Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

• Type: Article in International Scientific Journal
• Date: 2014

Authors

Ana I. Gomes (Author) Other; José C. M. Pires (Author) FEUP; Sónia A. Figueiredo (Author) Other; Rui A. R. Boaventura (Author) FEUP

Journal

Title: ENVIRONMENTAL TECHNOLOGY

Vol. 35 No. 8

Pages: 945-955

ISSN: 0959-3330

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 6 Citations

Scopus - 5 Citations

Scientific classification

CORDIS: Natural sciences > Environmental science

FOS: Engineering and technology > Environmental engineering

Associated Projects

UI0511 - PROJECTO ESTRATÉGICO - UI 511 - 2013-2014

Other information

Authenticus ID: P-009-33G

DOI: 10.1080/09593330.2013.856956

Abstract (EN): The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response. With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leca river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leca River.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11