Search

Field measurements, after extrapolation, suggest that deep Yedoma deposits (formed during the Pleistocene) and peatlands (formed during the Holocene) account for over 700 Pg C of soil carbon storage. Incorporating this old, deep, cold carbon into land surface models (LSMs) is crucial for accurately quantifying soil carbon responses to future warming. However, it remains underrepresented or absent in current LSMs, which typically include a passive soil carbon pool to represent all 'old carbon' and lack the vertical accumulation processes that deposited deep carbon in the soil layers of peat and Yedoma. In this study, we propose a new, more realistic protocol for simulating deep and cold carbon accumulation in the high latitudes, using the ORCHIDEE-MICT model. This is achieved by 1) integrating deep carbon from Yedoma deposits whose formation is calculated using Last Glacial Maximum climate conditions, and 2) prescribing the inception time and location of northern peatlands during the Holocene using spatially explicit data on peat age. Our results show an additional 157 Pg C in present-day Yedoma deposits, as well as a shallower peat carbon depth (by 1–5 m) and 35 Pg C (43 %) less passive soil carbon in northern peatlands, compared to the old protocol that ignored Yedoma deposits and applied a uniform, long-duration (13,500 years) peat carbon accumulation across all peatlands. As a result, the total organic carbon stock across the Northern Hemisphere (> 30° N) simulated by the new protocol is 2,028 Pg C, which is 226 Pg C higher than the previous estimate. Despite the significant challenge in simulating deep carbon with ORCHIDEE-MICT, the improvements in the representation of carbon accumulation from this study provide a model version to predict deep carbon evolution during the last glacial-deglacial transition and its response to future warming. The methodology implemented for deep carbon initialization in permafrost and cold regions in ORCHIDEE-MICT is also applicable to other LSMs. [ABSTRACT FROM AUTHOR]

Prediction of surface freshwater flux (precipitation or evaporation) in a CO2‐enriched climate is highly uncertain, primarily depending on the hydrological responses to physiological and radiative forcings of CO2 increase. Using the 1pctCO2 (a 1% per year CO2 increase scenario) experiments of 12 CMIP6 models, we first decouple and quantify the magnitude of global hydrological sensitivity to CO2 physiological and radiative forcings. Results show that the direct global hydrological sensitivity (for land plus ocean precipitation) to CO2 increase only is −0.09 ± 0.07% (100 ppm) −1 and to CO2‐induced warming alone is 1.54 ± 0.24% K−1. The latter is about 10% larger than the global apparent hydrological sensitivity (i.e., including all effects, not only direct responses to warming, ηa ${\eta }_{a}$ = 1.39 ± 0.22% K−1). These hydrological sensitivities are relatively stable over transient 2× to 4 × CO2 scenario. The intensification of the global water cycle are dominated by the CO2 radiative effect (79 ± 12%) with a smaller positive contribution from the interaction between the two effects (6 ± 12%), but are reduced by the CO2 physiological effect (−10 ± 8%). This finding underlines the importance of CO2 vegetation physiology in global water cycle projections under a CO2‐enriched and warming climate. Plain Language Summary: Projections of future water resource under rising CO2 and warming scenarios are highly uncertain, which is mainly due to the poor understanding of hydrological responses within the Earth system. We evaluate two major hydrological responses associated with rising CO2 related effects: physiological effect (e.g., decrease in plant stomatal conductance per unit leaf area, increase in leaf area index and net available energy, etc.) and radiative effect (e.g., rising CO2‐induced warming, rapid atmospheric adjustment and surface energy budget change, etc.). Using 12 Earth system models' experiments, we find that the CO2 physiological effect will cause ∼0.1% decline for precipitation or evaporation per 100 ppm CO2 increase at a global scale. The CO2 radiative effect will cause ∼1.5% increase for precipitation or evaporation per Kelvin warming. These changing rates of increase or decline are relatively stable with increasing CO2 forcing. The modeling experiments under high CO2 forcing project that the intensification of the global water cycle is mainly controlled by the CO2 radiative effect, but the CO2 physiological effect and the interaction between the two effects also play important roles. Key Points: Global hydrological responses to forcings from rising CO2‐induced physiological and radiative effects were decoupled from CMIP6 models' simulations with 1% per year CO2 increaseGlobal hydrological sensitivity to CO2 physiological forcing is −0.09 ± 0.07% (100 ppm)−1 and to CO2 radiative forcing is 1.54 ± 0.24% K−1 from transient 4 × CO2 simulationsGlobal hydrological sensitivities to CO2 physiological and radiative forcings have little changes over transient 2 × CO2 to 4 × CO2 scenario [ABSTRACT FROM AUTHOR]

Background and aims: As a significant land carbon sink, highly acid subtropical forests in southern China continued to accumulate a significant amount of soil carbon under elevated acid deposition, yet the mechanism of how soil organic carbon (SOC) and its two components: particulate (POC) and mineral-associated (MAOC) organic carbon increased remain unclear. We aim to assess which mechanism and drivers dominated the accumulation of SOC and its two fractions under elevated acid deposition. Methods: We conducted a 11-year field acid addition experiment to study how acid deposition affected the accumulation of SOC and its fractions. Lignin phenols and amino sugars were used as two tracers for plant- and microbe-derived carbon. Results: We found that both POC (0–20 cm) and MAOC (10–20 cm) were significantly increased by acid addition. Acid addition significantly reduced the contributions of fungal-, bacterial- or total microbial residue carbon to SOC but significantly increased the plant-derived soil carbon in both soil depths. The increase of lignin phenol and suppressed soil organic matter decomposition from soil microbes suggested that soil POC increased with acid addition. Soil acidification strongly enhanced MAOC accumulation through increased lignin and mineral protection by iron-aluminum oxides and cations. Conclusion: Our results showed that increased mineral protection of plant-derived carbon was the dominant driver of the increased SOC sequestration under acid addition. This finding identified the dominant pathway for SOC accumulation in a highly acidic subtropical forest and provides new insights into understanding how plant-soil-mineral interact under increasing acid deposition in the region. [ABSTRACT FROM AUTHOR]

Spatially explicit prediction of soil organic carbon (SOC) serves as a crucial foundation for effective land management strategies aimed at mitigating soil degradation and assessing carbon sequestration potential. Here, using more than 1000 in situ observations, we trained two machine learning models (a random forest model and a k -means coupled with multiple linear regression model) and one process-based model (the vertically resolved MIcrobial-MIneral Carbon Stabilization, MIMICS, model) to predict the SOC stocks of the top 30 cm of soil in Australia. Parameters of MIMICS were optimised for different site groupings using two distinct approaches: plant functional types (MIMICS-PFT) and the most influential environmental factors (MIMICS-ENV). All models showed good performance with respect to SOC predictions, with an R2 value greater than 0.8 during out-of-sample validation, with random forest being the most accurate; moreover, it was found that SOC in forests is more predictable than that in non-forest soils excluding croplands. The performance of continental-scale SOC predictions by MIMICS-ENV is better than that by MIMICS-PFT especially in non-forest soils. Digital maps of terrestrial SOC stocks generated using all of the models showed a similar spatial distribution, with higher values in south-eastern and south-western Australia, but the magnitude of the estimated SOC stocks varied. The mean ensemble estimate of SOC stocks was 30.3 t ha -1 , with k -means coupled with multiple linear regression generating the highest estimate (mean SOC stocks of 38.15 t ha -1) and MIMICS-PFT generating the lowest estimate (mean SOC stocks of 24.29 t ha -1). We suggest that enhancing process-based models to incorporate newly identified drivers that significantly influence SOC variation in different environments could be the key to reducing the discrepancies in these estimates. Our findings underscore the considerable uncertainty in SOC estimates derived from different modelling approaches and emphasise the importance of rigorous out-of-sample validation before applying any one approach in Australia. [ABSTRACT FROM AUTHOR]

Biochar (BC) application to croplands aims to sequester carbon and improve soil quality, but its impact on soil organic carbon (SOC) dynamics is not represented in most land models used for assessing land-based climate change mitigation; therefore, we are unable to quantify the effects of biochar application under different climate or land management conditions. Here, to fill this gap, we implement a submodel to represent biochar in a microbial decomposition model named MIMICS (MIcrobial-MIneral Carbon Stabilization). We first calibrate and validate MIMICS with new representations of the density-dependent microbial turnover rate, adsorption of available organic carbon on mineral soil particles, and soil moisture effects on decomposition using global field-measured cropland SOC at 285 sites. We further integrate biochar in MIMICS by accounting for its effect on microbial decomposition and SOC sorption/desorption and optimize two biochar-related parameters in these processes using 134 paired SOC measurements with and without biochar addition. The MIMICS-biochar version can generally reproduce the short-term (≤ 6 years) and long-term (8 years) SOC changes after adding (mean addition rate of 25.6 t ha -1) biochar (R2= 0.79 and 0.97, respectively) with a low root-mean-square error (RMSE = 3.73 and 6.08 g kg -1 , respectively). Our study incorporates sorption and soil moisture processes into MIMICS and extends its capacity to simulate biochar decomposition, providing a useful tool to couple with dynamic land models to evaluate the effectiveness of biochar application with respect to removing CO 2 from the atmosphere. [ABSTRACT FROM AUTHOR]

Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions. [ABSTRACT FROM AUTHOR]

Spatially explicit prediction of soil organic carbon (SOC) serves as a crucial foundation for effective land management strategies aimed at mitigating soil degradation and assessing carbon sequestration potential. Here, using more than 1000 in-situ observations, we trained two machine learning models (random forest, and K-means coupled with multiple linear regression), and one process-based model (the vertically resolved MIcrobial-MIneral Carbon Stabilization (MIMICS)) to predict SOC content of the top 30 cm of soil in Australia. Parameters of MIMICS were optimized for different site groupings, using two distinct approaches, plant functional types (MIMICS-PFT), and the most influential environmental factors (MIMICS-ENV). We found that at the continental scale, soil bulk density and mean annual temperature are the dominant controls of SOC variation, and that dominant controls vary for different vegetation types. All models showed good performance in SOC predictions with R2 greater than 0.8 during out-of-sample validation with random forest being the most accurate, and SOC in forests is more predictable than that in non-forest soils. Parameter optimization approaches made a notable difference in the performance of MIMICS SOC prediction with MIMICS-ENV performing better than MIMICS-PFT especially in non-forest soils. Digital maps of terrestrial SOC stocks generated using all the models showed similar spatial distribution with higher values in southeast and southwest Australia, but the magnitude of estimated SOC stocks varied. The mean ensemble estimate of SOC stocks was 30.08 t/ha with K-means coupled with multiple linear regression generating the highest estimate (mean SOC stocks at 38.15 t/ha) and MIMICS-PFT generating the lowest estimate (mean SOC stocks at 24.29 t/ha). We suggest that enhancing process-based models to incorporate newly identified drivers that significantly influence SOC variations in different environments could be key to reducing the discrepancies in these estimates. Our findings underscore the considerable uncertainty in SOC estimates derived from different modelling approaches and emphasize the importance of rigorous out-of-sample validation before applying any one approach in Australia. [ABSTRACT FROM AUTHOR]

Background: The allocation of photosynthate among the parts of plants (e.g., leaves, wood tissues and roots) strongly regulates their growth, and this conditions the terrestrial carbon cycle. Recent studies have shown that atmospheric CO2 and climate change dominate the changes in carbon allocation in plants, but the magnitude and mechanism of its effects remain unclear. Methods: The Community Atmosphere Biosphere Land Exchange (CABLE) model can accurately simulate the responses of carbon allocation to environmental changes. This study quantifies the contributions of four environmental factors—atmospheric CO2, temperature, precipitation, and radiation—on resource availability and carbon allocation from 1979 to 2014 by using the CABLE model. Results: The results of the CABLE model showed that rising CO2 significantly reduced carbon allocation to the leaves of plants at a global scale, but the other three environmental factors exhibited contrasting effects that dominated the rise in carbon allocation to the leaves. The increased precipitation and CO2 significantly reduced the light availability and increased carbon allocation to the wooden parts of plants. By contrast, the rising temperature reduced the water availability, resulting in a decrease in carbon allocation to the wooden parts. All four environmental factors consistently exhibited negative effects on carbon allocation to the roots, with rising precipitation causing the largest reduction in carbon allocation to them. Moreover, except for CO2, the effects of the other three environmental factors were heterogeneous owing to their variable interactions in different regions. Conclusions: The CABLE model can accurately represent the mechanisms of response of resource availability and carbon allocation to environmental changes. Our study highlights the substantial environmental regulation of global carbon allocation. The responses of carbon allocation to global environmental changes need to be extensively studied through ecosystem models based on different hypotheses. [ABSTRACT FROM AUTHOR]

The article is a response to a commentary by Xiao et al. that questioned the conclusions of a study by Tao et al. on the role of microbial carbon use efficiency (CUE) in global soil organic carbon (SOC) storage. Tao et al. used a model to evaluate the relative importance of microbial CUE and other processes in determining SOC storage. They found that microbial CUE was more important than non-microbial carbon transfer and decomposition coefficients in determining SOC storage at a global scale. However, the authors acknowledge that more empirical evidence and mechanistic modeling studies are needed to establish causal relationships between CUE and SOC. They also emphasize the importance of incorporating process-based models with big data to gain a better understanding of global SOC storage. The study was funded by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship and the European Research Council. [Extracted from the article]

Most phosphorus (P) in soils is unavailable for direct biological uptake, as it is locked within primary or secondary mineral particles, adsorbed to mineral surfaces, or immobilized inside of organic material. Deciphering the composition of different P forms in soil is critical for understanding P bioavailability and its underlying dynamics. However, widely used global estimates of different soil P forms are based on a dataset containing few measurements in which many regions or soil types are unrepresented. This poses a major source of uncertainty in assessments that rely on these estimates to quantify soil P constraints on biological activity controlling global food production and terrestrial carbon balance. To address this issue, we consolidated a database of six major soil P "forms" containing 1857 entries from globally distributed (semi-)natural soils and 11 related environmental variables. These six different forms of P (labile inorganic P (Pi), labile organic P (Po), moderately labile Pi, moderately labile Po, primary mineral P, and occluded P) were measured using a sequential P fractionation method. As they do not represent precise forms of specific discrete P compounds in the soil but rather resemble operational pools, we will now refer to them as P pools. In order to quantify the relative importance of 11 soil-forming variables in predicting soil P pool concentrations and then make further predictions at the global scale, we trained random forest regression models for each of the P pools and captured observed variation with R2 higher than 60 %. We identified total soil P concentration as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH and only secondarily by total soil P concentration. When expressed in relative values (proportion of total P), the model showed that soil pH is generally the most important predictor for proportions of all soil P pools, alongside the prominent influences of soil organic carbon, total P concentration, soil depth, and biome. These results suggest that, while concentration values of P pools logically strongly depend on soil total P concentration, the relative values of the different pools are modulated by other soil properties and the environmental context. Using the trained random forest models, we predicted soil P pools' distributions in natural systems at a resolution of 0.5∘×0.5∘. Our global maps of different P pools in soils as well as the pools' underlying drivers can inform assessments of the role of natural P availability for ecosystem productivity, climate change mitigation, and the functioning of the Earth system. [ABSTRACT FROM AUTHOR]

Nitrogen (N) deposition usually increases plant tissue N concentrations and thus phosphorus (P) demand in young and/or N‐limited forests, but the N deposition effect on plant P demand has rarely been assessed in N‐saturated forests.Impacts of 18‐year external N additions (Control: 0, Low N: 50, Moderate N:100 and High N: 150 kg N ha−1 year−1) on leaf P of four plant life‐forms (tree, shrub, herb and liana), P fractions of bulk and rhizosphere soils were examined in a N‐saturated mature tropical forest in southern China.Leaf N, P and N: P ratios of all plant life‐forms remained stable under three N additions. Among soil P fractions, moderate labile organic P increased by 25%–33% across three N additions; and soil total P was increased by 11.76% under Low N, and 8.87% under High N, compared with the control. The PLS‐PM results showed that path coefficient of microbial community to available P significantly increased and of inorganic P to available P significantly decreased under N additions than control. N additions improved soil P availability through microbe‐mediated P transformation: Low N significantly increased soil microbial taxonomic diversity, and a higher microbial diversity could enlarge the sources of nutrient acquisition and stimulate decomposition of recalcitrant organic matters; while High N significantly decreased soil microbial taxonomic diversity, the remaining microorganisms that were screened by N‐rich environments had the characteristics of resisting the N addition effects and maintained efficient P acquisition.Synthesis. Our findings provide a novel line of evidence that long‐term N deposition did not increase plant P demand in a N‐saturated mature tropical forest. The underlying mechanism is that plants did not increase N uptakes therefore nor increase P uptakes (a stable leaf N: P stoichiometry) in an already N‐saturated ecosystem. Different N addition rates regulated soil P transformation via microbial community transition. These findings help improve the understanding of plant P acquisition and modelling of biogeochemical N–P cycling and vegetation productivity in N‐rich forest ecosystems, particularly considering the fact that chronic N deposition may likely lead to soil N richness and even saturation of many forests in the future. [ABSTRACT FROM AUTHOR]

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5–7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8–11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.A deep learning and data-driven modelling study finds that microbial carbon use efficiency is a major determinant of soil organic carbon storage and its spatial variation across the globe. [ABSTRACT FROM AUTHOR]

