A sub-surface forest fire is a type of smoldering combustion with a slower spread rate, longer combustion time, and lower combustion temperature compared with flame combustion. Sub-surface fires are usually accompanied by surface fires, and the surface fires’ conversion from sub-surface fires has great uncertainty. Therefore, there are considerable difficulties in monitoring and fighting sub-surface fires. However, there are few studies on the conversion from sub-surface fires to surface fires, and the mechanism and influencing factors of the conversion remain unclear. This study focuses on Larix gmelinii forests, which are representative of the boreal forest of China and hot spots of sub-surface fires, studies the moisture content limit of sub-surface fires’ conversion to surface fires by simulating a smoldering experiment, and establishes a monitoring model of sub-surface fires and an occurrence probability prediction model of sub-surface fires’ conversion to surface fires. The results showed that the moisture content limit of the conversion was 25% in the grass–Larix gmelinii forest and Ledum palustre–Larix gmelinii forest and 20% in Rhododendron dauricum–Larix gmelinii forest. There was a significant positive correlation between the time and temperature caused by the smoldering. The monitoring model of the sub-surface fires based on the surface temperature and moisture content had a good fitting effect (p < 0.01). The occurrence probability prediction model of the sub-surface fires’ conversion to surface fires, based on a logistic regression model, had high prediction accuracy (AUC = 0.987). The lower the moisture content of the humus, the closer the smoldering came to the surface and the higher the probability of conversion. This research could contribute to the study of the mechanism of sub-surface fires’ conversion into surface fires.

A sub-surface forest fire is a kind of fire that spreads slowly with no flames and lower temperatures, and threatens the ecosystem and human life. The moisture content of humus is considered to be an important factor in determining fire occurrence and sustaining. The humus of the Larix gmelinii in the Daxing’an Mountains was selected for the experiment, the limit moisture content condition of sub-surface forest fires was determined by an experiment simulating smoldering, and the prediction model of the probability of sub-surface forest fire occurrence was established. The results will be of great significance for the prevention, monitoring, and fighting of sub-surface forest fires in the boreal forest. The results showed that when the moisture content of humus in the upper layer was low, the smoldering process could be self-sustaining at 20%. For deeper layers of a depth of 18 cm, this increased to 30% moisture content of the humus and was the critical depth for sub-surface fires. The moisture content of 40% was a limit to burning where smoldering can only last for a short duration and is then extinguished. When the moisture content of the humus was 20%, the smoldering temperature was higher and the rate of spread was faster, with smoldering being maintained for longer periods at 30% moisture content. The regression prediction model of the highest temperature and vertical rate of spread in a column of humus was correlated to moisture content and depth, and the model significance was good at p < 0.01. Based on moisture content and depth, the occurrence probability prediction model of sub-surface fires has a good correlation (R² = 0.93) and high prediction accuracy (AUC = 0.995). The effect of moisture content (Or = 4.008) on the occurrence probability of sub-surface fires is higher than that of depth (Or = 2.948). The results point out that it is necessary to prevent and monitor the occurrence of sub-surface fires when the humus moisture content is less than 40%. In order to reduce the risk of sub-surface fires, the monitoring time of the fire field should be extended after the fire is extinguished due to the slow-burning process of the sub-surface fire. Increasing the moisture content of the humus is an important method to reduce the probability and restrain the spread of sub-surface fires.

Smouldering combustion can emit a large amount of CO₂, CO and particulate matter (PM). Moisture content is an important factor of the emission characteristics. As the hot spot of forest smouldering combustion, the gas and particulate emissions of the Huzhong National Nature Reserve with different moisture contents are discussed herein. The emission factors (EF) of CO₂ and CO were 100.71 ± 39.14 g/kg and 11.76 ± 3.89 g/kg, respectively. The EF of PM_2.5, PM₄ and PM₁₀ were 87.11 ± 19.47 g/kg, 353.37 ±159.25 g/kg and 602.59 ± 276.80 g/kg, respectively. PM_2.5 accounted for 16.59 ± 5.25% of the PM, and PM₄ and PM₁₀ were 54.03 ± 13.46% and 91.00 ± 10.81%, respectively. There was no significant difference in the EF of CO₂ and CO with different moisture contents, nor in the EF of PM_2.5, but there was a significant difference in the EF of PM₄ and PM₁₀ with different moisture contents. In addition, the peak of CO₂ and CO appeared at 2~3 h; the peak of PM_2.5 lagged behind that of PM₄ and PM₁₀. According to the regression analysis, experimental expressions were obtained for the modified combustion efficiency (MCE) and the EF of PM.

