A document by Jason J. Venkiteswaran. Click on the document to view its contents.

1. This study combines two approaches to explore the utility of Monod growth kinetics to predict competition outcomes between freshwater cyanobacteria and chlorophytes at low iron Fe. Fe threshold concentrations (FeT) below which growth ceases, and growth affinities (slope of Fe concentration vs growth rate near FeT) were estimated for three large-bodied cyanobacteria (two N-fixers and Microcystis) and two chlorophytes in batch cultures. 2. Mean FeT for N-replete cyanobacteria, N-deplete (when N-fixing) cyanobacteria and chlorophytes were 0.076, 0.736 and 0.245 nmol L-1 , respectively. Mean affinities were 0.937, 0.597 and 0.412 L nmol-1 d-1 , respectively. Assuming that the mean affinities are representative of their groups, affinities predict that N-replete cyanobacteria are more efficient at acquiring Fe than chlorophytes and should dominate when Fe is low but greater than their FeT. 3. A second study evaluated the competitive abilities of a pico-cyanobacterium and a third chlorophyte in dual species, serial dilution culture. The pico-cyanobacterium was dominant at 50 nmol L-1 total Fe (which limited both taxa) and 500 nmol L-1 total Fe. At 0.5 nmol L-1 total Fe, a stressful concentration below FeT during most of the incubation, growth rates and cell densities were extremely low but neither had washed out after several months. 4. These results show that Monod kinetics can successfully predict competition outcomes in laboratory settings at low Fe. While important, Monod kinetics are only one mechanism governing competition between cyanobacteria and eukaryotes in natural systems. Observed deviations from Monod predictions can be partially explained with known mechanisms.

Cyanobacterial blooms present challenges for water treatment, especially in regions like the Canadian prairies where poor water quality intensifies water treatment issues. Buoyant cyanobacteria that resist sedimentation present a challenge as water treatment operators attempt to balance pre-treatment and toxic disinfection by-products. Here, we used microscopy to identify and describe the succession of cyanobacterial species in Buffalo Pound Lake, a key drinking water supply. We used indicator species analysis to identify temporal grouping structures throughout two sampling seasons from May to October 2018 and 2019. Our findings highlight two key cyanobacterial bloom phases – a mid-summer diazotrophic bloom of Dolichospermum spp. and an autumn Planktothrix agardhii bloom. Dolichospermum crassa and Woronchinia compacta served as indicators of the mid-summer and autumn bloom phases, respectively. Different cyanobacterial metabolites were associated with the distinct bloom phases in both years: toxic microcystins were associated with the mid-summer Dolichospermum bloom and some newly monitored cyanopeptides (anabaenopeptin A and B) with the autumn Planktothrix bloom. Despite forming a significant proportion of the autumn phytoplankton biomass (greater than 60%), the Planktothrix bloom had previously not been detected by sensor or laboratory-derived chlorophyll-a. Our results demonstrate the power of targeted taxonomic identification of key species as a tool for managers of bloom-prone systems. Moreover, we describe an autumn Planktothrix agardhii bloom that has the potential to disrupt water treatment due to its evasion of detection. Our findings highlight the importance of identifying this autumn bloom given the expectation that warmer temperatures and a longer ice-free season will become the norm.

Flow management has the potential to significantly affect water quality. Shallow lakes in arid regions are especially susceptible to flow management changes which can have important implications for the formation of cyanobacterial blooms. Here, we reveal water quality shifts across a gradient of managed source water inflow regimes. Using in situ monitoring data, we studied a seven-year time span during which inflows to a shallow, eutrophic drinking water reservoir transitioned from primarily natural landscape runoff (2014 to 2015) to managed flows from a larger upstream reservoir (Lake Diefenbaker; 2016 to 2020) and identified significant changes in cyanobacteria (as phycocyanin) using generalized additive models to classify cyanobacterial bloom formation. We then connected changes in water source with shifts in chemistry and the occurrence of cyanobacterial blooms using principal components analysis. Phycocyanin was greater in years with managed reservoir inflow from mesotrophic Lake Diefenbaker (2016 to 2020) but dissolved organic matter (DOM) and specific conductivity, important determinants of drinking water quality, were greatest in years when landscape runoff dominated lake water source (2014 to 2015). Most notably, despite changing rapidly, it took multiple years for lake water to return to a consistent and reduced level of DOM after managed inflows from upstream Lake Diefenbaker were resumed, an observation that underscores how resilience may be hindered by weak resistance to change and slow recovery. Environmental flows for water quality are rarely defined yet here it appears trade-offs exist between poor water quality via elevated conductivity and DOM, and higher bloom risk. Taken together, our findings have important implications for water managers who must protect water quality while adapting to projected hydroclimatic change.