The ratio of high aspartate aminotransferase to alanine aminotransferase: an independent risk factor associated with poor prognosis in IgA nephropathy.

OBJECTIVE: To investigate the relationship between the aspartate aminotransferase to alanine aminotransferase ratio (AAR) and the prognosis of IgA nephropathy (IgAN). METHODS: Clinical, pathological and follow-up data of 271 patients with IgAN from January 1, 2013, to July 31, 2023, were collected. A 50% decrease in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD) was used as renal composite end point events. A receiver operating characteristic (ROC) curve was plotted to predict the composite end point events by AAR. The optimal cutoff value of 1.24 was determined, and patients were allocated to high AAR and low AAR groups. Kaplan‒Meier (K‒M) curves and Cox proportional hazard models were used to evaluate the predictive effect of AAR on renal composite end point events. RESULTS: After a mean follow-up of 29 months, 39 patients achieved renal composite end point events. Among them, 9 and 30 patients in the low and high AAR groups achieved renal composite end point events, respectively, with a significant difference (P < 0.001). After adjustment for confounding factors, AAR was found to be an independent prognostic factor for renal composite end point events (HR = 3.283, 95% CI: 1.489-7.238, P = 0.003). Kaplan‒Meier analysis showed that high AAR was associated with achieving renal composite end point events in patients with IgAN. Moreover, the clinical features in the high AAR group were more severe. Further subgroup analysis showed that high AAR had a better predictive effect in patients with more severe clinicopathological manifestations. CONCLUSION: AAR is an independent prognostic factor in patients with IgAN.

Effects of ambient temperature and humidity on COPD mortality in Ganzhou city, China.

This study used the time series data of Ganzhou city to explore the individual and interaction effects of temperature and humidity on COPD death, and identify vulnerable subgroups of the population. We collected daily COPD mortality and meteorological data in Ganzhou from 2016 to 2019. The nonlinear distribution lag model was used to examine the associations and interaction between daily mean temperature and humidity and COPD mortality. For the total population, male and 65 years old or above, the relative risk (RR) for COPD mortality could be significant at extremely low temperature (3.3 ℃), reaching 1.799 (95% confidence interval [CI]: 1.216, 2.662), 1.894 (95% CI: 1.164, 3.084) and 1.779 (95% CI:1.185, 2.670). Also, at extremely low humidity (47.8%), the risk reached 1.888 (95% CI: 1.217, 2.930), 1.837 (95% CI: 1.066, 3.165) and 2.166 (95% CI: 1.375, 3.414). The cumulative COPD death risk for females was 3.524 (95% CI: 1.340, 9.267) at high temperature (30.7 ℃), 1.953(95% CI: 1.036, 3.683) at low humidity (47.8%) and 1.726 (95% CI: 1.048, 2.845) at high humidity (96.7%). For the total COPD deaths and subgroups, the interaction effects between daily temperature and humidity were not significant (p > 0.05). Both extremely low temperature and low humidity increased the risk of COPD death in Ganzhou city, especially for males and people over 65 years old. Females were more sensitive to extremely high temperature and humidity. Patients with COPD should pay attention to self-protection under extreme temperature and humidity weather conditions.

Association between ambient temperature and hospitalizations for urolithiasis in four counties of Ganzhou, China.

We collected meteorological and urolithiasis-related hospitalization data from four counties in Ganzhou City for 2018-2019 and used the DLNM method to assess the lagged and cumulative effects of temperature on urolithiasis hospitalizations and obtain the total effect after meta-combination. Based on the nonlinear association between temperature and urolithiasis hospitalizations, the relative risk of overall high temperature (30℃) was 2.10 (95% CI: 1.07-4.10). No statistically significant difference (p = 0.07) was observed between males (RR = 2.04, 95% CI: 1.42-2.94) and females (RR = 1.45, 95% CI: 1.09-1.92) for the heat effect, which was higher in the ≥ 60 years age group (RR = 3.18, 95% CI: 1.76-5.76) than in the < 60 years age group (p = 0.007). High temperatures increased the risk of hospitalization for urolithiasis in Ganzhou, China, and the risk was greatest for individuals aged 60 and above, with similar risks observed across counties and genders.

Plant Community Associates with Rare Rather than Abundant Fungal Taxa in Alpine Grassland Soils.

