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Date Permissions Signed


Date of Award

Winter 2021

Document Type

Masters Thesis

Department or Program Affiliation

Environmental Sciences

Degree Name

Master of Science (MS)


Environmental Sciences

First Advisor

Sofield, Ruth M.

Second Advisor

Matthews, Robin A., 1952-

Third Advisor

Bodensteiner, Leo R., 1957-


This study analyzed water quality, metals concentrations, and algal taxa richness data from 68 lakes in Northwest Washington that have been sampled by Western Washington University’s Institute of Watershed Studies. The primary goals of this analysis were to survey unmonitored lakes to gain a better understanding of the current conditions and to compare how lakes are characterized using combinations of the three data sets. Higher elevation lakes in the North Cascades were expected to have lower concentrations of metals and nutrients and more sensitive algae taxa than low elevation lakes in the Puget Sound Lowlands. When compared against Washington State benchmarks, some lakes exceeded aluminum, iron, copper, temperature, dissolved oxygen, and/or pH values. The most common exceedance was for a modified temperature criteria with 49 of the 68 lakes exceeding the least protective designated use criteria and 66 of the 68 lakes exceeding the most protective designated use criteria. Water quality and metal variables each produced clusters that supported traditional lake trophic state classifications. Algae taxa richness informed clusters showed significant differences between groups and the number of desmid and euglenoid taxa were used to characterize the clustering results. Water quality, metals, and algae richness all produced non-random clusters. Water quality clustering produced clustering largely along productivity variables. Metal clustering produced three clusters representing lakes with high, low, and variable metal concentrations. Cobalt, iron, chromium, and magnesium were significantly different for each cluster and may be useful indicators of total metal loading in lakes. Algae clustering produced less informative clusters than the other data sets due to the use of 419 variables for this analysis and may indicate that a different classification system or more sampling locations could produce a more parsimonious clustering result. Lake groupings between clusters were non-random; overlaying the metal clusters with the water quality clusters produced informative lake descriptions. Use of all three data sets provides a more complete representation of each lake and the groups of lakes as a whole than using only water quality parameters or trophic state. This study found no significant differences between lakes in the North Cascades and Puget Lowlands.




Western Washington University

OCLC Number


Subject – LCSH

Water quality--Washington (State), Western; Principal components analysis; Hierarchical clustering (Cluster analysis)

Geographic Coverage

Washington (State), Western




masters theses




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appendix.xlsx (262 kB)