Capturing the spatial variability of algal bloom development in a shallow temperate lake

Algal blooms can have profound effects on the structure and function of aquatic ecosystems and have the potential to interrupt valuable ecosystem services. Despite the potential ecological and economic consequences of algal blooms, the spatial dynamics of bloom development in spatially complex ecosystems such as shallow lakes remain poorly characterised. Our goal was to evaluate the magnitude and drivers of spatial variability of algal biomass, dissolved oxygen, and pH over the course of a season, in a shallow lake in order to better understand the spatial dynamics of algal blooms in these ecosystems. We sampled 98 locations in a small eutrophic lake on a 65‐m grid for several parameters (chlorophyll a, phycocyanin, dissolved oxygen, pH, and temperature), weekly over 122 days. This was done to estimate the dynamics of variability and spatial autocorrelation during the course of multiple bloom events. We also compared the spatial measurements to a high frequency sensor deployed at a fixed station and estimated the optimal spatial sampling resolution by performing a rarefaction analysis. Spatial heterogeneity of algal pigments was high, particularly during bloom events, and this pattern and the overall severity of the bloom were not well captured with the fixed station monitoring. The pattern of algal pigments and other limnologically important variables (dissolved oxygen and pH) was related to the direction of prevailing winds 24 hr prior to sampling, the shallow northern basin where the main surface inlet is located, and heavy precipitation. Additionally, a dense bed of floating‐leaf macrophytes contributed to local patchiness in all variables. Finally, from the rarefaction analysis we found that minimal information about the mean state of the ecosystem was gained after c. 30 locations had been sampled. This study revealed how spatially heterogeneous shallow lakes are over the course of a single season, and that the magnitude of variability was highest during biologically intensive periods such as algal blooms. As such, continued research is needed across a range of trophic conditions to better understand the structure of horizontal variability in lakes. Overall, these data demonstrate the need for spatially explicit monitoring to better understand the dynamics and drivers of algal blooms in shallow lakes and to better manage ecosystem services.