Global change ecology nowadays embraces ever‐growing large observational datasets (big‐data) and complex mathematical models that track hundreds of ecological processes (big‐model). The rapid advancement of the big‐data‐big‐model has reached its bottleneck: high computational requirements prevent further development of models that need to be integrated over long time‐scales to simulate the distribution of ecosystems carbon and nutrient pools and fluxes. Here, we introduce a machine‐learning acceleration (MLA) tool to tackle this grand challenge. We focus on the most resource‐consuming step in terrestrial biosphere models (TBMs): the equilibration of biogeochemical cycles (spin‐up), a prerequisite that can take up to 98% of the computational time. Through three members of the ORCHIDEE TBM family part of the IPSL Earth System Model, including versions that describe the complex interactions between nitrogen, phosphorus and carbon that do not have any analytical solution for the spin‐up, we show that an unoptimized MLA reduced the computation demand by 77%–80% for global studies via interpolating the equilibrated state of biogeochemical variables for a subset of model pixels. Despite small biases in the MLA‐derived equilibrium, the resulting impact on the predicted regional carbon balance over recent decades is minor. We expect a one‐order of magnitude lower computation demand by optimizing the choices of machine learning algorithms, their settings, and balancing the trade‐off between quality of MLA predictions and need for TBM simulations for training data generation and bias reduction. Our tool is agnostic to gridded models (beyond TBMs), compatible with existing spin‐up acceleration procedures, and opens the door to a wide variety of future applications, with complex non‐linear models benefit most from the computational efficiency. [ABSTRACT FROM AUTHOR]

Significant land greening since the 1980s has been detected through satellite observation, forest inventory, and Earth system modeling. However, whether and to what extent global land greening enhances ecosystem carbon stock remains uncertain. Here, using 40 global models, we first detected a positive correlation between the terrestrial ecosystem carbon stock and leaf area index (LAI) over time. Then, we diagnose the source of uncertainty of simulated the sensitivities of ecosystem carbon stock to LAI based on a traceability analysis. We found that the sensitivity of gross primary productivity (GPP) to LAI is the largest contributor to the model uncertainty in more than 60% of the vegetated grids. Using the ensemble of four long‐term global data sets of GPP and three satellite LAI products from 1982 to 2014, we provided an emergent constraint on the ecosystem carbon stock increase as 0.75 ± 0.46 kg C m−2 per unit LAI over global land areas. Furthermore, the biome‐based results reveal that the tropical forest regions have the highest inter‐model variation and model bias. Overall, this study identifies the uncertainty source and provides constrained estimates of the greening effect on ecosystem carbon stock at the global scale. Plain Language Summary: In the last few decades, we can see that there has been more green land from looking at satellite images, checking forest records, and using computer models. However, we do not know if having more green land is helping the ecosystem store more carbon. This study investigated the greening effect on ecosystem carbon stock among the 40 global models, but this effect varied between models. Therefore, we diagnosed the simulated source of uncertainty based on the traceability analysis framework. Based on satellite‐derived data sets, we further constrained the greening effect on ecosystem carbon stock at the global scale. Land greening enhances ecosystem carbon stock, although this increase is highly heterogeneous on a global scale. Key Points: A globally enhanced ecosystem C stock (ECS) by land greening has been detected since the 1980s from 40 global modelsThe sensitivity of gross primary productivity to leaf area index (LAI) is the largest contributor to the modeled greening effect on ECS uncertaintyThis study estimated the effect of global greening on ECS with the emergent constraint method [ABSTRACT FROM AUTHOR]

Soil parent material can strongly influence soil's physical and chemical properties, significantly affecting soil organic carbon (SOC) stabilization. However, the importance of different soil parent materials on the amount and composition of subsoil carbon in subtropical soils remains poorly qualified. Subsoil SOC (below A horizon) is chosen for this study because of its higher proportion of stable carbon than surface soils in A horizon. Here, we investigated the dependence of soil mineral‐associated organic carbon (MAOC) and its three mineral‐stabilized fractions on soil physical and chemical parameters (clay content, cation exchange capacity (CEC) and metal oxides) in the subsoil soil (B and C horizons) originating from three contrasting parent materials (sandshale, granite, limestone). The results showed that MAOC accounts for an average of 88% of total SOC, of which organo‐metal complexes (extracted with sodium pyrophosphate) are the dominant form at all three sites. MAOC and its three fractions were significantly correlated with soil clay, CEC, sodium pyrophosphate extractable Fe and oxalate extractable Fe concentrations (P < 0.05), which varied significantly with soil parent material. Since the sodium pyrophosphate plus oxalate‐ extracted mineral‐associated carbon accounted for more than 70% of MAOC, and the molar ratio between sodium pyrophosphate or oxalate‐ extracted mineral‐associated carbon and Fe (C:Fe) ranged from 2.7 to 17.1. The formation of Fe‐associated organic complex is dominated by co‐precipitation when C:Fe is >1. Therefore we conclude that non‐sorptive interactions with the mineral phase through co‐precipitation are the dominant mechanism for SOC stabilization in subtropical forest soils. Plain Language Summary: Identifying the mechanisms for the accumulation and stabilization of forest soil organic carbon (SOC) is particularly important for increasing land‐based carbon mitigation as a part of the solution toward carbon neutrality by 2060 in China. However, our understanding of the mechanism of SOC stabilization is still limited, particularly how soil carbon stabilization is influenced by soil parent material, which has been shown to have strong influences on soil's physical and chemical properties, therefore on SOC stabilization. By analyzing the carbon content and composition of the soils developed from the different parent materials, we showed that soil parent material indirectly affected SOC through soil physical and chemical properties, of which soil clay content, CEC and soil Fe oxides played an important role in SOC stabilization. Both sorptive and co‐precipitation interactions between Fe and SOC contributed to SOC stabilization in subtropical forest soil with co‐precipitation as the dominant mechanism. Key Points: Mineral‐associated organic carbon accounts for >80% of soil organic carbon (SOC) in southern China forest soilsCo‐precipitation with Fe is the dominant SOC stabilization mechanismParent material is a significant contributor to the observed SOC variations [ABSTRACT FROM AUTHOR]

A large body of literature has shown that ginseng had a role in diabetes mellitus management. Ginsenosides are the main active components of ginseng. But what ginsenosides can manage in diabetic are not systematic. The targets of these ginsenosides are still incomplete. Our aim was to identify which ginsenosides can manage diabetes mellitus through network pharmacology and molecular docking. To identify the targets of these ginsenosides. In this work, we retrieved and screened ginsenosides and corresponding diabetes mellitus targets across multiple databases. PPI networks of the genes were constructed using STRING, and the core targets were screened out through topological analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by using the R language. Finally, molecular docking was performed after bioinformatics analysis for verification. Our research results showed that 28 ginsenosides in ginseng might be against diabetes mellitus by modulating related proteins such as VEGFA, Caspase 3, and TNF-α. Among the 28 ginsenosides, 20(R)-Protopanaxatriol, 20(R)-Protopanaxadiol, and Ginsenoside Rg1 might play a significant role. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis showed that the management of diabetes mellitus by ginsenosides may be related to the positive regulation of reactive oxygen metabolic processes, associated with the insulin signaling pathway, TNF signaling pathway, and AMPK signaling pathway. Molecular docking results and molecular dynamics simulation showed that most ginsenosides could stably bind to the core target, mainly hydrogen bonding and hydrophobic bond. This study suggests the management of ginseng on diabetes mellitus. We believe that our results can contribute to the systematic study of the mechanism of ginsenosides for the management of diabetes mellitus. At the same time, it can provide a theoretical basis for subsequent studies on the management of ginsenosides in diabetes mellitus. [ABSTRACT FROM AUTHOR]

