Shifts in microbial communities do not explain the response of grassland ecosystem function to plant functional composition and rainfall change

Ecosystem functioning in grasslands is regulated by a range of biotic and abiotic factors, and the role of microbial communities in regulating ecosystem function has been the subject of much recent scrutiny. However, there are still knowledge gaps regarding the impacts of rainfall and vegetation change upon microbial communities and the implications of these changes for ecosystem functioning. We investigated this issue using data from an experimental mesotrophic grassland study in south-east England, which had been subjected to four years of rainfall and plant functional composition manipulations. Soil respiration, nitrogen and phosphorus stocks were measured, and the abundance and community structure of soil microbes were characterised using quantitative PCR and multiplex-TRFLP analysis, respectively. Bacterial community structure was strongly related to the plant functional composition treatments, but not the rainfall treatment. However, there was a strong effect of both rainfall change and plant functional group upon bacterial abundance. There was also a weak interactive effect of the two treatments upon fungal community structure, although fungal abundance was not affected by either treatment. Next, we used a statistical approach to assess whether treatment effects on ecosystem function were regulated by the microbial community. Our results revealed that ecosystem function was influenced by the experimental treatments, but was not related to associated changes to the microbial community. Overall, these results indicate that changes in fungal and bacterial community structure and abundance play a relatively minor role in determining grassland ecosystem function responses to precipitation and plant functional composition change, and that direct effects on soil physical and chemical properties and upon plant and microbial physiology may play a more important role.

Gauging MSSM global symmetries and SUSY breaking in de Sitter vacuum

We elaborate on a recent study of a model of supersymmetry breaking we proposed recently, in the presence of a tunable positive cosmological constant, based on a gauged shift symmetry of a string modulus, external to the Standard Model (SM) sector. Here, we identify this symmetry with a global symmetry of the SM and work out the corresponding phenomenology. A particularly attracting possibility is to use a combination of Baryon and Lepton number that contains the known matter parity and guarantees absence of dimension-four and -five operators that violate B and L.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.