The survival probability of a tree exposed to surface fire varies widely depending on its bark. To advance the understanding of insulation properties of bark, mean thickness (BT), moisture content (MCb), surface structure (BS) and density (ρb) of bark samples of Mongolian oak (Quercus mongolica) (n = 395) for four diameter classes were investigated. In addition, data from 158 heating experiments simulating low-intensity surface fires in the laboratory were used to assess the relative importance of these properties affecting thermal insulation and evaluate the applicability of two stem heating models, an analytical, one-dimensional model and the FireStem2D model. Overall, BT is the best predictor of bark insulation capacity and MCb only contributes significantly to explain the residence time of cambial temperature >60°C (τ>60), whereas ρb and BS have minor effects. Although the two stem heating models overestimate the time required for cambium temperatures to reach 60°C (τ60), FireStem2D performed better than analytical model. Furthermore, FireStem2D provides good predictions of τ>60 and maximal cambial temperature (Tmax). In addition, errors in FireStem2D may be driven mainly by the errors in temperature measurement and the limitation of a two-dimensional model. The study provides a better knowledge of interactions between bark properties and heat transfer, which may improve the predictability of fire-caused stem injury for Mongolian oak and other species with similar bark properties.

Dendrolimus superans, a prominent forest pest in northeast China, exerts detrimental effects on tree growth and development, disrupts the ecological functioning of forests, and even alters the trajectory of succession. The objective of this study was to investigate the influence of habitat conditions on the occurrence probability and density of overwintering D. superans, aiming to provide scientific insights for the effective prevention of and control measures against this pest infestation. The investigation encompassed 142 plots (20 m × 20 m) in various forest types within the primary distribution area of D. superans in the Great Xing’ an Mountains, focusing on factors such as topography, forest vegetation, and larval density. Binary logistic regression was employed to establish models for predicting the occurrence probability of D. superans, while generalized linear models (GLMs) and categorical regression (CATREG) were utilized to develop models for estimating its population size. Subsequently, an evaluation was conducted to assess the performance of these models. The occurrence probability model showed high accuracy (AUC = 0.826) in predicting infestation. The slope aspect and herb cover were the key factors affecting the occurrence of D. superans. The occurrence probability was the lowest on shady slopes and the highest on sunny slopes. The occurrence probability of D. superans increased with the increase in herb cover. The model of quantification showed that the density of D. superans was the least on shady slopes and the highest on sunny slopes. As the slope gradient increased, the density decreased. D. superans occurred most frequently on ridges. Similarly, with the increase in canopy cover or the decrease in diameter at breast height (DBH) and stand density, the density of D. superans increased. The influence of the topography factors surpassed that of the forest vegetation factors in shaping the population dynamics of D. superans, despite both being significant contributors. The study revealed that D. superans is prone to occur on sunny slopes, flat slopes, and ridges, which should be the focus of prevention and control in forest management practices, such as replanting, thinning, and regular weeding, to help restrain the growth of the population of this pest.

The frequency of wildfires ignited by lightning is increasing due to global climate change. Since the forest ecological recovery is influenced by numerous factors, the process of post-fire vegetation recovery in Siberian dwarf pine shrublands remains unclear and demands in-depth study. This paper explored the short-term recovery process of vegetation after two lightning-ignited fires in the Great Xing’an Mountains that occurred in 2017 and 2020, respectively. The study was aimed at presenting a monitoring approach for estimating the post-fire vegetation state and assessing the influence of various driving factors on vegetation recovery. Spectral indices were computed to evaluate forest vegetation recovery dynamics. The differences in vegetation recovery under various fire severity and topography conditions were also examined. Correlation analysis was employed to assess the influence of moisture content on the recovery of fire sites. The results show that fire severity, topographic features, and moisture content significantly impacted the rate of vegetation recovery. Specifically, regeneration takes place more rapidly on warm, high-altitude, and gentle slopes within highly and moderately burned areas. Additionally, areas marked by high moisture content demonstrate rapid recovery. Our study enriches the research cases of global wildfires and vegetation recovery and provides a scientific basis for forest management and the restoration of post-fire ecosystems.

The city's local climate zone (LCZ) was considered to be a powerful tool for urban climate mapping. But for cities in different countries and regions, the LCZ division methods and results were different, thus targeted researches should be performed. In the current work, a LCZ mapping method was proposed, which is convenient in operation and city planning oriented. In this proposed method, the local climate zoning types were adjusted firstly, according to the characteristics of Chinese city, that more tall buildings and high density. Then the classification method proposed by WUDAPT based on remote sensing data was performed on Xi'an city, as an example, for LCZ mapping. Combined with the city road network, a reasonable expression of the dividing results was provided, to adapt to the characteristics in city planning that land parcels are usually recognized as the basic unit. The proposed method was validated against the actual land use and construction data that surveyed in Xi'an, with results indicating the feasibility of the proposed method for urban LCZ mapping in China.