Projections of future climate change for given CO2 and other greenhouse gas emission scenarios depend on the response of global climate‐carbon cycle feedback, which consists of carbon‐concentration feedback (e.g., CO2 physiology effect on land carbon sink) and carbon‐climate feedback (e.g., CO2 radiative effect on land carbon sink). Previous studies have assumed no significant interaction between these two feedbacks within the Earth system. This study quantifies the interaction of these two feedbacks, or the nonlinear feedback on land using the fully, biogeochemically, and radiatively coupled simulations under a 1% yr−1 CO2 increase path from nine Earth system models of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results show that the nonlinear feedback is 1.64 ± 2.92 × 10−2 GtC ppm−1 K−1 at the end of 140‐year simulation with a quadrupling CO2 (4 × CO2), where its strength is 11% ± 18% of the carbon‐concentration feedback or −27% ± 49% of the carbon‐climate feedback on land. Compared to previous assumptions that did not consider this interaction, the nonlinear feedback contributes about 8% ± 12% of the land carbon increase accumulated at the 4 × CO2. The nonlinear feedback largely results from the combined effect of increased CO2‐induced additional fertilization effect on warming‐induced additional leaf area index and vegetation productivity over the Northern Hemisphere. The magnitude of the nonlinear feedback on land decreases with an increase in atmospheric CO2 or warming under the high emission scenario. This study highlights the significance of land nonlinear climate‐carbon cycle feedback in increasing land carbon sink and slowing down future climate change. Plain Language Summary: The land biosphere absorbs a significant fraction of anthropogenic carbon emissions, and the rate of this carbon sink increases with atmospheric CO2 concentration‐induced physiology effect on carbon sink (the so‐called carbon‐concentration feedback), but generally decreases with CO2‐induced radiatively warming effect on land carbon sink (i.e., the so‐called carbon‐climate feedback). Quantifying the strength of these two feedbacks is one of the great challenges of climate change science today. Most previous studies examining these two feedbacks have ignored their nonlinear interaction, which may induce large uncertainty for future climate projections under high CO2 emission scenarios. To quantify this nonlinear feedback, we used simulations by nine Earth system models driven by a prescribed 1% per year increasing atmospheric CO2 concentration for 140 years. We find that the nonlinear feedback can provide a strong additional contribution (about 8% ± 12%) to the global land carbon increase for a quadrupled CO2 concentration scenario. Further analysis shows that the combined effects of rising CO2 fertilization and warming‐induced growing vegetation productivity over the Northern Hemisphere dominate the nonlinear feedback. This study based on Earth system models provides new insights into the interaction between climate and carbon cycle, and highlights the significant nonlinear effect in projecting future carbon mitigation. Key Points: The Coupled Model Intercomparison Project Phase 6 1pctCO2 experiments suggest a strong nonlinear climate‐carbon cycle feedback on landThe nonlinear feedback is mainly contributed by the combined effect of increasing CO2 fertilization and warming‐induced additional vegetation growth over the Northern HemisphereThe magnitude of the nonlinear feedback decreases with an increase in atmospheric CO2 concentration [ABSTRACT FROM AUTHOR]

Saponins from the roots of Platycodon grandiflorum, an edible medicinal plant, have shown a wide range of beneficial effects on various biological processes. In this study, an animal model was established by a single intraperitoneal injection of cisplatin (20 mg/kg) for evaluating the protective effects of saponins from the roots of P. grandiflorum (PGS, 15 mg/kg and 30 mg/kg) in mice. The results indicated that PGS treatment for 10 days restored the destroyed intestinal mucosal oxidative system, and the loosened junctions of small intestinal villi was significantly improved. In addition, a significant mitigation of apoptotic effects deteriorated by cisplatin exposure in small intestinal villi was observed by immunohischemical staining. Also, western blot showed that PGS could effectively prevent endoplasmic reticulum (ER) stress-induced apoptosis caused by cisplatin in mice by restoring the activity of PERK (an ER kinase)-eIF2 α -ATF4 signal transduction pathway. Furthermore, molecular docking results of main saponins in PGS suggested a better binding ability with target proteins. In summary, the present work revealed the underlying protective mechanisms of PGS on intestinal injury induced by cisplatin in mice. [ABSTRACT FROM AUTHOR]

Aims: Soil warming significantly influences soil organic carbon (SOC) pools in terrestrial ecosystems through its impact on the processes of carbon (C) input and decomposition as well as the stabilization of SOC pools. Most studies demonstrated that soil warming reduces SOC pools, but the magnitude is highly variable, and the underlying mechanisms are poorly understood. Methods: The concentration, stability (dissolved, particulate, and mineral-associated SOC) and source (plant-derived vs. microbial-derived) of SOC, soil microbial community composition, and enzymatic activities were studied in a 10-year soil warming field experiment in an East Asian monsoon forest. Results: 10-year soil warming significantly enhanced SOC in the top 0–10 cm soil. The increased SOC induced by warming was mainly derived from plants, with lignin and phenol markers increasing by 60% on average, accompanied by a 27% decrease in microbial-derived SOC. However, the overall effect of warming on SOC stability was not statistically significant. Conclusions: The results suggest that the moist monsoon forest soil could sequester SOC upon long-term warming. The discrepancy between our findings and those from other regions highlights an urgent need for a better understanding of how the contrasting effects of plant- and microbial-derived C mediate the response of the SOC pool to warming across biomes. [ABSTRACT FROM AUTHOR]

Global terrestrial vegetation dynamics have been rapidly altered by climate change. A widespread vegetation greenness over a large part of the planet from the 1980s to early this century has been reported, whereas weakening of CO2 fertilization effects and increasing climate extremes and the adverse impact of increasing rate of warming and severity of drought on vegetation growth were also reported. Earth system models project that the land carbon sink will decrease in size in response to an increase in warming during this century. How global vegetation is changing during this century in response to global warming and water availability across spatial and temporal scales remains uncertain. Our understanding of the widespread vegetation greening or browning processes and identifying the biogeochemical mechanisms remain incomplete. Here we use multiple long‐term satellite leaf area index (LAI) records to investigate vegetation growth trends from 1982 to 2018. We find that the widespread increase of growing‐season integrated LAI (greening) since 1980s was reversed (p‐value < 0.05) around the year 2000 over 90% of the global vegetated area, and continued in only 10% of the global vegetated area. The reversal of greening trend was largely explained by the inhibitive effects of excessive optimal temperature on photosynthesis in most of the tropics and low latitudes, and by increasing water limitation (increasing in atmospheric vapor pressure deficit and decreasing in soil water availability) in the northern high latitudes (>45°N). Overall, the reversal of greening trend since 2000 weakened the negative feedback of carbon sequestration on the climatic system and should be considered in the strategies for climate warming mitigation and adaptation. Our findings of the diversity of processes that drive browning across bioclimatic‐zones and ecosystems and of how those driving processes are changing would enhance our ability to project global future vegetation change and its climatic and abiotic consequences. Plain Language Summary: A widespread vegetation greenness over a large part of the planet from the 1980s to early this century has been reported, whereas weakening of CO2 fertilization effects and increasing climate extremes and the adverse impact of increasing rate of warming and severity of drought on vegetation growth were also reported. We find that the widespread increase of growing‐season integrated LAI (greening) since 1980s was reversed (p‐value < 0.05) around year 2000 over 90% of the global vegetated area, and continued in only 10% of the global vegetated area. The reversal of greening trend was largely explained by the negative influence of excessive air temperature on photosynthesis of vegetation growth in most of the tropics and low latitudes, and by increasing in atmospheric vapor pressure deficit and decreasing in soil water availability in the northern high latitudes (>45°N). Our findings of the diversity of browning mechanisms across bioclimatic‐zones and ecosystems are useful for projecting global future vegetation change and its climatic and abiotic consequences. Key Points: The widespread increase of vegetation greening trend since 1980s was reversed around the year 2000 over 90% of the global vegetated areaThe leveling off of global greenness arisen from recent exceeding optimal temperature and increasing water limitation for photosynthesisOur findings of the diversity of browning mechanisms are useful for projecting global future vegetation change and its climatic consequences [ABSTRACT FROM AUTHOR]

This study is to develop a method for isolation, identification, and quantitative determination of dammarane-type triterpene saponins in the Panax notoginseng fruits (PNF). The saponins were isolated by a serious of chromatographic methods, and their structures were elucidated on the basis of spectroscopic evidence and comparison with those of literature reports. Quantitative assay was performed on an ultra-performance liquid chromatography-UV (UPLC-UV) method. As a result, 22 saponins were isolated from the extract of PNF, among them, compound 1 was a new saponin, named as malonylgypenoside IX, compounds 3–10, and 14–18 were isolated from the PNF for the first time. As to quantitative analysis, the calibration curves showed good linearity (r > 0.998) within the concentration range, and the method validation provided good reproducibility and sensitivity for the quantification of eight major saponins with precision and accuracy of less than 3.0%. [ABSTRACT FROM AUTHOR]

Saponins from the roots of Platycodon grandiflorum, an edible medicinal plant, have shown a wide range of beneficial effects on various biological processes. In this study, an animal model was established by a single intraperitoneal injection of cisplatin (20 mg/kg) for evaluating the protective effects of saponins from the roots of P. grandiflorum (PGS, 15 mg/kg and 30 mg/kg) in mice. The results indicated that PGS treatment for 10 days restored the destroyed intestinal mucosal oxidative system, and the loosened junctions of small intestinal villi was significantly improved. In addition, a significant mitigation of apoptotic effects deteriorated by cisplatin exposure in small intestinal villi was observed by immunohischemical staining. Also, western blot showed that PGS could effectively prevent endoplasmic reticulum (ER) stress-induced apoptosis caused by cisplatin in mice by restoring the activity of PERK (an ER kinase)-eIF2 α -ATF4 signal transduction pathway. Furthermore, molecular docking results of main saponins in PGS suggested a better binding ability with target proteins. In summary, the present work revealed the underlying protective mechanisms of PGS on intestinal injury induced by cisplatin in mice. [ABSTRACT FROM AUTHOR]

