Document Type

Thesis - Open Access

Award Date

2008

Degree Name

Master of Science (MS)

Department / School

Wildlife and Fisheries Science

First Advisor

David W. Willis

Abstract

Yellow perch Perca flavescens are a popular sportfish in eastern South Dakota glacial lakes. In addition to their recreational importance, yellow perch serve as a prey species for predators. Thus, understanding the factors that affect yellow perch population dynamics is a top priority among fishery managers in South Dakota. The objectives of this study were to 1) estimate the magnitude and duration for a decrease in water temperature that would induce mortality of yellow perch eggs, 2) investigate the relation between climatological variables and larval perch abundance in six eastern South Dakota glacial lakes, and 3) relate long-term larval perch abundance to walleye growth and condition in six eastern South Dakota glacial lakes. For my first objective, yellow perch egg skeins were collected from nearby lakes in spring 2007 and 2008 and transferred to a laboratory tank system. Egg skeins were split into multiple sections to minimize any individual, maternal effects and randomly allocated to treatment or control tanks. The first experiment decreased water temperature by 6°C in 24 h; however, no significant difference in mean hatch success was observed between treatment and control tanks (control 55%, SE=6.0; treatment 48%, SE=5.8). In the next experiment, we increased the magnitude (8°C) and decreased the duration (45 min) to determine the lower end of the temperature threshold. Again no significant difference in mean hatch success was observed between treatment and control tanks (control 38%, SE=5.0; treatment 37%, SE=5.6). I conclude that a decrease in water temperature associated with a cold-front likely has little effect on yellow perch egg survival in South Dakota waters. I suggest that further research is needed on the effect of simulated cold-fronts on larval yellow perch development and survival during the switch to exogenous feeding. To address my second objective, I utilized three climatological predictor variables (mean March wind speed, total April precipitation, and mean May temperature) that were found to have relations with larval yellow perch abundance in a previous study. Larval yellow perch were collected from six lakes in eastern South Dakota from 1995 to 1997 and 2000 to 2008 using a 0.75-m, 1,000-um mesh (bar measure) ichthyoplankton surface trawl fitted with a flowmeter to determine larval density. Correlation analysis was used to assess the relation between larval yellow perch abundance and the predictor variables within and among lakes. I also used Akaike’s Information Criterion to assess variability in larval yellow perch abundance in relation to climatological predictor variables. In general, larval yellow perch abundance was negatively correlated with mean March wind speed, and positively correlated with total April precipitation and mean May temperature. The most influential variable in predicting larval yellow perch abundance seemed to vary by lake. Therefore, I suggest that future research be restricted to lake-specific analyses. Additionally, I believe the time at which larval yellow perch switch to exogenous feeding may be a critical life stage in the early life history of perch and further research should focus on the relation of climate variables within this time period to larval perch abundance. For my final objective, I utilized the same larval yellow perch abundance data from objective 2 to examine the relation of yellow perch as prey for walleye. Age-0 walleye growth and adult walleye condition data were compiled from South Dakota Department of Game, Fish and Parks annual lake surveys. I used mean total length of age-0 walleye captured during fall night electrofishing as an index of age-0 walleye growth and mean relative weight by size category as an index of adult walleye condition. Correlation analysis was used to assess relations between age-0 walleye growth and age-0 walleye catch per unit effort (i.e., density-dependent growth), larval yellow perch density, and cumulative warming degree days. Weak relations between these predictor variables and age-0 walleye growth were observed. Similarly, weak correlations were observed between larval yellow perch density and adult walleye condition. Akaike’s Information Criterion analysis was used to assess variability in age-0 walleye growth with the predictor variables. Cumulative warming degree days was selected as the best candidate model in predicting age-0 walleye growth. However, other models were competing, indicating limited performance of the candidate models in explaining age-0 walleye growth. I believe that when alternative prey items are sufficiently abundant, walleyes can maintain growth and condition in the absence of yellow perch. I recommend that future research be restricted to lake-specific comparisons due to variability among populations.

Library of Congress Subject Headings

Yellow perch -- Larvae -- South Dakota
Walleye (Fish) -- Food -- South Dakota

Description

Includes bibliographical references (page 55-64)

Format

application/pdf

Number of Pages

76

Publisher

South Dakota State University

Rights

Copyright © 2008 Andrew C. Jansen. All rights reserved.

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