Primary Productivity and Lake Health: Examination of Phytoplankton Growth Rate Regulations in Keuka Lake via Short-term Microcosm Experiments

Introduction: Lakes are ecological systems that can integrate changes throughout their watersheds resulting from anthropogenic activity. Consequently, investigation of biological processes within lakes can elucidate the effects of watershed activity on lake health. Phytoplankton (i.e. suspended algae) the primary producers of pelagic systems – are a conduit through which watershed activity can affect lake health. Due to their location within the pelagic food web, phytoplankton abundance and diversity in part determines the abundance and diversity of organisms belonging to higher trophic levels (e.g. zooplankton, mollusks and fish). Historically, various groups have studied algal abundance in Keuka Lake using survey techniques. This approach provides snapshots of change, but does not illuminate the mechanisms that regulate phytoplankton growth. Our research group is thus seeking to quantify phytoplankton growth rates in response to changes in nutrients, light and grazing (i.e. phytoplankton consumption by zooplankton and zebra mussels) by developing short-term microcosm experimental techniques. Ultimately, phytoplankton growth rates generated from these experiments will be used to formulate predictive models to further our understanding of how watershed activity impacts the health of Keuka Lake via effects of primary productivity. Between June of 2005 and May of 2006, we have conducted a series of nine experiments to investigate the effects of light, nutrients and grazing on phytoplankton growth rates. Whole water samples were collected from the Keuka College access point and incubated for 96 hours within an environmental chamber. By placing samples within an environmental chamber, temperatures were effectively controlled at ambient levels. Phytoplankton abundance was measured using fluorometry, and fluorescence measurements were used to derive daily growth rates. To detect significant differences among treatments, results were analyzed using one and two-way ANOVAs in conjunction with a Tukey post-hoc test.