This study analyzes the forest flammability hazard in the south of Tyumen Oblast (Western Siberia, Russia) and identifies variation patterns in fire areas depending on weather and climate characteristics in 2008-2023. Using correlation analysis, we proved that the area of forest fires is primarily affected by maximum temperature, relative air humidity, and the amount of precipitation, as well as by global climate change associated with an increase in carbon dioxide in the atmosphere and the maximum height of snow cover. As a rule, a year before the period of severe forest fires in the south of Tyumen Oblast, the height of snow cover is insignificant, which leads to insufficient soil moisture in the following spring, less or no time for the vegetation to enter the vegetative phase, and the forest leaf floor remaining dry and easily flammable, which contributes to an increase in the fire area. According to the estimates of the CMIP6 project climate models under the SSP2-4.5 scenario, by the end of the 21st century, a gradual increase in the number of summer temperatures above 35 degrees C is expected, whereas the extreme SSP5-8.5 scenario forecasts the tripling in the number of such hot days. The forecast shows an increase of fire hazardous conditions in the south of Tyumen Oblast by the late 21st century, which should be taken into account in the territory's economic development.

Substituting alternative materials and energy sources with forest biomass can cause significant environmental consequences, such as alteration in the released emissions which can be described by displacement factors (DFs). Until now, DFs of wood-based materials have included greenhouse gas (GHG) emissions and have been associated with lower fossil and process-based emissions than non-wood counterparts. In addition to GHGs, aerosols released in combustion processes, for example, alter radiative forcing in the atmosphere and consequently have an influence on climate. In this study, the objective was to quantify the changes in the most important aerosol emission components for cases when wood-based materials and energy were used to replace the production of high-density polyethylene (HDPE) plastic, common fossil-based construction materials (concrete, steel and brick), non-wood textile materials and energy produced by fossil fuels and peat. For this reason, we expanded the DF calculations to include aerosol emissions of total suspended particles (TSP), respirable particulate matter (PM10), fine particles (PM2.5), black carbon (BC), nitrogen oxides (NOx), sulphur dioxide (SO2) and non-methane volatile organic compounds (NMVOCs) based on the embodied energies of materials and energy sources. The DFs for cardboard implied a decrease in BC, SO2 and NMVOC emissions but an increase in the other emission components. DFs for sawn wood mainly indicated higher emissions of both particles and gaseous emissions compared to non-wood counterparts. DFs for wood-based textiles demonstrated increased particle emissions and reduced gaseous emissions. DFs for energy biomass mainly implied an increase in emissions, especially if biomass was combusted in small-scale appliances. Our main conclusion highlights the critical need to thoroughly assess how using forest biomass affects aerosol emissions. This improved understanding of the aerosol emissions of the forestry sector is crucial for a comprehensive evaluation of the climate and health implications associated with forest biomass use.

From the beginning of May 2023 to the end of August 2023, the Northern Hemisphere experienced significant wildfire activity with the most widespread fires occurring in Canada. Forest fires in Canada destroyed more than 15.6 million hectares of forests. These wildfires worsened air quality across the region and other parts of the world. The smoke reached southern Europe by the end of June 2023. To better understand the consequences of such forest fires far from the site of origin, aerosol optical, microphysical and radiative properties were analyzed during this event for southern Europe using data from the Visible Infrared Imaging Radiometer Suite (VIIRS), TROPOspheric Monitoring Instrument (TROPOMI), and Aerosol Robotic Network (AERONET). TROPOMI aerosol index (AI) and the carbon monoxide (CO) product confirm that the smoke originated directly from these forest fires. AERONET data from the El Arenosillo site in southern Spain showed maximum aerosol optical depth (AOD) values on June 27 reached 2.36. Data on Angstrom Exponent (AE), aerosol volume size distribution (VSD), single scattering albedo (SSA), fine mode fraction (FMF), volume particle concentration, effective radius (R Eff ), absorption AOD (AAOD), extinction AE (EAE) and absorption AE (AAE) showed that fine-mode particles with carbonaceous aerosols contribution predominated in the atmosphere above the El Arenosillo site. Direct aerosol radiative forcing (DARF) at the top (DARF TOA ) and bottom of atmosphere (DARF BOA ) were-103.1 and-198.93 Wm-2 , respectively. The atmospheric aerosol radiative forcing (DARF ATM ) was found to be 95.83 Wm-2 and with a heating rate 2.69 K day-1 , which indicates the resulting warming of the atmosphere.

