Describing and simulating phytoplankton of a small and shallow reservoir using decision trees and rule-based models.

Phytoplankton represents one of the most important biological components of primary production, trophic interactions, and circulation of organic matter in lakes and reservoirs. To contribute to the understanding of eutrophication processes and ecological status of the small, shallow Butoniga reservoir, a machine learning tool for induction of models in form of decision trees and rule-based models was applied on a dataset comprising physical, chemical, and biological variables measured at four stations. Two types of models were successfully elaborated, i.

Hybrid modeling approach for the northern Adriatic watershed management.

Northern Adriatic (NA) is one of the most productive parts of the Mediterranean Sea due to vast nutrient discharges from the contributing watershed. To understand better the excess of nutrients as stressors to the state of the marine ecosystem, a hybrid modeling approach following the DPSIR framework and terminology was developed, linking: 1) the AVGWLF model for modeling the pressures, i.e.