Modeling of Spatial Distribution of Alien Species of Plants Using Remote Sensing Data on the Example of Paulownia tomentosa

Abstract

Purpose: The purpose of the work is to conduct a comparative analysis of the use of remote sensing data, as well as bioclimatic and ecological-geographical data for modeling the spatial distribution of alien species, using the example of the Paulownia tomentosa species. Methods: The modeling was performed by the SAHM software using the maximum entropy method. During analysis, we used Worldclim bioclimatic rasters, exposure, elevation, slope, built-up area, net primary productivity, topographic humidity index, the remoteness of spatial points from settlements, roads, and rivers, as well as Landsat 5 satellite images. Results: We found that the most effective predictors of the spatial distribution of paulownia are altitude, topographic humidity index, spatial location of the river network, annual precipitation, maximum temperature of the warmest month of the year, average temperature of the driest quarter of the year, precipitation in the wet quarter of the year as well as a Landsat 5 satellite image taken in May. Conclusions: The complex of spatial data used made it possible to identify the places most suitable for growing paulownia, which is mainly located in mountain river valleys at altitudes from 20 to 240 meters above sea level. The total area of the territory of Greater Sochi, the most suitable for the growth of paulownia is 208 sq. Km. (5.9 %). Climate change (scenarios: RCP2.6, RCP4.5, RCP6.0) will contribute to the further spread of Paulownia tomentosa. The most extreme climate change scenario (RCP8.5) will reduce the spread of Paulownia tomentosa.