bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coupling and Decoupling of Soil Carbon and Nutrient Cycles Across an Aridity Gradient in the Drylands of Northern China: Evidence From Ecoenzymatic Stoichiometry
Authors: Feng Jiao , Wei Kai , Chen Zhenhua , Lü Xiaotao , Tian Jihui , Wang Chao , Chen Lijun 
Published: April 2019

AbstractDrylands are characterized by stressful conditions with the limitation of both carbon (C) and nutrients, particularly nitrogen (N) and phosphorus (P). Biological C, N, and P releases from soil organic matter by enzymes are essential components for biogeochemical cycles and are sensitive to the climate in drylands. However, how the ecoenzymatic C:N:P stoichiometry responds to environmental factors (i.e., climatic and edaphic factors) over broad geographical scales remains largely unclear. We examined the patterns of ecoenzymatic C:N:P ratios across a 3,700‐km aridity gradient (0.43 < aridity < 0.97) in northern China. In wetter sites (aridity < 0.70), the relative C:N:P acquisition ratios via enzymes remained relatively constant with increasing aridity. In contrast, in drier sites (aridity > 0.70), the enzymatic C:nutrient (N and P) ratios declined as the aridity increased, while the enzymatic P:N ratios were mostly lower than those in the wetter sites. In drier sites with low C availability, the increasing carbon use efficiency and the increasing proportion of C converted to biomass (than the proportion of respiration) contributed to the declines of the enzymatic C:nutrient ratios as the aridity increased. The overall lower enzymatic P:N ratios were related to the higher soil P availability compared with N availability (higher organic P and lower soil NH4+:available P ratios) in drier sites. Overall, our findings indicate that intrinsic linkages of biological C, N, and P acquisitions and cycles were broken at the aridity threshold of 0.70, with higher acquisition efforts for N and P (particularly for N) with increasing aridity in drier sites with aridity > 0.70.
Upper Crustal Weak Zone in Central Tibet: An Implication From Three‐Dimensional Seismic Velocity and Attenuation Tomography Results
Authors: Zhou Beibei , Liang Xiaofeng , Lin Guoqing , Tian Xiaobo , Zhu Gaohua , Mechie James , Teng Jiwen 
Published: April 2019

AbstractA series of conjugate strike‐slip faults is the most prominent geologic feature in central Tibet and is considered to accommodate east‐west extension and coeval north‐south contraction. The development mechanism of the conjugate strike‐slip fault system is under debate because of unclear crustal physical properties and compositional variations. P and S wave arrivals from 414 local earthquakes recorded by the temporary Seismic Array Integrated Detection for a Window of Indian Continental Head array and the permanent China National Seismic Network were used for the velocity tomography, with additional P and S wave arrivals from 12 shots of the International Deep Profiling of Tibet and the Himalaya III reflection/refraction profile. The local earthquakes were simultaneously relocated with the updated velocity models. We also inverted for a three‐dimensional upper crustal Qp model with the same earthquake data set. The Vp structure near the surface shows that low‐Vp anomalies generally correspond to sedimentary basins and high‐Vp anomalies are related to exhumed metamorphic blocks in the study area. Relatively low Vp/Vs ratios in the upper crust indicate widely distributed quartz‐rich rocks. The low‐Vp zone from 0‐ to 10‐km depth (resolving depth limit) is spatially correlated with the Bangong‐Nujiang suture, possibly reflecting the compositional difference along the ophiolitic mélange belt accompanied by twin volcanic arcs from a double‐sided subduction. This interpretation is supported by relatively heterogeneous Qp values. This low‐velocity zone also implies relatively uniform stress and continuous deformation in the upper crust of central Tibet. The relatively weak materials in at least the upper crust would result in strain concentration and help the development of the conjugate strike‐slip fault system along the Bangong‐Nujiang suture.
Generation of Archaean TTG Gneisses Through Amphibole‐Dominated Fractionation
Authors: Liou Peng , Guo Jinghui 
Published: April 2019

