6,091 research outputs found

    Biophysical controls on light response of net CO<inf>2</inf>exchange in a winter wheat field in the North China Plain

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    To investigate the impacts of biophysical factors on light response of net ecosystem exchange (NEE), CO2 flux was measured using the eddy covariance technique in a winter wheat field in the North China Plain from 2003 to 2006. A rectangular hyperbolic function was used to describe NEE light response. Maximum photosynthetic capacity (Pmax) was 46.6±4.0 μmol CO2 m-2 s-1 and initial light use efficiency (α) 0.059±0.006 μmol μmol-1 in April-May, two or three times as high as those in March. Stepwise multiple linear regressions showed that Pmax increased with the increase in leaf area index (LAI), canopy conductance (gc) and air temperature (Ta) but declined with increasing vapor pressure deficit (VPD) (P25°C or VPD>1.1-1.3 kPa, NEE residual increased with the increase in Ta and VPD (P<0.001), indicating that temperature and water stress occurred. When gc was more than 14 mm s-1 in March and May and 26 mm s-1 in April, the NEE residuals decline disappeared, or even turned into an increase in gc(P<0.01), implying shifts from stomatal limitation to non-stomatal limitation on NEE. Although the differences between sunny and cloudy sky conditions were unremarkable for light response parameters, simulated net CO2 uptake under the same radiation intensity averaged 18% higher in cloudy days than in sunny days during the year 2003-2006. It is necessary to include these effects in relevant carbon cycle models to improve our estimation of carbon balance at regional and global scales. © 2014 Tong et al

    Wave equation-based reflection tomography of the 1992 Landers earthquake area

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    In the framework of a recent wave equation-based traveltime seismic tomography, we show that incorporating Moho-reflected phases (PmP and SmS) in addition to the direct P and S phases can significantly increase tomography resolution in the lower crust and this may provide additional evidence to resolve important tectonic issues. To highlight the resolving power of the new strategy, we apply it in the region around the 1992 Landers earthquake (Mw = 7.3) in Southern California using seismic arrivals from local earthquakes, obtaining 3-D high-resolution P and S wave crustal velocity models and Poisson''s ratio structures. In the upper crust, our method confirmed features that had been previously found. However, in the middle-to-lower crust, we found low-velocity anomalies on the southeastern section of the San Jacinto Fault and high Vp and low Vs structures to the west of the Big Bear earthquake, which may be related to upwelling of partial melt from the mantle

    Urban Crime Trends Analysis and Occurrence Possibility Prediction based on Light Gradient Boosting Machine

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    Big Data and Machine learning have been increasingly used to fight against Urban crimes. Our goal is to discover the connection between crime-related factors and the underlying complex crime pattern. Therefore, to predict the possibility of crime occurrence. Light Gradient Boosting Machine (LightGBM) Model is adopted in our study to predict the crime occurrence possibility based on actual crime information. We found that the prediction results are approximately consistent with an actual variation. We hope this work could help with crime prevention and policing

    Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

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    Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100&ndash;800 mm yr&minus;1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001&ndash;2015. Growing season ANPP in the arid zone (100&ndash;300 mm yr−1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300&ndash;700 mm yr&minus;1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after  &gt; 14 consecutive dry days and that a rainfall intensity of  ∼ 13 mm day&minus;1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere

    Angle-Resolved X-Ray Circular and Magnetic Circular Dichroisms: Definitions and Applications

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    We introduce definitions of angle-resolved x-ray circular dichroism (ARXCD) and magnetic x-ray circular dichroism (ARMXCD). As defined, the much larger effect of circular dichroism (ARXCD) is separated from the smaller magnetic (ARMXCD) effect. In all materials, ARXCD is zero along mirror planes while nonzero elsewhere. ARMXCD is nonzero only in magnetic materials. The measurement and analysis of ARMXCD allow element specific surface magnetism and surface structure as well as their inter-relationship to be studied as functions of the outgoing electron\u27s direction

    Towards sustainability: An assessment of an urbanisation bubble in China using a hierarchical - Stochastic multicriteria acceptability analysis - Choquet integral method

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    Urbanisation bubbles have become an increasingly serious problem. Attention has been paid to the speed of urbanisation; however, the issue of quality has been neglected, particularly in the case of China. Therefore, the aim of this research is to evaluate China's urbanisation bubbles by employing a hierarchical - stochastic multicriteria acceptability analysis (SMAA) - Choquet integral method. In order to highlight regional disparities, we measure the urbanisation bubbles at a provincial level. Our study aggregates the urbanisation bubble indices using the Choquet integral preference model, and considers the interactions between various indicators. Furthermore, robust ordinal regression and SMAA are applied to resolve the robustness issues associated with the entire set of weights assigned to the urbanisation bubble composite indicator. In addition, by employing a multiple criteria hierarchy process, the study aggregates urbanisation bubble indices not only at the comprehensive level, but also at the intermediate levels of the hierarchy. Our findings suggest that the ranking of urbanisation bubbles is positively related to the level of regional development. This study contributes to the evaluation of regional urbanisation and sustainable development

    Opportunities for improving waterlogging tolerance in cereal crops—Physiological traits and genetic mechanisms

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    Waterlogging occurs when soil is saturated with water, leading to anaerobic conditions in the root zone of plants. Climate change is increasing the frequency of waterlogging events, resulting in considerable crop losses. Plants respond to waterlogging stress by adventitious root growth, aerenchyma formation, energy metabolism, and phytohormone signalling. Genotypes differ in biomass reduction, photosynthesis rate, adventitious roots development, and aerenchyma formation in response to waterlogging. We reviewed the detrimental effects of waterlogging on physiological and genetic mechanisms in four major cereal crops (rice, maize, wheat, and barley). The review covers current knowledge on waterlogging tolerance mechanism, genes, and quantitative trait loci (QTL) associated with waterlogging tolerance-related traits, the conventional and modern breeding methods used in developing waterlogging tolerant germplasm. Lastly, we describe candidate genes controlling waterlogging tolerance identified in model plants Arabidopsis and rice to identify homologous genes in the less waterlogging-tolerant maize, wheat, and barley
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