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Southerly Africa's Wellbeing Advertising Garnishment: Excise levy findings as well as collateral prospective.
Soil erosion made the distribution of soil seed bank to deeper soil layer, the accumulation of which will need a long time after vegetation restoration.Given the importance of undergrowth vegetation to plantation ecosystem, this study analyzed the effects of three kinds of understory management measures, including understory preservation, understory removal, and interplanting, on the soil bacterial diversity, community structure and relative abundance under large diameter timber plantation of Cunninghamia lanceolata using high-throughput sequencing technology. The relationship between soil physical and chemical properties and bacterial community diversity were analyzed. The results showed that Chao1, Ace and Shannon indices of soil bacterial communities of understory preservation were higher than those of understory removal and interplanting. Actinobacteria, Acidobacteria and Chloroflexi were the dominant bacteria groups in the soil of C. lanceolata plantation. Compared with understory removal and interplanting, the relative abundance of Proteobacteria, Planctomycetes, Firmicutes and Verrucomicrobia in the soil of understory preservation was relatively high, while that of Actinobacteria, Acidobacteria and Chloroflexi was relatively low. There were significant differences in the relative abundance of Firmicutes, Planctomycetes, Verrucomicrobia, Parcubacteria and Actinobacteria among three understory management measures. The contents of moisture, total nitrogen, total phosphorus, hydrolyzed nitrogen and available phosphorus in the soil were important factors affecting soil bacterial community structure. Soil bacterial diversity indices had significant positive correlation with the contents of total nitrogen, total phosphorus, total potassium, hydrolyzed nitrogen and available potassium in the soil.Understanding the changes and driving factors of forest fire can provide scientific basis for prevention and management of forest fire. In this study, we analyzed the changes and driving factors of forest fire in Zhejiang Province during 2001-2016 based on trend analysis and Logistic regression model with the MODIS satellite fire point data combined with meteorological (daily ave-rage wind speed, daily average temperature, daily relative humidity, daily temperature difference, daily cumulative precipitation), human activities (distance from road, distance from railway, distance from resident, population, per capita GDP), topographic and vegetation factors (elevation, slope, vegetation coverage). The results showed that the number of forest fires in spring and summer had significantly increased, while the forest fires in the autumn and winter increased first and then decreased. Forest fire in autumn significantly declined. The four seasons' fire occurrence prediction models had good prediction accuracy, reaching 75.8% (spring), 79.1% (summer), 74.7% (autumn) and 79.6% (winter). The meteorological, human activity, topographic and vegetation factors significantly affected fire occurrence in spring and summer, while meteorological factors were the main fire drivers in autumn and winter in Zhejiang. The focus of forest fire management should be on human activities. Fire prevention campaign should be done in spring and summer when high-risk forest fires were scattered in the study area. In autumn and winter, observatory and monitoring equipment could be built to facilitate fire management and detect in the area of high fire risk that was concentrated in the southwest region.To understand the contents of various phosphorus forms, phosphorus solubilizing bacte-rial community structure and the relationship between them in soils after restoration from the seriously burning, we collected soil samples from artificial restoration (Pinus sylvestris var. mongolica plantation, Larix gmelinii plantation), artificial accelerated natural restoration (secondary forest) and natural restoration (natural secondary forest) stands in Greater Khingan Mountain area. Using methods of Sui et al. modified from Hedley phosphorus fractionation, we measured the contents of different phosphorus forms in rhizosphere soil and bulk soil (0-10, 10-20 cm). click here Abundances of phosphorus solubilizing bacteria were quantified by high-throughput sequencing method. The results showed that the contents of H2O-Pi, NaHCO3-Pi and NaHCO3-Poin 0-10 cm bulk soil and NaHCO3-Po in rhizosphere soil followed the order of L. gmelinii plantation P. sylvestris var. mongolica plantation natural secondary forest secondary forest. They forest in 0-10 cm layer of bulk soil,and ranked as L. gmelinii plantation P. sylvestris var. mongolica plantation natural secondary forest secondary forest in the 10-20 cm layer. The content of residual-P in the soil was not sensitive to restoration methods. Bradyrhizobium, Streptomyces, Burkholderia and Bacillus were the main phosphorus solubilizing bacteria across all forest stands. The abundances of phosphorus solubilizing bacteria in soil of L. gmelinii plantation and P. sylvestris var. mongolica plantation were significantly higher than that of secondary forest and natural secondary forest. Results of redundancy analysis showed that the correlation between phosphorus solubilizing bacteria and various phosphorus forms was different. Our results showed that artificial afforestation was more conducive in improving the availability of phosphorus in soil and the abundance of phosphorus solubilizing bacteria.We used tree rings of Pinus tabuliformis sampled in the Muwang National Forest Park to establish a standardized chronology (STD) and calculated the correlation coefficients between the standardized chronology and climatic factors of Zhen'an meteorological station. With linear regression analysis, we reconstructed the March-April mean maximum temperature of Zhen'an over 165 years from 1853 to 2017. The highest correlation coefficient was observed between the standardized chronology and the March-April mean maximum temperature (r=0.596, n=60, P＜0.01). The variance interpretation of the March-April mean maximum temperature reconstruction function was 33.2%, and the reconstruction function and results were credible and reliable. Warm years occurred 25 times and cold years occurred 29 times in the reconstruction sequence. The warm years were more accompanied by flood events, while the cold years were accompanied by more drought events. Temperature fluctuated obviously in the reconstruction sequence, with two cold periods (1902-1917 and 1953-2000) and four warm periods (1868-1892, 1917-1937, 1941-1953 and 2001-2012).
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