AbstractThe early continental crust is characterized by the tonalite‐trondhjemite‐granodiorite gneisses (TTG) of Archaean terrains. There is a consensus that TTGs were formed by partial melting of hydrated mafic rocks. High‐pressure melts tend to be more trondhjemitic with higher Sr/Y ratios due to the presence of garnet and absence of plagioclase, whereas low‐pressure melts are more tonalitic with relatively lower Sr/Y ratios. Here we present a geochemical study of diorites, TTGs, and hornblendites from Eastern Hebei, North China Craton. Geochemical analyses show that dioritic parental magmas may evolve to tonalites and trondhjemites through a maximum of 27% fractional crystallization of amphibole and apatite. We also identified the cumulate apatite‐bearing hornblendite, a predicted solid fractionate and chemical complement to the TTGs. Mixing of the trondhjemite and the hornblendite can generate similar chemical compositions to the diorites in this region. The mixing trends are consistent with those predicted for fractional crystallization. Based on these analyses, we conclude that these trondhjemites and tonalites can be formed by fractional crystallization of amphiboles and accessory minerals from the calc‐alkaline diorites. Partial melting is not a unique solution to the problem of how to form the Archean TTG gneisses and how to make an Archean continent. Thick crust or lithosphere (in the garnet stability field) is also not a unique requirement. Amphibole fractionation may also cause an abrupt increase of Eu/Eu* of Archean granitoids at 3.2–3.0 Ga, which may be linked to a transition period in tectonic style at ~3 Ga in Earth's evolution.
Exploring a Variable‐Resolution Approach for Simulating Regional Climate Over the Tibetan Plateau Using VR‐CESM
Authors: Rahimi Stefan R. , Wu Chenglai , Liu Xiaohong , Brown Hunter 
Published: April 2019

AbstractThis study implements a variable resolution version of Community Earth Systems Model (VR‐CESM; regionally refined at 1/8° resolution) to assess the improvement in simulating the seasonal climate across the Tibetan Plateau (TP) at higher horizontal resolutions compared to its uniform (UN) 1° counterpart (UN‐CESM). The Weather Research and Forecasting (WRF) model, run at 12‐km horizontal grid spacing, is compared to both CESM simulations. VR‐CESM and WRF are more comparable to satellite and surface‐based observations than UN‐CESM in simulating summertime (June to August) temperature across the TP and TP foothills, respectively. WRF and VR‐CESM also more accurately simulate precipitation than UN‐CESM across the region due to more accurate terrain treatment. The number of days in which effective (>2.5 mm/day) and heavy (>25 mm/day) precipitation events are generally better captured in VR‐CESM compared to UN‐CESM and WRF. Finally, snow cover fraction in VR‐CESM is better simulated for all months compared to UN‐CESM, with the largest improvements simulated from June to August, while WRF performs even better than VR‐CESM in simulating snow cover fraction. The improvements in simulated temperature, precipitation, and snow cover are due to WRF and VR‐CESM's ability to resolve more complex topographic features rather than time step differences between the UN‐CESM and VR‐CESM experiments. While it is fairly intuitive that improved topography accuracy should bring forth more accurate simulated meteorology, this evaluation suggests that VR‐CESM is competitive or may even be preferred over regional climate models (such as WRF) when examining internal and external climate variability, as it bypasses several drawbacks associated with regional climate models.
Spatio‐temporally Resolved Methane Fluxes From the Los Angeles Megacity
Authors: Yadav Vineet , Duren Riley , Mueller Kim , Verhulst Kristal R. , Nehrkorn Thomas , Kim Jooil , Weiss Ray F. , Keeling Ralph , Sander Stanley , Fischer Marc L. , Newman Sally , Falk Matthias , Kuwayama Toshihiro , Hopkins Francesca , Rafiq Talha , Whetstone James , Miller Charles 
Published: April 2019

