Describing and simulating phytoplankton of a small and shallow reservoir using decision trees and rule‑based models (CROSBI ID 323779)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Volf, Goran ; Žutinić, Petar ; Gligora Udovič, Marija ; Kulaš, Antonija ; Mustafić, Perica
engleski
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 data set comprising physical, chemical and biological variables measured at four stations. Two types of models were successfully elaborated, i.e. (1) model describing phytoplankton Phylum which describes and connects phytoplankton Phylum with phytoplankton abundance and biomass, and (2) model simulating phytoplankton biomass according to environmental variables which could be used in management purposes. Such models and their presentation contribute to a better understanding of the Butoniga reservoir ecosystem functioning.
Butoniga reservoir ; Phytoplankton Phylum ; Phytoplankton abundance and biomass ; Statistical analysis ; Machine learning ; Decision trees ; Rule-based models
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
195 (4)
2023.
508
20
objavljeno
0167-6369
1573-2959
10.1007/s10661-023-11060-9
Povezanost rada
Biologija, Građevinarstvo, Interdisciplinarne tehničke znanosti