Assessment of Natural Plant Communities through the Use of Remote Sensing Data of the Stavropol Territory Steppes

Abstract

Introduction. The relevance of the study of steppe phytocenoses is caused by the unsatisfactory state of natural grass stands, namely a low level of biodiversity and a high degree of degradation. The aim of the work is to determine the features of the connection of the Earth remote sensing data with the state and degree of degradation of natural grass stands in unstable moistening zone and arid zone of the Stavropol Territory. The Earth remote sensing data with certain temporal and spatial resolutions make it possible to carry out almost continuous monitoring of the state of natural grass stands. Materials and Methods. The study of steppe phytocenoses was carried out in 2016–2020 on the ground at discount areas (100 m2) according to the requirements of methods generally accepted in phytocenology. Vegetation condition was assessed using the Earth remote sensing data based on the values of the Normalized Difference Vegetation Index. According to the satellite data, Normalized Difference Vegetation Index cartograms were constructed for each point of the study. Results. The proportion of polygons with a high degree of degradation is 18.8% of research objects located in the zone of unstable moistening and the proportion of polygons with an average degree of degradation is 37.5%, while in the arid zone 70.6 and 23.5%, respectively. In the zone of unstable moistening, the highest coefficients of rank correlation between the degradation degree and the area occupied by herbaceous vegetation with a certain value of the vegetation index are observed in the case if Normalized Difference Vegetation Index is in the range of 0.0–0.4, and in the arid zone 0.0–0.3 (at 0.01 significance level). Discussion and Conclusion. When using the Earth remote sensing data to assess the degree of degradation of steppe ecosystems of the Stavropol Territory, it is necessary to use regression models specific to various soil and climatic conditions.

Keywords

• biodiversity
• vegetation index
• degradation
• remote sensing data
• arid zone
• cartogram
• plant communities