Changes in Diversity of Silica-Scaled Chrysophytes during Lake–River–Reservoir Transition (Baikal–Angara–Irkutsk Reservoir)

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Abstract

Hydroelectric dams create new ecosystems such as reservoirs. Several hydroelectric dams forming shallow reservoirs were built on the Angara River flowing out of Lake Baikal. The first of them in downstream Angara is Irkutsk Reservoir, with several shallow bays. Since silica-scaled chrysophytes are effective bioindicators for aquatic ecosystems, this paper aimed to determine their distribution, taxonomic structure and species richness in South Baikal and Irkutsk Reservoir, which have different environmental parameters. Thirty-one species were found using scanning and transmission electron microscopy. Only seven of them inhabited South Baikal in June 2023 at 3.66–4.51 °C and pH 7.80–8.24, with Chrysosphaerella baicalensis, Spiniferomonas trioralis f. cuspidata and Mallomonas alpina being prevalent. Only one species (M. alpina) was dominant in Irkutsk Reservoir at all stations at a water temperature of 5.33–11.55 °C and pH 8.10–8.52, alongside three other abundant species, Synura cf. glabra, Mallomonas acaroides and M. crassisquama. The maximum number of species (23) was found in a shallow bay of the reservoir at maximal values of temperature (11.5 °C) and pH (8.57) and minimal values of phosphate and nitrate concentrations during the study. The enrichment of Irkutsk Reservoir in species of silica-scaled chrysophytes was due both to cosmopolitan widespread and polyzonal species as well as to rare boreal, arctic–boreal, and unknown, possibly new species.

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Ecologically meaningful transformations for ordination of species data

Pierre Legendre, Eugene Gallagher (2001)

This paper examines how to obtain species biplots in unconstrained or constrained ordination without resorting to the Euclidean distance [used in principal-component analysis (PCA) and redundancy analysis (RDA)] or the chi-square distance [preserved in correspondence analysis (CA) and canonical correspondence analysis (CCA)] which are not always appropriate for the analysis of community composition data. To achieve this goal, transformations are proposed for species data tables. They allow ecologists to use ordination methods such as PCA and RDA, which are Euclidean-based, for the analysis of community data, while circumventing the problems associated with the Euclidean distance, and avoiding CA and CCA which present problems of their own in some cases. This allows the use of the original (transformed) species data in RDA carried out to test for relationships with explanatory variables (i.e. environmental variables, or factors of a multifactorial analysis-of-variance model); ecologists can then draw biplots displaying the relationships of the species to the explanatory variables. Another application allows the use of species data in other methods of multivariate data analysis which optimize a least-squares loss function; an example is K-means partitioning.