Search

Studying how populations in various environments differ genetically is crucial for gaining insights into the evolution of biodiversity. In order to pinpoint potential indicators of divergence and adaptation to diverse environments, we conducted a comprehensive analysis of 3,491,868 single nucleotide polymorphisms (SNPs) derived from five populations of Brachymystax lenok. We discovered significant geographic divergence among these 5 populations, which lack evidence of gene flow among them. Our results further demonstrated that the current distribution pattern of Brachymystax lenok are driven by geographical isolation and changes in oceans and rivers. We also performed genome-wide scan and identified the genes evolved to adapt the different environments, including stress response. In general, these results provide genomic support for high-level genetic divergence and the genetic basis of adaptation to different environments.

A total of 18 samples of shallow groundwater around the Hancheng mining area in the Guanzhong Basin were collected from 1–4 May 2018. According to the analysis of hydrochemical data, the Gibbs semi-logarithmic diagram and Piper diagram were used to research the hydrogeochemical behavior of shallow groundwater around the Hancheng mining area in the Guanzhong Basin. The results of the groundwater hydrochemical analyses shown on the Gibbs and Piper plots are as follows: The chemical composition analysis showed that the main cation components were Mg2+, Ca2+, Na+, and K+, the anion components were HCO3−, Cl−, and SO42−. A measure of 89% of the groundwater samples in this area were freshwater, the HCO3− were mainly dolomite, calcite, and gypsum dissolved precipitation resulted. Na+ and Cl− came from the dissolution of halite. Most of the groundwater was of the SO4·Cl-Ca·Mg type, accounting for 61.1%. The main ion chemistry of the shallow groundwater in this area is controlled by rock weathering, and pyrite oxidation is a significant factor affecting the SO42− concentration. These research results will help analyze the formation mechanism of chemical components and provide some basic data for the evolution of mine water in this area in the future.

To enhance the positioning accuracy of standalone GNSS receivers in environments unable to provide precise ephemeris and clock offset, such as undeveloped forest areas that lack network communication and power supply, this study employed the Time Difference Carrier Phase (TDCP) technology to improve the positioning accuracy of Standard Point Positioning (SPP), where the Least-Squares (LS) and the extended Multi-Epoch Least Squares (MELS) method were applied in the position domain filtering for a single GNSS receiver and compare its performance with the existing observation domain filtering method. Firstly, the simulated data sets with various positioning accuracies were used to verify the effectiveness and convergence of the LS filtering methods. The results indicate that the LS filtering method produces a lower root mean square (RMS) error than the original strategy. Secondly, this study uses two kinematic GNSS data sets to evaluate the performance of the observation and position domain filtering, with an emphasis on the MELS method. The numerical experiment results show that the position domain LS filtering method outperforms the other two methods. The open environment experiments result shows that the positioning domain filtering method achieved positioning accuracies of 0.202 m, 0.843 m, and 2.036 m in the E, N, and U directions, respectively, with improvements of 68.0%, 21.6%, and 24.0%, compared to the original algorithm which achieved positioning accuracies of 0.631 m, 1.076 m, and 2.680 m. It also achieved improvements of 24.0%, 4.0%, and 18.3%, respectively, compared to the observation domain filtering method with positioning accuracies of 0.353 m, 0.886 m, and 2.526 m. The forest scenes experiments result shows that the positioning domain filtering method achieved positioning accuracies of 1.308 m, 1.375 m, and 2.133 m in the E, N, and U directions, respectively, with improvements of 42.4%, 36.2%, and 27.6%, compared to original algorithm which achieved positioning accuracies of 1.863 m, 1.873 m, and 2.722 m, and also achieved improvements of 27.0%, 19.4% and 10.6%, respectively, comparing to observation domain filtering method with positioning accuracies of 1.661 m, 1.642 m and 2.359 m. Moreover, the examination of the LS method results based on different epochs reveals that the filtering accuracy increases as more epochs are incorporated into the position domain integration and the enhancement value reaches a few millimeters.