Influence of soil moisture regime on the species diversity and biomass of the herb layer of pine forests in the Ural Mountains

Abstract

Adaptation of plant communities is an important factor for maintaining their functioning and stability in changing conditions. The aim of our research is study of the effect of soil moisture regime on the species richness and biomass of the herb layer for old-growth coniferous forests in the Ural Mountains (Russia). The research has been carried out between 57° 00'N; 60° 15''E and 57° 05'N; 60° 25'E. The studied area is part of the Zauralsky hilly piedmont province, the Southern boreal forest region. Sample plots (0.25 hectares) were laid in pine forests growing in habitats with different moisture regimes: insufficient, optimal (stable), and excessive. The research was conducted in 2010.To determine the herb layer productivity, 10-20 subplots 1x1 m in size were laid on each sample plot. Data analysis is based on the One-way ANOVA and species abundance distributions. It has been established that species richness in extreme (insufficient and excessive soil moisture regime (Cowberry pine forest and Pine forest with shrubs and sphagnum) and optimal (stable) soil moisture regime (Multi-herb pine forest) were found to vary significantly, with soil moisture regime being a statistically significant factor. By contrast, herb layer biomass is maintained fairly stable regardless of the soil moisture regimes. ANOVA showed no significant differences between pine forests growing under different soil moisture regimes. It has been found that biomass is maintained by increasing of the dominant species contribution to the overall biomass and increasing of the approximation function graph slope. At the same time, the parameter β of exponential and power approximating functions is increased and can be considered as an indicator of influencing on forest ecosystems and a measure of their adaptation to insufficient and excessive soil moisture. Thus, species abundance distributions can be used as method to measure the effects of factors that determine forest ecosystem composition and functioning.