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin‐up of land carbon cycle models by tens of times. The accelerated spin‐up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever‐increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle. Plain Language Summary: Earth system models (ESMs) are the tools we have to predict future states of climate and ecosystems. However, land carbon cycle models, a critical component of ESMs, are highly diverse in both structures and predictions, hindering our ability to obtain consistent future projections. The latter is needed as part of the evidence base to inform climate change mitigation strategies. This paper describes a matrix approach that unifies land carbon cycle models in one matrix form. The matrix models offer consistency and simplicity in structure that make the models analytically tractable. In addition, the matrix approach provides a theoretical framework for understanding the general behavior of the land carbon cycle. More importantly, the matrix approach solves some key contemporary issues in land carbon cycle modeling, such as pinning down sources of model uncertainty and accelerating spin‐up. The accelerated spin‐up speeds up land carbon cycle simulations by tens of times, making it feasible to perform parameter sensitivity analysis and data assimilation to constrain models with big data. Overall, the matrix approach represents a step change forward for understanding and modeling the land carbon cycle. Key Points: The matrix approach unifies land carbon cycle models in a matrix form and thus helps gain simplicity in model structureThe matrix approach provides a theoretical framework to understand the general behavior of land carbon cycleIt helps address contemporary issues in land carbon cycle modeling, including pinning down model uncertainty and accelerating spin‐up [ABSTRACT FROM AUTHOR]

South China has been experiencing very high rate of acid deposition and severe soil acidification in recent decades, which has been proposed to exacerbate the regional ecosystem phosphorus (P) limitation. We conducted a 10‐year field experiment of simulated acid deposition to examine how acidification impacts seasonal changes of different soil P fractions in a tropical forest with highly acidic soils in south China. As expected, acid addition significantly increased occluded P pool but reduced the other more labile P pools in the dry season. In the wet season, however, acid addition did not change microbial P, soluble P and labile organic P pools. Acid addition significantly increased exchangeable Al3+ and Fe3+ and the activation of Fe oxides in both seasons. Different from the decline of microbial abundance in the dry season, acid addition increased ectomycorrhizal fungi and its ratio to arbuscular mycorrhiza fungi in the wet season, which significantly stimulated phosphomonoesterase activities and likely promoted the dissolution of occluded P. Our results suggest that, even in already highly acidic soils, the acidification‐induced P limitation could be alleviated by stimulating ectomycorrhizal fungi and phosphomonoesterase activities. The differential responses and microbial controls of seasonal soil P transformation revealed here should be implemented into ecosystem biogeochemical model for predicting plant productivity under future acid deposition scenarios. [ABSTRACT FROM AUTHOR]

In this study, an efficient screening method based on a modified quick, easy, cheap, effective, rugged, and safe extraction method combined with ultra‐high‐performance liquid chromatography coupled to tandem quadrupole time‐of‐flight mass spectrometry was established for the determination of 90 pesticides residues in Panax Ginseng. The accuracy of the method was then verified by analyzing the false positive rate and the screening detection limit in Ginseng. The results revealed that the screening detection limit of 33 of 90 pesticide residues were 0.01 mg·kg−1, 22 species were 0.05 mg·kg−1, 11 species were 0.10 mg·kg−1, 8 species were 0.20 mg·kg−1, and another 16 species were greater than 0.20 mg·kg−1. A total of 73 pesticides were ultimately suitable to be practically applied for rapid analysis of pesticide residues in Ginseng. Finally, the established method was used to analyze the pesticide residues in 35 Ginseng samples available on the market. And the residual of dimethomorph, azoxystrobin, tebuconazole, and pyraclostrobin was relatively severe in Ginseng samples. This work expanded the range of pesticides detected and provided a rapid, effective method for pesticides screening in Ginseng. [ABSTRACT FROM AUTHOR]

The terrestrial carbon (C) cycle is shifting to a state of dynamic disequilibrium under a rapid global climate change. However, the magnitude of such disequilibrium is inherently hard to measure directly. Abundant studies have revealed that the availability of nutrients, particularly nitrogen (N) and phosphorus (P), constrains ecosystem productivity and carbon stocks across the globe. However, whether and how nutrient limitation affects the disequilibrium magnitude of the terrestrial C cycle (Xp) has never been evaluated. Here, we developed an approach by combining a process‐based numerical model and an analytical framework to evaluate the role of nutrient limitation on Xp. We found that nutrient limitation did have significant impacts on the Xp. Over the modeled period of 1901–2013, absolute change in Xp was 497.6 PgC under the C‐only run, while it decreased to 155.6 and 124.3 PgC under N and NP limitations, respectively. To understand the underlying reasons, we further disaggregated the changes of Xp into changes in steady‐state C storage and transit C storage with the former being decomposed into a productivity‐driven change, an ecosystem‐C‐residence‐time‐driven (τE‐driven) change, and a change induced by productivity‐τE interactions. We found that nutrient constrained the increase in Xp primarily by dampening the productivity‐driven changes in the steady‐state C storage. Reductions in the productivity‐driven term under N and NP limitations accounted for 94.7% and 94.9%, respectively, of the reductions in the steady‐state C storage. These results indicate that nutrient limitations have profound impacts on future climate‐biosphere feedback by reducing the disequilibrium magnitude of the terrestrial C cycle. Plain Language Summary: The steady‐state assumption is prevalent in terrestrial carbon (C) cycle studies, where C influxes are assumed to balance against C effluxes. However, climate change and other disturbances have caused dynamic disequilibrium of the terrestrial C cycle. The disequilibrium magnitudes of the terrestrial C sink and source vary over time under disturbances. Nutrient limitation, particularly from N and P, is widely acknowledged as one of the influential factors to the terrestrial C sink. It remains unknown whether and how nutrient limitation affects the disequilibrium magnitude of the terrestrial C cycle (Xp). In this study, we first used an analytical way to estimate the Xp and further proposed a framework to disaggregate controls on the dynamics of Xp. We then applied the analytical framework to a C‐N‐P‐coupled land‐surface model to investigate the role of nutrient limitation on the Xp. We found a significant nutrient limitation on the Xp. Over the modeled period, the absolute change in Xp was reduced by 68.7% and 75.0% under N and NP limitations, respectively. These results indicate that nutrient availability can regulate the pattern of dynamic disequilibrium in the terrestrial C cycle under future climate change. Key Points: The disequilibrium magnitude of global terrestrial carbon cycle showed dramatic reduction under the modeled nutrient limitationNutrient limitation affects the disequilibrium magnitude primarily by dampening the productivity‐driven changesInfluences from changes in ecosystem carbon residence time are minor under the modeled nutrient limitation [ABSTRACT FROM AUTHOR]

Surface litter layer strongly influences CO2, N2O, and CH4 fluxes (FCO2, FN2O, and FCH4) between the atmosphere and forest floor through litter decomposition (litter-internal, fL-L) or interactions between litter and mineral soil (litter-induced, fL-S). However, the relative contribution of fL-L or fL-S to these greenhouse gas (GHG) fluxes in forests at different succession stages remain unclear. We conducted a field experiment where surface litter was either removed (LR), left intact (CT), doubled (LD), or exchanged (LE) in a Masson pine forest (PF, early stage of succession) and an evergreen broadleaved forest (BF, climax of succession) at the Dinghushan Nature Reserve in southern China, and studied the responses of FCO2, FN2O, and FCH4 from August 2012 to July 2013. The results showed that both FCO2 and FN2O were increased by LD treatment with a greater increase in BF (41% for FCO2 and 30% for FN2O) and decreased by LR treatment with the greater decrease in PF (−61% for FCO2 and −58% for FN2O). LD treatment decreased FCH4 by 14% in PF and 6% in BF, and LR treatment increased FCH4 by 5% in PF and 18% in BF. fL-S contributed more to FCO2 (36%) and FN2O (45%) than fL-L in PF, whereas contributions of fL-L to FCO2 (41%) and FN2O (30%) were much bigger than fL-S in BF. The greater FCH4 in PF and BF resulted from the contributions of fL-L (−14%) and fL-S (−12%), respectively. Our results indicated that fL-L is the major source of GHG fluxes in BF, whereas fL-S dominates GHG fluxes in PF. The results provide a scientific reference for quantifying the contributions of fL-L and fL-S to GHG fluxes during the subtropical forest succession and should be considered in ecosystem models to predict global warming in the future. [ABSTRACT FROM AUTHOR]

Biochar has been proposed as a promising negative CO2 emission technology to mitigate future climate change with the additional benefit of increasing agricultural production. However, the spatial responses of soil organic carbon (SOC) to biochar addition in cropland are still uncertain, and the economic feasibility of large‐scale biochar implementation remains unclear. Here, we analyzed the response of SOC to biochar addition using 389 paired field measurements. The results show that biochar addition significantly increased SOC by 45.8% on average with large regional variations. Using a random forest model trained with soil, climate, biotic, biochar, and management factors, we found that the response of SOC to biochar addition was mainly dependent on biochar application rates, initial SOC, edaphic (e.g., pH), and climatic (e.g., mean annual precipitation) variables. Combined with the predicted SOC changes to biochar addition on the global cropland, we assessed the revenue of the biochar system based on the current and potential pyrolysis plants in the world using the life‐cycle analysis. Net revenue of the currently existing 144 pyrolysis plants increases with larger plant capacity and higher carbon price. Potential revenue of building new plants is high in regions like America and Europe but low in regions with infertile soil, low crop residues availability, and inconvenient transportation. The global CO2 removal of biochar application is 6.6 Tg CO2e (CO2 equivalent) year−1 with a net revenue of $ 177 million dollars at a carbon price of $ 50 t−1 CO2 for current pyrolysis plants with a biomass‐processing capacity of 20,000 t year−1. Our study provides a full economic assessment of idealized biochar addition scenarios and identifies the locations with maximal potential revenues with new pyrolysis plants. [ABSTRACT FROM AUTHOR]