In recent years, the influence of extreme weather patterns has led to an alarming increase in the frequency and severity of sub-surface forest fires in boreal forests. The Ledum palustre-Larix gmelinii forests of the Daxing’an Mountains of China have emerged as a hotspot for sub-surface fires, and terrain slope has been recognized as a pivotal factor shaping forest fire behavior. The present study was conducted to (1) study the effect of terrain slope on the smoldering temperature and spread rate using simulated smoldering experiments and (2) establish occurrence probability prediction model of the sub-surface fires’ smoldering with different slopes based on the random forest model. The results showed that all the temperatures with different slopes were high, and the highest temperature was 947.91 °C. The spread rates in the horizontal direction were higher than those in the vertical direction, and the difference increased as the slope increased. The influence of slope on the peak temperature was greater than that of spread rate. The peak temperature was extremely positively correlated with the slope, horizontal distance and vertical depth. The spread rate was extremely positively correlated with the slope. The spread rate in the vertical direction was strongly positively correlated with the depth, but was strongly negatively correlated with the horizontal distance; the horizontal spread rate was opposite. The prediction equations for smoldering peak temperature and spread rate were established based on slope, horizontal distance, and vertical depth, and the model had a good fit (p < 0.01). Using random forest model, we established the occurrence prediction models for different slopes based on horizontal distance, vertical depth, and combustion time. The models had a good fit (AUC > 0.9) and high prediction accuracy (accuracy > 80%). The study proved the effect of slope on the characteristics of sub-surface fire smoldering, explained the variation in peak temperature and spread rate between different slopes, and established the occurrence prediction model based on the random forest model. The selected models had a good fit, and prediction accuracy met the requirement of the sub-surface fire prediction.

Forests are affected by a wide range of disturbances globally, resulting in the decline or death of large areas of them. There is a lack of comparative studies on how soil properties change in forests that die under the influence of disturbances, especially considering different levels of disturbance. For this study, we took Larix olgensis—a major plantation forest species in northeast China—as the research object, one in which a large outbreak of bark beetle led to large-scale forest death, and set up fixed sample plots characterized by different disturbance intensities. We investigated the responses of soil physicochemical properties and microbial community compositions to different disturbance intensities through the determination of soil nutrient indices and high-throughput sequencing. The results show that there were significant differences (p < 0.05) in the effects of different disturbance intensities on soil physicochemical properties, where the soil moisture content, total nitrogen, total carbon, and total phosphorus in the control group were significantly higher than those in the disturbed groups. The soil pH was highest under low-intensity disturbance and the soil total potassium content was highest under high-intensity disturbance. At different disturbance intensities, the highest soil moisture content was found in the high-intensity group. Proteobacteria, Actinobacteria, Verrucomicrobia, Acidobacteria, Candidatus_Rokubacteria, Chloroflexi, Gemmatimonadetes, and Thaumarchaeota were the dominant populations with higher abundances; meanwhile, the relative abundance of Bacteroidetes, Tenericutes, and a tentatively unclassified fungus differed significantly (p < 0.05) across disturbance intensities. Among the dominant microbial populations, Acidobacteria showed a significant negative correlation with soil pH and a significant positive correlation with total potassium content, Thaumarchaeota showed significant positive correlations with soil moisture content and total nitrogen content, and Firmicutes and Gemmatimonadetes showed significant negative correlations with total carbon content in the soil. Furthermore, soil total nitrogen content was the key factor driving changes in microbial communities. The results of this study provide a scientific basis for the study of the long-term effects of tree mortality caused by insect pests on soil microbial communities and their response mechanisms, which is of great theoretical value for the establishment of scientific and effective methods for woodland restoration.

Forest sub-surface fires represent a challenging combustion phenomenon to control, and the process of smoldering is often overlooked in wildfire incidents. Traditional forest fire research has prioritized flaming combustion over smoldering dynamics, despite its critical risk factors including sustained high temperature and ground surface collapse that significantly endanger firefighter safety. This study focuses on The Daxing’an Mountains, a prime sub-surface fire-prone region in China, employing field investigations and controlled smoldering experiments to quantify the key risk factors for sub-surface fires suppression while elucidating moisture content’s regulatory effects. The results demonstrate that sub-surface smoldering fires maintain elevated temperatures with the surface peak temperature reaching 600.24 °C and sub-surface peak temperature up to 710.70 °C. The spread rate is relatively slow (maximum 27.00 cm/h), yet exhibits pronounced fluctuations along the vertical profile, creating a critical predisposition to overhanging collapse. The moisture content has extremely significant effects (p < 0.01) on key risk factors including surface temperature, sub-surface temperature, collapse time and ignition duration. Lower moisture content prompted earlier surface collapses, whereas higher moisture content displays delayed collapse but resulted in dangerously elevated temperatures at collapse points, presenting extreme suppression risks.