Effective assessment of the health risk of cyanobacterial blooms requires an early warning system, which enables rapid detection of species of concern and determination of whether their cell concentrations exceed advisory guidelines. Advanced digital flow cytometry using FlowCam® (Fluid Imaging Technologies) in combination with light microscopy is a solid prospect for tracking cyanobacterial communities in a timely manner. However, implementation of such a method poses several challenges for the user. We first address sample preparation, instrumentation, taxonomic enumeration, and trouble‐shooting to facilitate high throughput of analyses of water samples for total cyanobacterial cell counts and their species composition. Preservation and initial screening of samples using light microscopy to estimate community size structure are endorsed to insure their archival quality and avoid clogging of the flow cell. We show that the highest magnification (×20 objective) is needed to achieve representative total and species‐specific cell enumerations. We also report that total cyanobacterial cell counts for samples analyzed using FlowCam vs. inverted light microscopy show significant positive correlation, as do those for preserved vs. live samples. Quantification of community composition using FlowCam vs. light microscopy also shows strong concordance. Although our FlowCam method performs well in the context of the World Health Organization advisory threshold of a total cyanobacterial count of 100,000 cells mL−1, it remains a work in progress in terms of reliably automated species‐level identifications.
Remote mountain lakes in protected areas are sentinels of the ecological impacts of extreme and novel environmental changes occurring at broad regional scales. Ecosystem responses to such stressors are often first detected as shifts in community composition. We surveyed phytoplankton communities across 82 mountain lakes to test the hypothesis that taxonomic composition is indicative of more environmental changes than are aggregate properties, such as total biomass. Phosphorus was the only significant predictor of chlorophyll-inferred algal biomass, a correlative finding supported by evidence from our nutrient amendment bioassays. Inter-lake variances in taxonomically diagnostic algal pigments and 78 genera were indicative of changes in total phosphorus, glacial coverage, underwater light availability, and dissolved organic carbon. Lack of concordance was observed between ordinations of pigment- and genus-based data as environmental variables captured more variance in the pigment data. Our findings provide a baseline for future lake monitoring programs in the Canadian Rockies as they increasingly experience interactive effects involving climate change and landscape features, such as variation in turbid glacial meltwaters and aeolian phosphorus deposition from wildfires.
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