ABSTRACT
A rapid rise in industrialization has led to the accumulation of copious mining waste, which has caused serious destruction of the ecological environment, resulting in severe pollution problems that need to be addressed urgently. In this study, altered soil bacterial communities in different polluted areas were analyzed using the Illumina high-throughput sequencing technique. The primary factors along with physical and chemical factors influencing the soil bacterial communities were also investigated, and the associated potential ecological functions were predicted. The results of these analyses indicated that aggravated pollution caused severe loss of tailing soil nutrients. A total of 14253 bacterial OTU was obtained from the soil samples. The total numbers of OTU in the heavily polluted area (W1), moderately polluted area (W2), lightly polluted area (W3), and clean area (CK) were 3240, 3330, 3813, and 3870, respectively. However, the soil OTUs decreased gradually with increasing pollution. In the α-diversity index analysis, the richness and evenness of the soil bacterial community were significantly decreased in the W1 group. A significant decrease in the Chao1, ACE, and Shannon indexes was also observed in the W1 group, whereas no significant difference was observed in the W3 group compared to the control. The dominant bacterial phyla identified in the soil wereß-Actinobacteria, ß-Proteobacteria, and ß-Chloroflexi. Further, the relative abundance of ß-Actinobacteria and ß-Proteobacteria was high, whereas relative abundance of ß-Chloroflexi in the W1-W3 groups was low compared to that in the control. The relative abundance of the dominant phylum in the W1 group was significantly different than that in the CK group (P<0.05). RDA showed that the soil physical and chemical properties selected in this study explained the total variation in soil bacterial community by 93.35%. Spearman analysis showed that ß-Actinobacteria was negatively correlated with nitrogen source and organic matter and positively correlated with pH; ß-Proteobacteria was negatively correlated with nitrogen source, phosphorus source, available potassium, and organic matter and positively correlated with total potassium and pH; and ß-Chloroflexi was positively correlated with nitrogen source, phosphorus source, available potassium, and organic matter and negatively correlated with pH. Tax4 Fun was used to analyze the biological metabolic pathway. Heavy metal pollution in the soil affected the soil bacterial community and changed the main types of biological metabolism. The ecological functions of soil bacteria groups in different polluted areas were predicted by FAPROTAX. The results showed that the dominant metabolic patterns were affected by the pollution degree, and the metabolic patterns of soil bacteria in polluted areas were relatively single. The functional abundance of metabolic patterns of soil bacteria communities in CK was higher than that in polluted areas, which not only participated in degradation metabolism but also related to oxidation metabolism.
Subject(s)
Actinobacteria , Betaproteobacteria , Soil , Zinc , Lead , Environment , NitrogenABSTRACT
A spectrum-tunable ground scenery spectrum radiation source, using LEDs and bromine tungsten lamp as luminescence media, was introduced. System structure and control of the spectrum radiation source was expounded in detail. In order to simulate various ground scenery spectrum distribution with different shapes, a ground scenery spectral database was established in the control system. An improved genetic algorithm was proposed, and a large number of ground scenery spectra were produced by the simulator. Spectral similarity and the average spectral matching error of several typical ground scenery spectra were further analyzed. Spectral similarity of red bands, green bands, blue bands and near-infrared spectral band also was discussed. When the radiance of the target was 50 W x (m2 x sr)(-1), the average spectral matching error was less than 10% and spectral similarity was greater than 0.9, up to 0.983. Spectral similarity of red band, green band, blue band and near-infrared band (especially green band and near-infrared band) was less than that of full-band. Compared with blue band and red band, spectral similarity of green band and near-infrared band low-amplitude maximum can rearch 50%. Ground scenery spectrum radiation source can be used as radiometric calibration source for optical remote sensor, and calibration error, which is caused by objectives and calibration sources spectral mismatch, can be effectively reduced.
ABSTRACT
A method of determining relative spectral responsivity of photodetector by LED-based spectrum-tunable integrating sphere source is put forward, and the measuring principle and algorithm are exhaustively described. In the course of calculation, the radiant transmission integral equation was changed into summation formula, and the degree of approximation between integral value and summation value is related to the selected wavelength interval. The differences between integral value and summation value in different wavelength intervals of Si photodiode and CCD were simulated and analyzed. The simulated results demonstrated that the relative differences between signal integral value and signal summation value of Si photodiode and CCD were below 0.2% in 10 nm interval, so 10 nm interval was an ideal choice. In the end, the factors affecting measurement accuracy were discussed and the solution suggestions were given. This method is easy in structure, and it avoids the measurement transmission errors of some instruments, such as monochromator.
