In Situ Experimental Dataset of Population Density Effecting Allometric Growth of Agriophyllum squarrosum in Naiman Station of Inner Mongolia, China

GCdataPR ◽  
2020 ◽  
Author(s):  
Gaohua FAN ◽  
Yingxin HUANG ◽  
Xueyong ZHAO ◽  
Xiangjin SHEN
2017 ◽  
Vol 220 ◽  
pp. 76-84 ◽  
Author(s):  
Jianju Du ◽  
Xianghui Qin ◽  
Qingli Zeng ◽  
Luqing Zhang ◽  
Qunce Chen ◽  
...  

2019 ◽  
Vol 68 (2) ◽  
pp. 211-216
Author(s):  
MUHAMMAD ANEES ◽  
MUHAMMAD ABID ◽  
SOBIA CHOHAN ◽  
MUHAMMAD JAMIL ◽  
NADEEM AHMED ◽  
...  

Rhizoctonia solani is a soil-borne fungus causing a wide range of plants diseases. Trichoderma gamsii strain T30 has previously been reported as antagonistic against R. solani. Although there are a few studies about the influence of Trichoderma strains on the R. solani densityin a pathosystem in the presence of plant hosts, this report for the first time comprehensively describes in situ effects of a T. gamsii strain on the population density of R. solani in the soil microcosmic conditions. The population dynamics of R. solani were followed in the autoclaved and non-autoclaved soils in artificially prepared microcosms up to day 25 after co-inoculation with T. gamsii in the variable ratios (R1/T1; R1/T0.1; R1/T0.01 of R. solani/T. gamsii). The population density of R. solani was evaluated by qPCR. In the autoclaved soil, target DNA copies of R. solani increased in the control samples from 1 × 105 to 6.5 × 106. At R1/T0.01, the number of target DNA copies were not significantly changed until day 11; however, it decreased by around five times at day 25. At R1/T0.1 and R1/T1, the number of DNA copies was reduced to 2.1 × 106 and 7.6 × 105 at day 11, respectively and the reduction was as much as 17 times at day 25. In the non-autoclaved soil, the number of the fungal cells decreased at day 25 whether inoculated or not with Trichoderma indicating a general suppression by the soil microbiome. In brief, T. gamsii significantly inhibited the growth of R. solani in the soil in situ and there was a general suppressive effect of the natural microbiome.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 655 ◽  
Author(s):  
Fangpeng Cui ◽  
Qiang Wu ◽  
Chen Xiong ◽  
Xiang Chen ◽  
Fanlan Meng ◽  
...  

On 1 March 2010, a disastrous groundwater inrush occurred at the Luotuoshan coalmine in Wuhai (Inner Mongolia, China). Great effort was taken during the post-accident rescue. However, triggered by a large amount of groundwater rushed in from the Ordovician limestone aquifer underlying the No.16 coal seam through the fractured sandy claystone and the karst collapse column, it caused great damage, including 32 deaths and direct economic losses of over 48 million yuan. The groundwater inrush originated from the floor heave in the air return gallery of the No.16 coal seam. The peak inflow rate was 60,036 m3/h. The gallery excavation under conditions caused by the incompletely recognized hydrogeological environment induced the accident. The unidentified spatial distribution of the karst collapse column triggered the accident directly. The high-pressure groundwater accumulated in the collapse column and the gallery excavation, which caused the redistribution of the in situ stress, contributing to progressive fractures in the floor of the No. 16 coal seam. Eventually, an intensive water-conductive passage consisting of the fractured floor and the karst collapse column formed. Administratively/technically, that mandatory regulations on gallery excavation were not carried out which contributed the accident. Moreover, the poor awareness about groundwater inrush recognition and quick remediation also contoirbuted to the disastrous extent of the accident.


Author(s):  
Stanislav Opluštil ◽  
Jun Wang ◽  
Hermann W. Pfefferkorn ◽  
Josef Pšenička ◽  
Jiří Bek ◽  
...  

2021 ◽  
Vol 119 ◽  
pp. 104684
Author(s):  
Ruiyun Li ◽  
Xiaoqiang Li ◽  
Xuelian Wang ◽  
Bainian Sun

2011 ◽  
Vol 383-390 ◽  
pp. 3685-3689 ◽  
Author(s):  
Hai Feng Wang ◽  
Wen Jun Yin ◽  
Meng Zhang ◽  
Jin Dong

Advanced data assimilation method is used for the short-term wind power forecasting based on a meso-scale model. Considerable forecast error reduction is concluded from a case study in China, where a better resolved high-resolution initial condition is introduced via assimilating various in-situ observations.


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