The problem of a shortage of time series of phytoproducts is currently partially addressed by calculating vegetation indices, which provide a multi-temporal, spatially continuous picture of phytoproduction process variation. Using the Burtinskaya Steppe site of the Orenburgsky State Nature Reserve as an example, a functional portrait of the spatiotemporal variability of the phytoproduction process was compiled using a series of 51 Landsat satellite images for the 2010–2020 warm period. A formalized classification was implemented based on a set of vegetation indices, moisture, and reflectivity (albedo) of the vegetation cover. Field verification and determination of syntaxonomic rank of the identified phytocenosis classes were carried out. A geomorphological characterization of the ecological niches of phytocenosis classes was compiled. Characteristic types of annual cycles of green phytomass, transpiration, and temperature for phytocenosis classes, as well as the frequency of deviations from the background functioning mode, were found. Differences in the annual course of phytoproduction depend on the degree of topography concavity and the catchment area, an increase in which facilitates the accumulation of snow moisture, reduces its rate of consumption during the warm period, and prolongs the active growing season. The annual transpiration’ course and surface temperature is more similar across different classes of phytocenoses than the annual course of green phytomass. Classifying phytocenoses by the annual course of phytoproduction allows us to identify zones of influence of positional factors that cause intra-tract differentiation and to clarify the taxonomic affiliation of phytocenoses and landscape boundaries. The ratio of xerophilic and mesophilic species indicates the duration of soil moisture conservation and the phytomass’ annual course.
Ashikhmin et al. (Mon,) studied this question.