186 research outputs found

    Underestimated Interannual Variability of Terrestrial Vegetation Production by Terrestrial Ecosystem Models

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    Terrestrial vegetation production is a critical component of the global carbon cycle and plays an important role in regulating terrestrial carbon sinks (Beer et al., 2010; Jung et al., 2017). In particular, interannual variability (IAV) in vegetation production substantially regulates terrestrial carbon sinks (Desai et al., 2010), atmospheric CO 2 concentration (Yuan et al., 2019), and the climate system (Poulter et al., 2014). For example, previous studies indicated that the IAV in global gross vegetation production strongly correlates with IAV in atmospheric CO 2 concentration (Reichstein et al., 2013). With the rising frequency of extreme climate events, vegetation production shows an increasing interannual fluctuation

    Flood risk mapping for the area with mixed floods and human impact: a case study of Yarkant River Basin in Xinjiang, China

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    Flooding has been causing severe consequences worldwide, including loss of human life and damage to property. Flood risk mapping, as a nonstructural measure, is efficient for flood protection and disaster alleviation. This study aims at completing the flood risk mapping of the region located at the middle reaches of the Yarkant River Oasis in western China, which has a dry climate and suffers from mixed flooding consisting of glacial outburst floods (GLOFs) and many other floods. In view of the complexity of flooding in the area, the study adopts two typical types of scenarios, namely overflow scenarios and dike-break scenarios, to complete the flood risk mapping. The MIKE FLOOD 1D/2D coupled model is used for two-dimensional flood flow simulation to compute the inundation depths and duration for flood risk assessment. The spatial overlay analysis was then used to combine the modeling results and land use/land cover layers with socioeconomic data to generate flood risk maps and damage losses under different scenarios. It is noted that evaporation and infiltration losses in the study area are not negligible because of the long flood process, the low precipitation, and dry surface/subsurface conditions. Due to the insufficient evaporation and infiltration data, a new method of synthesis loss rate is proposed to compute the evaporation/infiltration loss rate. Based on the water balance principle, the upstream and downstream flow data is utilized to calculate the water attenuation, which is then used to estimate the evaporation/infiltration loss rate. The proposed method can solve the problem of calculating evaporation/infiltration loss rates during the flooding process in such data-scarce areas. The flood risk mapping results indicate that the flood risk is high along the Yarkant River and that floods can cause severe inundation losses

    Heavy metal contamination collapses trophic interactions in the soil microbial food web via bottom-up regulation

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    The soil microbial food web plays a vital role in soil health, nutrient cycling and agricultural productivity. Notably, there is a distinct paucity of information regarding the effects of heavy metal contamination on trophic-level interactions within the microbial food web of agricultural soils, which experience appreciably metal contamination worldwide. Herein, we investigated trophic interactions among predators (protists), their preys (bacteria and fungi) and competitors (nematodes) under four metal contamination levels using high-throughput sequencing and a laboratory verification experiment. Metal contamination decreased growth of protist-preferential prey (e.g., small-sized and gram-negative bacteria), increased the growth of protist-nonpreferential prey (e.g., pathogenic fungi and Actinobacteria), and had a limited effect on the soil protist-competitor (i.e., nematodes). This resulted in a considerable decrease in the diversity and abundance of protistan consumers and a re-arrangement of their interactions with other organisms. From a systemic view, the direct link was weaker between heavy metal contamination and the protist community than the indirect linkage, i.e., metal-induced changes in the prey community. We further validated these results with laboratory incubation trials that documented growth inhibition of protist (Colpoda) and protist-preferential prey (Spingomonas) versus growth stimulation of protist-nonpreferential prey (Arthrobacter) under metal contamination. These findings indicate that metal contamination collapses trophic-level interactions within the soil microbial food web via bottom-up regulation, providing important implications for managing trophic interactions to maintain agricultural ecosystem services under the challenge of worldwide metal contamination

    Heavy metal effects on multitrophic level microbial communities and insights for ecological restoration of an abandoned electroplating factory site

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    The response of soil microbes to heavy metal pollution provides a metric to evaluate the soil health and ecological risks associated with heavy metal contamination. However, a multitrophic level perspective of how soil microbial communities and their functions respond to long-term exposure of multiple heavy metals remains unclear. Herein, we examined variations in soil microbial (including protists and bacteria) diversity, functional guilds and interactions along a pronounced metal pollution gradient in a field surrounding an abandoned electroplating factory. Given the stressful soil environment resulting from extremely high heavy metal concentrations and low nutrients, beta diversity of protist increased, but that of bacteria decreased, at high versus low pollution sites. Additionally, the bacteria community showed low functional diversity and redundancy at the highly polluted sites. We further identified indicative genus and "generalists" in response to heavy metal pollution. Predatory protists in Cercozoa were the most sensitive protist taxa with respect to heavy metal pollution, whereas photosynthetic protists showed a tolerance for metal pollution and nutrient deficiency. The complexity of ecological networks increased, but the communication among the modules disappeared with increasing metal pollution levels. Subnetworks of tolerant bacteria displaying functional versatility (Blastococcus, Agromyces and Opitutus) and photosynthetic protists (microalgae) became more complex with increasing metal pollution levels, indicating their potential for use in bioremediation and restoration of abandoned industrial sites contaminated by heavy metals

