Search

Rare earth ion doped fluorescent powder, as a key material for the application of white light-emitting diodes (w-LEDs), green components often face the problem of poor thermal stability. Developing fluorescent powders with excellent thermal stability is of great significance. This article synthesized a series of Gd 5 Si 2 BO 13 :Tb3+ blue phosphors and non rare earth Bi3+ ion doped Gd 5 Si 2 BO 13 :Tb3+ green phosphors using a high-temperature solid-phase method. The phase structure and photoluminescence characteristics of the sample were analyzed in detail through XRD, excitation and emission spectra, as well as attenuation curves. The energy transfer from Bi3+ to Tb3+ was studied and confirmed through photoluminescence spectra and lifetime decay curves. Research has shown that the addition of Bi3+ significantly enhances the emission intensity of Tb3+ in the near ultraviolet range, and tunes the emission color of Gd 5 Si 2 BO 13 :Bi3+ and Tb3+ from blue to green, attributed to the energy transfer from Bi3+ to Tb3+. In addition, the addition of Bi3+ increased the thermal stability of single doped fluorescent powder Gd 5 Si 2 BO 13 :0.55Tb3+ from 88.21 % to 92.82 % at 150 °C, proving that the Gd 5 Si 2 BO 13 :Bi3+ and Tb3+ samples have good thermal stability. This study not only deepens our understanding of the new main material Gd 5 Si 2 BO 13 , but also provides a reference for the development of green phosphors with excellent thermal stability. [Display omitted] • A series of Gd 5 Si 2 BO 13 :Bi3+, Tb3+ phosphors were successfully synthesized. • The co-doped Gd 5 Si 2 BO 13 :Bi3+, Tb3+ phosphors have excellent emission intensity and thermal stability. • The Gd 5 Si 2 BO 13 :Bi3+, Tb3+ green phosphors is promising for use in high-power LED lighting devices and backlight displays. [ABSTRACT FROM AUTHOR]

[Display omitted] • The northwest area of the BTSSCP suffered severe dust-affected zones based on the dust flow trajectory. • The ESs in severe dust-affected areas were relatively poor. • ESs and the dust flow trajectory were integrated to identify ecological governance zones. • Governance suggestions were proposed for the ecological management zone combined with the driving forces. Achieving ecological conservation and governance based on ecosystem services (ESs) can balance regional ecological protection and development, which is of great significance for sustainable development. Existing research has mainly focused on the extraction of priority ecological conservation areas, thereby neglecting to consider the classification and management of ecological engineering areas. To improve regional ecological governance, we combine ESs and dust movement trajectory, using the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) as the research object to generate watersheds' ecological governance zones. Six ESs were assessed to determine ecological zones. Trajectory simulation of dust movement, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function, was used to determined zones affected by dust. By combining these two aspects, five main ecological governance clusters were identified. We found that: (1) the area with low ESs in the northwest of the BTSSCP suffered from severe dust impacts; (2) slight dust-affected zones were mainly distributed in the eastern of the BTSSCP, and in the area, ESs gradually decreased from south to north; (3) ESs in the region was primarily influenced by natural factors and the influencing factors of ESs vary among different zones. These findings will not only contribute to the overall planning and governance of the BTSSCP, but can offer general guidance for the formulation of targeted ecological protection and restoration measures in other areas. [ABSTRACT FROM AUTHOR]

