Meta-analysis shows the impacts of ecological restoration on greenhouse gas emissions.

International initiatives set ambitious targets for ecological restoration, which is considered a promising greenhouse gas mitigation strategy. Here, we conduct a meta-analysis to quantify the impacts of ecological restoration on greenhouse gas emissions using a dataset compiled from 253 articles. Our findings reveal that forest and grassland restoration increase CH4 uptake by 90.0% and 30.8%, respectively, mainly due to changes in soil properties. Conversely, wetland restoration increases CH4 emissions by 544.4%, primarily attributable to elevated water table depth. Forest and grassland restoration have no significant effect on N2O emissions, while wetland restoration reduces N2O emissions by 68.6%. Wetland restoration enhances net CO2 uptake, and the transition from net CO2 sources to net sinks takes approximately 4 years following restoration. The net ecosystem CO2 exchange of the restored forests decreases with restoration age, and the transition from net CO2 sources to net sinks takes about 3-5 years for afforestation and reforestation sites, and 6-13 years for clear-cutting and post-fire sites. Overall, forest, grassland and wetland restoration decrease the global warming potentials by 327.7%, 157.7% and 62.0% compared with their paired control ecosystems, respectively. Our findings suggest that afforestation, reforestation, rewetting drained wetlands, and restoring degraded grasslands through grazing exclusion, reducing grazing intensity, or converting croplands to grasslands can effectively mitigate greenhouse gas emissions.

Effects of drought and nutrient deficiencies on the allocation of recently fixed carbon in a plant-soil-microbe system.

Carbon (C) allocation plays an important role in plant adaptation to water and nutrient stresses. However, the effects of drought and nutrient deficiencies on the allocation of recently fixed C in the plant-soil-microbe system remain largely unknown. Herein, we studied the response of C allocation of Sophora moorcroftiana (an indigenous pioneer shrub in Tibet) to drought, nitrogen (N) deficiency and phosphorus (P) deficiency using a microcosm experiment. The 13CO2 continuous labeling was used to trace C allocation in the plant-soil-microbe system. We found that drought significantly reduced plant 13C, but it increased 13C accumulation in soil. The decreased plant 13C under drought was attributed to the decrease of 13C in stem and root rather than that in leaf. The excess 13C fraction in the microbial biomass (MB13C) was reduced by N deficiency, but it was not affected by the combination of drought and N deficiency, indicating that drought weakened the effects of N deficiency on MB13C. By contrast, MB13C increased under the combination of drought and P deficiency, suggesting that drought enhanced the effects of P deficiency on MB13C. Drought and nutrient deficiencies regulated the belowground 13C allocation. Specifically, drought and P deficiency increased the allocation of 13C to root and N deficiency regulated the allocation of 13C to microbial biomass C and dissolved organic C in soil. Notably, soil 13C decreased with increasing plant 13C, while MB13C first decreased and then increased with increasing plant 13C. Overall, our study demonstrated that drought and nutrient deficiencies interactively affected C allocation in a plant-soil-microbe system and provided insights into C allocation strategies in response to multiple resource (water and nutrient) stresses under environmental changes.

Effect of multiple spatial scale characterization of land use on water quality.

Land use in uplands is an important factor affecting water quality in its respective catchment, and its influences at the different spatial scales and configurations warrant further investigation. Here, we selected 26 catchments in the upper Han River (China) and sampled the surface water at the outlet of each catchment in four seasons during 2019. Multivariate statistics were used to identify the relationships between land use characteristics in uplands and water quality in river system. The results indicated that chemical oxygen demand (CODMn); pH; dissolved oxygen; electrical conductivity; nutrient, i.e., NH4+-N, NO3--N; and dissolved phosphorus (DP) in rivers displayed significant seasonal variations. Stepwise regression revealed that landscape metrics such as patch density, landscape shape index, and splitting index were important factors influencing water quality in rivers regardless of their spatiality and seasonality. Urban was the most frequently chosen land-use type in the best prediction models, and forest area showed a negative correlation with water quality parameters in most cases for example, DP. Overall, the influence of land use on river water quality was slightly stronger at reach scale than at catchment and riparian scales. Also, nutrients (i.e., NH4+-N, NO3--N, and DP) in rivers were primarily impacted by the land use characteristic at catchment and riparian scales. Our results suggested that multi-scale explorations would help to achieve a fully understanding on the impacts of land use on river water quality.