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time‐series records of remotely sensed Ku‐band vegetation optical depth (Ku‐VOD), a proxy of top‐canopy foliar mass and water content, and separated the signal of Ku‐VOD changes into drought‐induced reductions and subsequent non‐drought gains. Both drought‐induced reductions and non‐drought increases in Ku‐VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku‐VOD reductions during drought and larger non‐drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta‐analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem‐transport safety margins. Additionally, Ku‐VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height‐dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought. [ABSTRACT FROM AUTHOR]

Carbon cycle feedbacks were often quantified through the carbon–concentration and carbon–climate feedbacks with the assumption of no significant interaction between the two feedbacks in most previous studies. Here we calculated the strength of the interactions between the two responses using simulations of models participated in the phase 6 of the Coupled Model Intercomparison Project (CMIP6). We found that the nonlinear interaction contributed 11% of the land–atmosphere carbon exchange on average with large intermodel variation (from −20% to +162%). This nonlinear interaction is largely driven by the pattern of net primary production (NPP), with shifts in heterotrophic respiration that dampen the overall positive interactions from NPP. Photosynthetic rate per unit leaf area alone cannot adequately explain a wide variation of interactions in global NPP simulated by CMIP6 models. Plant respiration and processes that regulate leaf area are also important contributors to the interactions. Dominant factors that induce carbon–concentration and carbon–climate interactions are highly variable among models. One of those dominant factors is nutrient limitation. Using additional simulations of ACCESS‐ESM1.5 that include both nitrogen and phosphorus limitation, we found that the estimated interactions by ACCESS‐ESM1.5 with or without nutrient limitations covered the large intermodel variations among the CMIP6 models. It remains largely unknown how nutrient limitation complicates ecosystem's responses to simultaneously CO2 fertilization and warming at the global scale. Our modeling results point to a potential important role of nutrients, especially phosphorus on the nonlinear interactions. Yet, more studies are needed on ecosystem responses to concurrent changes in nutrient availability, atmospheric CO2 concentration, and warming. [ABSTRACT FROM AUTHOR]

Land use and management practices affect the response of soil organic carbon (C) to global change. Process-based models of soil C are useful tools to simulate C dynamics, but it is important to bridge any disconnect that exists between the data used to inform the models and the processes that they depict. To minimise that disconnect, we developed a consistent modelling framework that integrates new spatially explicit soil measurements and data with the Rothamsted carbon model (Roth C) and simulates the response of soil organic C to future climate change across Australia. We compiled publicly available continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated Roth C and ran simulations to estimate the baseline soil organic C stocks and composition in the 0–0.3 m layer at 4043 sites in cropping, modified grazing, native grazing and natural environments across Australia. We used data on the C fractions, the particulate, mineral-associated and resistant organic C (POC, MAOC and ROC, respectively) to represent the three main C pools in the Roth C model's structure. The model explained 97 %–98 % of the variation in measured total organic C in soils under cropping and grazing and 65 % in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to simulate the potential for C accumulation under constant climate in a 100-year simulation. With an annual increase of 1 Mg C ha -1 in C inputs, the model simulated a potential soil C increase of 13.58 (interquartile range 12.19–15.80), 14.21 (12.38–16.03) and 15.57 (12.07–17.82) Mg C ha -1 under cropping, modified grazing and native grazing and 3.52 (3.15–4.09) Mg C ha -1 under natural environments. With projected future changes in climate (+ 1.5, 2 and 5.0 ∘ C) over 100 years, the simulations showed that soils under natural environments lost the most C, between 3.1 and 4.5 Mg C ha -1 , while soils under native grazing lost the least, between 0.4 and 0.7 Mg C ha -1. Soil under cropping lost between 1 and 2.7 Mg C ha -1 , while those under modified grazing showed a slight increase with temperature increases of 1.5 ∘ C, but with further increases of 2 and 5 ∘ C the median loss of TOC was 0.28 and 3.4 Mg C ha -1 , respectively. For the different land uses, the changes in the C fractions varied with changes in climate. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C : N ratio and cropping were the most important controls on POC change. Clay content and climate were dominant controls on MAOC change. Consistent and explicit soil organic C simulations improve confidence in the model's estimations, facilitating the development of sustainable soil management under global change. [ABSTRACT FROM AUTHOR]

The dependence of inter‐annual ecosystem evapotranspiration (ET) partitioning on vegetation dynamics is crucial for understanding the long term coupling relationship between the water and carbon cycles. The objective of this study was to determine the spatial variation of ET partitioning (T/ET) and the inter‐annual dependencies of T/ET on vegetation gross primary productivity (GPP). The investigation was conducted at the global scale based on seven global datasets and at the point scale at 37 flux sites. The spatial variations of T/ET were divided into three phases, that is, the rapidly increasing phase (P1), slowly increasing phase (P2), and decreasing phase (P3), which were located in arid and cold regions, temperate regions, and tropical rainforest regions, respectively. The three‐phase spatial variations were primarily driven by the different spatial variations of the two water use pathways (i.e., transpiration, T and evaporation, E) in ecosystems with different productivity levels. In P1 and P2 ecosystems, the inter‐annual dependencies of T/ET on GPP were mostly positive, and in P3 ecosystems, it was mostly negative. This revealed a significantly decreased dependence as GPP increased, which was attributed to the different dependencies of T and E on GPP. Based on the effects of GPP on ET under climate variations (represented by precipitation, P), ET had the smallest inter‐annual variations in most of global vegetated grid cells due to the joint regulation of T and E by GPP and P. This study highlights the significant role of vegetation productivity in regulating inter‐annual ET partitioning, and improves understandings on the coupled water‐carbon cycles. Key Points: The spatial variations of T/ET can be divided into the rapidly increasing (P1), slowly increasing (P2), and decreasing (3) phasesAt the three phases, the dependencies of inter‐annual T/ET on gross primary productivity (GPP) were significantly decreasing from positive to negative as GPP increasedThe joint regulation of GPP and climate on evapotranspiration (ET) partitioning resulted in a relatively stable inter‐annual variability of ET in most of global vegetated grid cells [ABSTRACT FROM AUTHOR]

Background: Forest restoration has been considered an effective method to increase soil organic carbon (SOC), whereas it remains unclear whether long-term forest restoration will continuously increase SOC. Such large uncertainties may be mainly due to the limited knowledge on how soil microorganisms will contribute to SOC accumulation over time. Methods: We simultaneously documented SOC, total phospholipid fatty acids (PLFAs), and amino sugars (AS) content across a forest restoration gradient with average stand ages of 14, 49, 70, and > 90 years in southern China. Results: The SOC and AS continuously increased with stand age. The ratio of fungal PLFAs to bacterial PLFAs showed no change with stand age, while the ratio of fungal AS to bacterial AS significantly increased. The total microbial residue-carbon (AS-C) accounted for 0.95–1.66 % in SOC across all forest restoration stages, with significantly higher in fungal residue-C (0.68–1.19 %) than bacterial residue-C (0.05–0.11 %). Furthermore, the contribution of total AS-C to SOC was positively correlated with clay content at 0–10 cm soil layer but negatively related to clay content at 10–20 cm soil layer. Conclusions: These findings highlight the significant contribution of AS-C to SOC accumulation along forest restoration stages, with divergent contributions from fungal residues and bacterial residues. Soil clay content with stand age significantly affects the divergent contributions of AS-C to SOC at two different soil layers. [ABSTRACT FROM AUTHOR]

Successive evidence has established that maltol, a flavor‐enhancing agent, could provide resistance to oxidative stress‐induced tissue injury in various animal models though its benefits for aging‐induced liver and kidney injuries are still undetermined. In the present work, for demonstrating maltol's ameliorative effect and probable mechanism against aging‐induced liver and kidney injuries, D‐galactose (D‐Gal)‐induced animal in vivo and HEK293 cells in vitro models were established and results demonstrated that long‐term D‐Gal treatment increases the accumulation of advanced glycation end products (AGEs) in liver and kidney tissues, mitigates cell viability, and arrests the cycle. Interestingly, 4‐weeks maltol treatment at 50 and 100 mg/kg activated aging‐associated proteins including p53, p21, and p16 followed by inhibiting malondialdehyde (MDA)'s over‐production and increasing the levels of antioxidant enzymes. Therefore, decreases in cytochrome P450 E1 (CYP2E1) and 4‐hydroxydecene (4‐HNE)'s immunofluorescence expression levels are confirmed. Furthermore, maltol improved oxidative stress injury by activating the phosphatidylinositol‐3‐kinase (PI3K)/protein kinase B (Akt) signaling pathway. In conclusion, the purpose of the present study was to estimate the mechanistic insights into maltol's role as an antioxidant in liver and kidney cell senescence and injury, which will reflect potential of therapeutic strategy for antiaging and aging‐related disease treatment. [ABSTRACT FROM AUTHOR]

