Jenna Cook

Urban environments contend with an array of stressors, including salinization by deicing road salts. To advance understanding of how road salt pollution affects aquatic ecosystem functioning, we surveyed primary producers in 50 stormwater ponds in Brampton, Canada. We found that chloride concentrations decreased (benthic) periphytic algal biomass but had no detectable effect on the total biomass of (free‐floating) phytoplankton. However, impacts were obscured by underlying compositional shifts, as cyanobacteria generally compensated for declines of other taxa. Varying sensitivities of taxonomic groups (inferred from diagnostic pigments) revealed potential bioindicators, with the proportion of periphytic chromophytes declining most significantly and effects on the relative concentrations of green algae differing between planktonic and benthic communities. As chloride concentrations were a leading predictor of cyanobacterial dominance in our study of impaired, nutrient‐rich, urban ponds, findings reveal an emerging risk of potentially harmful organisms from the ongoing salinization of freshwater resources.

A mounting task in the aquatic sciences is to better monitor harmful algal blooms (HABs). In Canada, satellite Earth Observation is used to meet this challenge in a few large lakes (e.g., Lake Erie, Lake Winnipeg). Here, we highlight the novel ground truthing of an algorithm for multivariate analyses of HABs in a smaller Canadian prairie lake (Pigeon Lake, Alberta) using Sentinel 2 satellite-based data and confirmatory evidence from in situ concentrations of chlorophyll a and taxonomically diagnostic algal pigments. Calibration ( r² = 0.90, n = 73) and validation ( r² = 0.91, n = 86) of our model enabled testing for trends and discovery of within-lake sources of HABs using archival satellite imagery spanning a period of 6 years. Significant seasonality of the intensity, spatial extent, and severity of HABs in the study lake underscored our discovery of their origins near inflowing streams within the northwestern littoral zone. These findings highlight the potential of our remote-sensing approach to identify “hotspots” of HABs and help guide remediation strategies in small prairie lakes.

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. Interlake 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.

Cyanobacterial blooms in lakes of low nutrient status are recent ecological surprises. Culling of planktivorous fish may help suppress phytoplankton blooms via a trophic cascade effect. To test this hypothesis, we conducted a 90-day experiment adjacent to a shallow oligomesotrophic lake increasingly beset by midsummer cyanobacterial blooms in the presence of high abundances of minnows and sparse herbivorous zooplankton. The single-factor (± three spottail shiners, Notropis hudsonius) experimental design was replicated 10 times for a total of twenty 1200 L capacity mesocosms. Contrary to the trophic cascade hypothesis, minnow removal decreased the abundance of bosminids capable of grazing cyanobacteria. Nevertheless, removal of the minnows significantly both suppressed phytoplankton biomass and offset the development of cyanobacteria, such as Gloeotrichia echinulata. Lower concentrations of phosphorus and nitrogen in the fishless relative to stocked mesocosms best explained these differences in the phytoplankton community. Our findings highlight how fisheries management practices that enhance minnow populations in lakes of low productivity may inadvertently contribute to cyanobacterial blooms through increased nutrient cycling.

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.