The sign and magnitude of permafrost carbon (C)-climate feedback are highly uncertain due to the limited understanding of the decomposability of thawing permafrost and relevant mechanistic controls ...over C release. Here, by combining aerobic incubation with biomarker analysis and a three-pool model, we reveal that C quality (represented by a higher amount of fast cycling C but a lower amount of recalcitrant C compounds) and normalized CO
-C release in permafrost deposits were similar or even higher than those in the active layer, demonstrating a high vulnerability of C in Tibetan upland permafrost. We also illustrate that C quality exerts the most control over CO
-C release from the active layer, whereas soil microbial abundance is more directly associated with CO
-C release after permafrost thaw. Taken together, our findings highlight the importance of incorporating microbial properties into Earth System Models when predicting permafrost C dynamics under a changing environment.
Soil properties, such as clay content, are hypothesized to control decomposition of soil organic carbon (SOC). However, these hypotheses of soil property-C decomposition relationships have not been ...explicitly tested at large spatial scales. Here, we used a data-assimilation approach to evaluate the roles of soil properties and environmental factors in regulating decomposition of SOC. A three-pool (active, slow, and passive) C-cycling model was optimally fitted with 376 published laboratory incubation data from soils acquired from 73 sites with mean annual temperature ranging from −15 to 26°C. Our results showed that soil physical and chemical properties regulated decomposition rates of the active and the slow C pools. Decomposition rates were lower for soils with high clay content, high field water holding capacity (WHC), and high C:N ratio. Multifactor regression and structural equation modeling (SEM) analyses showed that clay content was the most important variable in regulating decomposition of SOC. In contrast to the active and slow C pools, soil properties or environmental factors had little effect on the decomposition of the passive C pool. Our results show inverse soil property-C decomposition relationships and quantitatively evaluate the essential roles of soil texture (clay content) in controlling decomposition of SOC at a large spatial scale. The results may help model development and projection of changes in terrestrial C sequestration in the future.
•We evaluated the roles of soil properties in regulating SOC decomposition.•A data-assimilation approach and 376 lab incubation data sets were used.•We found inverse soil property-C decomposition relationships.•Clay content is dominant in controlling SOC decomposition at a large spatial scale.
Vasorin (VASN), a transmembrane protein heavily expressed in endothelial cells, has garnered recent interest due to its key role in vascular development and pathology. The oligomeric state of VASN is ...a crucial piece of knowledge given that receptor clustering is a frequent regulatory mechanism in downstream signaling activation and amplification. However, documentation of VASN oligomerization is currently absent. In this brief report, we describe the measurement of VASN oligomerization in its native membranous environment, leveraging a class of fluorescence fluctuation spectroscopy. Our investigation revealed that the majority of VASN resides in a monomeric state, while a minority of VASN forms homodimers in the cellular membrane. This result raises the intriguing possibility that ligand-independent clustering of VASN may play a role in transforming growth factor signaling.
Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually ...parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (-8.2 ± 5.1% or -3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., > 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections.
Ensuring railway safety is a top priority, with a central focus on preventing accidents. By thoroughly analyzing data from railway accident investigations, we can pinpoint factors and patterns ...associated with different types of railway accidents. This proactive approach not only helps reduce the frequency of such incidents but also significantly boosts overall railway transportation safety. This paper investigates the impact of various risk factors on railway safety through the analysis of railway accidents by using data-driven Bayesian networks. First, key data representing the frequency of risk factors directly derived from railway accident reports are collected and analyzed. Then, the risk factors are incorporated into causal analysis for different types of railway accidents. Finally, a historical data-driven approach is utilized to model and gain new insights into the key risk factors causing different types of railway accidents. Meanwhile, a Tree-Augmented Naive Bayes (TAN) is employed to construct a model of interdependencies among risk factors, and the model is validated through sensitivity analysis and past accident records. The research findings demonstrate that the crucial risk factors for all types of accidents include undetected track damage, train operator skills, load, braking system conditions, train speed, traction system failures, level crossings, and bridge damage. Additionally, the research results highlight the differential impact of key factors on different types of accidents, providing a most probable explanation for observing the most likely configurations in the model for a specific scenario. This work contributes to accident prevention and safety decision-making.
