Can δ18O help indicate the causes of recent lake area expansion on the western Tibetan Plateau? A case study from Aweng Co

© 2020, Springer Nature B.V. Glacier-fed lakes on the Tibetan Plateau (TP) have undergone rapid expansions since the late 1990s, concurrent with the changing climate. However, the dominant cause(s) of lake area increases is still debated. To identify the drivers of lake expansion, we studied Aweng Co, a glacier-fed lake in the western TP, where surface area has increased (0.74km2year−1) since the late 1970s and most rapidly (0.998 km2year−1) since the late 1990s. A water balance model was used to clarify the reasons for increased lake water volume, supported by stable isotope hydrology and the δ18O change recorded in recent sediments. Results showed that glacial meltwater probably had the biggest impact on changes in Aweng Co lake level in recent decades, but that precipitation was also an important contributor. Our study shows that δ18O of carbonate (δ18Ocarb) has great potential for indicating source changes of water supply in such lakes, but there is a need to be cautious when interpreting δ18Ocarb due to the influence of multiple hydrological factors, which can change in dominance over time

The Pro12Ala Polymorphism of PPAR- γ

Peroxisome proliferator-activated receptor-γ (PPAR-γ) is a ligand-binding nuclear receptor, and its activation plays a prominent role in regulating the inflammatory response. Therefore, PPAR-γ has been suggested as a candidate gene for sepsis. In the present study, we investigated the association between the Pro12Ala polymorphism of PPAR-γ and sepsis in a Han Chinese population. A total of 308 patients with sepsis and 345 healthy controls were enrolled in this study. Genotyping was performed using the polymerase chain reaction-ligation detection reaction (PCR-LDR) method. No significant differences were detected in the allele and genotype distributions of the PPAR-γ Pro12Ala SNP between septic patients and controls (P=0.622 for genotype; P=0.629 for allele). However, stratification by subtypes (sepsis, septic shock, and severe sepsis) revealed a statistically significant difference in the frequency of the Ala allele and Ala-carrier genotype between the patients with the sepsis subtype and the healthy controls (P=0.014 for allele and P=0.012, for genotype). Moreover, significant differences were found in the frequency of the Ala allele and genotype between the sepsis survivors and nonsurvivors (all P=0.002). In the survivors, the PPAR-γ Pro12Ala genotype was significantly associated with decreased disease severity and recovery time (all P<0.001). Thus, genetic polymorphism is thought to play a role in the development and outcome of sepsis

Evolution of vegetation and climate variability on the Tibetan Plateau over the past 1.74 million years

The Tibetan Plateau exerts a major influence on Asian climate, but its long-term environmental history remains largely unknown. We present a detailed record of vegetation and climate changes over the past 1.74 million years in a lake sediment core from the Zoige Basin, eastern Tibetan Plateau. Results show three intervals with different orbital- and millennial-scale features superimposed on a stepwise long-term cooling trend. The interval of 1.74–1.54 million years ago is characterized by an insolation-dominated mode with strong ~20,000-year cyclicity and quasi-absent millennial-scale signal. The interval of 1.54–0.62 million years ago represents a transitional insolation-ice mode marked by ~20,000- and ~40,000-year cycles, with superimposed millennial-scale oscillations. The past 620,000 years are characterized by an ice-driven mode with 100,000-year cyclicity and less frequent millennial-scale variability. A pronounced transition occurred 620,000 years ago, as glacial cycles intensified. These new findings reveal how the interaction of low-latitude insolation and high-latitude ice-volume forcing shaped the evolution of the Tibetan Plateau climate.publishedVersio

Relationship between climatic conditions and the relative abundance of modern C<inf>3</inf> and C<inf>4</inf> plants in three regions around the North Pacific