Due to climate change, human activities and natural disturbances in high-latitude permafrost and seasonally frozen areas are gradually increasing, attracting more attention from scholars. However, research primarily focuses on soil biology and chemistry in these regions, with limited exploration of their mechanical properties, especially compression properties. This study aims to evaluate the effects of gravel content and freeze-thaw (F-T) cycles on the compression properties of coarse-grained layered forest soil from northeast China's seasonally frozen regions, with the goal of predicting the soil's compressive changes under heavy mechanical loads. Specifically, using uniaxial confined compression tests (UCCT) on 252 disturbed soil samples (including two soil layers: AB and Bhs; hs ; six gravel contents; and seven F-T cycles), three characteristic compression coefficients-precompression stress (6pc), compression index (Cc),and swelling index (Cs)-were s )-were measured. Additionally, scanning electron microscopy (SEM) was used to analyze the mesostructure evolution of coarse-grained gravel-bearing soil. Volume changes of samples were measured after 15F-T cycles with varying gravel contents. Results indicate non-linear effects of gravel content and F-T cycles on 6pc. pc . Gravel content below 50% positively influences 6 pc , while content above 50% increases soil pore content, decreasing 6 pc . Cc c and Cs s exhibit an approximately negative correlation with gravel content and initially increase followed by a decrease with more F-T cycles. Moreover, the 6pcand pc and Ccof c of the AB layer are higher than those in the B hs layer, likely due to differences in clay and organic carbon contents. Notably, the observed trends differ from previous studies on other soil types such as farmland and paddy fields. This study fills a gap in understanding the compression characteristics of layered gravel-bearing forest soil in seasonally frozen regions, providing valuable insights for evaluating soil compression in both seasonally frozen and permafrost regions, and understanding mechanical vehicle- soil interactions. It also lays the theoretical groundwork and provides data support for constructing compression models of layered gravel-bearing forest soil.

Extreme weather events are increasingly recognized as major stress factors for forest ecosystems, causing both immediate and long-term effects. This study focuses on the impacts experienced by the forests of Valdisotto, Valfurva, and Sondalo (28% of the total area is covered by forests) in Upper Valtellina (Italy) due to the Vaia storm that occurred in October 2018. To define the immediate impacts of Vaia, we assess the economic value of forest ecosystem services (ESs), particularly those provided by timber production and carbon sequestration, pre- and post-Vaia and during the emergency period. We used the market price method to assess the economic values of timber production and carbon sequestration, as these are considered to be marketable goods. Based on data processed from Sentinel-2 satellite images (with a spatial resolution of 10 m), our results show that, despite the reduction in forest area (-2.02%) and timber stock (-2.38%), the economic value of the timber production increased after Vaia due to higher timber prices (i.e., from a total of 124.97 million to 130.72 million). However, considering the whole emergency period (2019-2020), the total losses are equal to 5.10 million for Valdisotto, 0.32 million for Valfurva, and 0.43 million for Sondalo. Instead, an economic loss of 2.88% is experienced for carbon sequestration, with Valdisotto being the more affected municipality (-4.48% of the pre-Vaia economic value). In terms of long-term impacts, we discuss the enhanced impacts due to the spread of the bark beetle Ips typopgraphus.

Water temperature extremes can pose serious threats to the aquatic ecosystems of mountain rivers. These rivers are influenced by snow and glaciermelt, which change with climate. As a result, the frequency and severity of water temperature extremes may change. While previous studies have documented changes in non-extreme water temperature, it is yet unclear how extreme water temperatures change in a warming climate and how their hydro-meteorological drivers differ from those of non-extremes. This study aims to assess temporal changes and spatial variability in water temperature extremes and enhance our understanding of the driving processes across European mountain rivers in the current climate, at both a regional and continental scale. First, we describe the characteristics of extreme events and explore their relationships with catchment characteristics. Second, we assess trends in water temperature extremes and compare them with trends in mean water temperature. Third, we use random forest models to identify the main driving processes of water temperature extremes. Last, we conduct a co-occurrence analysis to examine the relationship between water temperature extremes and hydro-climatic extremes. Our results show that mean water temperature has increased by +0.38 +/- 0.14 ${+}0.38\pm 0.14$degrees C per decade, leading to more extreme events at high elevations in spring and summer. While non-extreme water temperatures are mainly driven by air temperature, water temperature extremes are also importantly influenced by soil moisture, baseflow, and meltwater. Our study highlights the complexity of water temperature dynamics in mountain rivers at the regional and continental scale, especially during water temperature extremes.