Increases in carbon (C) inputs to soil can replenish soil organic C (SOC) through various mechanisms. However, recent studies have suggested that the increased C input can also stimulate the ...decomposition of old SOC via priming. Whether the loss of old SOC by priming can override C replenishment has not been rigorously examined. Here we show, through data-model synthesis, that the magnitude of replenishment is greater than that of priming, resulting in a net increase in SOC by a mean of 32% of the added new C. The magnitude of the net increase in SOC is positively correlated with the nitrogen-to-C ratio of the added substrates. Additionally, model evaluation indicates that a two-pool interactive model is a parsimonious model to represent the SOC decomposition with priming and replenishment. Our findings suggest that increasing C input to soils likely promote SOC accumulation despite the enhanced decomposition of old C via priming.
The priming effect (PE) plays a critical role in the control of soil carbon (C) cycling and influences the alteration of soil organic C (SOC) decomposition by fresh C input. However, drivers of PE ...for the fast and slow SOC pools remain unclear because of the varying results from individual studies. Using meta-analysis in combination with boosted regression tree (BRT) analysis, we evaluated the relative contribution of multiple drivers of PE with substrate and their patterns across each driver gradient. The results showed that the variability of PE was larger for the fast SOC pool than for the slow SOC pool. Based on the BRT analysis, 67% and 34% of the variation in PE were explained for the fast and slow SOC pools, respectively. There were seven determinants of PE for the fast SOC pool, with soil total nitrogen (N) content being the most important, followed by, in a descending order, substrate C:N ratio, soil moisture, soil clay content, soil pH, substrate addition rate, and SOC content. The directions of PE were negative when soil total N content and substrate C:N ratio were below 2 g kg-1 and 20, respectively, but the directions changed from negative to positive with increasing levels of this two factors. Soils with optimal water content (50%–70% of the water-holding capacity) or moderately low pH (5–6) were prone to producing a greater PE. For the slow SOC pool, soil pH and soil total N content substantially explained the variation in PE. The magnitude of PE was likely to decrease with increasing soil pH for the slow SOC pool. In addition, the magnitude of PE slightly fluctuated with soil N content for the slow SOC pool. Overall, this meta-analysis provided new insights into the distinctive PEs for different SOC pools and indicated knowledge gaps between PE and its regulating factors for the slow SOC pool.
Alzheimer’s disease (AD) emerges as a perturbing neurodegenerative malady, with a profound comprehension of its underlying pathogenic mechanisms continuing to evade our intellectual grasp. Within the ...intricate tapestry of human health and affliction, the enteric microbial consortium, ensconced within the milieu of the human gastrointestinal tract, assumes a role of cardinal significance. Recent epochs have borne witness to investigations that posit marked divergences in the composition of the gut microbiota between individuals grappling with AD and those favored by robust health. The composite vicissitudes in the configuration of the enteric microbial assembly are posited to choreograph a participatory role in the inception and progression of AD, facilitated by the intricate conduit acknowledged as the gut-brain axis. Notwithstanding, the precise nature of this interlaced relationship remains enshrouded within the recesses of obscurity, poised for an exhaustive revelation. This review embarks upon the endeavor to focalize meticulously upon the mechanistic sway exerted by the enteric microbiota upon AD, plunging profoundly into the execution of interventions that govern the milieu of enteric microorganisms. In doing so, it bestows relevance upon the therapeutic stratagems that form the bedrock of AD’s management, all whilst casting a prospective gaze into the horizon of medical advancements.
Past global change studies have identified changes in species diversity as a major mechanism regulating temporal stability of production, measured as the ratio of the mean to the standard deviation ...of community biomass. However, the dominant plant functional group can also strongly determine the temporal stability. Here, in a grassland ecosystem subject to 15 years of experimental warming and hay harvest, we reveal that warming increases while hay harvest decreases temporal stability. This corresponds with the biomass of the dominant C4 functional group being higher under warming and lower under hay harvest. As a secondary mechanism, biodiversity also explains part of the variation in temporal stability of production. Structural equation modelling further shows that warming and hay harvest regulate temporal stability through influencing both temporal mean and variation of production. Our findings demonstrate the joint roles that dominant plant functional group and biodiversity play in regulating the temporal stability of an ecosystem under global change.
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