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Fire is a crucial event regulating the structure and functioning of many ecosystems. Yet few studies have focused on how fire affects taxonomic and functional diversities of soil microbial communities, along with changes in plant communities and soil carbon (C) and nitrogen (N) dynamics. Here, we analyze these effects in a grassland ecosystem 9 months after an experimental fire at the Jasper Ridge Global Change Experiment site in California, USA. Fire altered soil microbial communities considerably, with community assembly process analysis showing that environmental selection pressure was higher in burned sites. However, a small subset of highly connected taxa was able to withstand the disturbance. In addition, fire decreased the relative abundances of most functional genes associated with C degradation and N cycling, implicating a slowdown of microbial processes linked to soil C and N dynamics. In contrast, fire stimulated above- and belowground plant growth, likely enhancing plant-microbe competition for soil inorganic N, which was reduced by a factor of about 2. To synthesize those findings, we performed structural equation modeling, which showed that plants but not microbial communities were responsible for significantly higher soil respiration rates in burned sites. Together, our results demonstrate that fire 'reboots' the grassland ecosystem by differentially regulating plant and soil microbial communities, leading to significant changes in soil C and N dynamics.

The ecological concept of the r-K life history strategy is widely applied in macro-ecology to characterize functional traits of taxa. However, its adoption in microbial communities is limited, owing to the lack of a measureable, convenient functional trait for classification. In this study, we performed an experiment of stepwise organic amendments in triplicate anaerobic digesters. We found that high resource availability significantly favored microbial r-strategists such as Bacillus spp. Incremental resource availability heightened average rRNA operon copy number of microbial community, resulting in a strong, positive correlation (r>0.74, P

Microbial decomposition of soil organic carbon (SOC) in thawing Arctic permafrost is important in determining greenhouse gas feedbacks of tundra ecosystems to climate. However, the changes in microbial community structure during SOC decomposition are poorly known. Here we examine these changes using frozen soils from Barrow, Alaska, USA, in anoxic microcosm incubation at -2 and 8°C for 122 days. The functional gene array GeoChip was used to determine microbial community structure and the functional genes associated with SOC degradation, methanogenesis, and Fe(III) reduction. Results show that soil incubation after 122 days at 8°C significantly decreased functional gene abundance (P < 0.05) associated with SOC degradation, fermentation, methanogenesis, and iron cycling, particularly in organic-rich soil. These observations correspond well with decreases in labile SOC content (e.g., reducing sugar and ethanol), methane and CO2 production, and Fe(III) reduction. In contrast, the community functional structure was largely unchanged in the -2°C incubation. Soil type (i.e., organic vs. mineral) and the availability of labile SOC were among the most significant factors impacting microbial community structure. These results demonstrate the important roles of microbial community in SOC degradation and support previous findings that SOC in organic-rich Arctic tundra is highly vulnerable to microbial degradation under warming.

Global warming has shifted climate zones poleward or upward. However, understanding the responses and mechanism of microbial community structure and functions relevant to natural climate zone succession is challenged by the high complexity of microbial communities. Here, we examined soil microbial community in three broadleaved forests located in the Wulu Mountain (WLM, temperate climate), Funiu Mountain (FNM, at the border of temperate and subtropical climate zones), or Shennongjia Mountain (SNJ, subtropical climate). Although plant species richness decreased with latitudes, the microbial taxonomic α-diversity increased with latitudes, concomitant with increases in soil total and available nitrogen and phosphorus contents. Phylogenetic NRI (Net Relatedness Index) values increased from -0.718 in temperate zone (WLM) to 1.042 in subtropical zone (SNJ), showing a shift from over dispersion to clustering likely caused by environmental filtering such as low pH and nutrients. Similarly, taxonomy-based association networks of subtropical forest samples were larger and tighter, suggesting clustering. In contrast, functional α-diversity was similar among three forests, but functional gene networks of the FNM forest significantly (P < 0.050) differed from the others. A significant correlation (R = 0.616, P < 0.001) between taxonomic and functional β-diversity was observed only in the FNM forest, suggesting low functional redundancy at the border of climate zones. Using a strategy of space-for-time substitution, we predict that poleward climate range shift will lead to decreased microbial taxonomic α-diversities in broadleaved forest.

