Spatial variation of earthworm communities in the motorway proximity

Abstract

Background. The spatial features of the structure of earthworm communities in the area of influence of motor vehicles were analyzed. Five species of lumbricides belonging to three families were found in the studied biocenosis located near the M06 Kyiv–Chop motorway (Ukraine): Aporrectodea caliginosa (Savigny, 1826), A. rosea (Savigny, 1826), A. trapezoidеs (Dugesi, 1828), Lumbricus terrestris (Linnaeus, 1758) and Dendrobaena octaedra (Savigny, 1826). Materials and Methods. Earthworms were collected during 2021–2022 in the biocenosis near the M06 Kyiv–Chop motorway (Berezyna village, Zhytomyr region). The material was collected by excavation and layer-by-layer analysis of soil samples. The thickness of each layer was 10 cm. The maximum depth – 0.5 m. Samples were taken every 10 m from the road to a distance of 210 m. The distance between the rows of samples along the road was 30 m. STATISTICA software package was used for statistical analysis of the data. Biodiversity assessments were calculated using the PAST software package. SAGA and Q-GIS software packages were used for spatial analysis and mapping of the data. Results and Discussion. The key factor that influences the structure of earthworm communities in the area of road transport impact is the distance from the source of impact. The maximum values of the dominance, Margalef and Berger–Parker indexes and the number of species are observed in areas near the motorway, while the values of the Shannon, Simpson, Menhinik and Brillouin indexes have the opposite trend. There is a correlation between the spatial variability of the structure of earthworm communities and the values of reflectance in the bands B3, B5, B11 of the Sentinel-2 satellite image. It allowed us to apply a geographically weighted regression algorithm with several predictors that indirectly reflect environmental parameters to the data. Conclusion. The results obtained show that the use of predictors allows us to obtain a more mosaic model of the distribution of indicator values compared to interpolation by kriging, which can be used to predict the values of earthworm biodiversity indicators within the study area.