A History OF Forest Transformation IN THE Upper Kolva River Basin (The Northern Cis-Urals): From Slash-And-Burn Agriculture to Post-Industrial Demutation

Aim . Based on the analysis of unique archival forest management materials, to reconstruct the long-term (1850−2024) dynamics of forest cover in the inaccessible foothills of the Northern Urals, and to identify the stages and key factors of forest ecosystems transformation. Methodology . The study is based on the analysis of forest management materials from 1938, 1956, and 1994. After scanning, georeferencing, and manual digitisation of each forest subcompartment, all sites were classified by terrestrial ecosystem type. The type and date of disturbance (fire, logging, windthrow) were determined for each site. To update the data to 2024 and verify the results, forest management materials from 1981, satellite data, archival satellite imagery, and published geodata on windthrows were used. Results . Four stages of forest transformation were identified: pre-industrial (1850–1938) dominated by fires (affecting at least 37% of the territory) and selective logging; transitional (1938–1980) characterised by the absence of fires and logging with ongoing natural dynamics, including the catastrophic windthrow of 1975 that affected 41% of the study area; industrial (1980–2000) with a peak of anthropogenic and natural disturbances, including fires in windthrow areas (4.6% of the area) and clearcuts (2.9% of the area); post-industrial (2000–2024) with a complete cessation of logging and the absence of fires and windthrows. By 2024, the area of dark coniferous forests exceeded the 1956 level (+11%). The modern forest cover is a mosaic of communities: old burnt areas, clearcuts, windthrow areas, and agricultural lands are gradually re-vegetating. Only the remaining patches of undisturbed dark coniferous forests with Siberian stone pine are of commercial interest. Research implications . The results are important for assessing the long-term consequences of anthropogenic disturbances, primarily fires and logging of varying intensity, as well as determining the rate of forest recovery. The data obtained can be used to identify the most preserved forests that should be protected in the event of the resumption of active logging operations.