452 research outputs found

    Loss of Rubidium and Potassium from Barley Roots on Sudden Chilling

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    Global oceanic production of nitrous oxide

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    We use transient time distributions calculated from tracer data together with in situ measurements of nitrous oxide (N2O) to estimate the concentration of biologically produced N2O and N2O production rates in the ocean on a global scale. Our approach to estimate the N2O production rates integrates the effects of potentially varying production and decomposition mechanisms along the transport path of a water mass.We estimate that the oceanic N2O production is dominated by nitrification with a contribution of only approximately 7 per cent by denitrification. This indicates that previously used approaches have overestimated the contribution by denitrification. Shelf areas may account for only a negligible fraction of the global production; however, estuarine sources and coastal upwelling of N2O are not taken into account in our study. The largest amount of subsurface N2O is produced in the upper 500 m of the water column. The estimated global annual subsurface N2O production ranges from 3.1+/-0.9 to 3.4+/-0.9 Tg N yr^-1. This is in agreement with estimates of the global N2O emissions to the atmosphere and indicates that a N2O source in the mixed layer is unlikely. The potential future development of the oceanic N2O source in view of the ongoing changes of the ocean environment (deoxygenation, warming, eutrophication and acidification) is discussed

    Development and application of process-based simulation models for cotton production: a review of past, present, and future directions

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    The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeastern United States in the 1960's and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation models, examines applications of the models since the turn of the century, and identifies opportunities for improving models and their use in cotton research and decision support. Cotton models reviewed include those specific to cotton (GOSSYM, Cotton2K, COTCO2, OZCOT, and CROPGRO-Cotton) and generic crop models that have been applied to cotton production (EPIC, WOFOST, SUCROS, GRAMI, CropSyst, and AquaCrop). Model application areas included crop water use and irrigation water management, nitrogen dynamics and fertilizer management, genetics and crop improvement, climatology, global climate change, precision agriculture, model integration with sensor data, economics, and classroom instruction. Generally, the literature demonstrated increased emphasis on cotton model development in the previous century and on cotton model application in the current century. Although efforts to develop cotton models have a 40-year history, no comparisons among cotton models were reported. Such efforts would be advisable as an initial step to evaluate current cotton simulation strategies. Increasingly, cotton simulation models are being applied by non-traditional crop modelers, who are not trained agronomists but wish to use the models for broad economic or life cycle analyses. While this trend demonstrates the growing interest in the models and their potential utility for a variety of applications, it necessitates the development of models with appropriate complexity and ease-of-use for a given application, and improved documentation and teaching materials are needed to educate potential model users. Spatial scaling issues are also increasingly prominent, as models originally developed for use at the field scale are being implemented for regional simulations over large geographic areas. Research steadily progresses toward the advanced goal of model integration with variable-rate control systems, which use real-time crop status and environmental information to spatially and temporally optimize applications of crop inputs, while also considering potential environmental impacts, resource limitations, and climate forecasts. Overall, the review demonstrates a languished effort in cotton simulation model development, but the application of existing models in a variety of research areas remains strong and continues to grow

    Biological sources and sinks of nitrous oxide and strategies to mitigate emissions

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    Nitrous oxide (N 2 O) is a powerful atmospheric greenhouse gas and cause of ozone layer depletion. Global emissions continue to rise. More than two-thirds of these emissions arise from bacterial and fungal denitrification and nitrification processes in soils, largely as a result of the application of nitrogenous fertilizers. This article summarizes the outcomes of an interdisciplinary meeting, ‘Nitrous oxide (N 2 O) the forgotten greenhouse gas’, held at the Kavli Royal Society International Centre, from 23 to 24 May 2011. It provides an introduction and background to the nature of the problem, and summarizes the conclusions reached regarding the biological sources and sinks of N 2 O in oceans, soils and wastewaters, and discusses the genetic regulation and molecular details of the enzymes responsible. Techniques for providing global and local N 2 O budgets are discussed. The findings of the meeting are drawn together in a review of strategies for mitigating N 2 O emissions, under three headings, namely: (i) managing soil chemistry and microbiology, (ii) engineering crop plants to fix nitrogen, and (iii) sustainable agricultural intensification. </jats:p

    Methane emission from high-intensity marine gas seeps in the Black Sea into the atmosphere

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    Submarine high‐intensity methane seeps have been surveyed in the Sorokin Trough and Paleo Dnepr Area in the Black Sea from May to June, 2003 to estimate the sea‐air methane flux. The Sorokin Trough mud volcano area in around 2080 m water depth shows no direct effects on the methane concentration in the surface water and the atmosphere (average methane saturation ratios (SR) of 143%). The average sea‐air methane flux can be determined as 0.2–0.57 nmol m−2 s−1, using two different sea‐air gas exchange models; mean wind speed were extraordinary low throughout the cruise (1.16 m s−1). The investigations in the Paleo Dnepr Area (60 to 800 m water depth) reflects a more diverse pattern. Spots of high methane concentrations in the surface water have been recorded above a seep location in around 90 m water depth (SR up to 294%). The air‐sea methane flux above this seep site (0.96–2.32 nmol m−2 s−1) is 3 times higher than calculated for the surrounding shelf (0.32–0.77 nmol m−2 s−1) and 5 times higher than assessed for open Black Sea waters (water depth > 200 m, 0.19–0.47 nmol m−2 s−1)

    Protein Pattern Formation

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    Protein pattern formation is essential for the spatial organization of many intracellular processes like cell division, flagellum positioning, and chemotaxis. A prominent example of intracellular patterns are the oscillatory pole-to-pole oscillations of Min proteins in \textit{E. coli} whose biological function is to ensure precise cell division. Cell polarization, a prerequisite for processes such as stem cell differentiation and cell polarity in yeast, is also mediated by a diffusion-reaction process. More generally, these functional modules of cells serve as model systems for self-organization, one of the core principles of life. Under which conditions spatio-temporal patterns emerge, and how these patterns are regulated by biochemical and geometrical factors are major aspects of current research. Here we review recent theoretical and experimental advances in the field of intracellular pattern formation, focusing on general design principles and fundamental physical mechanisms.Comment: 17 pages, 14 figures, review articl

    Emergence of fractal geometries in the evolution of a metabolic enzyme

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    Fractals are patterns that are self-similar across multiple length-scales. Macroscopic fractals are common in nature; however, so far, molecular assembly into fractals is restricted to synthetic systems. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into SierpiƄski triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution
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