AbstractWe combine sustained observations from a network of atmospheric monitoring stations with inverse modeling to uniquely obtain spatiotemporal (3‐km, 4‐day) estimates of methane emissions from the Los Angeles megacity and the broader South Coast Air Basin for 2015–2016. Our inversions use customized and validated high‐fidelity meteorological output from Weather Research Forecasting and Stochastic Time‐Inverted Lagrangian model for South Coast Air Basin and innovatively employ a model resolution matrix‐based metric to disentangle the spatiotemporal information content of observations as manifested through estimated fluxes. We partially track and constrain fluxes from the Aliso Canyon natural gas leak and detect closure of the Puente Hills landfill, with no prior information. Our annually aggregated fluxes and their uncertainty excluding the Aliso Canyon leak period lie within the uncertainty bounds of the fluxes reported by the previous studies. Spatially, major sources of CH4 emissions in the basin were correlated with CH4‐emitting infrastructure. Temporally, our findings show large seasonal variations in CH4 fluxes with significantly higher fluxes in winter in comparison to summer months, which is consistent with natural gas demand and anticorrelated with air temperature. Overall, this is the first study that utilizes inversions to detect both enhancement (Aliso Canyon leak) and reduction (Puente Hills) in CH4 fluxes due to the unintended events and policy decisions and thereby demonstrates the utility of inverse modeling for identifying variations in fluxes at fine spatiotemporal resolution.
The Impact of Human‐Induced Climate Change on Regional Drought in the Horn of Africa
Authors: Marthews T. R. , Jones R. G. , Dadson S. J. , Otto F. E. L. , Mitchell D. , Guillod B. P. , Allen M. R. 
Published: April 2019

AbstractA severe drought hit the Greater Horn of Africa (GHA) in 2014, but it remains unclear whether this extreme event was attributable to anthropogenic climate change or part of longer‐term natural cycles. Precipitation patterns are known to be changing across the GHA, but trajectories in land surface variables are much less well known. We simulated the GHA land surface environment to assess the balance between natural cycles and human‐induced climate change. Using a new form of event attribution study where we focused on both climate variables and also directly simulated land surface variables, we combined publicly volunteered distributed computing with land surface simulations to quantify land surface responses. Uncertainty was quantified both for climate model and land surface model outputs. We identified two distinct “drought trajectories” in the GHA bimodal seasonality area during the March–May (Long Rains season) of 2014. Human‐induced climate change may have resulted in regions from Lake Nalubaale (Lake Victoria) to Northern Kenya receiving less precipitation in this season and having up to 20% higher probability of drought‐level evapotranspiration rates (increasing drought). In contrast, the simulated anthropogenic climate change signal for this season induced somewhat wetter conditions and up to 20% lower probability of drought‐level evapotranspiration in Eastern Ethiopia, Southern Somalia, and coastal Kenya (decreasing drought). Uncertainties in our modeling system varied by region and variable of focus, but broadly we found that land surface simulation uncertainty neither added significantly to climate model uncertainty nor significantly reduced it.
Seasonal Sources of Whole‐Lake CH4 and CO2 Emissions From Interior Alaskan Thermokarst Lakes
Authors: Elder C. D. , Schweiger M. , Lam B. , Crook E. D. , Xu X. , Walker J. , Walter Anthony K. M. , Czimczik C. I. 
Published: April 2019

