Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea

Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea

Abstract Phytoplankton blooms exhibit varying patterns in timing and number of peaks within ecosystems. These differences in blooming patterns are partly explained by phytoplankton:nutrient interactions and external factors such as temperature, salinity and light availability. Understanding these in...

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Bibliographic Details
Main Authors: Maximilian Berthold, Pascal Nieters, Rahel Vortmeyer-Kley
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Scientific machine learning
Sparse identification of nonlinear dynamics
General additive mixed model
Baltic Sea
Phytoplankton blooms
Online Access:https://doi.org/10.1038/s41598-025-85605-y
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https://doi.org/10.1038/s41598-025-85605-y

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