Date of Award

2011

Document Type

Thesis

Degree Name

Master of Science (MS) in Biology

Department

Biology

Abstract

"Rainbow trout growth and condition were examined in 17 ecologically diverse lakes from which physical, limnological, and biological parameters were sampled. Parameters were correlated with rainbow trout growth and condition to identify factor(s) that predict rainbow trout growth and condition across eastern Washington lakes stocked annually with rainbow trout fry. We tested the hypothesis Ho: the environmental variables examined do not predict rainbow trout growth and condition. Data were natural log transformed for better fit, and were analyzed by season. Several models were identified using stepwise multiple regression analysis and general linear modeling which significantly predicted trout growth or condition using one or more of the biotic and abiotic independent variables. Trends in trout growth and condition correlated to biomass of odonates, amphipods, caddisflies, calanoid copepods and density of dipterans and hemipterans were generally positive regardless of season. Among autumn measures, single biological predictors including biomass of coenagrionid damselflies and Aglaodiaptomus copepods explained approximately 42% and 49% of the lake-to-lake variation in rainbow trout growth and condition, respectively. In addition, more than 84% of the variation in rainbow trout condition was explained by the variables maximum lake depth (Zmax), autumn caddisfly larvae biomass, and autumn dipteran density. Rainbow trout condition factor compared with spring measures was inversely proportional to Zmax and rainbow trout stocking density. Both variables explained 51% of the spring lake-to-lake variation in condition factor. Among combined measures (spring and autumn), odonate and calanoid copepod biomass, and odonate density and amphipod biomass were directly proportional to rainbow trout growth and condition,. respectively, with more than 54% of the lake-to-lake variation explained by the models. The best regression models explained as much as 95% of lake-to-lake variation in trout growth and condition. General linear models explained 58% to 99% of the variation in trout condition. General linear modeling identified several negative relationships with rainbow trout condition. Stocking density, presence of largemouth bass, green sunfish, brown trout, and tiger trout negatively affected rainbow trout condition. The collection of significant models suggests that rainbow trout stocked into eastern Washington lakes realize higher growth rates and better condition in the presence of abundant forage base and in the absence of competition or predation by resident fish species. Both single environmental variables and collections of environmental variables can significantly predict rainbow trout growth and condition. Thus, the environmental variables used in this study, or other variables, could be monitored and used by regional resource agencies in managing rainbow trout fisheries"--Document.

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Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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