Using -24‰ and -14‰ as the endpoints of stable carbon isotopic composition of total organic carbon (δ13CTOC) of surface soil under pure C3 and C4 vegetation, and surface soil δ13CTOC data from eastern China, Australia and the Great Plains of North America, we estimate the relative abundance of C3/C4 plants (i. e., the ratio of C3 or C4 biomass to local primary production) in modern vegetation for each region. The relative abundance of modern C3/C4 vegetation from each region is compared to the corresponding climatic parameters (mean annual temperature and precipitation) to explore the relationship between relative C4 abundance and climate. The results indicate that temperature controls the growth of C4 plants. However, even where temperature is high enough for the growth of C4 plants, they will only dominate the landscape when precipitation declines as temperatures increase. Our results are consistent with those of other investigations of the geographic distribution of modern C4 plant species. Therefore, our results provide an important reference for interpretation of past C3/C4 relative abundance records in these three regions. © 2010 Science China Press and Springer-Verlag Berlin Heidelberg

Effect of Material Characteristics of High Damping Rubber Bearings on Aseismic Behaviors of a Two-Span Simply Supported Beam Bridge

There are a large number of damping materials in high-damping rubber (HDR) bearings, so the HDR bearings have the characteristics of both common rubber bearings and damping measures and show good aseismic effect. In this paper, the time-history dynamic analysis method is used to study the seismic effects of HDR bearings on the aseismic behaviors of two-span simply supported beam bridge under Northridge earthquake by changing the damping characteristics of the bearings. It is found that, with increasing damping of the bearings, both the horizontal shear and the displacement of the HDR bearings decrease, and the seismic energy dissipates through both the yield deformation and damping of the bearings. Although the girder and bearings have smaller displacement, when the HDR bearings with larger damping, the seismic responses, including displacement of pier top, shear force of pier bottom, and bending moment of pier bottom, are hardly affected by the change of the damping of the bearings. The HDR bearings with higher damping and yield characteristics separate and dissipate the seismic energy transmitted to the superstructure of the bridge and have better seismic effect on the structure in an earthquake

The Cooperation Partner Selection of Private Sector under Public-Private-Partnership Projects: An Improved Approach under Group Decision-Making Based on FRS, SAW, and Integrated Objective/Subjective Attributes

With the intensification of market competition, the choice of partners in the private sector plays a vital role in the success or failure of the government’s public sector in the bidding process. Based on FRS (factor risk scoring system), SAW (simple additive weighted), and the integrated subjective or objective fuzzy group decision-making methods, the private sector partner selection is carried out under the PPP (public-private partnership) model in this paper. First of all, a decision committee is established to select attributes and identify potential partners. Secondly, we determine the important decision of the consistency of the manufacturer, introduce linguistic variables, calculate and collect the fuzzy weighted personal attributes, evaluate the importance of the attributes, and get the comprehensive fuzzy evaluation. Thirdly, we establish fuzzy value matrix based on fuzzy evaluation and get the total fuzzy vector by multiplying respective weighted vectors and fuzzy evaluation matrix, then calculate the defuzzification value of each total score, and choose the alternative with the maximum score. Finally, an example is given to demonstrate the rationality of the algorithm

Study on the Seismic Performance of Different Combinations of Rubber Bearings for Continuous Beam Bridges

Rubber isolation bearings have been proven to be effective in reducing the seismic damage of bridges. Due to the different characteristics of isolation bearings, the mechanical properties of bridges with different combinations of rubber bearings are complex under the action of earthquakes. This paper focuses on the application of combinations of rubber isolation bearings on seismic performance of continuous beam bridges with T-beams. The seismic performances of continuous beam bridges with different combinations of rubber isolation bearings, pier height, and span length were studied by the dynamic time history analysis method. It was found that the bridges with natural rubber bearings (NRBs) have the largest seismic responses compared to the other types of bearings. The continuous beam bridge with isolation bearings, such as lead rubber bearings (LRBs) and high damping rubber bearings (HDRBs), has approximately 20%∼30% smaller seismic response than that with NRBs under the action of earthquakes due to the hysteretic energy of the bearings, indicating that the isolation bearings improve the seismic performance of the bridge. The continuous beam bridges with both NRBs and LRBs or NRBs and HDRBs have larger seismic response of the piers than those with a single type of isolation bearings (LRBs or HDRBs) but smaller seismic response of the piers than those with only NRBs. For a continuous beam bridge with shorter span and lower pier, it is not economical to use LRBs or HDRBs underneath every single girder, but it is more reasonable to use cheaper NRBs underneath some girders. The larger difference in stiffness of the bearings between the side and middle piers leads to the more unbalanced seismic response of each pier of the bridge structure. The results also show that with increasing pier height and span length, the difference in the seismic response value between the cases gradually increases