The importance of the rare microbial biosphere in maintaining biodiversity and ecological functions has been highlighted recently. However, the current understanding of the spatial distribution of rare microbial taxa is still limited, with only a few investigations for rare prokaryotes and virtually none for rare fungi. Here, we investigated the spatial patterns of rare and abundant fungal taxa in alpine grassland soils across 2,000 km of the Qinghai-Tibetan plateau. We found that most locally rare fungal taxa remained rare (13.07%) or were absent (82.85%) in other sites, whereas only a small proportion (4.06%) shifted between rare and abundant among sites. Although they differed in terms of diversity levels and compositions, the distance decay relationships of both the rare and the abundant fungal taxa were valid and displayed similar turnover rates. Moreover, the community assemblies of both rare and abundant fungal taxa were predominantly controlled by deterministic rather than stochastic processes. Notably, the community composition of rare rather than abundant fungal taxa associated with the plant community composition. In summary, this study advances our understanding of the biogeographic features of rare fungal taxa in alpine grasslands and highlights the concordance between plant communities and rare fungal subcommunities in soil. IMPORTANCE Our current understanding of the ecology and functions of rare microbial taxa largely relies on research conducted on prokaryotes. Despite the key ecological roles of soil fungi, little is known about the biogeographic patterns and drivers of rare and abundant fungi in soils. In this study, we investigated the spatial patterns of rare and abundant fungal taxa in Qinghai-Tibetan plateau (QTP) alpine grassland soils across 2,000 km, with a special concentration on the importance of the plant communities in shaping rare fungal taxa. We showed that rare fungal taxa generally had a biogeographic pattern that was similar to that of abundant fungal taxa in alpine grassland soils on the QTP. Furthermore, the plant community composition was strongly related to the community composition of rare taxa but not abundant taxa. In summary, this study significantly increases our biogeographic and ecological knowledge of rare fungal taxa in alpine grassland soils.

Association between daily temperature and hospital admissions for urolithiasis in Ganzhou, China: a time-series analysis.

Urolithiasis was a global disease and it was more common in southern China. This study looked into the association between daily temperature and urolithiasis hospital admissions in Ganzhou, a large prefecture-level city in southern China. In Ganzhou City from 2016 to 2019, a total of 60,881 hospitalized cases for urolithiasis from 69 hospitals and meteorological data were gathered. The effect of high ambient temperature on urolithiasis hospital admissions was estimated using a distributed lag nonlinear model. Stratified analysis was done to examine sex differences. The study found that in Ganzhou of China, the exposure-response curves approximated a "J" shape which across genders were basically similar. The maximum lag effect occurred on the second day after high temperatures for males but on the third day for females. Compared to the 10 °C reference temperature and considering the cumulative lag effect of 10 days, the relative risks of the daily mean temperature at the 95th percentile on the total, male, and female hospital admissions for urolithiasis were 2.026 (95% CI: 1.628, 2.521), 2.041 (95% CI: 1.603, 2.598), and 2.030 (95% CI: 1.552, 2.655), respectively, but the relative risks between sex were not statistically significant (p = 0.977). Urolithiasis morbidity risk in China could be exacerbated by high temperatures. The effect of high temperature on urolithiasis was similar across genders.

Relationship between body dissatisfaction, insufficient physical activity, and disordered eating behaviors among university students in southern China.

BACKGROUND: With an increasing incidence of obesity, the relationship between obesity and body image has become a hot research topic worldwide. From high school to university, young people experience changes in their social environment. University students have a high incidence of eating disorders and insufficient physical activity. The purpose of this study was to explore the relationship between body dissatisfaction, insufficient physical activity, and disordered eating behaviors among university students in southern China. METHODS: In total, 1296 university students aged 18-23 years were recruited for this study. The participants completed anthropometric measurements, the Physical Activity Rating scale-3 (PARS-3), and the Chinese-Dutch Eating Behavior Questionnaire (C-DEBQ). The ideal weight and silhouette were reported by university students using a questionnaire. RESULTS: Compared with men, young women had a higher level of body dissatisfaction. For men, body mass index (BMI; ß = 0.76, P <  0.01), physical activity score (ß = - 0.11, P <  0.01), and restrained eating score (ß = 0.10, P <  0.01) were the significant factors predictive of body dissatisfaction. For women, BMI (ß = 0.57, P <  0.01), muscle mass (ß = 0.12, P <  0.01), physical activity score (ß = - 0.11, P <  0.01), and restrained eating score (ß = 0.09, P <  0.01) were the significant factors predictive of body dissatisfaction. CONCLUSIONS: University students with high body dissatisfaction had lower physical activity scores and higher restrained eating scores. The data presented here highlight the impact of university students' body dissatisfaction on physical activity deficiency and disordered eating behaviors in China.

