Environmental factors influencing phytoplankton assemblage dynamics in freshwater ecosystems are an area of ongoing research in the Great Lakes, particularly Lake Erie where harmful algal blooms have impacted the system. Due to impacts on aquatic life and public health, studies worldwide have investigated environmental thresholds influencing the emergence and abundance of phytoplankton species. These thresholds are useful in the evaluation of ecosystem health and the implementation of conservation strategies. However, how these thresholds influence the phytoplankton assemblage shifts over time and space have yet to be explored in Lake Erie, USA. Our goal was to investigate the thresholds of environmental variables responsible for major phytoplankton group dynamics (cyanobacteria (CY), cryptophyta (CP), diatoms (DI), and chlorophyta (GA)) in the western basin of Lake Erie. Using phytoplankton group concentrations determined by a Fluoroprobe (bbe) and water quality data collected between spring-fall from 2015 to 2019, we explored the most significant variables driving changes in phytoplankton concentration at 4 monitoring locations. We applied a multi-method approach, starting with principal component analysis (PCA), Redundancy Analysis (RDA), Regression Trees, and ending with a change point analysis. This approach was successful in the detection of major environmental variables and their thresholds responsible for the emergence and dominance of each phytoplankton group. Results revealed that CY concentrations are primarily correlated to turbidity conditions while DI are more likely to dominate when dissolved oxygen concentrations are high. The presence of CP was mostly related to lower temperatures compared to CY. Lastly, N:SRP ratio was a strong predictor of GA. These environmental variables were relevant predictors of both seasonal and spatial dynamics. Our results reveal critical thresholds in environmental conditions that shape the predominance of each phytoplankton group in the western Lake Erie and emphasize how the spatial component of these conditions can affect phytoplankton assemblage dynamics. These findings may serve as a guide to modelers and decision-makers.