Comparative algological and bacteriological examinations on biofilms developed on different substrata in a shallow soda lake

Ács, Éva and Borsodi, Andrea K. and Kiss, Éva and Kiss, Keve Tihamér and Szabó, Katalin Éva and Vladár, P. and Várbíró, Gábor and Záray, Gyula (2008) Comparative algological and bacteriological examinations on biofilms developed on different substrata in a shallow soda lake. Aquatic Ecology, 42 (4). pp. 521-531. ISSN 1386-2588 (print), 1573-5125 (online)

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Abstract

According to the European Water Framework Directives, benthic diatoms of lakes are a tool for ecological status assessment. In this study, we followed an integrative sample analysis approach, in order to find an appropriate substratum for the water qualification-oriented biomonitoring of a shallow soda lake, Lake Velencei. Six types of substrata (five artificial and one natural), i.e., andesite, granite, polycarbonate, old reed stems, Plexiglass discs and green reed, were sampled in May and in November. We analysed total alga and diatom composition, chlorophyll a content of the periphyton, surface tension and roughness of the substrata and carbon source utilisation of microbial communities. Water quality index was calculated based on diatom composition. Moreover, using a novel statistical tool, a self-organising map, we related algal composition to substratum types. Biofilms on plastic substrates deviated to a great extent from the stone and reed substrata, with regard to the parameters measured, whereas the biofilms developing on reed and stone substrata were quite similar. We conclude that for water quality monitoring purposes, sampling from green reed during springtime is not recommended, since this is the colonization time of periphyton on the newly growing reed, but it may be appropriate from the second half of the vegetation period. Stone and artificially placed old reed substrata may be appropriate for biomonitoring of shallow soda lakes in both spring and autumn since they showed in both seasons similar results regarding all measured features.

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