Contrasting response of coexisting plant's water-use patterns to experimental precipitation manipulation in an alpine grassland community of Qinghai Lake watershed, China

Understanding species-specific changes in water-use patterns under recent climate scenarios is necessary to predict accurately the responses of seasonally dry ecosystems to future climate. In this study, we conducted a precipitation manipulation experiment to investigate the changes in water-use patterns of two coexisting species (Achnatherum splendens and Allium tanguticum) to alterations in soil water content (SWC) resulting from increased and decreased rainfall treatments. The results showed that the leaf water potential (Psi) of A. splendens and A. tanguticum responded to changes in shallow and middle SWC at both the control and treatment plots. However, A. splendens proportionally extracted water from the shallow soil layer (0-10cm) when it was available but shifted to absorbing deep soil water (30-60 cm) during drought. By contrast, the A. tanguticum did not differ significantly in uptake depth between treatment and control plots but entirely depended on water from shallow soil layers. The flexible water-use patterns of A. splendens may be a key factor facilitating its dominance and it better acclimates the recent climate change in the alpine grassland community around Qinghai Lake

Global Analysis of Gene Expression Profiles in Developing Physic Nut (Jatropha curcas L.) Seeds

Background: Physic nut (Jatropha curcas L.) is an oilseed plant species with high potential utility as a biofuel. Furthermore, following recent sequencing of its genome and the availability of expressed sequence tag (EST) libraries, it is a valuable model plant for studying carbon assimilation in endosperms of oilseed plants. There have been several transcriptomic analyses of developing physic nut seeds using ESTs, but they have provided limited information on the accumulation of stored resources in the seeds. Methodology/Principal Findings: We applied next-generation Illumina sequencing technology to analyze global gen

Spatial variations of hydrochemistry and stable isotopes in mountainous river water from the Central Asian headwaters of the Tajikistan Pamirs

Water resources in Central Asia from the mountainous headwater catchments is changing due to the shrinkage of glaciers in the Tian Shan and Pamir mountain systems. In order to predict future changes in water quality, it is crucial to understand what factors are governing the spatial variations of water chemistry and hydrological processes in mountainous headwater catchments. In this study, water chemistry including major ions and stable isotopes in the headwaters of major Tajikistan rivers was studied. Results showed that Tajikistan river water had an alkaline pH value (mean: 8.2) and total dissolved solids (mean: 368.5mg/L) were higher than the global average value. Ca2+, Na+, HCO3-, and SO42- in the rivers were the most abundant cations and anions, controlled by the rock weathering process and evaporation-crystallization processes. The hydrochemical facies of river water was dominated by Ca-HCO3 (71.7%) and exhibited spatial heterogeneity, which was related to the lithologic compositions and water source across Tajikistan. A significant negative correlation of river water delta O-18 with elevation was observed with a vertical lapse rate of 0.17%/100 m. The more negative delta O-18 values in rivers from eastern Tajikistan were scattered in the lower left corner of the delta O-18-delta H-2 plot, implying that the rivers were primarily supplied by snow/glacier meltwater because of the substantial number of glaciers and high elevation mountain in eastern regions. The drinking and irrigation suitability from ionic compositions revealed that the water quality of Tajikistan rivers was naturally good, though some sites posed a safety concern. These findings can provide new insights into sustainable management of water quality in the climatically and lithologically distinct segments of headwater regions in the Tajikistan Pamirs

Comparison of n-alkane concentrations and delta D values between leaves and roots in modern plants on the Chinese Loess Plateau

Sedimentary delta Dn-alkane values have been widely used as a valuable proxy for paleoenvironmental reconstruction. A number of studies have focused on delta D(n-alkne )values that derived exclusively from leaves, while less attention has been paid to the root-derived n-alkanes and their impact on sedimentary delta Dn-alkane values. In this study, we sampled modern plant leaf and root materials from different growth contexts (slopes and seasons) on the Chinese Loess Plateau to compare leaf-derived n-alkanes with root-derived n-alkanes. Our results demonstrated that total n-alkane (C-27-C-33) concentrations varied substantially between leaf and root materials, with average values of 209 and 29.5 mu g/g observed in leaves and roots respectively. The results suggest that ca. 12% of the n-alkane concentrations in sediments may be derived from plant roots. Furthermore, leaf-derived delta Dn-alkane values for Stipa bungeana (grass), Artemisisa vestita (shrub) and Bothriochloa ischaemum (grass) averaged -184 parts per thousand, -152 parts per thousand, and -198 parts per thousand, compared with their root-derived delta Dn-alkane values of -19 parts per thousand, -179 parts per thousand, and -163 parts per thousand, respectively. These statistically significant differences in concentrations and delta D values between leaf-derived and root-derived n-alkanes suggest that the contribution of n-alkanes derived from plant roots is important for evaluating the resultant n-alkane compositions of sediments for paleoenvironmental reconstruction. Our findings indicates that the effects of root-derived n-alkanes on total sedimentary delta Dn-alkane values should be considered carefully in future paleoenvironmental reconstruction efforts. (C) 2019 Elsevier Ltd. All rights reserved

