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Study of the impact of TIN/PO4 ratio on mucilage formation in the northern Adriatic using regression trees

Goran Volf orcid id orcid.org/0000-0002-7058-9012 ; Građevinski fakultet, Katedra za hidrotehniku, Sveučilište u Rijeci, Hrvatska
Nataša Atanasova orcid id orcid.org/0000-0002-8506-1667 ; Faculty of Civil and Geodetic Engineering, Institute of Sanitary Engineering, University of Ljubljana, Slovenia
Boris Kompare ; Faculty of Civil and Geodetic Engineering, Institute of Sanitary Engineering, University of Ljubljana, Slovenia
Robert Precali ; Centar za istraživanje mora, Institut Ruđer Bošković, Hrvatska
Nevenka Ožanić ; Građevinski fakultet, Katedra za hidrotehniku, Sveučilište u Rijeci, Hrvatska


Puni tekst: engleski pdf 795 Kb

str. 207-222

preuzimanja: 347

citiraj


Sažetak

The north-western part of the northern Adriatic (NA) exhibits eutrophic to mesotrophic characteristics with recurrent algal blooms and quite unpredictable mucilage events. To contribute to the understanding of the mucilage events in the NA a machine learning algorithm for induction of regression trees was applied on a long-term data-set comprising physical, chemical and biological
parameters, measured at six stations on the profile from the Po River delta (Italy) to Rovinj (Croatia). A model describing the connection between the TIN/PO4 ratio, considered as a necessary factor and sometimes even a trigger for mucilage events, and the environmental conditions in NA, was elaborated. The model for TIN/PO4 ratio confirmed the assumption that the mucilage events are connected with this ratio, e.g. mucilage events coincides with its high values. This finding indicates that at certain levels of phosphorus limitation (from TIN/PO4 ratio) mucilage event frequency increases.
The model also reveals that salinity and temperature are responsible for the changes of the TIN/PO4 ratio and gives an insight on their threshold values which lead to high values of this ratio, further
related to mucilage events.

Ključne riječi

TIN/PO4 ratio; mucilage events; machine learning; regression trees; northern Adriatic

Hrčak ID:

152249

URI

https://hrcak.srce.hr/152249

Datum izdavanja:

15.12.2015.

Podaci na drugim jezicima: hrvatski

Posjeta: 1.066 *