84 research outputs found

    Differential Responses and Controls of Soil CO2 and N2O Fluxes to Experimental Warming and Nitrogen Fertilization in a Subalpine Coniferous Spruce (Picea asperata Mast.) Plantation Forest

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    Emissions of greenhouse gases (GHG) such as CO2 and N2O from soils are affected by many factors such as climate change, soil carbon content, and soil nutrient conditions. However, the response patterns and controls of soil CO2 and N2O fluxes to global warming and nitrogen (N) fertilization are still not clear in subalpine forests. To address this issue, we conducted an eight-year field experiment with warming and N fertilization treatments in a subalpine coniferous spruce (Picea asperata Mast.) plantation forest in China. Soil CO2 and N2O fluxes were measured using a static chamber method, and soils were sampled to analyze soil carbon and N contents, soil microbial substrate utilization (MSU) patterns, and microbial functional diversity. Results showed that the mean annual CO2 and N2O fluxes were 36.04 ± 3.77 mg C m−2 h−1 and 0.51 ± 0.11 µg N m−2 h−1, respectively. Soil CO2 flux was only affected by warming while soil N2O flux was significantly enhanced by N fertilization and its interaction with warming. Warming enhanced dissolve organic carbon (DOC) and MSU, reduced soil organic carbon (SOC) and microbial biomass carbon (MBC), and constrained the microbial metabolic activity and microbial functional diversity, resulting in a decrease in soil CO2 emission. The analysis of structural equation model indicated that MSU had dominant direct negative effect on soil CO2 flux but had direct positive effect on soil N2O flux. DOC and MBC had indirect positive effects on soil CO2 flux while soil NH4+-N had direct negative effect on soil CO2 and N2O fluxes. This study revealed different response patterns and controlling factors of soil CO2 and N2O fluxes in the subalpine plantation forest, and highlighted the importance of soil microbial contributions to GHG fluxes under climate warming and N deposition

    DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning

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    Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training. One of the most effective and widely used semantic information for zero-shot image classification are attributes which are annotations for class-level visual characteristics. However, the current methods often fail to discriminate those subtle visual distinctions between images due to not only the shortage of fine-grained annotations, but also the attribute imbalance and co-occurrence. In this paper, we present a transformer-based end-to-end ZSL method named DUET, which integrates latent semantic knowledge from the pre-trained language models (PLMs) via a self-supervised multi-modal learning paradigm. Specifically, we (1) developed a cross-modal semantic grounding network to investigate the model's capability of disentangling semantic attributes from the images; (2) applied an attribute-level contrastive learning strategy to further enhance the model's discrimination on fine-grained visual characteristics against the attribute co-occurrence and imbalance; (3) proposed a multi-task learning policy for considering multi-model objectives. We find that our DUET can achieve state-of-the-art performance on three standard ZSL benchmarks and a knowledge graph equipped ZSL benchmark. Its components are effective and its predictions are interpretable.Comment: AAAI 2023 (Oral). Repository: https://github.com/zjukg/DUE

    Shrub type dominates the vertical distribution of leaf C : N : P stoichiometry across an extensive altitudinal gradient

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    Understanding leaf stoichiometric patterns is crucial for improving predictions of plant responses to environmental changes. Leaf stoichiometry of terrestrial ecosystems has been widely investigated along latitudinal and longitudinal gradients. However, very little is known about the vertical distribution of leaf C :N: P and the relative effects of environmental parameters, especially for shrubs. Here, we analyzed the shrub leaf C, N and P patterns in 125 mountainous sites over an extensive altitudinal gradient (523-4685 m) on the Tibetan Plateau. Results showed that the shrub leaf C and C :N were 7.3-47.5% higher than those of other regional and global flora, whereas the leaf N and N: P were 10.2-75.8% lower. Leaf C increased with rising altitude and decreasing temperature, supporting the physiological acclimation mechanism that high leaf C (e.g., alpine or evergreen shrub) could balance the cell osmotic pressure and resist freezing. The largest leaf N and high leaf P occurred in valley region (altitude 1500 m), likely due to the large nutrient leaching from higher elevations, faster litter decomposition and nutrient resorption ability of deciduous broadleaf shrub. Leaf N: P ratio further indicated increasing N limitation at higher altitudes. Interestingly, drought severity was the only climatic factor positively correlated with leaf N and P, which was more appropriate for evaluating the impact of water status than precipitation. Among the shrub ecosystem and functional types (alpine, subalpine, montane, valley, evergreen, deciduous, broadleaf, and conifer), their leaf element contents and responses to environments were remarkably different. Shrub type was the largest contributor to the total variations in leaf stoichiometry, while climate indirectly affected the leaf C :N: P via its interactive effects on shrub type or soil. Collectively, the large heterogeneity in shrub type was the most important factor explaining the overall leaf C :N: P variations, despite the broad climate gradient on the plateau. Temperature and drought induced shifts in shrub type distribution will influence the nutrient accumulation in mountainous shrubs. © Author(s) 2018

    MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid

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    As an important variant of entity alignment (EA), multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) with relevant images attached. We noticed that current MMEA algorithms all globally adopt the KG-level modality fusion strategies for multi-modal entity representation but ignore the variation in modality preferences for individual entities, hurting the robustness to potential noise involved in modalities (e.g., blurry images and relations). In this paper, we present MEAformer, a multi-modal entity alignment transformer approach for meta modality hybrid, which dynamically predicts the mutual correlation coefficients among modalities for entity-level feature aggregation. A modal-aware hard entity replay strategy is further proposed for addressing vague entity details. Experimental results show that our model not only achieves SOTA performance on multiple training scenarios including supervised, unsupervised, iterative, and low resource, but also has a comparable number of parameters, optimistic speed, and good interpretability. Our code and data are available at https://github.com/zjukg/MEAformer.Comment: Repository: https://github.com/zjukg/MEAforme

    Genome sequence of the insect pathogenic fungus Cordyceps militaris, a valued traditional chinese medicine

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    Species in the ascomycete fungal genus Cordyceps have been proposed to be the teleomorphs of Metarhizium species. The latter have been widely used as insect biocontrol agents. Cordyceps species are highly prized for use in traditional Chinese medicines, but the genes responsible for biosynthesis of bioactive components, insect pathogenicity and the control of sexuality and fruiting have not been determined. Here, we report the genome sequence of the type species Cordyceps militaris. Phylogenomic analysis suggests that different species in the Cordyceps/Metarhizium genera have evolved into insect pathogens independently of each other, and that their similar large secretomes and gene family expansions are due to convergent evolution. However, relative to other fungi, including Metarhizium spp., many protein families are reduced in C. militaris, which suggests a more restricted ecology. Consistent with its long track record of safe usage as a medicine, the Cordyceps genome does not contain genes for known human mycotoxins. We establish that C. militaris is sexually heterothallic but, very unusually, fruiting can occur without an opposite mating-type partner. Transcriptional profiling indicates that fruiting involves induction of the Zn2Cys6-type transcription factors and MAPK pathway; unlike other fungi, however, the PKA pathway is not activated.https://doi.org/10.1186/gb-2011-12-11-r11

    Diastereoisomer-Specific Biotransformation of Hexabromocyclododecanes by a Mixed Culture Containing Dehalococcoides mccartyi Strain 195

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    Hexabromocyclododecane (HBCD) stereoisomers may exhibit substantial differences in physicochemical, biological, and toxicological properties. However, there remains a lack of knowledge about stereoisomer-specific toxicity, metabolism, and environmental fate of HBCD. In this study, the biotransformation of (±)α-, (±)β-, and (±)γ-HBCD contained in technical HBCD by a mixed culture containing the organohalide-respiring bacterium Dehalococcoides mccartyi strain 195 was investigated. Results showed that the mixed culture was able to efficiently biotransform the technical HBCD mixture, with 75% of the initial HBCD (∼12 μM) in the growth medium being removed within 42 days. Based on the metabolites analysis, HBCD might be sequentially debrominated via dibromo elimination reaction to form tetrabromocyclododecene, dibromocyclododecadiene, and 1,5,9-cyclododecatriene. The biotransformation of the technical HBCD was likely diastereoisomer-specific. The transformation rates of α-, β-, and γ-HBCD were in the following order: α-HBCD > β-HBCD > γ-HBCD. The enantiomer fractions of (±)α-, (±)β-, and (±)γ-HBCD were maintained at about 0.5 during the 28 days of incubation, indicating a lack of enantioselective biotransformation of these diastereoisomers. Additionally, the amendment of another halogenated substrate tetrachloroethene (PCE), which supports the growth of strain 195, had a negligible impact on the transformation patterns of HBCD diastereoisomers and enantiomers. This study provided new insights into the stereoisomer-specific transformation patterns of HBCD by anaerobic microbes and has important implications for microbial remediation of anoxic environments contaminated by HBCD using the mixed culture containing Dehalococcoides

    Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: a perspective from long‐term data assimilation

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    It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback
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