Changes in the composition of rhizosphere bacterial communities in response to soil types and acid rain.

It is widely known how acid rain negatively impacts plant physiology. However, the magnitude of these effects may depend on soil types. Although the response of aboveground parts has received much attention, the effects of soil types and acid rain on underground processes are yet to be studied, specifically with respect to the composition and diversity of bacterial communities in the rhizosphere. Based on a high throughput sequencing approach, this study examined how different soil types, acid rain of different pH, and interactions between the two factors influenced the growth and rhizosphere bacterial communities of Jatropha curcas L. The present study pointed out that the soil pH, total nitrogen (TN), total phosphorus (TP), total potassium (TK), and total organic carbon/total nitrogen (C/N) were more related to soil type than to acid rain. The growth of J. curcas aboveground was mainly affected by acid rain, while the underground growth was mainly influenced by soil type. Changes in bacterial abundance indicated that the genera (Burkholderia-Paraburkholde, Bryobacter, Cupriavidus, Mycobacterium, and Leptospirillu) and phyla (Acidobacteria and Actinobacteria) could likely resist acid rain to some extent, with Acidobacteria, Gemmatimonadetes and Proteobacteria being well adapted to the copiotrophic environments. Results of correlational analyses between Firmicutes and soil properties (pH, TN, TK) further indicated that this phylum was also well adapted to a nutrient-deficient habitat of low pH. Finally, while Mycobacterium and Bradyrhizobium could adapt to low pH, high soil TK contents were not conducive to their enrichment. The results also showed that acid rain shifted the bacterial groups from fast-growing copiotrophic populations to slow-growing oligotrophic ones. The RDA analysis, and Pearson's rank correlation coefficients indicated that soil pH and TK were the main factors influencing bacterial richness.

The Carbon Emission Characteristics and Reduction Potential in Developing Areas: Case Study from Anhui Province, China.

Global warming and world-wide climate change caused by increasing carbon emissions have attracted a widespread public attention, while anthropogenic activities account for most of these problems generated in the social economy. In order to comprehensively measure the levels of carbon emissions and carbon sinks in Anhui Province, the study adopted some specific carbon accounting methods to analyze and explore datasets from the following suggested five carbon emission sources of energy consumption, food consumption, cultivated land, ruminants and waste, and three carbon sink sources of forest, grassland and crops to compile the carbon emission inventory in Anhui Province. Based on the compiled carbon emission inventory, carbon emissions and carbon sink capacity were calculated from 2000 to 2019 in Anhui Province, China. Combined with ridge regression and scenario analysis, the STIRPAT model was used to evaluate and predict the regional carbon emission from 2020 to 2040 to explore the provincial low-carbon development pathways, and carbon emissions of various industrial sectors were systematically compared and analyzed. Results showed that carbon emissions increased rapidly from 2000 to 2019 and regional energy consumption was the primary source of carbon emissions in Anhui Province. There were significant differences found in the increasing carbon emissions among various industries. The consumption proportion of coal in the provincial energy consumption continued to decline, while the consumption of oil and electricity proceeded to increase. Furthermore, there were significant differences among different urban and rural energy structures, and the carbon emissions from waste incineration were increasing. Additionally, there is an inverted "U"-shape curve of correlation between carbon emission and economic development in line with the environmental Kuznets curve, whereas it indicated a "positive U"-shaped curve of correlation between carbon emission and urbanization rate. The local government should strengthen environmental governance, actively promote industrial transformation, and increase the proportion of clean energy in the energy production and consumption structures in Anhui Province. These also suggested a great potential of emission reduction with carbon sink in Anhui Province.