    Energy loss enhancement of very intense proton beams in dense matter due to the beam-density effect

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    Thoroughly understanding the transport and energy loss of intense ion beams in dense matter is essential for high-energy-density physics and inertial confinement fusion. Here, we report a stopping power experiment with a high-intensity laser-driven proton beam in cold, dense matter. The measured energy loss is one order of magnitude higher than the expectation of individual particle stopping models. We attribute this finding to the proximity of beam ions to each other, which is usually insignificant for relatively-low-current beams from classical accelerators. The ionization of the cold target by the intense ion beam is important for the stopping power calculation and has been considered using proper ionization cross section data. Final theoretical values agree well with the experimental results. Additionally, we extend the stopping power calculation for intense ion beams to plasma scenario based on Ohm's law. Both the proximity- and the Ohmic effect can enhance the energy loss of intense beams in dense matter, which are also summarized as the beam-density effect. This finding is useful for the stopping power estimation of intense beams and significant to fast ignition fusion driven by intense ion beams

    Spatiotemporal Variations in the Sensitivity of Vegetation Growth to Typical Climate Factors on the Qinghai–Tibet Plateau

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    Gaining knowledge about vegetation sensitivity in response to climate change is a current research priority in the context of accelerated shifts generated by global warming, especially for the Qinghai–Tibet Plateau (QTP), where vegetation is known to be highly sensitive to ongoing climate change. However, the temporal variability of vegetation sensitivity in response to climate change is still poorly understood on the QTP. Here, we articulate the interannual variability of the vegetation sensitivity in response to typical climate factors, including temperature, solar radiation, and water availability, on the QTP during 2000–2021, using a variety of indicators characterizing vegetation dynamics, including the Leaf Area Index (LAI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and solar-induced chlorophyll fluorescence (SIF) data. The results indicate that temperature exerted positive impacts on forests, grasslands, and barren or sparsely vegetated areas (BSVs). However, all the land-cover types showed decreasing sensitivity to temperature variability. Solar radiation had a positive impact on forests, while it had a negative impact on grasslands and BSVs. An increasing trend was observed for forests, while a decreasing trend was found for grasslands and BSVs regarding their sensitivity to solar radiation. Water availability exerted a positive impact on grasslands and BSVs, and no obvious impact direction could be determined for forests. Over the last two decades, forests and BSVs exhibited increasing sensitivity to water availability, and no obvious trend was observed for grasslands. Overall, temperature was the most important climate factor, followed by solar radiation and water availability, regarding the regulation of vegetation sensitivity on the QTP. Spatially, temperature and solar radiation jointly dominated the vegetation sensitivity in the central to eastern QTP. Conversely, water availability dominated the sensitivity of forests in the southeastern QTP and grasslands in the northeastern and southwestern QTP. This study provides theoretical support for the ecological conservation and management of the QTP in the context of ongoing climate change

    Design of PEMFC bipolar plate cooling flow field based on fractal theory

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    During the operation of the proton exchange membrane fuel cell (PEMFC), the chemical reaction yields a large amount of heat. Long-term operation may cause local overheating problems which damage the proton exchange membrane structure, pull down the fuel cell performance drastically. Aiming at improving the temperature distribution and cooling capacity of PEMFC, a novel tree-shaped fractal fuel cell bipolar plate cooling flow field is proposed. The polarization curve, current density distribution, maximum temperature, temperature uniformity, cooling hydraulic pressure drop and the water content of proton exchange membrane are investigated for the fractal cooling flow field with different number of dimensions. The results show that the tree-shaped fractal cooling flow field can achieve better distributions of coolant and temperature uniformity than parallel cooling flow field. The maximum temperature reduces from 340.7 K to 337.8 K, and temperature uniformity index reduces from 1.47 to 0.45, respectively. Compared with the serpentine cooling flow field, the tree-shaped fractal cooling flow field effectively solves the problem of excessive cooling pressure drop and reduces the parasitic power loss while ensuring efficient cooling performance. This novel cooling flow field design offers an excellent solution to solve the local overheating of PEMFC

    Computational and Experimental Investigation of the Selective Adsorption of Indium/Iron Ions by the Epigallocatechin Gallate Monomer