Changed land use patterns are the most direct manifestation of ecological engineering implemented by humans, being among the driving factors for changes in ecosystem services (ESs). However, different ecological engineering governance measures can lead to different changes in land use, resulting in corresponding changes to ESs and ecosystem service value (ESV), yet these changes is the content that needs to be clarified. In this study, four kinds of ESs, namely water yield, soil conservation, carbon storage and water purification, were quantified in part region of the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP). In addition, eight scenarios were simulated according to the land use change caused by engineering management measures, and the ESs and ESV ensuing under these differing scenarios quantified accordingly. The results show that the main land use types in the study area from 2000 to 2020 were cropland and forestland, while during this period land use change mainly consisted of the expansion of grassland (+466.79 km2) and loss of cropland (−2095.27 km2). For different engineering management measures, protective governance will play a greater role in improving ESs than restoration governance. Protecting the existing governance outcomes from degrading can maintain a water yield of 36.85 × 108 m3, soil conservation of 73.72 × 106 t, carbon storage of 89.01 × 106 t, the purified water nitrogen content of 1.21 × 106 t, with the total ESV maintained at 54.237 billion yuan. Moreover, the high-investment counties clearly engage in ecological restoration that provides high ESV. Yet, there are still some counties with high project investment where the gains in ESV are low, such as Luanping county and Pingquan county. Therefore, it should be reasonably distributed based on the existing governance results in the next round of project investment allocation. In the past 20 years, engineering governance measures have significantly improved the ESs in the region. Nevertheless, looking ahead, it remains necessary to strengthen the emphasis on protecting governance outcomes. [Display omitted] • Scenario simulations were run under governance measures for ecological engineering. • Ecosystem service value (ESV) under differing governance measures were simulated. • ESV is higher when ecological protection rather than restoration measures are used. • Project investment vis-à-vis ESV under the different scenarios were analyzed. [ABSTRACT FROM AUTHOR]

The Drosophila hindgut is a classical model to study organogenesis. The adult hindgut originates from the precursor cells in the larval hindgut. However, the territory of these cells has still not been well determined. A ring of wingless (wg)-expressing cells lies at the anterior zone of both the larval and adult hindgut. The larval Wg ring was thought as a portion of precursor of the adult hindgut. By applying a cell lineage tracing tool (G-TRACE), we demonstrate that larval wg -expressing cells have no cell lineage contribution to the adult hindgut. Additionally, adult Wg ring cells do not divide and move posteriorly to replenish the hindgut tissue. Instead, we determine that the precursors of the adult pylorus and ileum are situated in the cubitus interruptus (ci)-expressing cells in the anterior zone, and deduce that the precursor stem cells of the adult rectum locate in the trunk region of the larval pylorus including hedgehog (hh)-expressing cells. Together, this research advances our understanding of cell lineage origins and the development of the Drosophila hindgut. [Display omitted] • Adult Wg ring cells do not divide and move posteriorly to replenish the hindgut tissue. • Larval Wg ring in the anterior zone of hindgut was not the precursors of adult hindgut. • The progenitors of the adult pylorus and ileum were situated in the ci expressing cells in the larval anterior zone. • The progenitors of the adult rectum were located in the trunk region of pylorus including hh expressing cells. [ABSTRACT FROM AUTHOR]

Shrub encroachment, characterized by the proliferation of shrubs into grasslands, is a challenge faced by grasslands worldwide that significantly impacts livestock production and ecosystem functions. Rapid and accurate estimation of shrub dominance is important for understanding changes in plant community structures and formulating grassland management policies. However, the limited spatial resolution of commonly used satellite imagery poses a challenge when estimating shrub dominance at the landscape scale. The rapid development of Unoccupied Aerial Vehicles (UAVs) has opened up new opportunities for cross-scale observations of shrub encroachment in grasslands by effectively bridging the scale gap between ground sampling and satellite image pixels while reducing the required groundwork. This study utilized ground reference data, UAV data (RGB, hyperspectral, and LiDAR), and satellite data (Sentinel-1 and Sentinel-2) to estimate shrub and total above-ground biomass (AGB) in temperate grasslands to map the shrub dominance. First, UAV data were applied at the plot scale for the classification of shrub and herbaceous vegetation using the maximum entropy model (MaxEnt), estimation of shrub AGB by employing the vegetation index weighted canopy volume model (CVM VI), and estimation of herbaceous AGB based on the partial least squares regression (PLSR). Second, UAV AGB mapping results were upscaled as samples at the landscape scale and integrated with satellite imagery to establish the shrub and total AGB models using the extreme gradient boosting (XGBoost). Finally, shrub dominance, represented as shrub AGB/total AGB, was mapped across the study area. We found that at the plot scale, the MaxEnt model achieved an overall accuracy of 0.990 for object-based classification. The CVM VI combined with canopy height model and narrow-band vegetation index achieved the highest accuracy for estimating shrub AGB (R2 = 0.821, RMSE = 30.1 g). The PLSR combined with features derived from all UAV data achieved the highest accuracy for estimating herbaceous AGB (R2 = 0.856, RMSE = 9.1 g/m2). At the landscape scale, the XGBoost achieved high accuracy for estimating both the shrub AGB (R2 = 0.719, RMSE = 4.2 g/m2) and total AGB (R2 = 0.961, RMSE = 5.0 g/m2). The high-precision mapping results further facilitate the generation of shrub dominance maps at a landscape scale. This study presents a more accurate and efficient framework for mapping shrub AGB, total AGB, and shrub dominance using multi-scale remote sensing data, which offers new approaches for large-scale grassland AGB mapping and monitoring of shrub encroachment in grasslands. • Multisensory UAV data were evaluated for shrub and herbaceous AGB estimation at the plot scale. • SAR and multispectral satellite data were used to map AGB and shrub dominance at the landscape scale. • Our multi-scale framework outperformed the traditional AGB estimation method. • Assessing shrub dominance is important for understanding shrub encroachment. [ABSTRACT FROM AUTHOR]

