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Aims and objectives: To detect the mediating effect of resilience on the relationship between perceived social support and burnout in Chinese palliative nurses. Background: Palliative nurses are a group that is vulnerable to burnout. Perceived social support may contribute to decreasing palliative nurses' burnout and facilitating their personal resilience, and resilience may be associated with lower levels of burnout. However, these relationships were unclear in the Chinese context. Design: A cross‐sectional design. Methods: The STROBE guideline was performed to report this study. A mixed sampling method including convenience sampling and stratified sampling was used to recruit participants, and a total of 319 palliative nurses completed the Nursing Burnout Scale, the Perceived Social Support Scale and the Connor–Davidson Resilience Scale from May 2021 to September 2021. Influencing factors were primarily identified using independent‐sample t tests and one‐way ANOVA. Bootstrap method was used to detect the mediating effect of resilience. Results: The level of burnout in palliative nurses (23.4 ± 7.68) was higher than that of general nurses in China. Education level, health condition and monthly income were influencing factors of burnout. Resilience was detected as a mediator in the relationships between perceived social support and dimensions of burnout. Conclusions: Chinese palliative nurses experience a relatively high level of burnout, which may be influenced by several sociodemographic variables. Resilience could mediate the effect of perceived social support on the dimensions of burnout. Problem‐oriented and palliative‐tailored strategies should be developed to further address burnout in Chinese palliative nurses. Relevance to clinical practice: Nurse managers and policy makers should support nurse ongoing education, adopt health‐promoting interventions and optimise salary systems. In addition, perceived social support resources and resilience training programmes are also warranted. Patient or public contribution: All participants were invited to complete the informed consent form and paper questionnaires. Human resource managers helped us collect some subjective data through the personnel management system. Nurse managers of palliative units conducted regular staff meetings to promote the data collection process. [ABSTRACT FROM AUTHOR]

Aerosols are complex compounds that greatly affect the global radiation balance and climate system and even human health; in addition, aerosols are currently a large source of uncertainty in the numerical simulation process. The arid and semi-arid areas have fragile ecosystems with abundant dust but lack related high-accuracy aerosol data. To solve these problems, we use the bagging trees ensemble model, based on 1 km aerosol optical depth (AOD) data and multiple environmental covariates, to produce a monthly advanced-performance, full-coverage, and high-resolution (250 m) AOD product (named FEC AOD, fusing environmental covariates AOD) covering the arid and semi-arid areas. Then, based on the FEC AOD products, we analyzed the spatiotemporal AOD pattern and further discussed the interpretation of environmental covariates to AOD. The results show that the bagging trees ensemble model has a good performance, with its verification R2 values always remaining at 0.90 and the R2 being 0.79 for FEC AOD compared with AERONET AOD product. The high-AOD areas are located in the Taklimakan Desert and on the Loess Plateau, and the low-AOD areas are concentrated in southern Qinghai province. The higher the AOD, the stronger the interannual variability. Interestingly, the AOD reflected a dramatic decrease on the Loess Plateau and an evident increase in the south-eastern Taklimakan Desert, while the southern Qinghai province AODs showed almost no significant change between 2000 and 2019. The annual variation characteristics show that the AOD was largest in spring (0.267±0.200) and smallest in autumn (0.147±0.089); the annual AOD variation pattern showed different features, with two peaks in March and August over Gansu province but only one peak in April in other provinces/autonomous regions. Farmlands and construction lands have high AOD levels compared to other land cover types. Meteorological factors demonstrate the maximum interpretation ability of the AODs on all set temporal scales, followed by the terrain factors, while surface properties have the smallest explanatory abilities; the corresponding average contributions are 77.1 %, 59.1 %, and 50.4 %, respectively. The capability of the environmental covariates to explain the AOD varies seasonally in the following sequence: winter (86.6 %) > autumn (80.8 %) > spring (79.9 %) > summer (72.5 %). In this research, we provide a pathbreaking high spatial resolution (250 m) and long time series (2000–2019) FEC AOD dataset covering arid and semi-arid regions to support atmospheric and related studies in northwest China; the full dataset is available at 10.5281/zenodo.5727119 (Chen et al., 2021b). [ABSTRACT FROM AUTHOR]

Background: Burnout occurs frequently in nurses and seems more common in nurses providing palliative care. However, to our knowledge, there is a lack of understanding regarding the factors influencing burnout among palliative nurses in China. Methods: A cross-sectional design was conducted. A total of 331 palliative nurses from 25 hospitals participated in this study. Anonymous data were collected through a self-designed social-demographic questionnaire, the Nursing Burnout Scale, the Perceived Social Support Scale, the General Self-Efficacy Scale, the Connor-Davidson Resilience Scale, and the Simplified Coping Style Questionnaire. Independent sample t tests, one-way ANOVA, Pearson correlations, and multiple linear regressions were performed to identify the related factors of the three dimensions of burnout. Results: In the results of multiple linear regression, resilience, health condition, coping style, and pessimistic personality were common related factors; in addition, end-of-life care training, social support, and income satisfaction were statistically significantly associated with burnout. These factors could explain 38.6%, 27.8%, and 34.5% of the total variance in emotional exhaustion, depersonalization, and reduced personal accomplishment, respectively. Conclusions: The findings of this study help policy makers and nurse managers better understand burnout among palliative nurses in China. The results highlighted the importance of implementing culture-oriented training programs, providing perceived organizational support, and building a reasonable salary system to decrease burnout among palliative nurses, increase the quality of nursing and promote the development of Chinese palliative care. [ABSTRACT FROM AUTHOR]

