Our ability to predict and prevent harmful algal blooms is directly related to our ability to study and understand cyanobacteria. Numerous studies have used the FlowCam to rapidly enumerate, image, and aid in the identification of harmful algae present in water samples to better track, trend and predict blooms. We've collected our favorite studies on cyanobacteria into one document that features synopses of the following papers:
- Chaffin et al., 2019, "Cyanobacterial blooms in the central basin of Lake Erie: Potentials for cyanotoxins and environmental drivers", Journal of Great Lakes Research
- Chaffin et al., 2018, "Interactions between nitrogen form, loading rate, and light intensity on Microcystis and Planktothrix growth and microcystin production", Harmful Algae
- Lehman et al., 2017, "Impacts of the 2014 severe drought on the Microcystis bloom in San Francisco Estuary", Harmful Algae
- Kinjanka et al., 2016, "Vertical distribution of buoyant Microcystis bloom in a Langrangian particle tracking model for short-term forecasts in Lake Erie", J. Geophys. Res. Oceans
- Graham et al., 2018, "High-resolution imaging particle analysis of freshwater cyanobacterial blooms", Limnol. Oceanogr.: Methods
- Nolan & Cardinale, 2018, "Species diversity of resident green algae slows the establishment and proliferation of the cyanobacterium Microcystis aeruginosa", Limnologica
