Search Results (4)

Cyanobacteria (blue-green algae) are a diverse group of prokaryotic microorganisms that impact global biogeochemical cycles. Under eutrophic conditions, cyanobacterial species can produce cyanotoxins, resulting in harmful algal blooms (cHABs) that degrade water quality and result in economic and recreational losses. The Laurentian Great Lakes, a key global freshwater source, are increasingly affected by these blooms. To understand the underlying mechanisms in cHAB formation, we investigated microcystin levels, cyanotoxin genes/transcripts, and taxonomic/microcystin metabarcoding across three sampling locations in the Canadian Great Lakes region, including Hamilton Harbour, Bay of Quinte, and Three Mile Lake (Muskoka), to observe the regional and longitudinal cyanobacterial dynamics. The results revealed a positive correlation between microcystin levels, the occurrence of cyanobacterial taxonomic/cyanotoxin molecular markers, and the relative widespread abundance of specific dominant cyanobacterial taxa, including Planktothrix, Microcystis, and Dolichospermum. The Cyanobium genus was not observed in Hamilton Harbor samples during late summer (August to September), while it was consistently observed in the Three Mile Lake and Bay of Quinte samples. Notably, Dolichospermum and saxitoxin genes were predominantly higher in Three Mile Lake (an inland lake), suggesting site-specific characteristics influencing saxitoxin production. Additionally, among the potential microcystin producers, in addition to Microcystis, Hamilton Harbour and Bay of Quinte samples showed consistent presence of less dominant microcystin-producing taxa, including Phormidium and Dolichospermum. This study highlights the complexity of cHAB formation and the variability in cyanotoxin production in specific environments. The findings highlight regional and site-specific factors that can influence cyanobacterial taxonomic and molecular profiles, necessitating the integration of advanced molecular technologies for effective monitoring and targeted management strategies. Full article

The nature of the exchange flow between the Bay of Quinte and Lake Ontario has been studied to illustrate the effects of the seasonal onset of stratification on the flushing and transport of material within the bay. Flushing is an important physical process in bays used as drinking water sources because it affects phosphorous loads and water quality. A 2-d analytical model and a 3-dimensional numerical coastal model (FVCOM) were used together with in situ observations of temperature and water speed to illustrate the two-layer nature of the late summer exchange flow between the Bay of Quinte and Lake Ontario. Observations and model simulations were performed for spring and summer of 2018 and showed a cool wedge of bottom water in late summer extending from Lake Ontario and moving into Hay Bay at approximately 3 cm/s. Observed and modelled water speeds were used to calculate monthly averaged fluxes out of the Bay of Quinte. After the thermocline developed, Lake Ontario water backflowed into the Bay of Quinte at a rate approximately equal to the surface outflow decreasing the flushing rate. Over approximately 18.5 days of July 2018, the winds were insufficiently strong to break down the stratification, indicating that deeper waters of the bay are not well mixed. Particle tracking was used to illustrate how Hay Bay provides a habitat for algae growth within the bay. Full article

The spatial and temporal (monthly) variability of river discharge has a significant effect on circulation and transport pathways within shallow embayments whose dynamics are largely controlled by wind and riverine inputs. This study illustrates the effects of the monthly variation in Trent River discharge on simulated particle transport and settling destination in the Bay of Quinte, Lake Ontario for the years 2016–2019. Observations of Lagrangian surface drifter data were used to derive Trent River discharge forcing for a three-dimensional hydrodynamic numerical model of the Bay of Quinte. Peak monthly flushing was up to three times as much as the lowest monthly flushing in any year, with the Trent River responsible for up to 95% of the flushing in low runoff years. Particle transport simulations showed that particles could be trapped along shorelines, which extended residence times, and Trent River releases suggest that researchers should look for delayed peaks in Total Phosphorous (TP) load measurements in observations between Trenton and Belleville as particles move downstream. Particles with constant settling velocities originating from the Trent River did not move downstream past Big Bay, and particles from the Napanee River were the primary source for Longreach. Full article

To better understand and mitigate threats to the long-term health and functioning of wetlands, there is need to establish comprehensive inventorying and monitoring programs. Here, remote sensing data and machine learning techniques that could support or substitute traditional field-based data collection are evaluated. For the Bay of Quinte on Lake Ontario, Canada, different combinations of multi-angle/temporal quad pol RADARSAT-2, simulated compact pol RADARSAT Constellation Mission (RCM), and high and low spatial resolution Digital Elevation and Surface Models (DEM and DSM, respectively) were used to classify six land cover classes with Random Forests: shallow water, marsh, swamp, water, forest, and agriculture/non-forested. Results demonstrate that high accuracies can be achieved with multi-temporal SAR data alone (e.g., user’s and producer’s accuracies ≥90% for a model based on a spring image and a summer image), or via fusion of SAR and DEM and DSM data for single dates/incidence angles (e.g., user’s and producer’s accuracies ≥90% for a model based on a spring image, DEM, and DSM data). For all models based on single SAR images, simulated compact pol data generally achieved lower accuracies than quad pol RADARSAT-2 data. However, it was possible to compensate for observed differences through either multi-temporal/angle data fusion or the inclusion of DEM and DSM data (i.e., as a result, there was not a statistically significant difference between multiple models). With a higher repeat-pass cycle than RADARSAT-2, RCM is expected to be a reliable source of C-band SAR data that will contribute positively to ongoing efforts to inventory wetlands and monitor change in areas containing the same land cover classes evaluated here. Full article