War threatens 18 % of protective plantations in eastern agroforestry region of Ukraine

12 S.

e-journal

200212429

Forest Ecology and Management ; Jrg. 578 ; 122361 (2025) , 12 S.

The ongoing Russian invasion in Ukraine has significantly impacted the forest ecosystems at national scale, including the crucial agroforestry systems in the eastern part of country. This study focuses on estimating the damage caused to forest protective plantations in 2022–2023, with particular focus on the loss of cropland protection function derived by shelterbelts. We used a soil type map and damaged forest cover estimates to report the areas of expected post-war regeneration options by tree species, both native and alien. We applied satellite remote sensing data and raster patch analysis to semi-automatically classify a forest cover mask (as of 2021) on functional types: shelterbelts, urban forests, ravine protection, water protection, and roadside protective plantations. We revealed that 18 % of the protective plantations have been damaged as of 2023. Despite this extensive damage, the overall loss of cropland protection function across the study area was relatively modest, at 2.7 % as of 2023. However, localized hotspots exhibited losses up to 57 %, correlating with the proximity to main fights occurred in 2022–2023. We reported that the majority (81 %) of the damaged plantations are on fertile black earth soils, which favor the regeneration using a variety of native tree species. However, there are hitherto risks associated with the use of alien species, driven both by economic pressures and legislative ambiguities. Our study highlights the importance of satellite data analysis as a tool to report direct war impact on eastern agroforestry region of Ukraine. Simultaneously, we call for strategies to collect high-resolution data for spatial models’ calibration and validation. We emphasize the necessity to consider spatial analysis for planning post-war forest regeneration efforts.
Keywords: Shelterbelts, Windbreaks, Environmental damage, Forest degradation, Remote sensing