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    Selective recovery of indium has been widely studied to improve the resource efficiency of critical metals. However, the interaction and selective adsorption mechanism of indium/iron ions with tannin-based adsorbents is still unclear and hinders further optimization of their selective adsorption performance. In this study, the epigallocatechin gallate (EGCG) monomer, which is the key functional unit of persimmon tannin, was chosen to explore the ability and mechanism of selective separation/extraction of indium from indium–iron mixture solutions. The density functional theory calculation results indicated that the deprotonated EGCG was easier to combine with indium/iron cations than those of un-deprotonated EGCG. Moreover, the interaction of the EGCG–Fe(III) complex was dominated by chelation and electrostatic interaction, while that of the EGCG–In(III) complex was controlled by electrostatic interactions and aromatic ring stacking effects. Furthermore, the calculation of binding energy verified that EGCG exhibited a stronger affinity for Fe(III) than that for In(III) and preferentially adsorbed iron ions in acidic or neutral solutions. Further experimental results were consistent with the theoretical study, which showed that the Freundlich equilibrium isotherm fit the In(III) and Fe(III) adsorption behavior very well, and the Fe(III) adsorption processes followed a pseudo-second-order model. Thermodynamics data revealed that the adsorption of In(III) and Fe(III) onto EGCG was feasible, spontaneous, and endothermic. The adsorption rate of the EGCG monomer for Fe(III) in neutral solution (1:1 mixed solution, pH = 3.0) was 45.7%, 4.3 times that of In(III) (10.7%). This study provides an in-depth understanding of the relationship between the structure of EGCG and the selective adsorption capacity at the molecular level and provides theoretical guidance for further optimization of the selective adsorption performance of structurally similar tannin-based adsorbents

    Tracking Global Patterns of Drought‐Induced Productivity Loss Along Severity Gradient

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    International audienceDrought is a major environmental risk for land ecosystems that causes significant mortality and considerable productivity reductions (Allen et al., 2010). In the context of global changes, droughts are increasing rapidly both in frequency and severity (Sheffield & Wood, 2008; Trenberth et al., 2014). Along with this, Earth system model projections show that the frequencies of extreme and severe droughts will vastly expand in the next decades (Dai, 2013; Zhai et al., 2020). For instance, a recent projection by 13 CMIP (coupled model intercomparison project) models showed that the frequencies of extreme droughts were likely to expand to 3.8 times in 2075-2099 relative to 1850-1999 under the high emission scenario RCP (representative concentration pathway) 8.5 (C. Xu, McDowell et al., 2019). The projected increase in drought severities and extreme events are consistent with the observed patterns over the last few decades (Chiang et al., 2021; Vicente-Serrano et al., 2014). For instance, rising temperatures have led to a significant increase in drought severity and the occurrences of extreme droughts in the European region (Grillakis, 2019; Markonis et al., 2021). Drought causes significant reductions in gross primary productivities (GPP)

    A Bayesian reanalysis of the Standard versus Accelerated Initiation of Renal-Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial

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    Background Timing of initiation of kidney-replacement therapy (KRT) in critically ill patients remains controversial. The Standard versus Accelerated Initiation of Renal-Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial compared two strategies of KRT initiation (accelerated versus standard) in critically ill patients with acute kidney injury and found neutral results for 90-day all-cause mortality. Probabilistic exploration of the trial endpoints may enable greater understanding of the trial findings. We aimed to perform a reanalysis using a Bayesian framework. Methods We performed a secondary analysis of all 2927 patients randomized in multi-national STARRT-AKI trial, performed at 168 centers in 15 countries. The primary endpoint, 90-day all-cause mortality, was evaluated using hierarchical Bayesian logistic regression. A spectrum of priors includes optimistic, neutral, and pessimistic priors, along with priors informed from earlier clinical trials. Secondary endpoints (KRT-free days and hospital-free days) were assessed using zero–one inflated beta regression. Results The posterior probability of benefit comparing an accelerated versus a standard KRT initiation strategy for the primary endpoint suggested no important difference, regardless of the prior used (absolute difference of 0.13% [95% credible interval [CrI] − 3.30%; 3.40%], − 0.39% [95% CrI − 3.46%; 3.00%], and 0.64% [95% CrI − 2.53%; 3.88%] for neutral, optimistic, and pessimistic priors, respectively). There was a very low probability that the effect size was equal or larger than a consensus-defined minimal clinically important difference. Patients allocated to the accelerated strategy had a lower number of KRT-free days (median absolute difference of − 3.55 days [95% CrI − 6.38; − 0.48]), with a probability that the accelerated strategy was associated with more KRT-free days of 0.008. Hospital-free days were similar between strategies, with the accelerated strategy having a median absolute difference of 0.48 more hospital-free days (95% CrI − 1.87; 2.72) compared with the standard strategy and the probability that the accelerated strategy had more hospital-free days was 0.66. Conclusions In a Bayesian reanalysis of the STARRT-AKI trial, we found very low probability that an accelerated strategy has clinically important benefits compared with the standard strategy. Patients receiving the accelerated strategy probably have fewer days alive and KRT-free. These findings do not support the adoption of an accelerated strategy of KRT initiation
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