• NDVI represents photosynthetic phenology only in deciduous trees. • Gcc tracks photosynthetic phenology more accurately than GRVI at the canopy scale. • ɸ NPQ and ɸ f,D have great influences on the spectral signal changes of NIRv and PRI. • Good consistency was found between NIRv and PRI for predicting A max. Vegetation photosynthetic phenology is an important indicator to characterize the biological responses of terrestrial carbon cycle to climate change. Remote sensing-derived spectral indices have been used to estimate photosynthetic phenology of terrestrial ecosystems, yet there are large uncertainties due to differences in leaf structure and canopy function between evergreen and deciduous trees. In this study, we used in-situ measured meteorology, the maximum rate of leaf-level CO 2 assimilation (A max), chlorophyll fluorescence and canopy color changes in evergreen and deciduous species to evaluate and compare the abilities of spectral indices for photosynthetic phenology modeling. Seasonal variation in A max is used as a proxy for photosynthetic phenology. Several indices were used, including the normalized difference vegetation index (NDVI), near-infrared reflectance vegetation index (NIRv), photochemical reflectance index (PRI), chlorophyll/carotenoid index (CCI), green-red vegetation index (GRVI), and green chromaticity coordinates (Gcc). We found that NIRv and PRI estimated phenological periods for Cedrus deodara and three deciduous trees all differed from A max by less than 5 days, and all were linearly related to A max (R2 > 0.6). CCI had less potential for A max modeling, while NDVI had the largest error in predicting A max. Gcc was a more accurate proxy for photosynthetic phenology than GRVI at the canopy scale. In addition, we found that the variability of different spectral indices in tracking photosynthetic phenology of evergreen and deciduous species was related to non-photochemical quenching processes. Especially for the fraction of absorbed light quenched by dynamic NPQ (ɸ NPQ) and the fraction of absorbed light quenched by sustained NPQ (ɸ f,D), they contribute more than 40 % to the variations of the NIRv and PRI spectral signals. Therefore, NIRv and PRI provide powerful tools for monitoring photosynthetic phenology, and future exploration of NIR v and PRI at larger spatial scales will favor the global plant phenology and carbon uptake modeling. [ABSTRACT FROM AUTHOR]

