Pasture diversification to combat climate change impacts on grazing dairy production

Among livestock systems, grazing is likely to be most impacted by climate change because of its dependency to feed quality and availability. In order to reduce the impact of climate change on grazing livestock systems, adaptation measures should be implemented. The goal of this study is to identify the best pasture composition for a representative grazing dairy farm in Michigan in order to reduce the impacts of climate change on production. In order to achieve the goal of this study, three objectives were sought: (1) identify the best pasture composition, (2) assess economic and resource use impacts of pasture compositions under future climate scenarios, and (3) evaluate the resiliency of pasture compositions. A representative farm was developed based on a livestock practices survey and incorporated into the Integrated Farm System Model (IFSM). For the pasture compositions, four cool-season grass species and two legumes were evaluated under both current and future climate scenarios. The effectiveness of adaptation measures based on economic and resource use criteria was evaluated. Overall, the pasture composition with 50% perennial ryegrass (Lolium multiflorum) and 50% red clover (Trifolium pratense) was identified as the best. In addition, the increase in precipitation and temperature of the most intensive climate scenario could significantly improve farm net return per cow (Bos taurus) and whole farm profit while no significant impact was observed on resource use criteria. Finally, the overall sensitivity assessment showed that the most resilient pasture composition under future climate scenarios was ryegrass with red clover and the least resilient was orchardgrass (Dactylis glomerata) with white clover (Trifolium repens).     

The effect of age on cognitive performance under the impact of vibration in a driving environment.

The effect of organismic variable age on human cognitive performance was studied under the impact of vibration in different automobile driving environments, namely city streets, rural roads and highways. Reaction time was measured in milliseconds through a human response measurement system specifically designed for the purpose. Results of the study showed that age had a significant effect in city street and rural road conditions. It was also found that the level of equivalent acceleration of vibration and a difficulty index significantly affected cognitive performance in all driving conditions. The organismic variable age observed to have a significant effect on task performance implied that youngsters and older people are stressed differently in specific environments of driving so proper stress management strategies should be evolved for them in order to minimize the number of accidents.     

River Dolphins in Bangladesh: Conservation and the Effects of Water Development

Platanista gangetica ) are threatened in Bangladesh from the effects of dams, large embankment schemes, dredging, fisheries bycatch, directed hunting, and water pollution. Visual surveys of the section of the Jamuna River located between the divergence of the Old Brahmaputra River and the confluence of the Padma River and the section of the Kushiyara River located between the Bangladesh–India border and the confluence of the Korangi River recorded a sighting rate of 0.13 sightings/km (mean group size = 1.8 dolphins) and 0.08 sightings/km (mean group size = 3.8 dolphins), respectively. These sections of river were considered to be priority areas for investigation because several water development projects have already been constructed and more are planned for the areas. During the surveys we examined the remains of dolphins caught accidentally in plastic gillnets and observed fishermen catching the fish species Clupisoma garua using dolphin oil and body parts as a fish attractor. Additional studies are needed to assess the status of dolphins and effects of water development and fisheries bycatch. Feasibility studies should be conducted on designating dolphin/fish sanctuaries and creating artificial habitat or enhancing existing habitat in eddy countercurrent scour pools to mitigate deleterious impacts. The environmental requirements of river dolphins reflect the needs of productive and biotically diverse tropical rivers.     

Resilient and sustainable supplier selection via a new framework: a case study from the steel industry

Environment, Development and Sustainability - This study addresses the problem of selecting a supplier bound by sustainability and resilience criteria, focusing on the steel industry as a case in...     

Eco-friendly dyeing of wool using natural dye from weld as co-partner with synthetic dye

Since the last decade, the application of natural dyes on textile materials is gaining popularity all over the world, possibly because of increasing awareness of environment, ecology, and pollution control. In this research, extraction of dyes from weld using soxhlet apparatus has been studied. The color components extracted and isolated from weld plant were characterized by Column Chromatography, Thin Layer Chromatography (TLC), NMR, mass, IR techniques. The natural dye extract obtained from the weld was used for the dyeing of wool fiber. The results indicated that the exhaustion rate for the extracted dye increases by 49% compared to the raw dye. This, in turn, leads to a considerable decrease in the amount of the extracted dye used to reach the same desired results. Finally, for comparative studies between synthetic and this natural dye, all dyed specimens were tested for wash and light fastness properties, making weld a viable alternative to synthetic acid dyes.     

