Biological soil crusts are common components of desert ecosystem; they cover ground surface and interact with topsoil that contribute to desertification control and degraded land restoration in arid and semiarid regions. To distinguish the changes in topsoil affected by biological soil crusts, we compared topsoil properties across three types of successional biological soil crusts (algae, lichens, and mosses crust), as well as the referenced sandland in the Mu Us Desert, Northern China. Relationships between fractal dimensions of soil particle size distribution and selected soil properties were discussed as well. The results indicated that biological soil crusts had significant positive effects on soil physical structure (P<0.05); and soil organic carbon and nutrients showed an upward trend across the successional stages of biological soil crusts. Fractal dimensions ranged from 2.1477 to 2.3032, and significantly linear correlated with selected soil properties (R² = 0.494∼0.955, P<0.01). Biological soil crusts cause an important increase in soil fertility, and are beneficial to sand fixation, although the process is rather slow. Fractal dimension proves to be a sensitive and useful index for quantifying changes in soil properties that additionally implies desertification. This study will be essential to provide a firm basis for future policy-making on optimal solutions regarding desertification control and assessment, as well as degraded ecosystem restoration in arid and semiarid regions.

Mongolian pine plantations (MPPs) composed of Pinus sylvestris var. mongolica (P. sylvestris) are used for desertification control and restoration of degraded land in arid and semi-arid regions. We studied soil changes associated with P. sylvestris by comparing top (0–20 cm) and sub-top (20–40 cm) soil properties across 8 stand density gradients of MPPs ranging from 900 ± 5–2700 ± 50 trees ha^–1. The study was conducted in the uncovered Sandy Land in the southern Mu Us Desert, China. The relationships between the volume fractal dimensions (D) of soil particle size distribution and soil physicochemical properties were evaluated. D was determined using a laser diffraction technique and soil properties were measured. In the top layer, P. sylvestris significantly positively affected soil physicochemical properties except for bulk density and total nitrogen. These effects were not observed in the sub-top soil layer. D values ranged from 1.52 ± 0.29–2.08 ± 0.06 and were significantly correlated with stand density. Significant correlations were observed between D and soil properties (except total nitrogen) in the top soil layer. Given these results, we concluded that D is a sensitive and useful index because it quantifies changes in soil properties that additionally implies desertification in the studied area.

With the development of computer technology, forest fire spread simulation using computers has gradually developed. According to the existing research on forest fire spread, the models established in various countries have typical regional characteristics. A fire spread model established in a specific region is only suitable for the local area, and there is still a great deal of uncertainty as to whether or not the established model is suitable for fire spread simulation for the same fuel in other regions. Although many fire spread models have been established, the fuel characteristics applicable to each model, such as the fuel loading, fuel moisture content, combustibility, etc., are not similar. It is necessary to evaluate the applicability of different fuel characteristics to different fire spread models. We combined ground investigation, historical data collection, model improvements, and statistical analysis to establish a multi-model forest fire spread simulation method (FIRER) that shows the burning time, perimeter, burning area, overlap area, and spread rate of fire sites. This method is a large-scale, high-resolution fire growth model based on fire spread in eight directions on a regular 30 m grid. This method could use any one of four different physical models (McArthur, Rothermel, FBP, and Wang Zhengfei (China)) for fire behavior. This method has an option to represent fire breaks from roads, rivers, and fire suppression. We can evaluate which model is more suitable in a specific area. This method was tested on a single historical lightning fire in the Daxing’an Mountains. Different scenarios were tested and compared: using each of the four fire behavior models, with fire breaks on or off, and with a single or suspected double fire ignition location of the historical fire. The results show that the Rothermel model is the best model in the simulation of the Hanma lightning fire; the overlap area is 5694.4 hm². Meanwhile, the real fire area in FIRER is 5800.9 hm²; both the Kappa and Sørensen values exceed 0.8, providing high accuracy in fire spread simulations. FIRER performs well in the automatic identification of fire break zones and multiple ignited points. Compared with FARSITE, FIRER performs well in predicting accuracy. Compared with BehavePlus, FIRER also has advantages in simulating large-scale fire spread. However, the complex data preparation stage of FIRER means that FIRER still has great room for improvement. This research provides a practical basis for the comparison of the practicability and applicability of various fire spread models and provides more effective practical tools and a scientific basis for decision-making and the management of fighting forest fires.

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, is one of the most severe forest diseases worldwide. PWD causes devastating disasters to Chinese pine trees, seriously threatening forestry production and the forest ecological environment, and causes economic losses of over ten billion yuan per year to China. Previous studies have shown that the spread of PWD is closely related to climate factors. Today, PWD is spreading rapidly owing to abnormal climate changes. In order to provide a reference for controlling the spread of PWD in China, in this study, we accurately assessed the risk of the continued spread of PWD in Northeast China; a correlative species distribution model (MaxEnt) (RM = 1, AUC = 0.9904) was used to evaluate China’s climate suitability for PWD. The effects of climate factors on the spread of PWD in Northeast China were studied using Liaoning Province as an example by analyzing the relationship between the changes in average precipitation, average temperature, average relative humidity, average vapor pressure deficit, average wind speed, average sunshine duration and the area of the PWD epidemic over the past five years. These results suggest that with the change in climate, the areas suitable for PWD have expanded, and certain previously unsuitable areas for its distribution have become suitable. Temperature and precipitation were found to play key roles in the occurrence and damage of PWD, and hot and arid conditions favored the spread of PWD. It is recommended that for areas within the suitable range of PWD but not yet epidemic areas, quarantine should be strengthened to prevent the further spread of PWD. In addition, special attention should be paid to epidemic areas with high temperatures and arid while the monitoring of PWD should be strengthened to achieve the early detection and timely treatment of infected epidemic trees. Our results indicate that PWD undoubtedly poses a major threat to Northeast Chinese pine species if climate change proceeds as projected. In the future, more attention should be paid to monitoring the northward spread of PWD, and further studies should consider meteorological data forecasts, which could facilitate timely control measures.

Hedysarum scoparium is an important, fast-growing and drought-resistant shrub that has been extensively used for grassland restoration and preventing desertification in semiarid regions of northwestern China. The primary objective of this study was to investigate the diurnal and seasonal variations in stem sap flow (J_s) and its relation to environmental factors. The stem heat balance method was applied to plants that were approximately 17 years old (with diameters of 25, 16, 13, and 9 mm at ground level and heights of 3.1, 1.8, 1.7 and 1.4 m) and growing under natural conditions. The vertical soil temperature profile (ST), soil surface heat flux (SoilG), volumetric soil moisture content (SWC) and meteorological variables such as solar radiation (R_n), air temperature (T_a), vapour pressure deficit (VPD), wind speed (W_s) relative humidity (RH) and precipitation (P) were simultaneously measured at a meteorological station on site. Results indicated that J_s varied regularly during the diurnal and seasonal term. The nocturnal J_s was substantial, with a seasonal variation similar to the patterns of daytime J_s. The magnitude of J_s changed considerably between sunny and rainy days. Redundancy (RDA) and Kendall’s tau analysis suggested that daily J_s in large plants was more sensitive to environmental factors, and the variation in daily J_s during the growing season could be described by a multiple linear regression against environmental variables including T_a, VPD, W_s, RH, ST, and SoilG. While the nocturnal J_s in smaller plants was more sensitive to meteorological factors. T_a, VPD, and W_s were significantly correlated with nighttime J_s. The hourly nighttime sap flow rate of H. scoparium corresponded closely to T_a and VPD following a non-linear pattern. The results of this study can be used to estimate the transpiration of H. scoparium.