
Table 2. Average Size at Age for Bluegill, Crappie and Perch
Table 3. Average CPUE Using 1 Line vs. 2 Lines vs. 3 Lines
Figure 1. Lake Mendota CPUE by Species and Depth
Figure 2. Close-up of Lake Mendota CPUE by Species and Depth
Figure 3. Monona Bay CPUE by Species and Depth
Figure 4. Mud Lake CPUE by Species and Depth
Figure 5. Bluegill Size Distributions
Figure 6. Crappie Size Distributions
Figure 7. Perch Size Distributions
Figure 8. Frequency Distribution of CPUE for Lake Mendota
Figure 9. Frequency Distribution of CPUE for Lake Wingra
Figure 10. Frequency Distribution of CPUE for Monona Bay
Figure 11. Frequency Distribution of CPUE for Mud Lake