A model for seasonal phytoplankton blooms
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Updated: Aug 17, 2026

Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton
Published on: July 28, 2023
Amit Huppert1, Bernd Blasius, Ronen Olinky
1Department of Zoology and the Porter Super Center for Ecological and Environmental Studies, Tel Aviv University, Ramat-Aviv, Tel Aviv 69978, Israel. ahuppert@whoi.edu
Abstract:
We analyse a generic bottom-up nutrient phytoplankton model to help understand the dynamics of seasonally recurring algae blooms. The deterministic model displays a wide spectrum of dynamical behaviours, from simple cyclical blooms which trigger annually, to irregular chaotic blooms in which both the time between outbreaks and their magnitudes are erratic. Unusually, despite the persistent seasonal forcing, it is extremely difficult to generate blooms that are both annually recurring and also chaotic or irregular (i.e. in amplitude) even though this characterizes many real time-series. Instead the model has a tendency to 'skip' with outbreaks often being suppressed from 1 year to the next. This behaviour is studied in detail and we develop analytical expressions to describe the model's flow in phase space, yielding insights into the mechanism of the bloom recurrence. We also discuss how modifications to the equations through the inclusion of appropriate functional forms can generate more realistic dynamics.
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