Drought and heat wave impacts on grassland carbon cycling across hierarchical levels.

Droughts and heat waves are increasing in magnitude and frequency, altering the carbon cycle. However, understanding of the underlying response mechanisms remains poor, especially for the combination (hot drought). We conducted a 4-year field experiment to examine both individual and interactive effects of drought and heat wave on carbon cycling of a semiarid grassland across individual, functional group, community and ecosystem levels. Drought did not change below-ground biomass (BGB) or above-ground biomass (AGB) due to compensation effects between grass and non-grass functional groups. However, consistently decreased BGB under heat waves limited such compensation effects, resulting in reduced AGB. Ecosystem CO2 fluxes were suppressed by droughts, attributed to stomatal closure-induced reductions in leaf photosynthesis and decreased AGB of grasses, while CO2 fluxes were little affected by heat waves. Overall the hot drought produced the lowest leaf photosynthesis, AGB and ecosystem CO2 fluxes although the interactions between heat wave and drought were usually not significant. Our results highlight that the functional group compensatory effects that maintain community-level AGB rely on feedback of root system responses, and that plant adjustments at the individual level, together with shifts in composition at the functional group level, co-regulate ecosystem carbon sink strength under climate extremes.

Auxiliary Diagnosis for COVID-19 with Deep Transfer Learning.

To assist physicians identify COVID-19 and its manifestations through the automatic COVID-19 recognition and classification in chest CT images with deep transfer learning. In this retrospective study, the used chest CT image dataset covered 422 subjects, including 72 confirmed COVID-19 subjects (260 studies, 30,171 images), 252 other pneumonia subjects (252 studies, 26,534 images) that contained 158 viral pneumonia subjects and 94 pulmonary tuberculosis subjects, and 98 normal subjects (98 studies, 29,838 images). In the experiment, subjects were split into training (70%), validation (15%) and testing (15%) sets. We utilized the convolutional blocks of ResNets pretrained on the public social image collections and modified the top fully connected layer to suit our task (the COVID-19 recognition). In addition, we tested the proposed method on a finegrained classification task; that is, the images of COVID-19 were further split into 3 main manifestations (ground-glass opacity with 12,924 images, consolidation with 7418 images and fibrotic streaks with 7338 images). Similarly, the data partitioning strategy of 70%-15%-15% was adopted. The best performance obtained by the pretrained ResNet50 model is 94.87% sensitivity, 88.46% specificity, 91.21% accuracy for COVID-19 versus all other groups, and an overall accuracy of 89.01% for the three-category classification in the testing set. Consistent performance was observed from the COVID-19 manifestation classification task on images basis, where the best overall accuracy of 94.08% and AUC of 0.993 were obtained by the pretrained ResNet18 (P < 0.05). All the proposed models have achieved much satisfying performance and were thus very promising in both the practical application and statistics. Transfer learning is worth for exploring to be applied in recognition and classification of COVID-19 on CT images with limited training data. It not only achieved higher sensitivity (COVID-19 vs the rest) but also took far less time than radiologists, which is expected to give the auxiliary diagnosis and reduce the workload for the radiologists.

Comparative transcriptome analyses provide novel insights into etiolated shoot development of walnut (Juglans regia L.).

MAIN CONCLUSION: In general, genes promoting IAA, CTK GA and ethylene biosynthesis were upregulated, while genes participating in ABA, chlorophyll and starch biosynthesis pathways performed opposite tendency during etiolation. Etiolation as a method for rejuvenation plays an important role in the vegetative propagation of woody plants. However, the molecular mechanism of etiolated shoot development remains unclear. In this study, we investigated changes at different etiolation stages of Juglans regia. The histology and transcriptome of J. regia were analysed using etiolated stems, which were treated in darkness for 30, 60, 90 days. The results showed that the ratios of pith (Pi) diameter/stem diameter (D), cortex (Co) width/D, and phloem (Ph) width/D increased, while the ratio of xylem (Xy) width/D decreased after etiolation, and the difference in these ratios between etiolated stems and the control was more significant at 60 days than 90 days. Differentially expressed genes (DEGs) were significantly enriched in pathways such as plant hormone biosynthesis and signal transduction, chlorophyll biosynthesis and degradation, and starch and sucrose metabolism. The difference in the contents of indole-3-acetic acid (IAA), abscisic acid (ABA), sugar and chlorophyll between etiolated stems and the control increased with increasing treatment duration; in contrast, the concentrations of gibberellin (GA), zeatin (ZT), and starch, as well as the difference between the etiolated stems and control were lowest at 60 days among the three stages. On the whole, the positive effect of etiolation on the rejuvenation of walnut stems changed as the treatment period increased. The present investigation lays a foundation for future studies on the effect of etiolation on rejuvenation and for promoting the efficiency of vegetative propagation.

Terrestrial N2 O emissions and related functional genes under climate change: A global meta-analysis.

Nitrous oxide (N2 O) emissions from soil contribute to global warming and are in turn substantially affected by climate change. However, climate change impacts on N2 O production across terrestrial ecosystems remain poorly understood. Here, we synthesized 46 published studies of N2 O fluxes and relevant soil functional genes (SFGs, that is, archaeal amoA, bacterial amoA, nosZ, narG, nirK and nirS) to assess their responses to increased temperature, increased or decreased precipitation amounts, and prolonged drought (no change in total precipitation but increase in precipitation intervals) in terrestrial ecosystem (i.e. grasslands, forests, shrublands, tundra and croplands). Across the data set, temperature increased N2 O emissions by 33%. However, the effects were highly variable across biomes, with strongest temperature responses in shrublands, variable responses in forests and negative responses in tundra. The warming methods employed also influenced the effects of temperature on N2 O emissions (most effectively induced by open-top chambers). Whole-day or whole-year warming treatment significantly enhanced N2 O emissions, but daytime, nighttime or short-season warming did not have significant effects. Regardless of biome, treatment method and season, increased precipitation promoted N2 O emission by an average of 55%, while decreased precipitation suppressed N2 O emission by 31%, predominantly driven by changes in soil moisture. The effect size of precipitation changes on nirS and nosZ showed a U-shape relationship with soil moisture; further insight into biotic mechanisms underlying N2 O emission response to climate change remain limited by data availability, underlying a need for studies that report SFG. Our findings indicate that climate change substantially affects N2 O emission and highlights the urgent need to incorporate this strong feedback into most climate models for convincing projection of future climate change.

Ecological responses to heavy rainfall depend on seasonal timing and multi-year recurrence.

Heavy rainfall events are expected to increase in frequency and severity in the future. However, their effects on natural ecosystems are largely unknown, in particular with different seasonal timing of the events and recurrence over multiple years. We conducted a 4 yr manipulative experiment to explore grassland response to heavy rainfall imposed in either the middle of, or late in, the growing season in Inner Mongolia, China. We measured hierarchical responses at individual, community and ecosystem levels. Surprisingly, above-ground biomass remained stable in the face of heavy rainfall, regardless of seasonal timing, whereas heavy rainfall late in the growing season had consistent negative impacts on below-ground and total biomass. However, such negative biomass effects were not significant for heavy rainfall in the middle of the growing season. By contrast, heavy rainfall in the middle of the growing season had greater positive effects on ecosystem CO2 exchanges, mainly reflected in the latter 2 yr of the 4 yr experiment. This two-stage response of CO2 fluxes was regulated by increased community-level leaf area and leaf-level photosynthesis and interannual variability of natural precipitation. Overall, our study demonstrates that ecosystem impacts of heavy rainfall events crucially depend on the seasonal timing and multiannual recurrence. Plant physiological and morphological adjustment appeared to improve the capacity of the ecosystem to respond positively to heavy rainfall.

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison.

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Feature Mixture on Pre-trained Model for Few-shot Learning.

