Effects of fires on vascular plant and microalgae communities of steppe ecosystems

  • V. V. Shcherbyna Dmytro Motornyi Tavria State Agrotechnological University
  • I. A. Maltseva Bogdan Khmelnitsky Melitopol State Pedagogical University
  • H. V. Maltseva Bogdan Khmelnitsky Melitopol State Pedagogical University
  • O. V. Zhukov Bogdan Khmelnitsky Melitopol State Pedagogical University
Keywords: grass height and projected area; abundance and biomass of microalgae and cyanobacteria; bioindication.


The article is focused on a hypothesis verification: the higher plants, microalgae and cyanobacteria may be used in bioindication of steppe ecosystem restoration dynamics after fires. On the territory of the Askania Nova biosphere reserve (Ukraine) 4 stationary polygons were investigated: SP1 – steppe area which had not been exposed to fire for 20 years preceding our study, as well as areas where single fires occurred in 2001 (SP2), 2005 (SP3), and a site where fires occurred in 2001 and 2004 (SP4). The investigation revealed the dynamics of height and projected area of the higher vegetation according to seasons during two years (2010 and 2011), as well as abundance and biomass of microalgae and cyanoprokaryotes in the soil layer by the layer of the depth to 15 cm. It was found that the effects of pyrogenic load remain evident for several years after the fires, manifesting in decrease of the height and projected area of herbage, the number and biomass of algae and cyanobacteria in the soil, especially to the depth of 5 cm. Multivariate general linear models were used to test the significance of the dependence of quantitative characteristics of vegetation, microalgae, and cyanoprokaryotes on environmental predictors (season, year, soil layer, and fire). In the model, 75.2% of the grass height variability and 91.6% of the grass projected area variability could be explained by the predictors under consideration. In the series SP1 → SP2 → SP3 → SP4 the grass height and projected area decreased. The differences in the projected area of the grass stand were most evident in spring. The model explained 89.1% of the variation in abundance and 91.6% of the variation in biomass of Bacillariophyceae. The abundance of Bacillariophyceae was greater in the upper soil layer than in the lower layer and decreased with depth. The abundance of this group of algae decreased in the series SP1 → SP2 → SP3 → SP4 at depths of 0–5 and 5–10 cm. Changes in abundances of Chlorophyta, Streptophyta, Heterokontophyta (Xanthophyceae and Eustigmatophyceae) equaling 47.6% could also be explained by the model. The abundance of this group of algae was greatest in the upper soil layer. In the upper soil layer, the maximum abundance of Chlorophyta, Streptophyta, and Heterokontophyta (Xanthophyceae and Eustigmatophyceae) was recorded for Polygon SP1 and the minimum for Polygon SP3. Within the model, 48.0% of the variation in biomass of Chlorophyta, Streptophyta, and Heterokontophyta (Xanthophyceae and Eustigmatophyceae) was explained by the environmental predictors. The biomass trend was coherent with the population trend. A special feature was that there was a significant increase in biomass at 10–15 cm depth at Polygon SP3 compared to other polygons at this depth. The model was able to explain 61.8% of the variation in abundance and 66.7% of the variation in cyanobacteria biomass. The highest abundance of cyanobacteria was found in the upper soil layer of polygon SP1. Somewhat lower numbers of cyanobacteria were at polygons SP2 and SP4, and the lowest were found in the upper soil layer at polygon SP3. In turn, the highest number of cyanobacteria was found particularly at this polygon in the 5–10 cm layer. The biomass in the 0–5 cm layer was coherent with the abundance pattern of this group. The research results confirmed that the quantitative characteristics of the higher vegetation (height and projected area) as well as of microalgae and cyanobacteria (abundance and biomass) may be used in bioindication of the dynamics of post-pyrogenic processes in steppe ecosystems.


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