AbstractThe lakes that form via ice‐rich permafrost thaw emit CH4 and CO2 to the atmosphere from previously frozen ancient permafrost sources. Despite this potential to positively feedback to climate change, lake carbon emission sources are not well understood on whole‐lake scales, complicating upscaling. In this study, we used observations of radiocarbon (14C) and stable carbon (13C) isotopes in the summer and winter dissolved CH4 and CO2 pools, ebullition‐CH4, and multiple independent mass balance approaches to characterize whole‐lake emission sources and apportion annual emission pathways. Observations focused on five lakes with variable thermokarst in interior Alaska. The 14C age of discrete ebullition‐CH4 seeps ranged from 395 ± 15 to 28,240 ± 150 YBP across all study lakes; however, dissolved 14CH4 was younger than 4,730 YBP. In the primary study lake, Goldstream L., the integrated whole‐lake 14C age of ebullition‐CH4, as determined by three different approaches, ranged from 3,290 to 6,740 YBP. A new dissolved‐14C‐CH4‐based approach to estimating ebullition 14C age and flux showed close agreement to previous ice‐bubble surveys and bubble‐trap flux estimates. Differences in open water versus ice‐covered dissolved gas concentrations and their 14C and 13C isotopes revealed the influence of winter ice trapping and forcing ebullition‐CH4 into the underlying water column, where it comprised 50% of the total dissolved CH4 pool by the end of winter. Across the study lakes, we found a relationship between the whole‐lake 14C age of dissolved CH4 and CO2 and the extent of active thermokarst, representing a positive feedback system that is sensitive to climate warming.
Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model
Authors: Chen Jinsong , Zhu Qing , Riley William J. , He Yujie , Randerson James T. , Trumbore Susan 
Published: April 2019

AbstractWe evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1‐ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and Δ14C values around the world. We analyzed observed and simulated SOC stocks and Δ14C values using machine learning methods at the Earth System Model grid cell scale (~200 km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and Δ14C values near the surface but underestimated Δ14C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC Δ14C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (≤30 cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and Δ14C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical‐chemical protection of SOC via root activities. Allowing for grid cell‐specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted Δ14C values and SOC content. Our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models.
Time Scale Decomposition of Climate and Correction of Variability Using Synthetic Samples of Stable Distributions
Authors: Gomez‐Garcia M. , Matsumura A. , Ogawada D. , Takahashi K. 
Published: April 2019

AbstractThe bias correction of the General Circulation Model (GCM) outputs has become a routine step that is taken in climate change impact assessments. To responsibly support the decision‐making processes, the climate‐modeling community has been debating about the conceptual requirements that bias‐correction methods should fulfill. Bearing in mind these requirements, we propose to decompose atmospheric variables into three temporal elements that represent the climate mean state, the interannual variability, and the daily variability. This decomposition is aimed at correcting the biases at one time scale without affecting the simulated climate (mean state) trend or the distributional properties at other time scales. The novelty of the proposed approach is, nevertheless, marked by the adjustment of interannual and daily variability that is made by replacing the GCM‐simulated data with synthetic samples drawn from Stable Distributions (SDs) that are fitted to the observed variability. The replacement prevents the transfer of the sampling variability of the calibration period and gives the corrected data the distributional properties of the observed climate. The employment of SDs was motivated by the fact that the climate‐change‐induced changes in the scale, the symmetry, and the frequency of extremes can be measured and applied to the SDs of the observed data. We correct the biases in the GCM‐simulated temperature and precipitation over northern South America using our proposed approach and two other existing ones. Our proposed method is capable of not only preserving the simulated climate trends but also reproducing the observed extremes as well as a more flexible method based on nonparametric distributions.
A Mechanistic Model for Relative Permeability of Gas and Water Flow in Hydrate‐Bearing Porous Media With Capillarity
Authors: Singh Harpreet , Mahabadi Nariman , Myshakin Evgeniy M. , Seol Yongkoo 
Published: April 2019