High-Throughput Metabolic Soft-Spot Identification in Liver Microsomes by LC/UV/MS: Application of a Single Variable Incubation Time Approach.

CYP-mediated fast metabolism may lead to poor bioavailability, fast drug clearance and significant drug interaction. Thus, metabolic stability screening in human liver microsomes (HLM) followed by metabolic soft-spot identification (MSSID) is routinely conducted in drug discovery. Liver microsomal incubations of testing compounds with fixed single or multiple incubation time(s) and quantitative and qualitative analysis of metabolites using high-resolution mass spectrometry are routinely employed in MSSID assays. The major objective of this study was to develop and validate a simple, effective, and high-throughput assay for determining metabolic soft-spots of testing compounds in liver microsomes using a single variable incubation time and LC/UV/MS. Model compounds (verapamil, dextromethorphan, buspirone, mirtazapine, saquinavir, midazolam, amodiaquine) were incubated at 3 or 5 µM with HLM for a single variable incubation time between 1 and 60 min based on predetermined metabolic stability data. As a result, disappearances of the parents were around 20-40%, and only one or a few primary metabolites were generated as major metabolite(s) without notable formation of secondary metabolites. The unique metabolite profiles generated from the optimal incubation conditions enabled LC/UV to perform direct quantitative estimation for identifying major metabolites. Consequently, structural characterization by LC/MS focused on one or a few major primary metabolite(s) rather than many metabolites including secondary metabolites. Furthermore, generic data-dependent acquisition methods were utilized to enable Q-TOF and Qtrap to continuously record full MS and MS/MS spectral data of major metabolites for post-acquisition data-mining and interpretation. Results from analyzing metabolic soft-spots of the seven model compounds demonstrated that the novel MSSID assay can substantially simplify metabolic soft-spot identification and is well suited for high-throughput analysis in lead optimization.

Soil bacteria are more sensitive than fungi in response to nitrogen and phosphorus enrichment.

Anthropogenic activities have dramatically increased nitrogen (N) and phosphorous (P) enrichments in terrestrial ecosystems. However, it is still unclear on how bacterial and fungal communities would respond to the simultaneously increased N and P enrichment. In this study, we used a field experiment to simulate N and P input, and examined the effects of N and P additions on the abundance, alpha-diversity, and community composition of soil bacteria and fungi in a riparian forest. Six nutrient-addition treatments, including low N (30 kg N ha-1 year-1), high N (150 kg N ha -1 year-1), low P (30 kg P2O5 ha-1 year-1), high P (150 kg P2O5 ha -1 year-1), low N+P, high N+P, and a control (CK) treatment were set up. We found that the N and P additions significantly affected bacterial abundance, community composition, but not the alpha diversity. Specifically, 16S, nirK, and nirS gene copy numbers were significantly reduced after N and P additions, which were correlated with decreases in soil pH and NO- 3-N, respectively; Co-additions of N and P showed significantly antagonistic interactions on bacterial gene copies; Nutrient additions significantly increased the relative abundance of Proteobacteria while reduced the relative abundance of Chloroflexi. Mantel's test showed that the alteration in bacterial composition was associated with the changes in soil pH and NO- 3-N. The nutrient additions did not show significant effects on fungal gene copy numbers, alpha diversity, and community composition, which could be due to non-significant alterations in soil C/N and total P concentration. In conclusion, our results suggest that soil bacteria are more sensitive than fungi in response to N and P enrichment; the alterations in soil pH and NO- 3-N explain the effects of N and P enrichment on bacterial communities, respectively; and the co-addition of N and P reduces the negative effects of these two nutrients addition in alone. These findings improve our understanding of microbial response to N and P addition, especially in the context of simultaneous enrichment of anthropogenic nutrient inputs.

[Species-habitat association of a deciduous broadleaved forest in the subtropical and tempe-rate transition zone]. / 亚热带-温带气候过渡区落叶阔叶林物种-ç”Ÿå¢ƒå ³è”åˆ†æž.

The species-habitat association analysis facilitates a better understanding of species coexis-tence and community assembly. Here, all trees in a 25-hm2 broadleaved deciduous forest plot in the Qinling Mountains of North-central China were classified into three life stages (i.e., seedling, sapling, and adult). The Torus-translation test was used to examine the species-habitat association. The results showed that the association of species with habitats varied across different species. Most species were significantly associated with high slopes, 95.7% of which showed negative association. 89.5% and 90.9% of tree species were negatively associated with low slopes and ridges, respectively. Most species had positive association with high valley, with only one negative association (0.03%). There were 80, 44 and 23 significant associations with habitats at seedling, sapling and adult stages, respectively, indicating that a greater dependence of seedlings on habitat. 38 species at seedling stage and 25 species at the sapling stage were associated with at least one habitat type, while only 17 species at the adult stage were significantly associated. The effects of habitat on species varied across life stages, showing a weaker species-habitat association at the later stage. Due to the specific environmental demands, most species showed different habitat preferences across life stages.

Spatial and temporal differentiation and influencing factors of environmental governance performance in the Yangtze River Delta, China.

As the development of Yangtze River Delta urban agglomeration has been upgraded to a national level development strategy in China, relevant regions need to pay more attention to the environmental governance issues. Based on the 2013-2018 development data of 41 cities and the established evaluation indicator system with "press-state-response" (PSR) model, we mainly use a combination of global principal component analysis (GPCA) and entropy method to comprehensively measure regional environmental governance performance (EGP) in the Yangtze River Delta urban agglomeration. Next, the spatial relationship is explored and discussed with spatial autocorrelation analysis. Finally, the panel Tobit model is used to perform a regression analysis on the factors affecting the performance of environmental governance in the Yangtze River Delta region. The results are summarized as follows. (1) From 2013 to 2018, the overall environmental governance performance of the Yangtze River Delta region maintained a steady growth trend, of which the environmental governance performance of Jiangsu Province and Shanghai maintained a steady increase, and the environmental governance performance of Anhui and Zhejiang Province fluctuated greatly. (2) These cities with better EGP are mainly located in the central and southern regions of the Yangtze River Delta, and those cities with poor EGP are mainly located in the northern part of the Yangtze River Delta. The environmental governance performance gap between provinces and cities is obviously large, and there are significant spatial positive correlations, spatial spillover effects and a trend of agglomeration with increased volatility. (3) The regression analysis shows that the economic development level has a significant positive impact on the EGP of the Yangtze River Delta region. Meanwhile, the negative impact of industrial structure and foreign investment is significant, but the positive impact of R&D investment intensity is insignificant, on the performance of environmental governance in the Yangtze River Delta region.

Performance evaluation of urban environmental governance in Anhui Province based on spatial and temporal differentiation analyses.

When the process of urbanization has brought economic benefits in the Yangtze River Delta of China, environmental pollution becomes increasingly prominent. In order to achieve integrated sustainable green development and reduce the gap in environmental governance performance between regions, this study analyzed the environmental issues of provincial cities in Anhui Province from 2013 to 2017 in the urban agglomeration of Yangtze River Delta. Governance performance is analyzed and the evaluation index system framework is determined using the "pressure-state-response" model with the panel and spatial data. Based on the global principal component analysis method and spatial autocorrelation analysis, the environmental governance performance of Anhui Province has generally increased steadily from 2013 to 2017. The situation in northern Anhui is still developing in a good state. Southern Anhui is in a trend of rising first and then stabilizing, whereas central Anhui has a downward trend after a rapid rise; in terms of the spatial pattern, the overall situation is central Anhui > northern Anhui > southern Anhui. The urban spatial distribution pattern of the region shows a positive spatial correlation. Particularly, the performance levels of Maanshan City and Huainan City have been at a poor level for a long time, whereas Hefei and Huangshan have strong comprehensive environmental governance capabilities with average efficiency values of 0.55 and 0.47, respectively. Corresponding countermeasures have been proposed to rectify polluting enterprises and optimize structure of industries, increase scientific and technological investment and infrastructure construction, strengthen the radiation driving effects, and establish a pollution monitoring system. Based on all the analyses and resulted findings, we concluded the study with corresponding policy implications/suggestions and recommended countermeasures.

Assessing the corporate green technology progress and environmental governance performance based on the panel data on industrial enterprises above designated size in Anhui Province, China.

Assessing the corporate green technology progress and environmental governance performance is essential to estimate the technological levels and environment regulation capabilities of enterprises. With the official statistics of collected panel data, we estimate and evaluate the differential levels of provincial corporate green technology and environmental governance performance of industrial enterprises above designated size (IEADSs) in Anhui Province across multiple dimensions. We firstly chose each surveyed city as the decision-making unit (DMU) in data envelopment analysis (DEA). Subsequently, we estimated the green technology efficiency of IEADSs from a static perspective by using the bootstrap DEA model and an improved super-efficiency (SE) DEA model. Secondly, we used the algorithm of Malmquist productivity index to analyze the dynamic efficiency development tendency and spatiotemporal characteristics in the DMUs. From a dynamic perspective, the evolutionary divergence and convergence characteristics of provincial green technology efficiency were brought about by the estimating algorithm of Malmquist productivity index based on the different regional divisions in Anhui Province. Furthermore, in combination with Malmquist-data envelopment analyses, we also used gray correlation analysis to analyze and evaluate the influencing factors of the industrial green technology efficiencies. This study shows many interesting findings across multiple dimensions. Among the 16 DMUs, there are only eight with the regional green technology efficiencies of IEADSs greater than the expected threshold of 0.9. Nevertheless, the green technology efficiencies of provincial industrial enterprises are still far from the national optimized goals in most of the surveyed cities. The regional green technology efficiencies of IEADSs were ranked as South Anhui > North Anhui > Middle Anhui. The overall average industrial green technology efficiency is 0.8650 in Anhui Province, but the provincial differences of sub-area distribution are relatively large and heterogeneous. The average provincial industrial green technology efficiency appeared as the overall tendency to rise, fall, and then rise, although there is an average bootstrapped Malmquist productivity indices of 1.009 in Anhui Province. Among the declined provincial Malmquist productivity indices, the effch, techch, and sech indices are vital causers of the overall decline of the provincial Malmquist productivity indices. Ultimately, based on all these quantitative estimates and findings, we put forward the following concluding remarks with policy implications and corresponding strategies.

Plumbagin inhibits proliferation and promotes apoptosis of ovarian granulosa cells in polycystic ovary syndrome by inactivating PI3K/Akt/mTOR pathway.

Polycystic ovary syndrome (PCOS) is recognized as a general endocrine disease and reproductive disorder. Although evidence indicates that PCOS has a complex etiology and genetic basis, the pathogenic mechanisms and signal pathway in PCOS remain unclear. In this study, the normal structure of follicle and corpus luteum were observed, and no cyst nor hyperemia was observed under the light microscopic study with hematoxylin and eosin (H&E) staining. Eestosterone and progesterone were evaluated by radioimmunoassay in rat serum. The alterations of proliferative ability and cell cycle distribution of each group were assessed by Cell Counting Kit-8 (CCK8) assay and flow cytometry. The protein expression of p-mTOR/mTOR, p-PI3K/PI3K, p-AKT/AKT, and GAPDH were analyzed by western blotting. Both doses of PLB could benefit the ovarian morphology and polycystic property. PLBinduced a suppress effect on the proliferation of rat ovarian granulosa cells. In addition, PLB also induced concentration-dependent apoptosis in rat ovarian granulosa cells. The rat ovarian granulosa cells treated with PLB that the expression levels of p-AKT, p-mTOR, and p-PI3K were significantly decreased in a concentration-dependent manner. PLB not only plays a critical role in attenuating the pathology and polycystic property changes in the ovary but can also induce rat ovarian granulosa cell apoptosis through the PI3K/Akt/mTOR signal pathway. This study showed the innovative role of PLB in the pathogenesis of PCOS and provides a new therapeutic modality for the treatment of PCOS.