Current permafrost models in Canadian boreal forests are generally of low spatial resolution as they cover regional or continental scales. This study aims to understand the viability of creating a temperature at the top of permafrost (TTOP) model on a local scale in the boreal wetland environment of What & igrave;, Northwest Territories from short-term field-collected temperature data. The model utilizes independent variables of vegetation, topographic position index, and elevation, with the dependent variables being ground surface temperature collected from 60 ground temperature nodes and 1.5 m air temperature collected from 10 temperature stations. In doing this, the study investigates the relationship vegetation and disturbance have on ground temperature and permafrost distribution. The model predicts that 31% of the ground is underlain by permafrost, based on a mean annual temperature at TTOP of <0 degrees C. This model shows an accuracy of 62.5% when compared to cryotic assessment sites (CAS). Most inaccuracies, showing the limitations of the TTOP model, came from peat plateaus that had been burned in the most recent forest fire in 2014. These resulted in out-of-equilibrium permafrost and climatic conditions that TTOP cannot handle well. Commonly, permafrost mapping places What & igrave; in the extensive discontinuous zone, estimating that between 50% and 90% of the ground is underlain by permafrost. The study shows that a climatically driven TTOP model calibrated with CAS can be used to illustrate ground temperature heterogeneity from short-term data in boreal forest wetland environments. However, this approach likely underestimates permafrost extent and is perhaps not the best-suited modelling choice for nearsurface permafrost, which is currently out of equilibrium with the current climate.

Wildfire strongly influences permafrost environment and soil organic carbon (SOC) pool. In this study, we reviewed the effects of fire severity, time after a fire, and frequency on SOC in boreal permafrost regions. This review highlighted several key points: the effect of wildfires on SOC increased with an increase of fire severity, and the amount of vegetation returned and surface organic matter replenished was less in a short term, which resulted in a significantly lower SOC content compared to that of before the fire. Within a short period after fire, the SOC in near-surface permafrost and the active layer decreased significantly due to the loss of above ground biomass, permafrost thaw, and increased microbial decomposition; as the years pass after a fire, the SOC gradually accumulates due to the contributions of litter layer accumulation and rooting systems from different stages of succession. The increase in fire frequency accelerated permafrost thawing and the formation of thermokarst, resulting in the rapid release of a large amount of soil carbon and reduced SOC storage. Therefore, the study on the effects of wildfires on SOC in the boreal permafrost region is of great significance to understanding and quantifying the carbon balance of the ecosystem.

Recently, as global climate change and local disturbances such as wildfires continue, long- and short-term changes in the high-latitude vegetation systems have been observed in various studies. Although remote sensing technology using optical satellites has been widely used in understanding vegetation dynamics in high-latitude areas, there has been limited understanding of various landscape changes at different spatiotemporal scales, their mutual relationships, and overall long-term landscape changes. The objective of this study is to devise a change monitoring strategy that can effectively observe landscape changes at different spatiotemporal scales in the boreal ecosystems from temporally sparse time series remote sensing data. We presented a new post-classification-based change analysis scheme and applied it to time series Landsat data for the central Yakutian study area. Spectral variability between time series data has been a major problem in the analysis of changes that make it difficult to distinguish long- and short-term land cover changes from seasonal growth activities. To address this issue effectively, two ideas in the time series classification, such as the stepwise classification and the lateral stacking strategies were implemented in the classification process. The proposed classification results showed consistently higher overall accuracies of more than 90% obtained in all classes throughout the study period. The temporal classification results revealed the distinct spatial and temporal patterns of the land cover changes in central Yakutia. The spatiotemporal distribution of the short-term class illustrated that the ecosystem disturbance caused by fire could be affected by local thermal and hydrological conditions of the active layer as well as climatic conditions. On the other hand, the long-term class changes revealed land cover trajectories that could not be explained by monotonic increase or decrease. To characterize the long-term land cover change patterns, we applied a piecewise linear model with two line segments to areal class changes. During the former half of the study period, which corresponds to the 2000s, the areal expansion of lakes on the eastern Lena River terrace was the dominant feature of the land cover change. On the other hand, the land cover changes in the latter half of the study period, which corresponds to the 2010s, exhibited that lake area decreased, particularly in the thermokarst lowlands close to the Lena and Aldan rivers. In this area, significant forest decline can also be identified during the 2010s.

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought-induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi-day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short-term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called tree water deficit to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causality Soil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi-days) Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit