The vast Angara region, with an area of 13.8 million ha, is located in the southern taiga of central Siberia, Russia. This is one of the most disturbed regions by both fire and logging in northern Asia. We have developed surface and ground fuel-load maps by integrating satellite and ground-based data with respect to the forest-growing conditions and the disturbance of the territory by anthropogenic and natural factors (fires and logging). We found that from 2001 to 2020, fuel loads increased by 8% in the study region, mainly due to a large amount of down woody debris at clearcuts and burned sites. The expansion of the disturbed areas in the Angara region resulted in an increase in natural fire hazards in spring and summer. Annual carbon emissions from fires varied from 0.06 to 6.18 Mt, with summer emissions accounting for more than 95% in extreme fire years and 31–68% in the years of low fire activity. While the trend in the increase in annual carbon emissions from fires is not statistically significant due to its high interannual variability and a large disturbance of the study area, there are significantly increasing trends in mean carbon emissions from fires per unit area (p < 0.005) and decadal means (p < 0.1). In addition, we found significant trends in the increase in emissions released by severe fires (p < 0.005) and by fires in wetter, dark, coniferous (spruce, p < 0.005 and Siberian pine, p < 0.025) forests. This indicates deeper burning and loss of legacy carbon that impacts on the carbon cycle resulting in climate feedback.

In this study, we have analyzed tree stand disturbance by hthe Siberian Silk Moth (Dendrolimus sibiricus Tschetverikov (Lepidoptera: Lasiocampidae)) in Central Siberia (Krasnoyarsk region, Russia) in 2015–2020. We considered two plots that experienced silk moth outbreaks in 2015–2018 and 2018–2020 and used satellite data (Terra/MODIS, Landsat/ETM/OLI), field forest inventory data, a meteorological data set, and a vegetation cover vector layer. Silk moth-disturbed areas were classified using NDVI, which was calculated for each 15-day period during the growing season (April–September). We obtained formalized descriptions of the temporal dynamics of the disturbed area. Next, we classified the degree of disturbance of the forest stand after the impact of the silk moth by the threshold method according to the ranges of NDVI anomalies. Based on the generalized data from the forest inventory, we performed a correlation analysis of the relationship between the main characteristics of forests and the classes of disturbance. Finally, using a series of regression equations, we described a procedure for predicting the degree of impact on the stand during the time of silk moth outbreaks in the dark-needle coniferous stands of Central Siberia.

In this study, we have analyzed the spatial dynamics of the forests disturbed by Siberian Silk Moth (Dendrolimus sibiricus Tschetverikov (Lepidoptera: Lasiocampidae)) in Central Siberia and obtained model equations that fit these dynamics. We considered three sites that experienced silk moth outbreaks in 1993–1996, 2015–2018, and 2018–2020 and used satellite data (NOAA/AVHRR, Terra/MODIS, Landsat/ETM/OLI), field data, a digital elevation model, and maps of predominant forests. Silk moth-disturbed areas were classified using NDVI, which was calculated for each 15-day period during the growing season (April–September). Time series of disturbed forest areas were obtained for three sites located in the Krasnoyarsk region (Central Siberia, Russia). Total damaged areas for these sites were 41, 430, and 470 thousand hectares. We obtained formalized descriptions for the temporal dynamics of the disturbed area.