Effects of human disturbance activities and environmental change factors on terrestrial nitrogen fixation.

Biological nitrogen (N) fixation plays an important role in terrestrial N cycling and represents a key driver of terrestrial net primary productivity (NPP). Despite the importance of N fixation in terrestrial ecosystems, our knowledge regarding the controls on terrestrial N fixation remains poor. Here, we conducted a meta-analysis (based on 852 observations from 158 studies) of N fixation across three types of ecosystems with different status of disturbance (no management, restoration [previously disturbed], and disturbance [currently disturbed]) and in response to multiple environmental change factors (warming, elevated carbon dioxide [CO2 ], increased precipitation, increased drought, increased N deposition, and their combinations). We explored the mechanisms underlying the changes in N fixation by examining the variations in soil physicochemical properties (bulk density, texture, moisture, and pH), plant and microbial characteristics (dominant plant species numbers, plant coverage, and soil microbial biomass), and soil resources (total carbon, total N, total phosphorus (P), inorganic N, and inorganic P). Human disturbance inhibited non-symbiotic N fixation but not symbiotic N fixation. Terrestrial N fixation was stimulated by warming (+152.7%), elevated CO2 (+19.6%), and increased precipitation (+73.1%) but inhibited by increased drought (-30.4%), N deposition (-31.0%), and combinations of available multiple environmental change factors (-14.5%), the extents of which varied among biomes and ecosystem compartments. Human disturbance reduced the N fixation responses to environmental change factors, which was associated with the changes in soil physicochemical properties (2%-56%, p < .001) and the declines in plant and microbial characteristics (3%-49%, p ≤ .003) and soil resources (6%-48%, p ≤ .03). Overall, our findings reveal for the first time the effects of multiple environmental change factors on terrestrial N fixation and indicate the role of human disturbance activities in inhibiting N fixation, which can improve our understanding, modeling, and prediction of terrestrial N budgets, NPP, and ecosystem feedbacks under global change scenarios.

Disparity in elevational shifts of upper species limits in response to recent climate warming in the Qinling Mountains, North-central China.

Examinations of upper elevational distribution limits of tree species can provide indications of how subalpine vegetation responds to the ongoing climate warming. Dynamics and functional mechanisms of elevational treelines are reasonably well understood, while explanations for tree species-specific upper elevational distribution limits below the treeline still remain unclear. In this study, we used a state-of-the-art dendroecological approach to reconstruct long-term changes of species-specific upper elevational distribution limits of different plant functional type (i.e., light-demanding deciduous coniferous larch at treeline, shade-tolerant evergreen coniferous fir and shade-intolerant deciduous broad-leaved birch below treeline) along elevational gradients in the Qinling Mountains of north-central China. Over the past three centuries, all the upper species limits shifted upslope as a response to climate warming. However, the warming-induced upslope migrations showed substantial differences, displaying the maximum upward shift of larch with an average elevation of 24.7 m during the past century, while only a slight advance of the non-treeline tree species. The disparity in elevational advance of upper species limits might be attributable to the presence of interspecific competition, showing that the non-treeline tree species experienced intermediate interspecific competition while the treeline tree species experienced no interspecific competition. Thus, our findings suggested that in addition to climate warming, biotic interaction may contribute much to shaping the species-specific upper limit dynamics. This study not only enhanced mechanistic understanding of long-term species-specific upper elevational distribution limit changes, but also highlighted the jointly effects of rising temperatures and species interactions on subalpine vegetation dynamics.

Ecophysiological responses of Jatropha curcas L. seedlings to simulated acid rain under different soil types.

Acid rain is a global environmental problem. Acid rain can affect plants directly by damaging the leaves and indirectly by soil acidifying. Many studies have been conducted to investigate the impacts of acid rain on plant under a single soil type. However, there is little information on the effect of acid rain on plant under different soil types. Jatropha curcas L. is an energy plant widely distributed in acid rain pollution area with various soil types. In this study, we investigated the effects of acid rain (pH2.5, pH3.5, pH4.5, pH5.6) on the growth, physiology, nutrient elements and bacterial community of J. curcas seedlings under different soil types [Red soils (RS), Yellow soils (YS), Yellow-brown soils (YBS), and Purplish soils (PS)]. Acid rain and soil types significantly influence the growth of J. curcas seedlings, and there was a significant interaction between acid rain and soil types. Acid rain (pH 4.5) was beneficial to the growth of J. curcas seedlings, whereas acid rain (pH 2.5 or 3.5) inhibited growth of J. curcas seedlings. The growth of J. curcas seedlings could resist the stress of acid rain by scavenging and detoxification of active oxygen species in leaves. Combined with the increase in relative growth rate of seedlings treated with simulated acid rain at pH 4.5, we inferred that K can stimulate the growth of seedlings. The lower soil pH, cation exchange capacity and base saturation had stronger inhibitory effects on growth of J. curcas seedlings. YBS and PS were beneficial for growth of J. curcas seedlings by higher buffering capacity under acid rain treatments. The phylum Proteobacteria was found to predominate in rhizosphere soils. YBS was favorable to support Proteobacteria growth and reproduction. The redundancy analysis showed that the Cyanobacteria were favorable to growth of J. curcas seedlings.

Methodology for accounting the net mitigation of China's ecological restoration projects (CANM-EP).

The real emission mitigation by the ecological restoration projects depends upon the integrated effect of all greenhouse gas (GHG) budgets rather than the carbon sequestration alone. However, a comprehensive and robust methodology for estimating the relevant GHG budgets and net mitigation of China's ecological restoration projects is still urgently to await development. Based on the methods from IPCC and statistical data of the management practices under the projects, we constructed a methodology for carbon accounting and determining net mitigation for ecological restoration projects in China (CANM-EP). GHG emissions generated from different processes and practices of the projects were included in the CANM-EP, and by this methodology, carbon sequestration, GHG balance changes induced by ecological response, on-site and off-site GHG emissions could be estimated. Therefore, the CANM-EP provides comprehensive methods to estimate the whole GHG budgets as well as the net mitigation of China's ecological restoration projects. •The CANM-EP provides accounting methods for comprehensive processes and management practices under respective ecological restoration projects in China.•The CANM-EP could simultaneously estimate carbon sequestration and GHG emissions of the projects.•The CANM-EP indicates net carbon sequestration and net contribution of China's ecological restoration projects to climate change mitigation.

Empirical analysis of the intelligent influence factors of social network services effectiveness in e-commerce based on human learning behaviors.

Background: It is crucial for companies to understanding users' choices and learning behaviors, and the corresponding influencing factors and cognitive patterns regarding social network services to communicate with potential customers. Methods: In this study, a casual structural model was constructed and developed to model and characterize the relationships between problems to be resolved as antecedent variables and success factors as consequent variables with the intermediary variables based on human learning behaviors, whereas the concept of social network service was introduced to summarize the current issues of social network services and empirically factors affecting effectiveness of social network services. Discussion: This study highlighted the corporate need to examine the intelligent role and learning effectiveness of social network services when studying social creativity and intelligence in a social networking environment. Firstly, the framework and hypotheses of social network services were introduced to summarize the current issues of social network services and the main influencing factors affecting the working patterns of social network services. Subsequently, the empirically established model was further tested to explore the possible meaningful relationships among those variables used. Results: The study revealed that the social network services provider and the customer should improve their social creativity and community collaboration; these could be expanded and enhanced by increasing the social intelligence to raise the social network services' effect and the customer's externalization. Furthermore, social intelligence, community collaboration, and customer externalization were factors significantly influencing customers' social creativity, while the customer externalization and community collaboration were the two important factors affecting social intelligence. Conclusion: The study implied that social network services providers should provide more and more intelligent and inspiring services for their customers.

