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Document Type

Thesis - University Access Only

Award Date

2006

Degree Name

Master of Science (MS)

Department / School

Wildlife and Fisheries Science

Abstract

The objectives of my research were to: 1) identify seasonal and diel movement patterns of adult yellow perch in a complex lake basin in eastern South Dakota; 2) compare habitat use, distribution and movement rates among length groups, diel periods, and seasons; 3) develop a model predicting the summer distribution of adult yellow perch in a complex lake basin; 4) test this model in the field; and 5) identify any predator-prey relationships that may influence yellow perch distribution. Ultrasonic telemetry was used to determine seasonal and diel movement patterns of adult yellow perch. Transmitters were externally attached to yellow perch in two size groups. Tracking took place in all open-water seasons, ending with ice cover and beginning at ice out. Fall tracking included October, November, and December 2004; spring included April, May, and June 2005; and summer included July, August, and September 2005. To determine diel movements, a randomly selected subsample of approximately five fish from both length groups were located every one to two hours during a 24-h time period each month. Twenty-eight large (mean total length=268.3 mm, SE=4.0; mean weight=280.6 g, SE=11.9) and 29 small (mean total length=230.1 mm, SE=2.2; mean weight=170.8 g, SE=2.2) adult yellow perch were released with transmitters between 22 September 2004 and 22 July 2005. Yellow perch were located from 5 October 2004 to 9 December 2004 and from 14 April 2005 to 20 September 2005. There appeared to be no significant seasonal or length-specific influences in the movement or distance to shore of yellow perch in Lake Sinai. However, spatial segregation of size groups occurred in all seasons as small fish were located farther from shore and in deeper water (mean=297.7 m, SE=10.4; mean=6.4 m, SE=0.1, respectively) than the large fish (mean=213.2 m, SE=7.6; mean=4.7 m, SE=0.1, respectively). Highest movement rates were observed in the fall season (mean=48.8 m/h, SE=4.8). Mean rates in the fall dusk period were 52 m/h greater than the next highest season. Distance to shore (mean=270.7 m, SE=7.1) and water depth at location (mean=6.09 m, SE=0.1) did not appear to be related to diel period. In the fall, small yellow perch avoided muck substrate. In the summer, yellow perch of both sizes groups showed no substrate selection or avoidance. During the spring, small yellow perch selected for silt and avoided muck substrates. Throughout the three seasons of tracking no yellow perch were found within vegetated areas. July telemetry locations were the basis for predicting yellow perch distribution. The lake was sectioned into a grid of 200-m x 200-m cells using ArcMap and bottom slope, water depth, distance to shore, and presence or absence of a yellow perch location were identified for each cell. Cells with high and low probabilities of containing yellow perch were identified by constructing frequency histograms of the number of locations observed at specific slopes, water depths, and distances to shore. Fish, yellow perch diets, zooplankton, and benthic invertebrates were sampled in both high and low probability areas to identify any interactions between fish in probability areas and densities of the organisms sampled or in the diet. Spatial cells (200 m2) having a high probability of yellow perch occurrence were characterized by at least one of the following three parameters: water depths ranging from 2.5 to 6.5 m, bottom slopes from 2 to 3º, and distances to shore between 150 and 350 m. No difference was detected in yellow perch gill-net catch per unit effort between high or low probability areas. Therefore, I was unable to predict yellow perch distribution based on telemetry locations. I believe yellow perch may occupy predictable habitats during the summer months in a complex lake basin; however, due to the diversity of habitat in Lake Sinai, I was unable to detect this difference. There were no significant differences in densities of any benthic invertebrate taxa between high and low probability areas. Calanoid copepods were significantly more abundant in the high probability areas but were not an important prey item. The majority (high probability areas=98%, low probability areas=95%) of yellow perch had prey items in their stomach. Ninety and 87% of yellow perch in the high and low probability areas, respectively, consumed Daphnia spp. There appeared to be no relationship in diet and predator or prey abundance between the predicted high or low probability areas during summer sampling. Knowledge of yellow perch seasonal and diel distributions and movement patterns in Lake Sinai has several implications for fisheries managers. When attempting to characterize population structure, gill nets used for yellow perch should be set in a manner that would equally represent deep offshore habitats and shallower inshore habitats and encompass seasonal differences in spatial distribution to prevent biasing the sample toward larger or smaller individuals. Sampling effort could be concentrated during the fall as highest CPUE may occur, although sampling precision should be considered as well. Additionally, increased movement rates may be related to an increase in feeding activity, so catch rates and angler harvest may be high during the fall. It may be important to include fall creel surveys to obtain accurate estimates of annual angler exploitation.

Library of Congress Subject Headings

Yellow perch--Seasonal distribution--South Dakota
Yellow perch--Habitat--South Dakota

Description

Includes bibliographical references

Format

application/pdf

Number of Pages

79

Publisher

South Dakota State University

Rights

Copyright 2006 William F. Bauer. All rights reserved.

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