|Relatively little is known about fire regimes in grassland and cropland in Central Asia. In this study, eleven variables of fire regimes were measured from 2001 to 2019 by utilizing the burned area and active fire product, which was obtained and processed from the GEE (Google Earth Engine) platform, to describe the incidence, inter-annual variability, peak month and size of fire in four land cover types (forest, grassland, cropland and bare land). Then all variables were clustered to define clusters of fire regimes with unique fire attributes using the K-means algorithm. Results showed that Kazakhstan (KAZ) was the most affected by fire in Central Asia. Fire regimes in cropland in KAZ had the frequent, large and intense characters, which covered large burned areas and had a long duration. Fires in grassland mainly occurred in central KAZ and had the small scale and high-intensity characters with different quarterly frequencies. Fires in forest were mainly distributed in northern KAZ and eastern KAZ. Although fires in grassland underwent a shift from more to less frequent from 2001 to 2019 in Central Asia, vigilance is needed because most fires in grassland occur suddenly and cause harm to humans and livestock.|
|Hotan Prefecture is located at the southwestern edge of Taklimakan Desert, the world's largest shifting sand desert, of China. The desert is one of the main sources for frequent sand-dust weather events which strongly affect the air quality of Hotan Prefecture. Although this region is characterized by the highest annual mean PM10 concentration values that are routinely recorded by environmental monitoring stations across China, both this phenomenon and its underlying causes have not been adequately addressed in previous researches. Reliable pollutant PM10 data are currently retrieved using a tapered element oscillating microbalance (TEOM) 1400a, a direct real-time monitor, while additional concentration values including for PM2.5, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3) have been collected in recent years by the Hotan Environmental Monitoring Station. Based on these data, this paper presents a comparison of the influences of different kinds of sand-dust weather events on PM10 (or PM2.5) as well as the concentrations of other gaseous pollutants in Hotan Prefecture. It is revealed that the highest monthly average PM10 concentrations are observed in the spring because of the frequent occurrence of three distinct kinds of sand-dust weather events at this time, including dust storms, blowing dust and floating dust. The floating dust makes the most significant contribution to PM10 (or PM2.5) concentration in this region, a result that differs from eastern Chinese cities where the heaviest PM10 pollution occurs usually in winter and air pollution results from the excess emission of local anthropogenic pollutants. It is also shown that PM10 concentration varies within typical dust storms. PM10 concentrations vary among 20 dust storm events within Hotan Prefecture, and the hourly mean concentrations tend to sharply increase initially then slowly decreasing over time. Data collected from cities in eastern China show the opposite with the hourly mean PM10 (or PM2.5) concentration tending to slowly increase then sharply decrease during heavy air pollution due to the excess emission of local anthropogenic pollutants. It is also found that the concentration of gaseous pollutants during sand-dust weather events tends to be lower than those cases under clear sky conditions. This indicates that these dust events effectively remove and rapidly diffuse gaseous pollutants. The analysis also shows that the concentration of SO2 decreases gradually at the onset of all three kinds of sand-dust weather events because of rapidly increasing wind velocity and the development of favorable atmospheric conditions for diffusion. In contrast, changes in O3 and NO2 concentrations conformed to the opposite pattern during all three kinds of sand-dust weather events within this region, implying the inter transformation of these gas species during these events.|
In order to explore the effects of grazing frequency on functional traits and to test whether Stipa gandis has compensatory photosynthesis during the frequent grazing period, we investigated morphological traits, biomass allocation, photosynthetic traits, and chlorophyll fluorescence parameters of the species in Inner Mongolia, China. The grazing frequency treatments included fencing (T0), grazing in May and July (T1, i.e., two months per year) and grazing from May to September (T2, i.e., continuous five months per year). Results indicate that T1 and T2 treatments did not affect individual biomass, but T2 treatment negatively affected individual size, i.e., plant height, stem length, and leaf length. Physiological traits of S. grandis were significantly affected by grazing, year, and their interaction. In July 2014 (i.e., dry environment and low relative humidity), the photosynthetic rate, transpiration rate and water use efficiency were highest under T2 treatment, which was caused by the increase in stomatal conductance. However, in July 2015 (i.e., wet environment and high relative humidity), the photosynthetic rate and water use efficiency were higher under T1 and T2 treatments, which were caused by the increase in actual quantum efficiency and stomatal conductance. Our results implied that under frequent grazing treatment, S. grandis had small height and efficient compensatory photosynthesis, which promoted its resistance to severe grazing.
|API 20E strip test, the standard for Enterobacteriaceae identification, is not sufficient to discriminate some Yersinia species for some unstable biochemical reactions and the same biochemical profile presented in some species, e.g. Yersinia ferderiksenii and Yersinia intermedia, which need a variety of molecular biology methods as auxiliaries for identification. The 16S rRNA gene is considered a valuable tool for assigning bacterial strains to species. However, the resolution of the 16S rRNA gene may be insufficient for discrimination because of the high similarity of sequences between some species and heterogeneity within copies at the intra-genomic level. In this study, for each strain we randomly selected five 16S rRNA gene clones from 768 Yersinia strains, and collected 3,840 sequences of the 16S rRNA gene from 10 species, which were divided into 439 patterns. The similarity among the five clones of 16S rRNA gene is over 99% for most strains. Identical sequences were found in strains of different species. A phylogenetic tree was constructed using the five 16S rRNA gene sequences for each strain where the phylogenetic classifications are consistent with biochemical tests; and species that are difficult to identify by biochemical phenotype can be differentiated. Most Yersinia strains form distinct groups within each species. However Yersinia kristensenii, a heterogeneous species, clusters with some Yersinia enterocolitica and Yersinia ferderiksenii/intermedia strains, while not affecting the overall efficiency of this species classification. In conclusion, through analysis derived from integrated information from multiple 16S rRNA gene sequences, the discrimination ability of Yersinia species is improved using our method.|