Few-shot learning (FSL) aims at recognizing a novel object under limited training samples. A robust feature extractor (backbone) can significantly improve the recognition performance of the FSL model. However, training an effective backbone is a challenging issue since (1) designing and validating structures of backbones are time-consuming and expensive processes, and (2) a backbone trained on the known (base) categories is more inclined to focus on the textures of the objects it learns, which is hard to describe the novel samples. To solve these problems, we propose a feature mixture operation on the pre-trained (fixed) features: (1) We replace a part of the values of the feature map from a novel category with the content of other feature maps to increase the generalizability and diversity of training samples, which avoids retraining a complex backbone with high computational costs. (2) We use the similarities between the features to constrain the mixture operation, which helps the classifier focus on the representations of the novel object where these representations are hidden in the features from the pre-trained backbone with biased training. Experimental studies on five benchmark datasets in both inductive and transductive settings demonstrate the effectiveness of our feature mixture (FM). Specifically, compared with the baseline on the Mini-ImageNet dataset, it achieves 3.8% and 4.2% accuracy improvements for 1 and 5 training samples, respectively. Additionally, the proposed mixture operation can be used to improve other existing FSL methods based on backbone training.

Extreme drought alters methane uptake but not methane sink in semi-arid steppes of Inner Mongolia.

Global climate change, particularly drought, is expected to alter grassland methane (CH4) oxidation, a key natural process against atmospheric greenhouse gas accumulation, yet the extent of this effect and its interaction with future atmospheric CH4 concentrations increases remains uncertain. To address this research gap, we measured CH4 flux during an imposed three-month rain-free period corresponding to a 100-year recurrence drought in soil mesocosms collected from 16 different Eurasian steppe sites. We also investigated the abundance and composition of methanotrophs. Additionally, we conducted a laboratory experiment to explore the impact of elevated CH4 concentration on the CH4 uptake capacity of grassland soil under drought conditions. We found that regardless of the type of grassland, CH4 flux was still being absorbed at its peak, meaning that all grasslands functioned as persistent CH4 sinks even when the soil water content (SWC) was <5 %. A bell-shaped relationship between SWC and CH4 uptake was observed in the soils. The average maximum CH4 oxidation rate in the meadow steppe was higher than that in the typical and desert steppe soils during extreme drought. The experimental elevation of atmospheric CH4 concentration counteracted the anticipated reduction in CH4 uptake related to physiological water stress on methanotrophic soil microbes under the drought stress. On the contrary, we found that across the regional scale, nitrogen, phosphorous, and total soil organic content played a crucial role in moderating the duration and magnitude of CH4 uptake with respect to SWC. USC-γ (Upland Soil Cluster γ) and JR-3 (Jasper Ridge Cluster) were the dominant group of soil methanotrophic bacteria in three types of grassland. However, the methanotrophic abundance, rather than the methanotrophic community composition, was the dominant microbiological factor governing CH4 uptake during the drought.

Overlooked uneven progress across sustainable development goals at the global scale: Challenges and opportunities.

Differences in progress across sustainable development goals (SDGs) are widespread globally; meanwhile, the rising call for prioritizing specific SDGs may exacerbate such gaps. Nevertheless, how these progress differences would influence global sustainable development has been long neglected. Here, we present the first quantitative assessment of SDGs' progress differences globally by adopting the SDGs progress evenness index. Our results highlight that the uneven progress across SDGs has been a hindrance to sustainable development because (1) it is strongly associated with many public health risks (e.g., air pollution), social inequalities (e.g., gender inequality, modern slavery, wealth gap), and a reduction in life expectancy; (2) it is also associated with deforestation and habitat loss in terrestrial and marine ecosystems, increasing the challenges related to biodiversity conservation; (3) most countries with low average SDGs performance show lower progress evenness, which further hinders their fulfillment of SDGs; and (4) many countries with high average SDGs performance also showcase stagnation or even retrogression in progress evenness, which is partly ascribed to the antagonism between climate actions and other goals. These findings highlight that while setting SDGs priorities may be more realistic under the constraints of multiple global stressors, caution must be exercised to avoid new problems from intensifying uneven progress across goals. Moreover, our study reveals that the urgent needs regarding SDGs of different regions seem complementary, emphasizing that regional collaborations (e.g., demand-oriented carbon trading between SDGs poorly performed and well-performed countries) may promote sustainable development achievements at the global scale.

The associations between body dissatisfaction, exercise intensity, sleep quality, and depression in university students in southern China.

