INTERMITTENT MIXING AS A STABILIZING MECHANISM FOR CYANOBACTERIA BLOOM BIOMASS AND FUNCTIONAL DIVERSITY

Environmental processes are becoming increasingly extreme and stochastic with cascading effects on lake ecosystem function. Phytoplankton community assembly is traditionally predicted by seasonal phenology but can be influenced at short time scales by disturbance processes. Their relative contributions depend on the frequency and timing of disturbance, which must occur at scales relative to phytoplankton growth to interrupt competitive exclusion. However, we do not fully understand how the relative forcing effects of seasonal versus stochastic processes will influence phytoplankton composition and turnover with climate change. Here we investigate the influence of disturbance on phytoplankton biomass and functional diversity in a shallow, eutrophic lake over 6 years (2018-2024), leveraging an aeration intervention to conduct an ecosystem-scale experiment examining the influence of seasonal versus stochastic environmental processes. We show that intermittent mixing and anoxic-oxic shifts can sustain biodiversity, biomass, and stabilize cyanobacteria blooms in a eutrophic lake. We found that phytoplankton diversity was highest following disturbance, and that increased disturbance frequency resulted in asynchronous fluctuations of phytoplankton functional groups. Phytoplankton asynchrony predicted biomass stability, resulting in stable cyanobacteria blooms through summer and late fall which displaced the fall diatom bloom. Our results demonstrate that disturbance can stabilize cyanobacteria blooms in eutrophic lakes, underscoring the importance of understanding contributions of seasonal versus stochastic forcing effects on phytoplankton biodiversity under current and future climate scenarios. 

Presentation Preference: Oral

Primary Presenter: Ana Morales-Williams, University of Vermont (ana.morales@uvm.edu)

Authors:

Ana Morales-Williams, University of Vermont  (ana.morales@uvm.edu)

Katelynn Warner, University of Vermont  (Katelynn.warner@uvm.edu)

Ashton Kirol, Pacific Northwest National Laboratory  (ashton.kirol@gmail.com)

Jeremy Howland, City University of New York  (jhowl1996@gmail.com)

Audrey Manning, University of Vermont  (armannin@uvm.edu)

Andrew Schroth, University of Vermont  (andrew.schroth@uvm.edu)