Modeling is a core practice in science and is a meaningful way to learn the subject. This article introduces a modeling-based approach that highlights the idea that modeling is an iterative process and integrates the fundamental parts of scientists' work and key suggestions for teaching through modeling. The lesson "The Structure and Function of Kidneys" from a middle school biology course serves as an example of how to conduct the suggested modeling-based approach. By the end of the lesson, almost all students demonstrated a scientific understanding of the structure of nephrons and their functions. On the basis of the implementation of this lesson, we also provide further suggestions for modeling-based teaching. [ABSTRACT FROM AUTHOR]

Due to their important role in maintaining temperature and soil moisture, agricultural plastic covers have been widely utilized around the globe for improving crop-growing conditions, which include both plastic-covered greenhouses (PCGs) and plastic-mulched farmlands (PMFs). However, it is a challenging and long-neglected issue to separate PCGs from PMFs due to their spectral similarity. The objective of this study is to propose a deep semantic segmentation model for accurate PCG and PMF mapping based on very high-resolution satellite images and to improve the model's spatial generalization capability using a transfer learning strategy. Specifically, the proposed semantic segmentation model has an encoder-decoder structure, where the encoder is composed of a new convolutional neural network for discriminative spatial feature learning, while the decoder utilizes a multi-task strategy to improve the predictions on the boundaries. Meanwhile, a transfer learning framework is adopted to increase mapping performance and generalization ability under limited samples. Experimental results in several typical regions across the Eurasian continent show that the proposed model could separate PCGs from PMFs accurately with a mean overall accuracy of 94.49% and an average mIoU of 0.8377. Ablation studies verify the role of encoder-decoder and transfer learning strategy in improving classification performance. [ABSTRACT FROM AUTHOR]

In this paper, the application of the supervised descent method (SDM) for 2-D microwave thorax imaging is studied. The forward modeling problem is solved by the finite element-boundary integral (FE-BI) method. According to the prior information of human thorax, a 3-ellipse training set is generated offline. Then, the average descent direction between an initial background model and the training models is calculated. Finally, the reconstruction of the testing thorax model is achieved based on the average descent directions online. The feasibility using One-Step SDM for thorax imaging is studied. Numerical results indicate that the structural information of thorax can be reconstructed. It has potential for real-time imaging in future clinical diagnosis. [ABSTRACT FROM AUTHOR]

This paper investigated the influence of 2, 6‐di‐tert‐butyl‐p‐cresol (DBPC) on the long‐term ageing characteristics of oil–paper insulation and the deposition and migration of copper sulphide induced by the reaction of copper and dibenzyl disulphide (DBDS) in oil‐immersed transformers. A thermal ageing experiment at 130°C were designed and conducted by adding different concentrations of DBPC to the naphthenic mineral oil and after the experiments a set of characteristic parameters were tested. The result indicates that the excessive concentration (≥0.6%) of DBPC will slightly increase the ageing of insulating oil and increase the carboxyl group in the mineral oil, affecting the reaction of DBDS and copper, and the insulating paper wrapped on the copper strip was also aged seriously accordingly. Meanwhile, the deposition of copper sulphide on the insulating paper is found to be slightly increased with the increase of the concentration of DBPC. When insulating oil contains DBPC and DBDS, due to migration of DBDS–Cu and DBPC–Cu in oil, the copper ions in the oil would be fluctuating at a certain period of time. Although the addition of a small concentration of DBPC can improve the antioxygenic property of the insulting oil to some extent, the transformers that contain excessive concentration of DBPC may be more harmful than beneficial. [ABSTRACT FROM AUTHOR]

This study investigated the inhibitory effects of adsorption treatment on the degradation of oil–paper insulation and corrosive sulphur in oil. A thermal ageing experiment at 130°C was conducted using five different adsorbents to adsorb some impurities in oil on the 15th day of a 30 day ageing test, the related characteristics of oil–paper insulation before and after the adsorption treatment were measured and analysed. Meanwhile, a thermal ageing experiment at 150°C was also conducted before using five different adsorbents to adsorb dibenzyl disulphide (DBDS) in oil, energy dispersive X‐ray was used to evaluate the degree of the corrosion of windings. The result indicates that adsorption treatment is an effective method to inhibit the degradation of oil–paper insulation. A molecular sieve, silica gel and activated alumina can effectively improve the performance of oil–paper insulation. By contrast, the antioxidant (2, 6‐di‐tert‐butyl‐p‐cresol) can be also adsorbed by adsorbents, which accelerate the ageing degradation of the insulating oil. On the other hand, the adsorbents can adsorb DBDS in oil, but cannot remove all DBDS. The effect achieved from silica gel is especially significant, which not only effectively improves the performance of oil–paper insulation but also adsorbs DBDS in oil. [ABSTRACT FROM AUTHOR]