Using cilioplankton as an indicator of the ecological condition of aquatic ecosystems

Abstract

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. We assess the quality of surface water in water bodies located in the Middle Volga region (Russian Federation). The water quality is assessed using 19 chemical compounds and cilioplankton indicators, such as the total number of species, the abundance of each species, and, based on both of them, the saprobity index and the Shannon-Weaver diversity index (H). We classify the water quality from polluted to extremely dirty by using abiotic indicators, and from conditionally clean to dirty by means of biotic indicators. Using the logistic regression method, we are able to predict the water quality (clean or dirty) in correspondence with the species diversity index (H) and to clarify how the quality of the water is related to its physicochemical properties. The seven most significant chemical predictors of both natural origin (mineralization, hydro carbonates, and chlorides) and natural-anthropogenic origin (organic substances (according to BOD5), nitrates, total petroleum hydrocarbons, iron), identified during the stepwise selection procedure, have a substantial influence on the outcome of the model. Qualitative and quantitative indicators of development of ciliates, as well as indices calculated on their basis, allow assessing with a very high level of accuracy the water quality and the condition of aquatic ecosystems in general. The Shannon index calculated for the number of ciliates can be successfully used for ranking water bodies as “clean/dirty”.