Solid state fermentation of lipopeptide antibiotic iturin A by using a novel solid state fermentation reactor system

A new solid state fermentation reactor (SSFR) for solid substrate was used for the production of lipopeptide antibiotic iturin A using Bacillus subtilis RB14-CS. Solid state fermentation (SSF) is the technique of cultivation of microorganisms on solid and moist substrates in the absence of free water. SSF has shown much promise in the development of several bioprocesses and products because of their several advantages like absence of free water that allows simplified downstream processing and low cost. SSFR allows agitation of the SSF culture with improved temperature control and air supply. Interestingly, when okara, the widely available waste product from the tofu industries, was used as the solid substrate for the SSFR, no iturin A production was observed. However, without agitation, production of iturin A was observed in the SSFR but the production level remained low. The low production of iturin A was found to be due to the heat generation and excess temperature rise inside the reactor system during the fermentation process. Maintaining the temperature within a range of 25–30°C, production of iturin A was significantly improved in the SSFR. This was comparable to the laboratory scale production, and signifies the potential application of the SSFR for SSF.     

Modeling carbon sequestration under zero-tillage at the regional scale. II. The influence of crop rotation and soil type

For policy decisions with respect to CO₂-mitigation measures in the agricultural sector, national and regional estimations of the efficiency of such measures are required. The conversion of ploughed cropland to zero-tillage is discussed as an option to reduce CO₂ emissions and promises at the same time effective soil and water conservation. Based on the upscaling of simulation results with the soil and land resources information system SLISYS-BW, estimations of CO₂-mitigation rates in relation to crop rotations and soil type have been made for the state of Baden-Württemberg (Germany). The results indicate considerable differences in the CO₂-mitigation rates between crop rotations ranging from 0.48 to 0.03 Mg C ha⁻¹ a⁻¹ for winter cereals–spring cereals–rape rotations and winter cereals–spring cereals–corn silage rotations, respectively. The efficiency of the crop rotations is strongly related to the total carbon input and in particular the amount of crop residues. Among the considered soil types, highest CO₂-mitigation rates are associated with Cumulic Anthrosols (0.62 Mg C ha⁻¹ a⁻¹) and the lowest with Gleysols (−0.01 Mg C ha⁻¹ a⁻¹). An agricultural extensification scenario with conventional plowing but conversion of the presently applied intensive crop rotations to a clover–clover–winter cereals rotation indicated a CO₂-mitigation potential of 466 Gg C a⁻¹. However, the present high market prices for cereals and increasing demand for energy production from biomass encourages an intensification of the agricultural production and an excessive removal of biomass which in future will seriously reduce the potential for carbon sequestration on cropland.     

Large eddy simulation of dispersion around an isolated cubic building: evaluation of localized dynamic k_\mathrm{SGS}-equation sub-grid scale model

In the present study, the prediction accuracy of a dynamic one-equation sub-grid scale model for the large eddy simulation of dispersion around an isolated cubic building is investigated. For this purpose, the localized dynamic $k_\mathrm{SGS} $ -equation model (LDKM) is employed and the results are compared with the available experimental data and two other classic sub-grid scale models, namely, standard Smagorinsky–Lilly model (SSLM) and dynamic Smagorinsky–Lilly model (DSLM). It is shown that the three SGS models give results in good agreement with experiment. However, near the ground level of the leeward wall, dimensionless time-averaged concentration, $\langle K\rangle $ , profile is not quite similar to the experimental data. It is also demonstrated that the LDKM predicts the values of $\langle K\rangle $ on the roof, leeward and side walls more acceptably than the SSLM and DSLM. Whereas, the streamwise elongation of time-averaged structures of the plume shape is more over-estimated with the LDKM than with the other two SGS models. In terms of numerical difficulty, the LDKM is found to be stable and computationally reasonable. In addition, it does not suffer from a flow dependent constant such as the Smagorinsky coefficient employed in the SSLM model.     

Predicting arsenic concentration in groundwater of Bangladesh using Bayesian geostatistical model

The pattern of the spatial variation in arsenic concentration in groundwater of Bangladesh is usually needed for the planning of safe drinking water. Often a model-based prediction is required for this purpose. In this paper, we fit a Bayesian hierarchical geostatistical model by utilizing data from the project, ‘Groundwater studies of arsenic concentration in Bangladesh’ conducted by the British Geological Survey and the Department of Public Health Engineering of Bangladesh. We also develop a predictive model for arsenic concentration at different levels of well-depth using the same approach. The resulting predictive model has been cross-validated by appropriate statistical tools. Finally, we obtained reliable spatially continuous predictive maps and predictive probability maps showing the areas with high probability of arsenic concentration for different levels of well-depth. Results indicate that our model fits the data well and captures a substantial amount of spatial variation. Moreover, well-depth is found to have a significant contribution in explaining the observed variation in arsenic concentration. The predictive maps that have been produced are observed to be different for various levels of well-depths and are expected to be helpful to the policy makers in preparing proper regional planning for safe drinking water.