Background: In recent years, depression in early adulthood has become an urgent global public health concern. The university years mark a transitional period from adolescence to adulthood. Young people are required to face academic and life pressures independently, which increases the risk of mental health problems in university. Purpose: The main goal of the current study was to explore the sex differences in depression, body dissatisfaction, sleep quality, and exercise intensity among university students in southern China and to analyze the factors affecting the level of depression among university students. Methods: In total, 1,258 university students aged 18-23 years were recruited for this study. All participants completed anthropometric measurements, the Self-rating Depression Scale, Physical Activity Rating Scale, and Pittsburgh Sleep Quality Index. Body dissatisfaction levels were measured using sex-appropriate silhouettes. Results: Compared with young women, young men had higher exercise intensity and sleep quality, whereas young women's body dissatisfaction and depression levels were significantly higher than those of young men. Sleep quality score (ß = 0.34, p < 0.01), sex (ß = 0.15, p < 0.01), physical activity score (ß = -0.14, p < 0.01), and body dissatisfaction (ß = 0.14, p < 0.01) were significant predictive factors of the Self-rating Depression Scale score. Conclusion: Low levels of physical dissatisfaction have a positive effect on depression, and high levels of physical activity and quality sleep can also improve depressive symptoms. At the same time, increasing body satisfaction has the effect of increasing physical activity and improving sleep quality. Therefore, there is great potential to prevent and ameliorate depression by reducing body dissatisfaction.

Grassland biodiversity response to livestock grazing, productivity, and climate varies across biome components and diversity measurements.

Livestock overgrazing and climate change have been identified as the primary causes of grassland degeneration and biodiversity decline, yet the underlying mechanism remains unclear. To gain a better understanding of this, we conducted a meta-analysis of 91 local or regional field studies from 26 countries across all inhabited continents. Using concise statistical analyses, we assessed five theoretical hypotheses for grazing intensity, grazing history, grazing animal type, productivity, and climate, and decomposed the individual contributions of each factor in regulating multiple components of grassland biodiversity. After controlling for confounding effects, we found that: no significant linear or binomial pattern for the effect-size of grassland biodiversity as grazing intensity increased; the effect-size of producer richness was relatively lower (negative biodiversity response) in grasslands with a short grazing history, grazed by large livestock, high productivity, or high climate suitability; additionally, significant difference for the effect-size of consumer richness was only detected across grazing animal groups; and the effect-size of consumer abundance, and decomposer abundance all displayed significant differences with respect to grazing characters, grassland productivity, and climate suitability. Besides, results of hierarchical variance partitioning suggested that the total and individual contribution of predictors varied across biome components and diversity measurements. Specifically, grassland productivity acted as a key factor in driving producer richness. The findings presented here collectively suggest that the response of grassland biodiversity to livestock grazing, productivity, and climate varies across different components of the biome and measurements of diversity.

Navigating the landscape of global sustainable livelihood research: past insights and future trajectory.

Sustainable livelihoods (SL) have emerged as a crucial area of focus in global environmental change research, aligning with the Sustainable Development Goals (SDGs). This field is rapidly gaining prominence in sustainability science and has become one of the primary research paradigms. In our study, we conducted scientometrics analysis using the ISI Web of Science core collection database to examine research patterns and frontier areas in SL research. We selected 6441 papers and 265,759 references related to SL published from 1991 to 2020. To achieve this, we employed advanced quantitative analysis tools such as CiteSpace and VOSviewer to quantitatively analyze and visualize the evolution of literature in the SL research field. Our overarching objectives were to understand historical research characteristics, identify the knowledge base, and determine future research trends. The results revealed an exponential increase in SL research documentation since 1991, with the Consortium of International Agricultural Research Center (CGIAR) contributing the highest volume of research documents and citations. Key journals in this field included World Development, Global Environmental Change, Ecological Economics, and Ecology and Society. Notably, Singh RK and Shackleton CM emerged as prolific authors in SL research. Through our analysis, we identified six primary clusters of research areas: livelihoods, conservation, food security, management, climate change, and ecosystem services. Additionally, we found that tags such as rural household, agricultural intensification, cultural intensification, and livelihoods vulnerability remained relevant and represented active research hotspots. By analyzing keyword score relevance, we identified frontier areas in SL research, including mass tourism, solar home systems, artisanal and small-scale mining, forest quality, marine-protected areas, agricultural sustainability, sustainable rangeland management, and indigenous knowledge. These findings provide valuable insights to stakeholders regarding the historical, current, and future trends in SL research, offering strategic opportunities to enhance the sustainability of livelihoods for farmers and rural communities in alignment with the SDGs.

Vegetation structural shift tells environmental changes on the Tibetan Plateau over 40 years.

Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm.

Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.