[Display omitted] • A selection strategy for base-period images of spatio-temporal fusion was proposed. • The spatio-temporal inconsistency between field samples and images was reduced. • The estimation accuracy of grassland aboveground biomass was improved. The accurate estimation of the aboveground biomass (AGB) is crucial for the sustainable utilization and management of grassland resources. Spatio-temporal inconsistencies between field samples and satellite images are major source of error in the estimation of grassland AGB. To solve this problem, this study selected the Three Rivers Headwater Region as the study area and proposed a selection strategy for base-period images of spatio-temporal fusion that was suitable for use at a large spatial scale in which cloud-free images are difficult to obtain. The spatial and temporal adaptive reflectance fusion model (STARFM) based on the selection strategy was used to generate a synthetic Normalized Difference Vegetation Index (NDVI) dataset with high spatial-temporal resolution by using the maximum value composite of GF-1 NDVI and MODIS NDVI to enhance the spatial-temporal quality of the images for field-scale application. Three estimation models for grassland AGB were then constructed by the random forest algorithm using synthetic NDVI, MODIS NDVI, GF-1 NDVI respectively, together with ancillary data. Following this, the estimation model with the highest accuracy was used to generate a 16-m eight-day time-series AGB in the growing season. The results showed: (1) The synthetic NDVI was correlated closely with the observed GF-1 NDVI, with an average R of 0.825 and a RMSE of 0.087. The temporal trend of the synthetic NDVI for each grassland type was highly consistent with that of the MODIS NDVI in the growing season with a correlation higher than 0.9. (2) The synthetic NDVI reduced the spatial difference between field samples and images to 16-fold, and the temporal difference was controlled to within four days under ideal conditions. (3) The synthetic NDVI improved the estimation accuracy of grassland AGB by about 15.9% and 19.7% (R2), and 13.7% and 17.5% (RMSE) relative to MODIS NDVI and GF-1 NDVI, respectively. (4) The time-series AGB revealed accurately the spatial distribution of and seasonal temporal variations in the grassland biomass. The results of this study may serve as scientific guidance for timely monitoring of grassland conditions and precise management of grassland resources in China. [ABSTRACT FROM AUTHOR]

The Qinling Mountains (Qinling Mts.) are characterized as a distinct transition of bioclimatic zones along the north-south geographic boundary in China. Although ongoing global warming may affect the growth of most tree species across elevation gradients, the effect of modern warming on the stable hydrogen isotopes of tree-ring wood is still unknown. In this study, we developed early- and late-wood δ 2H chronologies from 1900 to 2018 CE of lignin methoxy groups (δ 2H LM) at 700-m intervals from 1700 to 3100 m a.s.l. along the elevation gradient in Mount Taibai (Mt. Taibai), the peak of the Qinling Mts. The δ 2H LM values of the earlywood were relatively enriched in 2H compared to the latewood, and an elevation-dependent depleting trend along the altitudinal gradient was observed. Comparing the δ 2H LM values with modelled δ 2H values of precipitation (δ 2H Pre) of the sample sites, similar isotopic patterns can be obtained. The reconstructions of δ 2H Pre values confirm the strong coherence between the isotopic composition of the source water and the methoxy groups in the growing season. The consistency of δ 2H LM chronologies between the early- and late-wood at the higher sites was stronger than that at the lower sites. The additional lagged effect and climate response revealed significant seasonal and altitudinal differences. At the timberline site, δ 2H LM values of earlywood were mainly related to the January and February temperatures, whereas δ 2H LM values of latewood correlated most strongly with temperature from July to September, and both values were controlled by the amount of total precipitation. In addition, the combined new δ 2H LM chronologies, based on the lag-1 autocorrelation and the weighted average of the current year earlywood and previous latewood, could be used to merge the corresponding temperature signals from the middle- and low-elevation sites. Altitudinal correlations of elevation offset between the annual δ 2H LM chronologies and interpolations of precipitation and temperature suggested that the δ 2H LM values at higher elevations better represent regional climatic changes. Therefore, topographic effects such as elevation differences should be considered in large-scale applications of δ 2H LM values in future studies. • Altitude- and seasonal-differences in δ 2H values of both tree-ring wood and precipitation were revealed in Qinling Mountains, China. • Elevational effects of temperature and precipitation resulted in the variations of δ 2H LM of lignin methoxy. • Timberline δ 2H LM recorded the significantly lagged effects and strong hydroclimatic signals. • Altitude specificity of δ 2H LM should be considered in the large-scale investigations. [ABSTRACT FROM AUTHOR]