Although the protective effect of ginsenoside on cisplatin-induced renal injury has been extensively studied, whether ginsenoside interferes with the antitumor effect of cisplatin has not been confirmed. In this paper, we verified the main molecular mechanism of 20(R)-ginsenoside Rg3 (R-Rg3) antagonizing cisplatin-induced acute kidney injury (AKI) through the combination of in vivo and in vitro models. It is worth mentioning that the two cell models of HK-2 and HepG2 were used simultaneously for the first time to explore the effect of the activation site of tumor-associated protein p53 on apoptosis and tumor suppression. The results showed that a single injection of cisplatin (20 mg/kg) led to weight loss, the kidney index of the mice increased, and creatinine (CRE) and blood urea nitrogen (BUN) levels in mice sharply increased. Continuous administration of R-Rg3 at doses of 10 and 20 mg/kg for 10 days could significantly alleviate this symptom. Similarly, R-Rg3 treatment reduced oxidative stress damage caused by cisplatin. Moreover, R-Rg3 could observably reduce the apoptosis and inflammatory infiltration of renal tubular cells induced by cisplatin. We used western blotting analysis to demonstrate that R-Rg3 restored cisplatin-induced AKI might be related to PI3K/AKT and NF- κ B mediated apoptosis and inflammation pathways. In the meantime, we also verified that R-Rg3 could activate different sites of p53 to control renal cell apoptosis induced by cisplatin without affecting its antitumor effect. [ABSTRACT FROM AUTHOR]

Although ginseng (Panax ginseng C.A. Meyer) has received extensive attention in the treatment and prevention of type 2 diabetes mellitus (T2DM) in the past few decades, there are few studies on the complications of T2DM. At present, obesity-linked diabetic nephropathy (DN) has become the most prevailing element of the end-stage renal failure in the world. The aim of this work is to evaluate the ameliorative effects of ginsenoside Rh1 (G-Rh1) on DN induced by high fat diet plus streptozotocin (HFD/STZ) through some potential and combined mechanisms of action. The results showed that G-Rh1 treatment at 5 and 10 mg/kg for 8 weeks exerted excellent effects in controlling fasting blood glucose (FBG), improving glucose tolerance, and increasing insulin level. In addition, G-Rh1 effectively prevents the excessive production of advanced glycation end products (AGEs), a diabetic nephropathy marker, in HFD/STZ induced DN mice. Meanwhile, oxidation indicators including SOD, GSH, and MDA were improved by G-Rh1 treatment to varying degrees. It is worth noting that G-Rh1 not only inhibits the secretion of Nox1 and Nox4 in kidney tissues, but also has an inhibitory effect on inflammatory factors and NF- κ B signaling pathway. Importantly, further in-depth research on molecular mechanisms provides vital evidence that the ameliorative effect of G-Rh1 on DN is related to the inhibition of apoptosis and the AMPK/PI3K/Akt signaling pathway. In summary, G-Rh1 may be of great value in improving the treatment of DN although more experimental data is needed. [ABSTRACT FROM AUTHOR]

The climate-carbon cycle feedback is one of the most important climate-amplifying feedbacks of the Earth system, and is quantified as a function of carbon-concentration feedback parameter (β) and carbon-climate feedback parameter (γ). However, the global climate-amplifying effect from this feedback loop (determined by the gain factor, g) has not been quantified from observations. Here we apply a Fourier analysis-based carbon cycle feedback framework to the reconstructed records from 1850 to 2017 and 1000 to 1850 to estimate β and γ. We show that the β-feedback varies by less than 10% with an average of 3.22 ± 0.32 GtC ppm−1 for 1880–2017, whereas the γ-feedback increases from −33 ± 14 GtC K−1 on a decadal scale to −122 ± 60 GtC K−1 on a centennial scale for 1000–1850. Feedback analysis further reveals that the current amplification effect from the carbon cycle feedback is small (g is 0.01 ± 0.05), which is much lower than the estimates by the advanced Earth system models (g is 0.09 ± 0.04 for the historical period and is 0.15 ± 0.08 for the RCP8.5 scenario), implying that the future allowable CO2 emissions could be 9 ± 7% more. Therefore, our findings provide new insights about the strength of climate-carbon cycle feedback and about observational constraints on models for projecting future climate. How to curb climate change is uncertain, in part because determination of allowable emissions depends on models with low accuracy. Here the authors re-analyze climate-carbon feedbacks and find that CO2 emissions could be 9 ± 7% higher and still meet Paris Agreement goals. [ABSTRACT FROM AUTHOR]

It is well‐known that soil carbon composition and turnover rate vary with soil depth, and the responses of soil carbon to global change in deeper soil layers may differ from those near the surface. Therefore, vertically resolved soil carbon models are needed for accurately predicting future soil carbon under global warming. In this study, we developed a vertically resolved soil carbon model by including vertical transport of soil carbon and using Michaelis‐Menten kinetics for soil carbon decomposition by microbes. The model was calibrated against six sites with the observed profiles of both soil carbon concentration and 14C measurements, and against 91 forest sites with soil carbon concentrations across a wide range of climate and soil conditions for four forest types in Europe and China. Results of independent model validation at another 93 sites showed that the calibrated model explained 40%–94% of the observed variance of soil carbon concentrations at different depths. Model sensitivity analysis showed that microbial activity and root carbon inputs are more important than soil carbon diffusion in simulating soil carbon profile. Results from our study highlight the need for detailed measurements of soil microbial activities and root carbon input at different soil depths in the field. Key Points: A vertically resolved soil carbon model‐based microbial kinetics is developedThe model explains 40%–94% of field observations from 93 forest sites in Europe and ChinaRoot‐carbon input has strongest influences on soil organic carbon concentration profiles [ABSTRACT FROM AUTHOR]

Cisplatin, a proven effective chemotherapeutic agent, has been used clinically to treat malignant solid tumors, whereas its clinical use is limited by serious side effect including nephrotoxicity. Platycodin D (PD), the major and marked saponin isolated from Platycodon grandiflorum, possesses many pharmacological effects. In this study, we evaluated its protective effect against cisplatin‐induced human embryonic kidney 293 (HEK‐293) cells injury and elucidated the related mechanisms. Our results showed that PD (0.25, 0.5, and 1 μM) can dose‐dependently alleviate oxidative stress by decreasing malondialdehyde and reactive oxygen species, while increasing the levels of glutathione, superoxide dismutase, and catalase. Moreover, the elevation of apoptosis including Bax, Bad, cleaved caspase‐3,‐9, and decreased protein levels of Bcl‐2, Bcl‐XL induced by cisplatin were reversed after PD treatment. Importantly, PD pretreatment can also regulate PI3K/Akt and ERK/JNK/p38 signaling pathways. Furthermore, PD was found to reduce NF‐κB‐mediated inflammatory relative proteins. Our finding indicated that PD exerted significant effects on cisplatin induced oxidative stress, apoptosis and inflammatory, which will provide evidence for the development of PD to attenuate cisplatin‐induced nephrotoxicity. [ABSTRACT FROM AUTHOR]

Heat stress (HS) reaction is a stress response caused by adverse conditions. Currently, the incidence of reproductive malignancies particularly in males has been constantly increasing. This work investigated the effects of saponins derived from the stems and leaves of Panax ginseng (GSLS) on testicular injury induced by scrotal hyperthermia in mice. GSLS (150, 300 mg/kg) were administered intragastrically to mice for 14 days, then exposed to a single scrotal heat treatment at 43°C for 18 min on seventh day. HS induced a significant loss of multinucleate giant cells, desquamation of germ cells in destructive seminiferous tubules. Moreover, HS reduced the serum testosterone, testicular tissue superoxide dismutase activity and glutathione (GSH) content, while significantly enhanced the production of malondialdehyde (p <.05). GSLS exhibited the protective potential against HS‐induced injury not only by modulating Bcl‐2 family and caspase protease family, but also by suppressing the protein levels of heme oxygenase‐1 (HO‐1), heat shock protein 70 (HSP70), hypoxia inducible factor‐1α (HIF‐1α) and activation of Mitogen‐activated protein kinase (MAPK) signaling pathways (p <.05). In conclusion, we clearly demonstrated that GSLS exhibited a significant protective effect against HS‐induced testicular dysfunction, mainly the inhibition of oxidative stress associated apoptosis partly via regulation of the MAPK signaling pathway. [ABSTRACT FROM AUTHOR]