Climatic and environmental change in the western Tibetan Plateau during the Holocene, recorded by lake sediments from Aweng Co

Understanding the strength and extent of the Asian summer monsoon (including the East Asian summer monsoon and the Indian summer monsoon) in the Tibetan Plateau (TP) region is crucial for predicting possible changes in the regional eco-environment and water resources under global warming. Due to the lack of well-dated and high-resolution paleoclimate records, long-term monsoon dynamics are still not well understood in the western TP, which is currently influenced by both the Indian summer monsoon (ISM) and the westerlies. Here we present a multi-proxy lacustrine record covering the past 10,500 years from Aweng Co, an alpine lake at the northern limit of the modern ASM in western Tibet. Our results show that the western TP was mainly controlled by the ISM during the Holocene and the regional ecosystem/environment was sensitive to climate change. The climate was the wettest between 10.5 and 7.3 cal kyr BP, when terrestrial plants in the catchment were productive and the biomass of benthic algae was low possibly due to limited sunlight at the lake bottom due to high lake level. From 7.3 to 5.0 cal kyr BP the climate shifted towards drier conditions, resulting in a decline in terrestrial plant cover. Between 5.0 and 3.1 cal kyr BP, the climate became even drier, resulting in a further decline in vegetation cover in the catchment. Between 4.6 and 3.1 cal kyr BP, 100% endogenic dolomite precipitated from the lake water, possibly induced by high Mg/Ca ratios. After 3.1 cal kyr BP, the climate was the driest and frequent centennial-scale droughts occurred. The lake level was low and would have resulted in more light reaching the lake bottom, favoring the growth of benthic algae. The reconstructed lake level change of Aweng Co agrees well with the paleo-shoreline records in the southern TP, demonstrating that the ISM evolution played a key role in lake hydrological processes in this region. A comparison of paleoclimate records shows the ISM reached 34.5° N in the western TP during the Holocene

Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models

Landslide susceptibility prediction (LSP) has been widely and effectively implemented by machine learning (ML) models based on remote sensing (RS) images and Geographic Information System (GIS). However, comparisons of the applications of ML models for LSP from the perspectives of supervised machine learning (SML) and unsupervised machine learning (USML) have not been explored. Hence, this study aims to compare the LSP performance of these SML and USML models, thus further to explore the advantages and disadvantages of these ML models and to realize a more accurate and reliable LSP result. Two representative SML models (support vector machine (SVM) and CHi-squared Automatic Interaction Detection (CHAID)) and two representative USML models (K-means and Kohonen models) are respectively used to scientifically predict the landslide susceptibility indexes, and then these prediction results are discussed. Ningdu County with 446 recorded landslides obtained through field investigations is introduced as case study. A total of 12 conditioning factors are obtained through procession of Landsat TM 8 images and high-resolution aerial images, topographical and hydrological spatial analysis of Digital Elevation Modeling in GIS software, and government reports. The area value under the curve of receiver operating features (AUC) is applied for evaluating the prediction accuracy of SML models, and the frequency ratio (FR) accuracy is then introduced to compare the remarkable prediction performance differences between SML and USML models. Overall, the receiver operation curve (ROC) results show that the AUC of the SVM is 0.892 and is slightly greater than the AUC of the CHAID model (0.872). The FR accuracy results show that the SVM model has the highest accuracy for LSP (77.80%), followed by the CHAID model (74.50%), the Kohonen model (72.8%) and the K-means model (69.7%), which indicates that the SML models can reach considerably better prediction capability than the USML models. It can be concluded that selecting recorded landslides as prior knowledge to train and test the LSP models is the key reason for the higher prediction accuracy of the SML models, while the lack of a priori knowledge and target guidance is an important reason for the low LSP accuracy of the USML models. Nevertheless, the USML models can also be used to implement LSP due to their advantages of efficient modeling processes, dimensionality reduction and strong scalability