A new improved study of cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain) using the MARS technique

• Published in: The Science of the total environment Vol. 430; pp. 88 - 92
• Main Authors: García Nieto, P.J., Alonso Fernández, J.R., Sánchez Lasheras, F., de Cos Juez, F.J., Díaz Muñiz, C.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 15.07.2012; Elsevier
• Subjects: analysis; Analysis methods; Applied sciences; Approximation; Bacterial Toxins; Bacterial Toxins - analysis; chemistry; Continental surface waters; Cyanobacteria; Cyanobacteria - chemistry; Cyanobacteria - growth & development; cyanobacterial toxins; Cyanotoxins; drinking water; Environmental Monitoring; Exact sciences and technology; growth & development; Lakes; Lakes - analysis; Lakes - chemistry; Lakes - microbiology; Mathematical analysis; Mathematical models; microbiology; Multivariate adaptive regression splines (MARS); Multivariate Analysis; Natural water pollution; Phytoplankton; Phytoplankton - chemistry; Phytoplankton - growth & development; Pollution; Regression; Regression Analysis; Reservoirs; risk; Seasons; Spain; Splines; Statistical learning techniques; Water treatment and pollution; water use; Europe; Spain; Spain, Asturias; Statistical learning techniques; Multivariate adaptive regression splines (MARS); Cyanobacteria; Cyanotoxins; Microcystin; Multivariate adaptive regression splines; Multiple regression; Toxin; Microbial origin; Regression model; Aminoacid; Artificial lake; Statistical model; MARS; Surface water; Bacteria; Water pollution; Hepatotoxicity; Splines (mathematics); Organic compounds; Concentration distribution
• ISSN: 0048-9697; 1879-1026; 1879-1026
• DOI: 10.1016/j.scitotenv.2012.04.068

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational water uses. The aim of this study is to improve our previous and successful work about cyanotoxins prediction from some experimental cyanobacteria concentrations in the Trasona reservoir (Asturias, Northern Spain) using the multivariate adaptive regression splines (MARS) technique at a local scale. In fact, this new improvement consists of using not only biological variables, but also the physical–chemical ones. As a result, the coefficient of determination has improved from 0.84 to 0.94, that is to say, more accurate predictive calculations and a better approximation to the real problem were obtained. Finally the agreement of the MARS model with experimental data confirmed the good performance. ► An improved MARS model is built as a predictive model of cyanotoxins presence. ► Cyanobacterial HABs are dangerous for environment and people in fresh waters. ► Biological and physical–chemical variables in this process are studied in depth.