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Land desertification is a bad manifestation of environmental degradation, which is jointly affected by irrational economic activities and fragile ecological environment. The red soil region in southern China is one of the most serious areas of soil and water loss. Soil and water loss has resulted in the decline of the soil and water conservation function, and the intensification of land desertification, thereby introducing huge ecological risks to the red soil region. In this study, the Dongjiang source area (DSA), a typical red soil region in South China, was selected as the study area. The random forest (RF) algorithm was used to extract refined desertification information, including spectrum, texture, and topography information, from the features of the DSA. The spatiotemporal evolution pattern and disturbance factors of desertification in the DSA from 1986 to 2020 was subsequently analyzed. Furthermore, to understand desertification development in a more detailed perspective, the land desertification changes in 2020 were revealed from the sub-watershed scale, and the spatiotemporal difference of a typical sub-watershed were deeply analyzed. The results indicate that the time period can be divided into three stages of desertification, namely development (1990–2000), stable reversal (2010–2015), and rapid reversal (2015–2020). The main reasons for the rapid reversal of desertification in this area are the strict ecological restoration policy and orchard environmental management measures implemented in southern Jiangxi during 2015–2020; however, the desertification in the DSA has not recovered to the pre-disturbed level. Moreover, it was found that the spatial distribution of the desertified land is basically consistent with the direction of the rivers in the DSA; with the main rivers as the center, the desertified land expands outwards in a flaky shape, and exhibits strong regionality. The spatial distributions of the desertified land in 2020 were found to be significantly different among the 18 sub-watersheds in the DSA, and the areas with larger differences were found to be concentrated in Dingnan County, which is mainly related to orchard reclamation. The desertification in the upper and lower reaches of the Xunwu river sub-watershed is continuously affected by the development of orchards and cultivated land on both sides of the river, and the desertification disturbance in the middle reaches is mainly caused by rare-earth element (REE) mining; the regional spatial distribution above the severely desertified land (SDL) grade is consistent with the concentrated area of REE minerals, which indicates that REE mining is an important reason for the aggravation of the desertification in the DSA. [ABSTRACT FROM AUTHOR]

Tungsten disulfide nanosheets(WS2) and dandelion-like platinum–silver nanoparticles(PtAg NCs) were synthesized by hydrothermal method and seed-mediated growth approach, and a novel dopamine(DA) electrochemical sensor based on PtAg/WS2/GCE was developed and a new method for detecting DA was established. The investigation of scanning electron microscopy (SEM) and transmission electron microscopy(TEM) exhibited that dandelion-like PtAg NCs were successfully dispersed on the surface of WS2 nanosheets with the size about ~ 10 nm and the thickness of WS2 nanosheet could be estimated to be 3.1 ± 0.02 nm with a lattice constants of 0.6 ± 0.03 nm, X-ray diffraction(XRD) and X-ray photoelectron spectroscopy(XPS) patterns proved PtAg exists as alloy form and both were metallic phases. The electrochemical results revealed the obtained sensors possessed ideal electrocatalytic activity toward DA with a wide linear range of 0.6 μM to 1 mM(R2 = 0.9991), high sensitivity (348.8 μA·mM−1·cm−2), low detection limit 0.2 μM (S/R = 3), the relative standard deviation (RSD) was estimated to be 2.3%, current respond toward DA remains 92.79% after several day, showing a good stability, repeatability and selectivity. Moreover, compared with other similar DA sensors, the linear range of the sensor was 2 orders of magnitude wider, and the detection limit was 5 times lower. [ABSTRACT FROM AUTHOR]

Special mining methods and red soil lead to large-scale land degradation and desertification in ion-type rare earth (RE) mining areas. Therefore, it is crucial for ecological management and restoration of mining areas to accurately understand the evolution process of desertification. In this study, remote sensing Landsat images from 1986 to 2019 were used to extract desertified land information from the Lingbei mining areas, Dingnan County, Ganzhou, China. To improve the reliability of the experiment, samples selected from Google images were used for verification to compare the accuracy of the desertification difference index (DDI) model and random forest (RF) algorithm for extracting land desertification information. The results showed that compared with the DDI model, the overall accuracy and kappa coefficient of the RF model based on multiple features were improved by 7% and 9.37%, respectively, indicating its higher applicability. Spatiotemporal change analysis of desertification in the mining area showed that the total area of desertification in the mining area increased most rapidly during 1986–1994 and reached 60.75 km2. The area of desertified land increased continuously from 1994 to 2004 and reached a maximum of 143.08 km2 in 2004. The area of desertified land decreased by 50.27 km2, but the severe desertified land (SDL) area increased by 1.69 km2 during 2004–2011. The area of desertified land gradually declined and stabilized from 2011 to 2019. Analysis of the desertification process in mining areas under different disturbance conditions showed that the desertified land disturbed by RE mining was most severely damaged. There is still an area of 16.77 km2 in the process of restoration, of which 2.24 km2 belongs to the SDL level. Moderate desertified land (MDL) and light desertified land (LDL) have not been completely contained and require the attention of the relevant departments to ensure their timely reclamation. [ABSTRACT FROM AUTHOR]