The impact of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province, China, from 2012 to 2016.

The study was designed to evaluate the impact of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province, China, during the period of 2012-2016. The econometric models of DEA and SEM-PLS and Malmquist index are used to explore the potential impacts of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province. After an initial analysis of SEM-PLS model, the models of DEA and Malmquist index are used to evaluate the differentiated degrees and dynamic development levels of local technological innovation efficiencies of industrial enterprises in different regions of Anhui province. With these analyses, the study presents three main results as follows. There is a positive correlation between the technological innovation efficiencies of industrial enterprises and the technological performance levels of environmental disposal. Meanwhile, there is a large gap among the environmental disposing performances of industrial enterprises in different regions of Anhui province. There is also a large gap between the expected and actual technological performances of industrial enterprises' environmental disposal, according to the results of SEM-PLS analysis. Furthermore, there are several obvious characteristics of geographical distribution in the impact of differentiated technological innovation efficiencies of industrial enterprises on local environmental pollutant emissions observed from the results of the DEA and Malmquist index models. However, it is not consistent with the overall provincial development trend and regional distribution pattern of industrial economics in Anhui province over the period of 2012-2016. Under the rapid development of social economics and modern technological advance, there is a weak impact of differentiated technological innovation efficiency on the technological performance of industrial environmental disposal in different regions of Anhui province. Meanwhile, the environmental disposal capacity of enterprises' technological innovation become declining too. Finally, some countermeasures and policy suggestions are put forward based on the investigation and comprehensive analyses of the DEA and SEM-PLS and Malmquist index models.

Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010.

The long-term stressful utilization of forests and grasslands has led to ecosystem degradation and C loss. Since the late 1970s China has launched six key national ecological restoration projects to protect its environment and restore degraded ecosystems. Here, we conducted a large-scale field investigation and a literature survey of biomass and soil C in China's forest, shrubland, and grassland ecosystems across the regions where the six projects were implemented (∼16% of the country's land area). We investigated the changes in the C stocks of these ecosystems to evaluate the contributions of the projects to the country's C sink between 2001 and 2010. Over this decade, we estimated that the total annual C sink in the project region was 132 Tg C per y (1 Tg = 1012 g), over half of which (74 Tg C per y, 56%) was attributed to the implementation of the projects. Our results demonstrate that these restoration projects have substantially contributed to CO2 mitigation in China.

Precise Dissolution Control and Bioavailability Evaluation for Insoluble Drug Berberine via a Polymeric Particle Prepared Using Supercritical CO2.

It is still controversial whether poor aqueous solubility is the most primary reason for the low oral bioavailability of insoluble drugs. Therefore, in this study, berberine-loaded solid polymeric particles (BPs) of varied dissolution profiles with ß-cyclodextrin (ß-CD) as carrier were fabricated using solution-enhanced dispersion by supercritical fluids (SEDS), and the relationship between dissolution and berberine (BBR) bioavailability was evaluated. Dissolution property was controlled via particle morphology manipulation, which was achieved by adjusting several key operating parameters during the SEDS process. Characterization on BP using infrared spectroscopy, differential scanning calorimetry, and X-ray diffraction indicated that BBR was dispersed in amorphous form, while nuclear magnetic resonance spectroscopy showed that methoxy groups of BBR were included into the cavities of ß-CD. In vivo pharmacokinetic studies showed that oral bioavailability increased by about 54% and 86% when the dissolution rate of BBR was increased by 51% and 83%, respectively. The entry speed of BBR into the bloodstream was also advanced with the degree of dissolution enhancement. It seemed that dissolution enhancement gave positive effect to the oral bioavailability of berberine, but this might not be the crucial point. Meanwhile, supercritical CO2 technology is a promising method for pharmaceutical research due to its advantages in regulating drug-dosage properties.