Changes in plant species richness distribution in Tibetan alpine grasslands under different precipitation scenarios

Species richness is the core of biodiversity-ecosystem functioning (BEF) research. Nevertheless, it is difficult to accurately predict changes in plant species richness under different climate scenarios, especially in alpine biomes. In this study, we surveyed plant species richness from 2009 to 2017 in 75 alpine meadows (AM), 199 alpine steppes (AS), and 71 desert steppes (DS) in the Tibetan Autonomous Region, China. Along with 20 environmental factors relevant to species settlement, development, and survival, we first simulated the spatial pattern of plant species richness under current climate conditions using random forest modelling. Our results showed that simulated species richness matched well with observed values in the field, showing an evident decrease from meadows to steppes and then to deserts. Summer precipitation, which ranked first among the 20 environmental factors, was further confirmed to be the most critical driver of species richness distribution. Next, we simulated and compared species richness patterns under four different precipitation scenarios, increasing and decreasing summer precipitation by 20% and 10%, relative to the current species richness pattern. Our findings showed that species richness in response to altered precipitation was grassland-type specific, with meadows being sensitive to decreasing precipitation, steppes being sensitive to increasing precipitation, and deserts remaining resistant. In addition, species richness at low elevations was more sensitive to decreasing precipitation than to increasing precipitation, implying that droughts might have stronger influences than wetting on species composition. In contrast, species richness at high elevations (also in deserts) changed slightly under different precipitation scenarios, likely due to harsh physical conditions and small species pools for plant recruitment and survival. Finally, we suggest that policymakers and herdsmen pay more attention to alpine grasslands in central Tibet and at low elevations where species richness is sensitive to precipitation changes

A Tensor-Based Framework for Studying Eigenvector Multicentrality in Multilayer Networks

Centrality is widely recognized as one of the most critical measures to provide insight in the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.Comment: 57 pages, 10 figure

Climate Variability Rather Than Livestock Grazing Dominates Changes in Alpine Grassland Productivity Across Tibet

Alpine grasslands on the Tibetan Plateau, being vulnerable to environmental and anthropogenic changes, have experienced dramatic climate change and intensive livestock grazing during the last half-century. Climate change, coupled with grazing activities, has profoundly altered alpine grassland function and structure and resulted in vast grassland degradation. To restore degraded grasslands, the Central Government of China has implemented the Ecological Security Barrier Protection and Construction Project since 2008 across the Tibetan Autonomous Region. However, the relative effect of climate change and grazing activities on the variation in alpine grassland productivity is still under debate. In this study, we quantified how aboveground net primary production (ANPP) varied before (2000-2008) and after (2009-2017) starting the project across different alpine grasslands and how much variance in ANPP could be attributed to climate change and grazing disturbance, in terms of temperature, precipitation, solar radiation, and grazing intensity. Our results revealed that Tibet's climate got warmer and wetter, and grazing intensity decreased after starting the project. Mean ANPP increased at approximately 81% of the sites, on average from 27.0 g C m(-2) during 2000-2008 to 28.4 g C m(-2) during 2009-2017. The ANPP positively correlated with annual temperature and precipitation, but negatively with grazing intensity for both periods. Random forest modeling indicated that grazing intensity (14.5%) had a much lower influence in controlling the dynamics of grassland ANPP than precipitation (29.0%), suggesting that precipitation variability was the key factor for alpine grassland ANPP increase across Tibet

Effect of parathyroid hormone on the structural, densitometric and failure behaviours of mouse tibia in the spatiotemporal space

Parathyroid hormone (PTH) is an anabolic bone drug approved by the US Food and Drug Administration (FDA) to treat osteoporosis. However, previous studies using cross-sectional designs have reported variable and sometimes contradictory results. The aim of the present study was to quantify the localized effect of PTH on the structural and densitometric behaviors of mouse tibia and their links with the global mechanical behavior of bone using a novel spatiotemporal image analysis approach and a finite element analysis technique. Twelve female C57BL/6J mice were divided into two groups: the control and PTH treated groups. The entire right tibiae were imaged using an in vivo micro-computed tomography (μCT) system eight consecutive times. Next, the in vivo longitudinal tibial μCT images were rigidly registered and divided into 10 compartments across the entire tibial space. The bone volume (BV), bone mineral content (BMC), bone tissue mineral density (TMD), and tibial endosteal and periosteal areas (TEA and TPA) were quantified in each compartment. Additionally, finite element models of all the tibiae were generated to analyze the failure behavior of the tibia. It was found that both the BMC and BV started to increase in the proximal tibial region, and then the increases extended to the entire tibial region after two weeks of treatment (p < 0.05). PTH intervention significantly reduced the TEA in most tibial compartments after two weeks of treatment, and the TPA increased in most tibial regions after four weeks of treatment (p < 0.05). Tibial failure loads significantly increased after three weeks of PTH treatment (p < 0.01). The present study provided the first evidence of the localized effect of PTH on bone structural and densitometric properties, as well as their links with the global mechanical behaviors of bone, which are important pieces of information for unveiling the mechanism of PTH intervention

Structure, morphology and magnetic properties of flowerlike gamma-Fe2O3@NiO core/shell nanocomposites synthesized from different precursor concentrations

The flowerlike gamma-Fe2O3@NiO core/shell nanocomposites are synthesized by the two-step method. Their structure and morphology can be controlled by tuning the precursor concentration. Microstructural analysis reveals that all the samples have distinct core/shell structure without impurities, and the NiO shells are built of many irregular nanosheets which enclose the surface of gamma-Fe2O3 core. As the precursor concentration decreases (i.e., more NiO content), the NiO grain grows significantly, and the thickness of NiO shells increases. Magnetic experiments are performed to analyze the influences of different microstructures on magnetic properties of samples and we have the following two results. First, at 5 K, along with increasing thickness of NiO shell, the saturation magnetization increases, while the residual magnetization decreases slightly. Second, the hysteresis loops under cooling field demonstrate that the value of exchange bias effect fluctuates between 13 Oe and 17 Oe. This is mainly because of the NiO shell that (i) is composed of irregular nanosheets with disordered orientations, and (ii) does not form a complete coating around gamma-Fe2O3 core

Highly Conductive In-SnO2/RGO Nano-Heterostructures with Improved Lithium-Ion Battery Performance

The increasing demand of emerging technologies for high energy density electrochemical storage has led many researchers to look for alternative anode materials to graphite. The most promising conversion and alloying materials do not yet possess acceptable cycle life or rate capability. In this work, we use tin oxide, SnO2, as a representative anode material to explore the influence of graphene incorporation and In-doping to increase the electronic conductivity and concomitantly improve capacity retention and cycle life. It was found that the incorporation of In into SnO2 reduces the charge transfer resistance during cycling, prolonging life. It is also hypothesized that the increased conductivity allows the tin oxide conversion and alloying reactions to both be reversible, leading to very high capacity near 1200 mAh/g. Finally, the electrodes show excellent rate capability with a capacity of over 200 mAh/g at 10C

Transport of intense ion beams in plasmas: collimation and energy-loss reduction

We compare the transport properties of a well-characterized hydrogen plasma for low and high current ion beams. The energy-loss of low current beams can be well understood, within the framework of current stopping power models. However, for high current proton beams, significant energy-loss reduction and collimation is observed in the experiment. We have developed a new particle-in-cell code, which includes both collective electromagnetic effects and collisional interactions. Our simulations indicate that resistive magnetic fields, induced by the transport of an intense proton beam, act to collimate the proton beam and simultaneously deplete the local plasma density along the beam path. This in turn causes the energy-loss reduction detected in the experiment

Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research