Characteristics of spatial and temporal variability in the distribution of biological soil crusts on the Loess Plateau, China.

Biological soil crust (biocrust) is widely distributed on the Loess Plateau and plays multiple roles in regulating ecosystem stability and multifunctionality. Few reports are available on the distribution characteristics of biocrust in this region, which limits the assessment of its ecological functions. Based on 388 sampling points in different precipitation zones on the Loess Plateau from 2009 to 2020, we analyzed the coverage, composition, and influencing factors of biocrust across different durations since land abandonment, precipitation levels, topography (slope aspect and position), and utilization of abandoned slopelands (shrubland, forest, and grassland). On this base, with the assistance of machine learning and spatial modeling methods, we generated a distribution map of biocrust and its composition at a resolution of 250 m × 250 m, and analyzed the spatial distribution of biocrust on the Loess Plateau. The results showed that the average biocrust coverage in the woodlands and grasslands was 47.3%, of which cyanobacterial crust accounted for 25.5%, moss crust 19.7%, and lichen crust 2.1%. There were significant temporal and spatial variations. Temporally, the coverage of biocrust in specific regions fluctuated with the extension of the abandoned durations and coverage of cyanobacterial crust, while moss crust showed a reverse pattern. In addition, the coverage of biocrust in the wet season was slightly higher than that in the dry season within a year. Spatially, the coverage of biocrusts on the sandy lands area on the Loess Plateau was higher and dominated by cyanobacterial crusts, while the coverage was lower in the hilly and gully area. Precipitation and utilization of abandoned land were the major factors driving biocrust coverage and composition, while slope direction and position did not show obvious effect. In addition, soil organic carbon content, pH, and texture were related to the distribution of biocrust. This study uncovered the spatial and temporal variability of biocrust distribution, which might provide important data support for the research and management of biocrust in the Loess Plateau region.

Exo-III Enzyme-Assisted Triple Cycle Signal Amplifications for Sensitive and Accurate Identification of Pathogenic Bacteria.

Early determination of infectious pathogens is vitally important to select appropriate antibiotics, and to manage nosocomial infection. Herein, we propose a target recognition triggered triple signal amplification-based approach for sensitive pathogenic bacteria detection. In the proposed approach, a double-strand DNA probe (capture probe) that is composed of an aptamer sequence and a primer sequence is designed for specific identification of target bacteria and initiation of following triple signal amplification. After recognition of target bacteria, primer sequence is released from capture probe to bind with the designed H1 probe, forming a blunt terminal in the H1 probe. Exonuclease-III (Exo-III enzyme) specifically recognizes the blunt terminal in H1 probe and degrades the sequence from 3' terminal, resulting a single-strand DNA to induce the following signal amplification. Eventually, the approach exhibits a low detection limit of 36 cfu/mL with a broad dynamic range. The high selectivity endows the method a promising prospective for clinical sample analysis.

[Representative landscape indices of biological soil crusts distribution in the hilly Loess Plateau of China]. / 黄土丘陵区生物结皮空间分布的代表性景观指数.

Landscape indices can quantitatively describe the distribution characteristics of biological soil crusts (biocrusts). However, there are too many landscape indices, with high redundancy. We investigated 58 plots of biocrusts with different distribution patterns in the Hegou watershed of Wuqi County, Shaanxi Province, located in the hilly Loess Plateau. First, we calculated 15 common landscape indices, and selected representative landscape indices that could describe the biocrust landscape pattern and had specific ecological significance, based on correlation analysis, factor analysis, and sensitivity analysis. The reliability and rationality of the representative landscape indices were verified with data of the different biocrusts coverage in the Yingwoshanjian watershed of Yangjing Town, Dingbian County, Shaanxi Province. The results showed that 10 of the 15 landscape indices had significant correlations. Total edge (TE) and edge density (ED) were not significantly correlated with number of patches (NP), patch density (PD), clumpiness (CLUMPY), and interspersion juxtaposition index (IJI), respectively. The percentage of landscape (PLAND), ED, patch cohesion index (COHESION), and splitting index (SPLIT) described the spatial distribution characteristics of biocrust from coverage, length, connectivity, and fragmentation, respectively. The cumulative contribution of the three common factors represented in describing the spatial distribution of biocrusts was 91.6%. The study identified the representative landscape indices that could quantify the complexity of biocrusts distribution and thus would provide a theoretical basis for studying the pattern evolution of biocrusts and their relationship with ecological processes.

Effects of the distribution of biological soil crust on the hydrodynamic characteristics of surface runoff.

The distribution pattern of biological soil crusts (biocrusts) is one of the main factors affecting runoff and sediment yield. The relationship between runoff and sediment yield and biocrusts' distribution pattern is not clear, which hinders understanding the mechanism underlying the effects of biocrusts on runoff and sediment from slopes. To fill the knowledge gap, we investigated the relationship between the landscape indices of three biocrusts' distribution patterns, i.e. zonation, chessboard and random, and the hydraulic parameters, using of simulated rainfall experiments and landscape ecology methods. The results showed that biocrust significantly affected the erosion force of slopes and that its distribution pattern could affect slope erosion dynamics. Compared to bare soil, the presence of biocrusts significantly reduced the runoff velocity (54.6%) and Froude number (67.0%), increased the runoff depth (86.2%) and Darcy-Weisbach resistance coefficient (10.68 times), but did not affect the Reynolds number and runoff power. Expect for the runoff depth, there were significant differences in the hydraulic parameters of the three biocrusts' distribution patterns, with the random pattern having the strongest impacts on the dynamics of slope erosion. Based on factor analysis and cluster analysis, five indices of percentage of patch to landscape area, patch density, landscape shape index, patch cohesion and splitting could be used as the indicators for the distribution characteristics of biocrust patches. The patch cohesion and splitting of biocrust patches were the main distribution pattern indices of the hydrodynamics of surface runoff. As the patches patch cohesion decreased, the splitting increased, which caused the surface runoff velocity increase, the resistance decrease, and the slope erosion became more severe.

Thermolysis, nonisothermal decomposition kinetics, specific heat capacity and adiabatic time-to-explosion of [Cu(NH3)4](DNANT)2 (DNANT= dinitroacetonitrile).

A new energetic copper complex of dinitroacetonitrile (DNANT), [Cu(NH3)4](DNANT)2, was first synthesized through an unexpected reaction. The thermal decomposition of [Cu(NH3)4](DNANT)2 was studied with DSC and TG/DTG methods. The gas products were analyzed through a TG-FTIR-MS method. The nonisothermal kinetic equation of the exothermic process is dα/dT = 10(10.92)/ß4(1 - α)[-ln(1 - α)](3/4) exp(-1.298 × 10(5)/RT). The self-accelerating decomposition temperature and critical temperature of thermal explosion are 217.9 and 221.0 °C. The specific heat capacity of [Cu(NH3)4](DNANT)2 was determined with a micro-DSC method, and the molar heat capacity is 512.6 J mol(-1) K(-1) at 25 °C. Adiabatic time-to-explosion of Cu(NH3)4(DNANT)2 was also calculated to be about 137 s.