• A spatio-temporal prediction framework was developed to map SOC. • The inter-decadal maps of China SOC were updated to the 2010s. • Effects of climatic factors for SOC variability are location- and scale- specific. • The soils in China function as carbon sinks at national scale from 1980s to 2010s. Spatiotemporal variability in soil organic carbon (SOC) plays key roles in ecosystem stability and terrestrial carbon cycling. However, the inter-decadal characteristics of SOC variability and its climate drivers in China from the 1980s to 2010s remain unclear. In this study, a modeling framework for combining spatiotemporal prediction models was proposed. Within this model, soil samples from each of the two periods were combined and calibrated to obtain three models, and their prediction outputs were selectively combined to obtain SOC maps for the different inter-decadal periods. A total of 8473 soil samples from three periods (1980s, 2000s and 2010s) were used for model validation. The results suggested that the SOC prediction accuracy in the top 0–20 cm of soil (SOC 020) was better than that of the first meter of soil (SOC 0100), and the predicted spatial patterns shared characteristics with findings from previous studies. Predictions for the 1990s exhibited relatively high uncertainty, especially in the Tibetan Plateau, Tien Shan, and Northeast China. Both individual and coupled climatic factors exerted scale- and location-specific effects on the SOC. Coupled climatic factors accounted for more than 65% of the SOC variability in both soil layers. The regional SOC in North and Northeast China exhibited inter-decadal decline. Soil in China functioned as carbon sinks from the 1980s to 2010s at a national scale, with SOC 020 increasing from 30.40 Pg to 33.97 Pg and SOC 0100 from 79.29 Pg to 82.26 Pg. Overall, our results provide reliable baseline data for optimizing carbon cycle models of terrestrial ecosystems, and to guide future carbon sequestration policies. [ABSTRACT FROM AUTHOR]

• The SOC in two depths were mapped at a resolution of 1 km and five-year interval during 1980–2100. • Three climate scenarios of SSP 1–1.9, SSP2-4.5 and SSP5-8.5 in CMIP6 were considered. • The top 20 cm and 100 cm SOC of China both acted as carbon sinks during 1980–2020. • The SOC will fluctuate significantly in the future under different climate scenarios. • Under the SSP2-4.5 scenario, SOC presented a larger likelihood of being a carbon source in most region. Revealing historical changes in soil organic carbon (SOC) and exploring its future status are important for safeguarding soil health and food security, giving full play to the service function of soil ecosystems, and coping with climate change. However, there is still a gap in our understanding of the SOC stocks in China and their spatial patterns in response to future climate change. Therefore, we attempted to fill this knowledge gap using a large amount of soil observation data, digital soil mapping technology, and global circulation models from Coupled Model Inter-comparison Project phase 6 (CMIP6). In this study, a random forest model was selected to construct the spatial relationship between SOC in the top 0–20 cm (SOC020) and 0–100 cm (SOC0100) of the soil and 21 environmental factors. Spatiotemporal changes in SOC from 1980 to 2100 were revealed at a resolution of 1 km and five-year interval for three climate scenarios in CMIP6. The cross-validation results indicated acceptable predictions for both depths of SOC; however, relatively large prediction uncertainties were observed for SOC0100 in the Tibetan Plateau and northeastern China. The mean values of SOC020 and SOC0100 over the last four decades were 35.77 and 84.62 Tg, respectively, and showed carbon sinks at the national scale, with accumulation rates of 0.05 Pg yr-1 and 0.036 Pg y-1 for the two depths. Compared with historical values (1980–2020), SOC will fluctuate significantly in the future under different climate scenarios. Among them, SOC showed a slow increasing trend at both depths under the SSP1-1.9 low emission scenario, while SOC presented a decreasing trend under the SSP2-4.5 and SSP5-8.5 medium–high emission scenarios. In particular, in most of China under the SSP2-4.5 scenario, SOC0100 presented a larger likelihood of being a carbon source. This study provides a reference for exploring the response of soil carbon pools to climate change and evaluating the effectiveness of land management and ecological protection. [ABSTRACT FROM AUTHOR]

• BEMD was applied to high-resolution SOM map in northwestern China. • Scale- and region-specific variations in SOM were unraveled. • The variance of SOM was partitioned by climate, topography and land surface. • Main factors that influencing SOM were different in different scales. Soil organic matter (SOM) significantly affects soil quality, food security, and the global carbon cycle. Variations in the SOM content are controlled by many environmental factors and differ depending on the scale and region. The Mountain–Oasis–Desert System (MODS) in arid areas is limited by climate conditions and water and soil resources. Therefore, the effects of environmental factors on the SOM content may differ. This study aimed to characterize spatial patterns of the SOM content in a MODS in northwestern China and reveal the SOM variations at different scales and regions. First, we employed the random forest model to predict the SOM content and the uncertainty at the nodes of a 90 m grid. We then extracted scale- and region-dependent variations in the SOM content using bivariate empirical mode decomposition (BEMD). Data analysis, geostatistics, and a two-dimensional fast Fourier transform were applied to analyze the SOM pattern and its correlations with environmental covariates at different scales. The results suggest that the variations in the SOM content were mainly concentrated at the large scale. The correlations between environmental factors and the SOM were scale- and region-specific, indicating complex interrelationships among topography, land use, salinization, soil erosion, and fertilization. At the intermediate-large spatial scale, topography characteristics and surface features were the major factors controlling the SOM content, whereas the climate had a larger effect on SOM than other factors at the large scale. Based on our results, BEMD has great potential to reveal SOM variations in the scale–region domain. BEMD can be used in environmental modeling in the future to gain insights into the variations in soil properties depending on environmental factors and anthropogenic activities. [ABSTRACT FROM AUTHOR]