Improving the ability to phytoplankton assemblage composition and the course of change in lakes is essential for anticipating and managing for the effects of watershed and climate changes on phytoplankton bloom dynamics. The degree to which phytoplankton assembly dynamics are controlled by extrinsic biogeochemical drivers or intrinsic species interactions is still debated in ecology, partly due to the influence of scale (temporal and spatial) on the interpretation of these controls. This research attempts to improve predictions of phytoplankton assemblage change at short and long time scales by posing two questions: (1) What are the dominant scales of variance in potential driver and phytoplankton community composition, and (2) How do changes in water column stability (occurring over hours to days) influence phytoplankton diversity and assemblage change (over weeks to months). At least two years of high frequency biogeochemical data and biweekly to monthly phytoplankton compositional data were obtained from four lakes that represent different mixing regimes and trophic states. Time series and wavelet analyses are being used to identify scales of variance in the two types of datasets, and correlations among these scales is examined. Water column stability appears to have an overriding influence on assemblage diversity and change, particularly during the 4-6 day period preceding phytoplankton observations. Analysis of these responses at the assemblage level reveal traits associated with stable and mixed water column conditions that can be used to improve predictions of assemblage composition at many temporal and possibly spatial scales.
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