Intensification of the Earth's hydrological cycle amplifies the interannual variability of precipitation, which will significantly impact the terrestrial carbon (C) cycle. However, it is still unknown whether previously observed relationship between soil respiration (Rs) and precipitation remains applicable under extreme precipitation change. By analyzing the observations from a much larger dataset of field experiments (248 published papers including 151 grassland studies and 97 forest studies) across a wider range of precipitation manipulation than previous studies, we found that the relationship of Rs response with precipitation change was highly nonlinear or asymmetric, and differed significantly between grasslands and forests, between moderate and extreme precipitation changes. Response of Rs to precipitation change was negatively asymmetric (concave‐down) in grasslands, and double‐asymmetric in forests with a positive asymmetry (concave‐up) under moderate precipitation changes and a negative asymmetry (concave‐down) under extreme precipitation changes. In grasslands, the negative asymmetry in Rs response was attributed to the higher sensitivities of soil moisture, microbial and root activities to decreased precipitation (DPPT) than to increased precipitation (IPPT). In forests, the positive asymmetry was predominantly driven by the significant increase in microbial respiration under moderate IPPT, while the negative asymmetry was caused by the reductions in root biomass and respiration under extreme DPPT. The different asymmetric responses of Rs between grasslands and forests will greatly improve our ability to forecast the C cycle consequences of increased precipitation variability. Specifically, the negative asymmetry of Rs response under extreme precipitation change suggests that the soil C efflux will decrease across grasslands and forests under future precipitation regime with more wet and dry extremes. [ABSTRACT FROM AUTHOR]

Cisplatin, as one of the most effective chemotherapeutic agents, its clinical use is limited by serious side effect of nephrotoxicity. Cisplatin‐induced nephrotoxicity is closely related to apoptosis induction and activation of caspase. The present study aimed to explore the potential protective effect of ginsenoside Rk1 (Rk1), a rare ginsenoside generated during steaming ginseng, on cisplatin‐induced nephrotoxicity and the underlying mechanisms in human embryonic kidney 293 (HEK‐293) cells. Our results showed that the reduced cell viability induced by cisplatin could significantly recover by Rk1. Furthermore, glutathione (GSH) as an oxidative index, was elevated and the lipid peroxidation product malondialdehyde (MDA) was significantly decreased after Rk1 treatment compared to the cisplatin group. Additionally, Rk1 can also decrease the ROS fluorescence expression and increase the protein levels of nuclear factor erythroid 2‐related factor 2 (Nrf2) and heme oxygenase‐1 (HO‐1) compared to the cisplatin group, which suggested a suppression of oxidative response. More importantly, the cisplatin‐induced elevated protein levels of Bax, cleaved caspase‐3, cleaved caspase‐9, and decreased protein level of Bcl‐2 were reversed after treatment with Rk1. Our results elucidated the possible protective mechanism of Rk1 for the first time, which may involve in its anti‐oxidation and anti‐apoptosis effects. [ABSTRACT FROM AUTHOR]

We simulated soil organic carbon (C) dynamics across Australia with the Rothamsted carbon model (ROTH C) under a framework that connects new spatially-explicit soil measurements and data with the model. Doing so helped to bridge the disconnection that exists between datasets used to inform the model and the processes that it depicts. Under this framework, we compiled continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated ROTH C and run simulations to predict the baseline soil organic C stocks and composition in the 0-0.3 m layer at 4,043 sites in cropping, modified grazing, native grazing, and natural environments across Australia. The ROTH C model uses measured C fractions, the particulate, humus, and resistant organic C (POC, HOC and ROC, respectively) to represent the three main C pools in its structure. The model explained 97-98% of the variation in measured total organic C in soils under cropping and grazing, and 65% in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to predict the potential for C accumulation in a 100-year simulation. With an annual increase of 1 Mg C ha[sup -1] in C inputs, the model predicted a potential soil C increase of 13.58 (interquartile range 12.19-15.80), 14.21 (12.38-16.03), and 15.57 (12.07-17.82) Mg C ha[sup -1] under cropping, modified grazing and native grazing, and 3.52 (3.15-4.09) Mg C ha[sup -1] under natural environments. Soils under native grazing were the most potentially vulnerable to C decomposition and loss, while soils under natural environments were the least vulnerable. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C:N ratio, and cropping were the most important controls on POC change. Clay content and climate were dominant controls on HOC change. Consistent and explicit soil organic C simulations improve confidence in the model's predictions, contributing to the development of sustainable soil management under global change. [ABSTRACT FROM AUTHOR]

Oxidative stress is considered as a major factor in aging and exacerbates aging process through a variety of molecular mechanisms. D-galactose, a normal reducing sugar with high dose can cause the accumulation of reactive oxygen species (ROS) or stimulate free radical production indirectly by the formation of advanced glycation end products in tissues, finally resulting in oxidative stress. 20(R)-ginsenoside Rg3 (20(R)-Rg3), a major and representative component isolated from red ginseng (Panax ginseng C.A Meyer), has been shown to observably have an anti-oxidative effect. We thereby investigated the beneficial effects of 20(R)-Rg3 on D-galactose-induced oxidative stress injury and its underlying mechanisms. Our results showed that continuous injection of D-galactose with 800 mg/kg/day for 8 weeks increased the levels of alanine aminotransferase (ALT) and blood urea nitrogen (BUN). However, such increases were attenuated by the treatment of 20(R)-Rg3 for 4 weeks. Meanwhile, 20(R)-Rg3 markedly inhibited D-galactose-caused oxidative stress in liver and kidney. The anti-oxidants, including catalase (CAT) and superoxide dismutase (SOD), were elevated in the mice from 20(R)-Rg3-treated group compared with that from D-galactose group. In contrast, a significant decrease in levels of cytochrome P450 E1 (CYP2E1) and the lipid peroxidation product malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE) were observed in the 20(R)-Rg3-treated group. These effects were associated with a significant increase of AGEs. More importantly, 20(R)-Rg3 effectively attenuated D-galactose induced apoptosis in liver and kidney via restoring the upstream PI3K/AKT signaling pathway. Taken together, our study suggests that 20(R)-Rg3 may be a novel and promising anti-oxidative therapeutic agent to prevent aging-related injuries in liver and kidney. [ABSTRACT FROM AUTHOR]

First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation. [ABSTRACT FROM AUTHOR]

Orobanche cernua is one of the species of Orobanche in Orobanchaceae family, which has been used in folk medicines for boost immunity and relieve swelling. The present study aimed to analyse the chemical constituents of the essential oils (EO) from O. cernua by GC/MS and evaluate the cytotoxic activity in vitro. Twenty-eight compounds, representing 83.41 % of the total EO were identified and the major volatile components were diethylhexyl adipate (35.34 %), followed by 2-methylheptane (12.65 %), α-cadinol (7.25 %), diethylphthalate (5.17 %), dibutyl phthalate (4.07 %), 3-methylheptane (3.51 %) and 1-tetradecanol (3.39 %). The EO cytotoxicity on the tumor cell lines (SH-SY5Y and BV-2) was determined by MTT assay and cell imaging, the results indicated that the potent cytotoxic effects with the IC50 values (55.89 μg/mL) in SH-SY5Y cells but weak in BV-2 cells with the IC50 (482.1 μg/mL) for 24 h, respectively. This paper is the first report of the chemical composition and cytotoxic activity of EO from O. cernua. [ABSTRACT FROM AUTHOR]

Acute liver injury (ALI) induced by acetaminophen (APAP) is the main cause of drug-induced liver injury. Previous reports indicated liver failure could be alleviated by saponins (ginsenosides) from Panax ginseng against APAP-induced inflammatory responses in vivo. However, validation towards ginsenoside Rb1 as a major and marker saponin may protect liver from APAP-induced ALI and its mechanisms are poorly elucidated. In this study, the protective effects and the latent mechanisms of Rb1 action against APAP-induced hepatotoxicity were investigated. Rb1 was administered orally with 10 mg/kg and 20 mg/kg daily for 1 week before a single injection of APAP (250 mg/kg, i.p.) 1 h after the last treatment of Rb1. Serum alanine/aspartate aminotransferases (ALT/AST), liver glutathione (GSH) depletion, as well as the inflammatory cytokines, such as tumor necrosis factor- α (TNF- α), interleukin-1 β (IL-1 β), inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2), were analyzed to indicate the underlying protective effects of Rb1 against APAP-induced hepatotoxicity with significant inflammatory responses. Histological examination further proved Rb1's protective effects. Importantly, Rb1 mitigated the changes in the phosphorylation of MAPK and PI3K/Akt, as well as its downstream factor NF- κ B. In conclusion, experimental data clearly demonstrated that Rb1 exhibited a remarkable liver protective effect against APAP-induced ALI, partly through regulating MAPK and PI3K/Akt signaling pathways-mediated inflammatory responses. [ABSTRACT FROM AUTHOR]