Flash drought is an extreme phenomenon, characterized by unusually rapid intensification of drought severity, with strong impacts on plant growth especially for crops. However, it's unclear how hydrometeorological changes contribute to flash drought and how vegetation physiology, greenness, and productivity respond to flash drought. In this study, we developed an multivariate integrated framework for flash drought identification using a regression model based on principal-components analysis (PCA): the PCA regression flash drought (PRFD) model. Three criteria are specified to emphasize the rapid intensification of drought and its impacts on vegetation growth and water resources. We applied our new model in two geographical units with different climates and hydrology: one is dominated by agriculture and subject to natural drought (the Loess Plateau) and the other, a natural region with infrequent drought (the Qinling Mountains). We found that high frequency of flash droughts is most likely to occur in the eastern and central Loess Plateau and part of the Qinling Mountains. However, in relatively humid areas, flash drought shows strong intensity such as the Qinling Mountains and western and eastern edges of the Loess Plateau. Trend analysis indicates that PRFD has increased frequency, longer duration, and stronger intensity since the 1990s in both regions. From an ecological perspective, PRFD also showed a spatial pattern consistent with values of vegetation-related proxies that were below the long-term average, demonstrating vegetation transpiration, normalized-difference vegetation index (NDVI), gross primary productivity have obvious feedback on flash drought events. The Loess Plateau's NDVI responded immediately to flash drought, versus a 1-month lag in the Qinling Mountains. Because our proposed framework integrates multiple aspects of drought information, it can be applied in areas outside the study region according to regional hydrometeorological conditions. This has significant implications for improving agricultural management and forecasting future severe impacts of flash drought on plant growth. • A new integrated framework is proposed to identify flash drought (FD) events. • FD with greater frequency, longer pentads, and stronger intensity since 1990s. • Vegetation structure and physiological function respond rapidly to FD. • The response time of plant activity to FD is different in diverse climate-water regions. [ABSTRACT FROM AUTHOR]

As the most frequent and longest-lasting climate-related disasters, droughts are complex processes caused by hydrological imbalance, and have significant effects on ecosystem function and socioeconomic development. However, most conventional satellite-based drought indices and combined drought indices are mechanically constrained by the fact that they were developed and evaluated for a specific climate or critical ecological region, especially in China. A comprehensive drought index should be developed for extensive application in different climate-hydrology regions. To address this problem, an optimised principal component analysis method (PCA-RF) was proposed to support drought assessment across the transitional area between the humid and arid regions in central China, including the Loess Plateau (LP) and Qinling Mountains (QL). This method eliminated the causal relationships of non-linear changes for multi-aspect parameters such as land surface temperature, precipitation and soil moisture, and was used in developing a new index named "Meteorological drought index by PCA-RF methods (PMDI)". The results showed that PMDI had higher correlations and lower root mean square error than other drought indices (established using the empirical-weights method) with the 1-month standardized precipitation evapotranspiration index (SPEI-1). That means PMDI performed well in meteorological drought monitoring. Additionally, the normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) were utilised to evaluate PMDI effectiveness in detecting vegetation response to drought, which represents agricultural drought. The results indicated that correlations between PMDI and vegetation indices (VIs) were stronger when severe or extreme droughts occurred, and that their relationships were affected by the high spatiotemporal heterogeneity in vegetation change over the LP and QL. Overall, PMDI was shown here to be a very suitable index for monitoring meteorological drought (short-term) and has effective action in capturing the response of vegetation signals to agriculture drought events (long-term). Given the excellent performance of PMDI in diverse climate-hydrology conditions of our study regions, we concluded that the PMDI has considerable potential as a drought monitoring methodology on a larger spatial scale. • A new drought index was developed (PMDI), which integrated multiple sources of information describing different aspects. • PMDI performed well in different climate-hydrology regions for short- and long-term drought monitoring. • PMDI has reasonably good potential applicability in drought monitoring on a larger spatial scale. [ABSTRACT FROM AUTHOR]