The negative impacts of the overexploitation of resources on regional environments have become increasingly obvious. The contradiction between the environment and development and the management of the ecological environment in mining areas are urgent problems to be solved. This paper uses Landsat images from four temporal phases from 1991 to 2018 in the Lingbei mining area of Dingnan County, China, to construct a rare earth remote sensing-based ecological index (RE-RSEI) suitable for rare earth mining areas and to analyze the impacts of different rare earth mining methods, mining scales and environmental management measures on the mining area environment over the past 27 years. The results show that since 1991, due to the mining techniques of "pond leaching" and "heap leaching" and the soil condition, mining has caused severe damage to the land and vegetation, and the ecological environment quality of the entire mining area has been seriously reduced with its RE-RSEI value dropping from 0.744 to 0.675. After 2010, through the optimization of mining technology and the government's attention to ecological environmental governance, the quality of the ecological environment was slowly restored, and the recovery effect at some mine sites was remarkable. The RE-RSEI model has good applicability to rare earth mining areas, can intuitively reflect the destruction and restoration of the ecological environment of rare earth mining areas under different mining modes, and provides scientific guidance for promoting the coordination of the development and utilization of rare earth resources and mine ecological environmental protection and sustainable development. [ABSTRACT FROM AUTHOR]

A bimetallic catalyst consisting of platinum-copper (Pt-CuNCs) anchored on graphene oxide (Pt-Cu/GO) was successfully synthesized by a one-pot aqueous method to detect sodium nitrite(NaNO2). The alloy was reduced and grown directly on the surface of graphene oxide(GO), which can maximize the interaction between metals and GO to achieve the enhanced catalytic activity. The transmission electron microscopy (TEM) results showed Pt-CuNCs were of spherical shape with an edge length of 5 ± 2 nm. Cyclicvoltammetry and chronoamperometry were used to test the electrochemical behavior of these nanocomposites and the results showed that Pt-Cu/GO nanocomposites have an excellent catalytic effect for nitrite analysis with a wide linear range of 2.0 × 10−7 to 9 × 10−3 mol L−1, low detection limit 3 μmol L−1 (SNR = 3), and high sensitivity (139.9μA·mM−1 cm−2). Furthermore, the sensor exhibited good stability, selectivity, and reproducibility. [ABSTRACT FROM AUTHOR]

A large set of potential microsatellites markers covering the entire genome are required for genetic diversity, mapping and functional genomics studies. In this study, a total of 37,572 microsatellites with frequency of 83.25 microsatellites per Mb were mined in the recently sequenced Fagopyrum tataricum. Among these 37,572 microsatellites, most of the microsatellites were di-nucleotide (26,196, 69.72%) and AT/TA repeat motifs were the most abundant (24,742, 65.85%). A total of 26,549 microsatellite markers were designed from the flanking sequences of 37,572 microsatellites and 2643 (9.96%) were genic microsatellite markers. All of these newly-developed microsatellite markers were physically anchored to the eight chromosomes of F. tataricum and the first and high-density physical map was constructed with an average marker density of 58.82 markers per Mb. Amplification efficiency and experimental evaluation of the newly-developed microsatellite markers assessed with 440 markers randomly selected in F. tataricum, showed that these microsatellite markers are highly effective and valuable. The large number of new microsatellite markers and their location on the physical map provided a valuable resource for studying diversity, constructing genetic maps, functional gene mapping, QTL exploration and molecular breeding in Fagopyrum species. [ABSTRACT FROM AUTHOR]

A correction to this paper has been published: https://doi.org/10.1007/s10653-021-00980-5 [ABSTRACT FROM AUTHOR]