Archaeoinformatics - Data Science

MA: Data Mining for deeper Understanding of Cyanobacteria Blooms in the Baltic Sea

Supervisor: Prof. Dr. Matthias Renz

cyano bacteria teaser

Abstract

Cyanobacteria (blue-green algae) blooms are of growing societal concern in the Baltic Sea. The potentially toxic algae deteriorate water quality and add extra nutrients to an already overfertilized system. Consequently, a comprehensive understanding of the controlling mechanisms are essential if eutrophication is to be managed effectively. This master project investigated the controlling factors that promote cyanobacteria mass accumulation in the Baltic Sea. The underlying data base consisted of a combination of numerical ocean model output, satellite observations and in-situ nutrient samples (collected from international partners and compiled by GEOMAR Helmholtz Centre for Ocean Research Kiel). Support vector machines, decision trees and random forest models were examined analytically and experimentally and compared with one another. Major challenges were given by the heterogeneity, the sparsity and noisiness of the available data, as well as by the large number of factors potentially inducing bacterial growth. The results show-case a remarkable forecast skill based on abiotic factors alone. Somewhat counter to intuition, ambient nutrient concentrations, feature only minor explanatory power.

For more information please contact Dr. Ulrike Löptien