• The RSDI is suitable for monitoring aeolian desertification. • The areas with significant restoration (34.1%) exceeded those with significant deterioration (6%) in the NSPB. • In the areas with significant restoration, 57.4% of the land was mainly affected by human activities. The northern sand-prevention belt (NSPB) is the key area for sand control in China, and the various ecological projects conducted there are important to the Chinese strategy for ecological security. In this paper, a new remote sensing-based desertification index (RSDI) based on principal component analysis was constructed from four aspects of vegetation greenness, surface moisture, soil grain size, and surface radiation. The overall evaluation accuracy of the index was 89.2%, and the kappa coefficient was 0.80, indicating high sensitivity to different degrees of aeolian desertification and suitability for multiscale research. The coefficient of variation, Mann–Kendall test, Theil–Sen median trend analysis, and residual analysis were used to analyze the spatiotemporal changes and driving forces of the RSDI in the NSPB from 2000 to 2020. The RSDI was used to compare aeolian desertification in different subregions, land use types, and ecological project areas. The important results are as follows: (1) the trend of the average RSDI was downward, but it increased significantly in 2008–2009 and 2013–2014; (2) the RSDI was characterized by relatively high volatility in 28.9% and moderate volatility in 27.1% of the area; (3) the areas with significant restoration (34.1%) greatly exceeded those with significant deterioration (6%), whereas 59.9% of the total area was stable; and (4) within the area with significant restoration, 57.4% was primarily affected by human activities, and 42.4% was primarily affected by climate change; however, most of the area with significant deterioration (71.1%) was affected by human activities. In general, the degree of aeolian desertification in the NSPB has decreased in the past 20 years and its ecological quality has continued to recover. However, unreasonable human activities still need to be reduced, and the ecological management of areas under serious threat of desertification needs to be strengthened. [ABSTRACT FROM AUTHOR]

• NPFF did not cause significant changes in the morphology of RAW 264.7 cells. • A total of 211 differentially expressed genes (DEGs) were obtained. • NPFF significantly inhibited the immune response-related pathway of macrophages. • Eight qPCR-verified hub genes were acquired by protein-protein interaction analysis. • The hub proteins optimized by molecular dynamics were obtained. Neuropeptide FF (NPFF) is a neuropeptide that modulates various physiological processes. The regulatory role of NPFF in the immune and inflammatory response is currently being revealed. However, the effect of NPFF at the transcriptome level in macrophages has not been fully elucidated. Here, the impact of NPFF on gene expression at the transcriptome level of RAW 264.7 cells was investigated by RNA-seq. RAW 264.7 macrophages were treated with NPFF (1 nM) for 18 h, followed by RNA-seq examination. Differentially expressed genes (DEGs) were acquired, followed by GO, KEGG, and PPI analysis. A total of eight qPCR-verified DEGs were obtained. Next, three-dimensional models of the eight hub proteins were constructed by using homology modeling with Modeller (9v23). Finally, molecular dynamics simulation (300 ns) was performed with GROMACS 2018.2 to investigate the structural characteristics of these hub proteins. NPFF had no detectable effect on the morphology of RAW264.7 cells. A total of 211 DEGs were acquired, and an enrichment study demonstrated that the immune response-related pathway was significantly inhibited by NPFF. Moreover, the molecular dynamics optimized-protein models of the hub proteins were obtained. Collectively, NPFF inhibited the expression of immune-related genes in RAW 264.7 cells at the transcriptome level, which suggested a negative relationship between NPFF and this set of immune-related genes in RAW 264.7 macrophages. Therefore, our data may provide direct evidence of the role of NPFF in peripheral or central inflammatory diseases. [ABSTRACT FROM AUTHOR]

• Three dimensional discrete points morphological operator, removing vegetation. • Union-find sets incorporated with the profile analysis method, removing large background objects. • The optimized profile analysis method with the topological characteristics, extracting the bridges. • OpenMP to improve the computation efficiency. Extraction of bridges from light detection and ranging (Lidar) images is a difficult problem with low detection accuracy and detection efficiency because of strong dependence on bridge shapes, the influence of vegetation and the large amount of data. This paper proposes an improved method based on morphology and profile analysis to extract bridges with removing background objects such as vegetation. To remove vegetation effectively, a new morphological three dimensional (3D) discrete points operator is applied which the gridding method is utilized to obtain the neighborhoods of the discrete points. Subsequently, union-find sets is incorporated with the profile analysis method to optimize the process of generating the minimum spanning tree (MST) and determining connected domains, which are used to remove large objects and leave the bridges behind. By combining the optimized profile analysis method with the topological characteristics of bridges, bridges are extracted without dependence on their shapes. Finally, in order to improve the computation efficiency of the Lidar data, the OpenMP is employed. Experimental results show that the proposed method can extract the bridges from Lidar data effectively. [ABSTRACT FROM AUTHOR]