Relating Oxygen Production and Buoyancy Rates of Aphanizomenon flos-aquae to Light History in Upper Klamath Lake. Introduction Upper Klamath Lake (UKL) is located on the east side of the Cascade mountain range in southern Oregon, 10 miles north of the California border. It has a surface area of 256 km 2 and an average depth of 3 meters. In spring, summer and fall, the open water of UKL is dominated by blooms of the cyanobacterium Aphanizomenon floss-aqua. Due to AFA blooms and high concentrations of phosphorus, the lake is classified as hypereutrophic. AFA blooms do not develop in a uniform pattern throughout the lake. Morphological lake features, meteorological factors, and buoyancy behavior of AFA contribute to the variable bloom pattern. The work for this study focused on the relationship between buoyancy rates and oxygen production for AFA under varying light intensities to quantify relationships between production and buoyancy behavior. The goal of the study was to show correlations between buoyancy rate under conditions of low to high light intensity and photosynthetic parameters measured from oxygen production versus intensity (PI) curves. It was expected that as light intensity increased, descending buoyancy rate would increase and oxygen production would decrease due to light intensity inhibition of photosynthesis. Buoyancy Behavior Oxygen Production and Buoyancy Rate Data Figure 1. Orientation of AFA clusters in standard spectrophotometric cuvettes after light preconditioning at 100 microeinsteins (A), 300 microeinsteins (B), and 800 microeinsteins (C) and a dark period of 10 minutes. Buoyancy behavior of AFA clusters after light preconditioning at 100 microeinsteins (D), 300 microeinsteins (E), and 800 microeinsteins (F) in and a dark period of 10 minutes. Oxygen Production and Buoyancy Rate Correlations Figure 4. Oxygen production vs intensity plots for AFA clusters after incubation in 0.5 liter mixed containers with a surface water intensity of 300 microeinsteins for 5min, 10min, 20min and 30min during the month of September 2009 Figure 5. Oxygen production vs intensity plots for AFA clusters after incubation in 0.5 liter mixed containers with a surface water intensity of 800 microeinsteins for 5min, 10min, 20min and 30min during the month of September 2009 Figure 2. Plots of correlations between ascending rate and descending rate (column 1), descending rate and time of incubation (column 2), and ascending rate and time of incubation (column 3). Rows 1,2 & 3 correspond to incubation intensities of 100, 300 & 800 respectively. Figure 3. Box plots in upper row display buoyancy rate means and variability between incubation intensities of 100, 300 and 800. Correlation plots in lower row display the direct relationship between ascending rates and descending rates as well as correlations between buoyancy rates and time of incubation at 800 microeinsteins. Figure 6. Matrix of correlation plots between AFA buoyancy rates preconditioned at 300 microeinsteins, PI curve parameters, and time of incubation. Figure 7. Matrix of correlation plots between AFA buoyancy rates preconditioned at 800 microeinsteins, PI curve parameters, and time of incubation. Results and Conclusions After preconditioning and 10 minutes of dark before analysis, clusters oriented themselves at different depths in the water column based upon intensity (Figure 1) Data measured from clusters preconditioned at 100 microeinsteins elucidated no distinct relationships (figure 2) The data indicates that that correlations between ascending buoyancy rates and descending buoyancy rates become stronger with increased time and water surface intensity for AFA clusters (Figure 3) Oxygen production curves vs light intensity indicate that oxygen production is more effective at higher preconditioning intensities (Figure 4 & 5) For ascending and descending buoyancy rates, correlation plots in Figures 6 & 7 show that descending and ascending buoyancy rates both correlate with time and intensity, but ascending rate correlations are stronger at 800 than at 300 For photosynthetic parameters (alpha, Pmax, and IK), this study data indicates that very weak correlations exist for buoyancy rates at 300, but strong, negative correlations exist between Pmax, ascending rate and descending rate at 800 (Figures 6 & 7) Overall, a negative correlation between descending rate and oxygen production was not indicated by the data in this study as expected. Instead, strong correlations were shown between ascending and descending rates as time and intensity increased. Only at the highest light intensity utilized in this study were negative correlations indicated between oxygen production and buoyancy rate.