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Influence of Mixing and Buoyancy on Competition Between Cyanobacteria Species in Upper Klamath Lake

Cyanobacterial blooms in lakes impact human health, the economy, and ecosystem health. It is predicted that climate change will promote and increase the frequency and intensity of cyanobacterial blooms due to unique physiological adaptions that allow cyanobacteria to exploit warm stable water bodies. Key cyanobacteria physiological adaptions include nitrogen fixation, buoyancy regulation and higher optimum growth temperatures. The largest uncertainty of predicting the effect of climate change is in understanding how the interactions among species will change. Adding to the ambiguity, cyanobacteria physiological adaptions can vary based on lakespecific ecotypes and can have different sensitivities to temperature. It is critical to understand how cyanobacterial physiological adaptions impact species interactions in order to improve and devise adaptable, short‐term management methods for bloom control. This study investigated how weather patterns and algal buoyancy regulation influence the competition and accumulation of two bloom‐forming buoyant cyanobacteria species (Aphanizomenon flos‐aquae (APFA) and toxin‐forming Microcystis aeruginosa (MSAE)) in Upper Klamath Lake (UKL), Oregon. The focus was confirming the buoyancy rate of the APFA in Upper Klamath Lake and exploring whether short‐term weather conditions could lead to dangerous accumulations of APFA or MSAE. A sensitivity analysis was conducted on the model's buoyancy terms and growth curves to see if the outcome of competition was influenced by these parameters.
UKL specific buoyancy rates were measured on APFA from samples taken directly from the lake in the summer of 2015. Tracking software was used to measure APFA movement through water, and individual colony movement was averaged to obtain a single buoyancy rate. There was a high degree of agreement between the calculated APFA buoyancy rate in UKL (0.89 ± 0.34 m hr-1) with the rate published by Walsby (1995; 0.9 ± 0.5 m hr-1).
This study investigated how weather patterns and buoyancy regulation influenced the outcome of competition between APFA and MSAE. Weather and water column temperature data were collected from UKL in the summer of 2016. A onedimensional hydrodynamic model was used to calculate the lake's thermal and turbulence structure on days with contrasting weather patterns (hot/cool and windy/calm). A competition model was used to calculate the accumulation of APFA and MSAE cells in regular intervals through the water column under the various weather scenarios. MSAE accumulation was significantly influenced by the thermal and turbulence regimes, but APFA maintained high accumulations under every regime and was the better competitor under every thermal and turbulence regime. MSAE was more negatively impacted by high turbulence than low temperatures.
APFA's optimum temperature growth curve was found to be important in determining the outcome of competition between APFA and MSAE. Surprisingly, competition was not sensitive to changes in buoyancy rates. Buoyancy was not found to be a function of algal accumulation under any thermal and turbulence regime.
The impacts of climate change and human‐induced enrichment has the potential to change existing patterns of species interactions in lentic systems. Restoration and management efforts should consider the significance of cascading ecological responses to climate change. Understanding how key physiological adaptions operate is the first step to assessing the scope of this impact. While buoyancy might not play a large role in competition in UKL, it might be possible to use mixing to suppress MSAE because it is negatively impacted by high turbulence. If MSAE hot spots become a reoccurring problem in UKL, lakes managers might be able to use localized mixing to suppress MSAE blooms in these problem areas.

Identiferoai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-5007
Date22 May 2017
CreatorsBrunkalla, Roberta Joann
PublisherPDXScholar
Source SetsPortland State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceDissertations and Theses

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