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The neurotoxic alkaloid β-N-methyl-amino-l-alanine (BMAA) and related isomers, including N-(2-aminoethyl glycine) (AEG), β-amino-N-methyl alanine (BAMA), and 2,4-diaminobutyric acid (DAB), have been reported previously in cyanobacterial samples. However, there are conflicting reports regarding their occurrence in surface waters. In this study, we evaluated the impact of amending lake water samples with trichloroacetic acid (0.1 M TCA) on the detection of BMAA isomers, compared with pre-existing protocols. A sensitive instrumental method was enlisted for the survey, with limits of detection in the range of 5–10 ng L−1. Higher detection rates and significantly greater levels (paired Wilcoxon's signed-rank tests, p < 0.001) of BMAA isomers were observed in TCA-amended samples (method B) compared to samples without TCA (method A). The overall range of B/A ratios was 0.67–8.25 for AEG (up to +725%) and 0.69–15.5 for DAB (up to +1450%), with absolute concentration increases in TCA-amended samples of up to +15,000 ng L−1 for AEG and +650 ng L−1 for DAB. We also documented the trends in the occurrence of BMAA isomers for a large breadth of field-collected lakes from Brazil, Canada, France, Mexico, and the United Kingdom. Data gathered during this overarching campaign (overall, n = 390 within 45 lake sampling sites) indicated frequent detections of AEG and DAB isomers, with detection rates of 30% and 43% and maximum levels of 19,000 ng L−1 and 1100 ng L−1, respectively. In contrast, BAMA was found in less than 8% of the water samples, and BMAA was not found in any sample. These results support the analyses of free-living cyanobacteria, wherein BMAA was often reported at concentrations of 2–4 orders of magnitude lower than AEG and DAB. Seasonal measurements conducted at two bloom-impacted lakes indicated limited correlations of BMAA isomers with total microcystins or chlorophyll-a, which deserves further investigation. [ABSTRACT FROM AUTHOR]

Instrumented buoys are used to monitor water quality, yet there remains a need to evaluate whether in vivo fluorometric measures of chlorophyll a (Chl a) produce accurate estimates of phytoplankton abundance. Here, 6 years (2014–2019) of in vitro measurements of Chl a by spectrophotometry were compared with coeval estimates from buoy‐based fluorescence measurements in eutrophic Buffalo Pound Lake, Saskatchewan, Canada. Analysis revealed that fluorometric and in vitro estimates of Chl a differed both in terms of absolute concentration and patterns of relative change through time. Three models were developed to improve agreement between metrics of Chl a concentration, including two based on Chl a and phycocyanin (PC) fluorescence and one based on multiple linear regressions with measured environmental conditions. All models were examined in terms of two performance metrics; accuracy (lowest error) and reliability (% fit within confidence intervals). The model based on PC fluorescence was most accurate (error = 35%), whereas that using environmental factors was most reliable (89% within 3σ of mean). Models were also evaluated on their ability to produce spatial maps of Chl a using remotely sensed imagery. Here, newly developed models significantly improved system performance with a 30% decrease in Chl a errors and a twofold increase in the range of reconstructed Chl a values. Superiority of the PC model likely reflected high cyanobacterial abundance, as well as the excitation–emission wavelength configuration of fluorometers. Our findings suggest that a PC fluorometer, used alone or in combination with environmental measurements, performs better than a single‐excitation‐band Chl a fluorometer in estimating Chl a content in highly eutrophic waters. [ABSTRACT FROM AUTHOR]

Climate‐driven decreases in ice‐cover duration have the potential to impact lake ecosystems, yet we have only partial understanding of the effects of winter conditions on physical, chemical, and biological properties of lakes. We used 39 years of monitoring data to examine under‐ice changes in nutrients, oxygen, and phytoplankton in a shallow drinking‐water reservoir. Two phases of winter were identified. Early winter was characterized by declining oxygen. In this phase, there were increases in specific conductance and concentrations of ammonium (NH4+‐N) and soluble reactive phosphorus (SRP). In the month prior to ice off these trends reversed themselves and phytoplankton began to increase. Specific conductance declined as meltwater entered the lake. Nutrients (SRP and NH4+‐N) declined, concurrent with increases in chlorophyll a and oxygen during late winter. This work demonstrates that chemical and biotic changes through winter are highly time dependent and differ between early and late winter phases. The late winter phase is often unstudied because of unsafe ice conditions, but here, the "spring" bloom commonly occurs in late winter under ice. The phases of winter, which are likely driven by changes in light, must be considered as we work to understand how diverse lakes will respond to declining periods of ice cover, and what drives differences in the spring ecology of diverse ice‐covered lakes. [ABSTRACT FROM AUTHOR]

While benthic algal biomass is one of the most commonly measured variables within littoral communities, it is also one of the most poorly characterized. The use of chlorophyll a as an estimate of biomass, while easy and inexpensive, can be affected by changes in environmental conditions and algal community composition. Biovolume-based measurements often have high variability and are affected by changes in cell volume due to preservation. Using 12 years of data from the Experimental Lakes Area (northwestern Ontario, Canada) as well as short-term surveys and experimental studies from the Experimental Lakes Area and the Canadian Rocky Mountains, we demonstrate that biovolume and chlorophyll a are often decoupled in the littoral zone of temperate oligotrophic lakes. We recommend that researchers revisit the limitations of both metrics and specifically caution against the use of chlorophyll a as a biomass indicator when light, temperature, or species composition vary significantly. [ABSTRACT FROM AUTHOR]