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Shagol, Charlotte C.,Subramanian, Parthiban,Krishnamoorthy, Ramasamy,Kim, Kiyoon,Lee, Youngwook,Kwak, Chaemin,Sundaram, Suppiah,Shin, Wansik,Sa, Tongmin Korean Society of Soil Science and Fertilizer 2014 한국토양비료학회지 Vol.47 No.3
Arsenic is a known hazardous metalloid not only to the animals but also to plants. With high concentrations, it can impede normal plant growth and cause even death of plants at extremely high levels. A known plant response to stress conditions such as toxic levels of metal (loids) is the production of stress ethylene, causing inhibitory effect on root growth in plants. When the effect of various arsenic concentrations was tested to maize plant, the stress ethylene emission proportionately increased with increasing concentration of As(V). The inoculation of two arsenic tolerant bacteria; Pseudomonas grimonti JS126 and Pseudomonas taiwanensis JS238 having respective high and low 1-aminocyclopropane-1-carboxylate (ACC) deaminase activity reduced stress ethylene emission by 59% and 30% in maize grown in arsenic polluted soils. The result suggested the possible use of Pseudomonas grimonti JS126 for phytoremediation of arsenic polluted soils.
Charlotte C. Shagol,Parthiban Subramanian,Ramasamy Krishnamoorthy,Kiyoon Kim,Youngwook Lee,Chaemin Kwak,Suppiah Sundaram,Wansik Shin,Tongmin Sa 한국토양비료학회 2014 한국토양비료학회지 Vol.47 No.3
Arsenic is a known hazardous metalloid not only to the animals but also to plants. With high concentrations, it can impede normal plant growth and cause even death of plants at extremely high levels. A known plant response to stress conditions such as toxic levels of metal (loids) is the production of stress ethylene, causing inhibitory effect on root growth in plants. When the effect of various arsenic concentrations was tested to maize plant, the stress ethylene emission proportionately increased with increasing concentration of As(V). The inoculation of two arsenic tolerant bacteria; Pseudomonas grimonti JS126 and Pseudomonas taiwanensis JS238 having respective high and low 1-aminocyclopropane-1-carboxylate (ACC) deaminase activity reduced stress ethylene emission by 59% and 30% in maize grown in arsenic polluted soils. The result suggested the possible use of Pseudomonas grimonti JS126 for phytoremediation of arsenic polluted soils.
High-Resolution Simulations for Vietnam - Methodology and Evaluation of Current Climate
Jack Katzfey,Kim Nguyen,John McGregor,Peter Hoffmann,Suppiah Ramasamy,Hiep Van Nguyen,Mai Van Khiem,Thang Van Nguyen,Kien Ba Truong,Thang Van Vu,Hien Thuan Nguyen,Tran Thuc,Doan Ha Phong,Bang Thanh Ng 한국기상학회 2016 Asia-Pacific Journal of Atmospheric Sciences Vol.52 No.2
To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (−60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.