Using delta Dn-alkane as a proxy for paleo-environmental reconstruction: A good choice to sample at the site dominated by woods

Some studies have demonstrated that leaf wax delta Dn-alkane values for a single species varied significantly with seasons. However, it is still not clear that the seasonality patterns of leaf wax delta Dn-alkane values in higher plants. Meanwhile, few efforts have been pursued to assess the effect of the light slopes (sunny vs. cloudy) on leaf wax delta Dn-alkane values. In this study, we systematically investigated plant wax delta Dn-alkane values and soil n-alkane delta D values along different light slopes in different seasons (spring vs. autumn), as well as the relationship of n-alkane delta D values between plant leaves and soil. We found that plant wax delta Dn-alkane values were D-enriched by ca. 20%0 in spring relative to autumn, and ca. 10 parts per thousand in the sunny slope than in the cloudy slope. Moreover, surface soil n-alkane delta D values varied consistently with plant wax delta Dn-alkane values for different seasons and light slopes. More importantly, plant wax delta Dn-alkane values showed clear seasonal variations, but varied slightly with light slopes. The variations of plant wax delta Dn-alkane values can be recorded in soil n-alkane delta Dn-alkane values. In addition, we found that leaf wax delta Dn-alkane values in a majority of species differed significantly among woods, non-woods and grasses at a site. Therefore, we suggested a good choice to sample at the site dominated by woods when leaf wax delta Dn-alkane values are utilized as a proxy for the reconstruction of the paleoenvironment. (C) 2017 Elsevier B.V. All rights reserved

Decoding the hundred-year water level changes of the largest Saline Lake in China: A joint lake-basin modeling study based on a revised SWAT+

Study region: Qinghai Lake Basin (QLB), the largest saline lake in China and its collecting basin Study focus: Climate change has caused clear shrinkage or dramatic water level fluctuation of lakes in arid and semi-arid regions, while the underlain mechanisms remain unclear. The joint lake-basin investigations (spatial) and long-term studies (temporal) are urgently needed. This study developed SWAT+ to jointly simulate the water cycle of QLB and investigated how the hydrological regime of QLB changed at the hundred-year scale. New hydrological insights for the region: The modeling framework consisted of the revised SWAT+ , reanalysis data, and reconstructed water level based on lake gravity core performed quite well (NSE > 0.9 for lake water level) in simulating the hydrological processes of QLB at the hundred-year scale (1910 – 2018). Temporally, decadal variations of hydrological components in QLB decreased in sequence of precipitation (46.33 mm), lateral flow (26.85 mm), evapotranspiration (16.03 mm), snowmelt (10.44 mm), groundwater flow (5.66 mm), and overland flow (1.18 mm). Spatially, precipitation, water yield, lateral flow, and groundwater flow in upstream regions of QLB, where the precipitation amount was small, were most sensitive to climate change. The long-term water level decrease of Qinghai Lake during 1928 – 2003 was mainly driven by variations of river runoff and lake surface evaporation; the clear water level increase since 2004 was dominated by river runoff changes

Adaptive Equivalent Consumption Minimization Strategy for Hybrid Heavy-Duty Truck Based on Driving Condition Recognition and Parameter Optimization

The accurate determination and dynamic adjustment of key control parameters are challenges for equivalent consumption minimization strategy (ECMS) to be implemented in real-time control of hybrid electric vehicles. An adaptive real-time ECMS is proposed for hybrid heavy-duty truck in this paper. Three efforts have been made in this study. First, six kinds of typical driving cycle for hybrid heavy-duty truck are obtained by hierarchical clustering algorithm, and a driving condition recognition (DCR) algorithm based on a neural network is put forward. Second, particle swarm optimization (PSO) is applied to optimize three key parameters of ECMS under a specified driving cycle, including equivalent factor, scale factor of penalty function, and vehicle speed threshold for engine start-up. Finally, combining all the above two efforts, a novel adaptive ECMS based on DCR and key parameter optimization of ECMS by PSO is presented and validated through numerical simulation. The simulation results manifest that proposed adaptive ECMS can further improve the fuel economy of a hybrid heavy-duty truck while keeping the battery charge-sustainability, compared with ECMS and PSO-ECMS under a composite driving cycle

Overview Of High-Step-Up Coupled-Inductor Boost Converters

High-step-up, high-efficiency, and cost-effective dc-dc converters, serving as an interfacing cell to boost the low-voltage output of renewable sources to the utility voltage level, are an important part in renewable energy systems. Over the past few years, there has been a substantial amount of studies devoted to high-step-up dc-dc converters. Among them, the category of coupled-inductor boost converters is widely researched and considered to be a promising solution for high-step-up applications. In this paper, these converters are categorized into five groups according to the major topological features. The derivation process, advantages, and disadvantages of these converters are systematically discussed, compared, and scrutinized. This paper aims to provide an introduction, review, and framework for the category of high-step-up coupled-inductor boost converters. General structures for the topologies are proposed to clarify the topological derivation process and to show potential gaps. Furthermore, challenges or directions are presented in this paper for deriving new topologies in this field