Challenges in Tracking The Highly Dynamic Cyanobacterial Blooms: Implications on its Monitoring for Central Alberta
Abstract
Cyanobacterial harmful algal blooms (hereafter, cyanobacterial blooms) in central Alberta are a growing concern due to its ecological, health, and economic consequences. Management of cyanobacterial blooms rely on comprehensive monitoring programs, which historically have yet to fully capture its variability across space and time. This study aims to consider the spatiotemporal variability of phytoplankton to effectively track cyanobacterial blooms. Partners at Alberta Lake Management Society’s LakeWatch program conducted a multi-site and a multi-visit sampling approach to six lakes in central Alberta throughout the summer of 2023. Then, I analyzed the phytoplankton pigments in those samples to investigate the dynamics of phytoplankton abundance, community composition, and spatial distribution across time. Our results indicate lake-specific trends in phytoplankton abundance and distribution, which peaks in late summer and are likely influenced by increased light and nutrient availability. There also seem to be an interaction between the spatial heterogeneity of phytoplankton abundance with seasonality. Cyanobacterial dominance increases in late summer, driven by higher nutrient levels. Total nitrogen, total phosphorus, and total dissolved phosphorus are identified as key predictors of cyanobacterial presence and spatial heterogeneity. Our findings highlight the challenges in monitoring cyanobacterial blooms, which suggests that traditional sampling of one particular point of the lake around once a month will not be sufficient to effectively track cyanobacterial blooms. Instead, sampling multiple sites for each lake across multiple visits per month is highly recommended if we wish to fully capture the highly dynamic shifts in phytoplankton abundance, community, and distribution throughout the summer. Alternatively, we can utilize remote sensing approaches like satellite-imagery to reduce economic and labour costs, while providing high frequency and high resolution tracking of harmful blooms.