AbstractLack of mechanistic models to describe petrophysical properties of mobile phases in gas hydrate‐bearing sediments is one of the key challenges in accurately predicting gas production. The major drawback of empirical models that are used to fit a relative permeability curve for mobile phases in gas hydrate‐bearing sediments is that they are based on experimental data, which are limited, and not able to account for hydrate morphology in pore space. This study proposes a relative permeability model that is mechanistic in nature and developed to account capillarity by building on the original nonempirical relative permeability model that assumes negligible capillary pressure. The proposed model implicitly accounts for capillarity with the help of four empirical parameters (two for each mobile phase) that incorporate each mobile phase pressure. It is shown that the proposed model provides an improved match to relative permeability data (derived from pore‐scale simulation of gas hydrate‐bearing sediments) than nonempirical relative permeability by accounting for the effect of capillary pressure. Additionally, unlike fully empirical models that can predict relative permeabilities reliably only at gas hydrate saturations for which experimental data are available, the proposed model only requires fitting the empirical parameters once with experimental data at any single gas hydrate saturation and then it can then be used to predict relative permeability at any gas hydrate saturation. The mechanistic nature of the proposed model allows studying relative permeability of hydrate‐bearing sediments as a function of hydrate morphology and wettability (fluid phase distribution) besides other physical parameters of the model (e.g., porosity, gas, and water residual saturation). Based on the sensitivity analysis of different hydrate morphologies on gas/water relative permeability, it is found that gas relative permeability is sensitive to hydrate morphologies, while water relative permeability shows little dependency on hydrate localization in pore space.
Improving the Spectral Analysis of Hydrological Signals to Efficiently Constrain Watershed Properties
Authors: Schuite J. , Flipo N. , Massei N. , Rivière A. , Baratelli F. 
Published: April 2019

AbstractThe footprint of catchment properties on water flow is reflected into hydrological signals, such as stream discharge. Here we demonstrate that it is possible to constrain catchment properties from the spectral analysis of hydrological signals but only when an appropriate transfer function (TF) is used for interpretation. We show that the appropriate theoretical TF, newly derived, is the only one to robustly describe a large diversity of experimental TFs that could be encountered in nature, because it entails the role of diffuse overflow and flow through the vadose zone, which have never been considered in spectral approaches before. The properties that may be estimated are the characteristic time scales of transfer in each compartment (surface, vadose zone, and aquifer) and the flow partitioning between surface and subsurface. We validate our approach by comparing the new and previous theoretical TFs to experimental TFs generated by a physically based distributed hydrological model, for a wide range of properties. The results confirm that without the use of the new TF, the interpretation of observed spectra may often lead to severe misestimations of catchment properties. The potential of the new TF to constrain catchment characteristics is exemplified by analyzing real hydrological signals from two watersheds with distinct behaviors. We finally discuss the broad implications of our findings and how they may contribute to a variety of topics in hydrology, thereby opening the way to a more widespread and robust use of spectral analysis to describe hydrosystems from effective rainfall, river discharge, and piezometric data.
Bortezomib-inducible long non-coding RNA myocardial infarction associated transcript is an oncogene in multiple myeloma that suppresses miR-29b
Authors: Fu Yunfeng , Liu Xiao , Zhang Fangrong , Jiang Siyi , Liu Jing , Luo Yanwei 
Published: April 2019

AbstractClinical outcomes of patients with multiple myeloma (MM) have almost doubled the overall survival over the last decade owing to the use of proteasome inhibitor such as bortezomib (BTZ). However, some patients with MM develop primary resistance to BTZ, whereas others develop resistance after treatment. In this study, we investigated relationships between BTZ resistance and dysfunction of long non-coding RNAs (lncRNAs) in patients with MM. Bone marrow samples were collected from patients with MM and healthy donors for lncRNA microarray and survival analyses. To investigate functions and underlying mechanisms of lncRNA-mediated BTZ resistance in MM, we performed CCK-8 assays, flow cytometry analyses, dual luciferase report gene assays, and RNA pulldown assays with samples from nude mice carrying tumor xenografts and in clinical samples. Differentially expressed lncRNA myocardial infarction associated transcripts (MIAT) were highly expressed in patients with MM compared with healthy controls, and were predictive of poor survival outcomes. Moreover, MIAT expression was significantly increased in BTZ-resistant patients with MM compared with newly diagnosed patients with MM, and was identified as a BTZ-inducible lncRNA. Specifically, BTZ upregulated MIAT expression through increased stat1 phosphorylation. Silencing of MIAT inhibited MM cell growth and sensitized MM cells to BTZ by negatively regulating miR-29b. Our data demonstrated the utility of MIAT as a tool for overcoming BTZ resistance in patients with MM.