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Date Permissions Signed

9-28-2010

Date of Award

2010

Document Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Biology

First Advisor

Matthews, Robin A., 1952-

Second Advisor

Hooper, David U., 1961-

Third Advisor

Peterson, Merrill A., 1965-

Abstract

Eutrophication is one of the foremost problems affecting our freshwater resources. Excessive nutrient loading impacts freshwater lakes by altering ecosystem processes and degrading water quality, often resulting in human-induced eutrophication. Worldwide, cyanobacteria blooms occur in many anthropogenically eutrophic lakes. Such blooms are of increasing concern in the Pacific Northwest because they negatively affect lake system and function. A major concern is their unpredictable production of toxins, which can be deadly to animals, including humans. Therefore, an improved understanding of the incidence and persistence of cyanobacteria blooms is a critical aspect of protecting our water supply. The goal of this thesis was to attempt to create a predictive model based on simple water quality characteristics that would classify lakes according to bloom status using a multivariate statistical approach. Additional possible bloom contributors such as, light availability, landscape properties, N:P ratios or other interactive effects were not investigated in this study. During 2007-2009, 50 lakes in Northwest Washington were sampled to measure standard water quality (water chemistry) parameters as part of the Institute of Watershed Studies' (IWS) small lakes monitoring project. In addition, algal samples were collected during 2007-2009. The IWS study created a water quality baseline for many previously unmonitored lakes and revealed that a number of lakes experienced cyanobacteria blooms. Previous studies have used high phosphorus as an indicator of cyanobacteria blooms. I tested phosphorus, as well as chlorophyll, as possible indicators of cyanobacteria blooms. Based on hierarchical, Kmeans and non-metric clustering, the lakes sampled by IWS can be clustered into two groups based on differences in conductivity, alkalinity, total phosphorus and turbidity. However, chlorophyll and phosphorus concentrations did not predict lakes that were dominated by cyanobacteria blooms. High phosphorus levels were usually associated with high chlorophyll levels, but high chlorophyll levels were not always associated with cyanobacteria dominance. Using the water chemistry, data high phosphorus was a good indicator of algal blooms, but could not be used as an exclusive predictor of cyanobacteria blooms. Linear discriminants analysis was used to build a predictive model based on the 2007-2008 water quality data to try to classify the 2009 samples by cyanobacteria dominance. The model was unsuccessful (30% success rate) in predicting cyanobacteria blooms within the 2009 data. Despite the fact that algal blooms are fairly predictable using water chemistry data, this study highlights the complexity of predicting harmful cyanobacteria blooms in the Pacific Northwest.

Type

Text

Publisher

Western Washington University

OCLC Number

668214616

Digital Format

application/pdf

Geographic Coverage

Washington (State), Western

Genre/Form

Academic theses

Language

English

Rights

Copying of this thesis in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this thesis for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.

Included in

Biology Commons

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