Over the last 20 years, aberrant algal blooms have been increasing in frequency and scope in coastal waters, likely as a result of anthropogenic influences (e.g. global climate change and nutrient loading). Modeling offers promise in enhancing our ability to project and ultimately mitigate these blooms by improving our understanding of their underlying causes. Here I model Coccolithophore and Pseudo-nitzschia blooms in the Monterey Bay and Santa Barbara regions. These models are based on actual bloom events that occurred in the spring and summer months of 2015, and rely on observations based on algal physiology (e.g. nutrient ratios and temperature-growth curve) for both taxa. Results indicate that models based on real world data can accurately depict the general trends of algal blooms. Models indicate that the ‘warm anomaly’, the large mass of unusually warm water that persisted on the west coast of North American from 2013 to 2015 was the primary driver of bloom for both taxa, with nutrient ratios also playing an important role. Both models show great promise in forecasting Coccolithophore and Pseudo-nitzschia blooms off of the North American west coast, as well as the propagation of domoic acid (a dangerous toxin produced by Pseudo-nitzschia) and how it may impact local fisheries in response to climatological and nutrient forcing. These models demonstrate the application of modeling and its role in helping us better understand the underlying factors that drive phytoplankton blooms.

Presentation Slides: https://www.scribd.com/presentation/320953561/Computer-modeling-of-anomalous-phytoplankton-blooms-off-the-California-Coast#fullscreen&from_embed