Dynamics of freshwater algae in forested watershed environment in Bull Run, Oregon.
AuthorRahman, Md. Azizur.
Committee ChairHawkins, Richard H.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractLong-term freshwater algae data from a number of reservoir locations and watershed outlets in Bull Run, Oregon are classified at taxonomic levels and analyzed for spatial-temporal dynamics of the concentration and diversity. The analysis is further extended to: (1) study associated relationships between and among algal, water chemistry, and hydrologic variables, and (2) multiple regression models predicting current and next month's algal concentration and diversity. Over fifty-thousand records covering more than twenty fields and contiguous eleven years for algae and eight years for environmental conditions are reduced and standardized to monthly average values. Of the 111 types of algae identified and characterized from the reservoir systems, Chlamydomonas taxa is most dominant which covered more than fifty-percent of the total algae concentration. The diatom Achnanthes is the second most dominant. Algal concentration and species diversity showed high temporal variability consistently across all locations. Algal species diversity slightly varied with locations without showing much change in the concentrations. Rainfall produced a number of direct and indirect associations with water chemistry variables, but few with algal characteristics. High correlation is observed between silica and specific conductivity, and their levels were higher mostly during the drier periods. Eight multiple regression models are presented to predict algal concentration and diversity for the current and next month. Recommendations are proposed to strengthen the existing water quality monitoring in the Bull Run watershed.
Degree ProgramRenewable Natural Resources