Remote sensing and environmental assessment of wetland ecological degradation in the Small Sanjiang Plain, Northeast China

IntroductionThe plain marsh wetland ecosystems are sensitive to changes in the natural environment and the intensity of human activities. The Sanjiang Plain is China’s largest area of concentrated marsh wetland, the Small Sanjiang Plain is the most important component of the Sanjiang Plain. However, with the acceleration of the urbanization and development of large-scale agricultural reclamation activities in the Small Sanjiang Plain in Northeast China, the wetland has been seriously damaged. In light of this degradation this study examines the Small Sanjiang Plain.MethodsFrom the four aspects of area, structure, function, and human activities, we try to construct a wetland degradation comprehensive index (WDCI) in cold region with expert scoring methods and analytic hierarchy process (AHP), coupled with network and administrative unit. The objective was to reveal the degradation of wetlands in Northeast China over three decades at a regional scale.ResultsThe results showed that (1) the overall wetland area decreased between 1990 and 2020 by 39.26×103 hm2. Within this period a significant decrease of 336.56×103 hm2 occurred between 1990 and 200 and a significant increase of 214.62×103 hm2 occurred between 2010 and 2020. (2) In terms of structural changes, the fractal dimension (FRAC) has the same trend as the Landscape Fragmentation Index (LFI) with little change. (3) In terms of functional changes, the average above-ground biomass (AGB) increased from 1029.73 kg/hm2 to 1405.38 kg/hm2 between 1990 and 2020 in the study area. (4) In terms of human activities, the average human disturbance was 0.52, 0.46, 0.57 and 0.53 in 1990, 2000, 2010 and 2020, with the highest in 2010. (5) The composite wetland degradation index shows that the most severe wetland degradation was 49.61% in 2010 occurred between 1990 and 2020. (6) Among the severely deteriorated trajectory types in 2010–2020, mild degradation → serious degradation accounted for the largest area of 240.23×103 hm2, and the significant improvement trajectory type in 1990–2000 accounted for the largest area of 238.50×103 hm2.DiscussionIn brief, we conclude that the degradation of the Small Sanjiang Plain wetland was caused mainly by construction, overgrazing, deforestation, and farmland reclamation. This study can also provide new views for monitoring and managing wetland degradation by remote sensing in cold regions

Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community.

BACKGROUND:It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in this region, which accounts for about 50% of the world's SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample). RESULTS:We show that longer-term (5 years) experimental winter warming at the same site altered microbial communities (p < 0.040). Thaw depth correlated the strongest with community assembly and interaction networks, implying that warming-accelerated tundra thaw fundamentally restructured the microbial communities. Both carbon decomposition and methanogenesis genes increased in relative abundance under warming, and their functional structures strongly correlated (R2 > 0.725, p < 0.001) with ecosystem respiration or CH4 flux. CONCLUSIONS:Our results demonstrate that microbial responses associated with carbon cycling could lead to positive feedbacks that accelerate SOC decomposition in tundra regions, which is alarming because SOC loss is unlikely to subside owing to changes in microbial community composition. Video Abstract

Improvement of lignocellulose bioconversion in Clostridium cellulolyticum and identification of active lignocellulose degraders in temperate grassland

As the most abundant sustainable carbon resource on the earth, lignocellulose is considered as one of the most promising feedstocks to produce biofuels, which can mitigate the environmental issues brought by burning of fossil fuels. However, the lignocellulosic biofuels face grand challenges on multiple fronts, including low-cost technology for utilization of cellulose and highly efficient conversion from cellulose to biofuels by high-yield microorganisms. Therefore, these challenges are calling for engineering designs to increase efficiency and reduce the costs. As a model mesophilic clostridial species for studying lignocellulose degradation, Clostridium cellulolyticum can perform one-step bioconversion of lignocellulose to biofuels and is considered as a potential candidate for future industrial biofuels productions. However, the efficiency of lignocellulose bioconversion in C. cellulolyticum is not high enough, which impedes its further application in industries. Thus, the major aim of this dissertation is to engineer the C. cellulolyticum by CRISPR-Cas9 editing method to improve its lignocellulose bioconversion efficiency. In addition to being feedstock for biofuels productions, lignocellulose is the primary carbon input in the natural soil and the microbial decomposition of the lignocellulose is an important global carbon sink. With current global warming, both photosynthesis rate by plants and the carbon decomposition rate by microorganisms can be enhanced but may not equally. As a result, whether warming can cause a positive feedback for C exchange between the terrestrial and atmosphere is unclear. Thus, another major aim of this dissertation is to identify the active lignocellulose bacteria and understand their lignocellulose degradation mechanisms responding to warming. In C. cellulolyticum, a unique extracellular multi-enzyme complex named cellulosome plays the most important role in degrading the cellulose. The cellulosome has great commercial values and can be used for consolidated bio-saccharification. However, the function for a cellulosomal component named X2 in C. cellulolyticum was still unclear, which limited our understanding for the cellulose degradation mechanisms by the cellulosome and its future commercial application. To have a better understanding of the in-vivo biological function of X2 modules, we employed CRISPR-Cas9 editing to create dual X2 modules mutant (△X2-NC) by deleting the conserved motif (NGNT) of X2 modules. Compared to the wild type strain, the degradation efficiency and saccharification ability in the △X2-NC were decreased. Further, the in vivo adhesion assay and the in vitro enzymatic assay found that the biological function of the X2 module was associated with the binding affinity between the cells and its cellulose substrate. This study provides new perspectives on engineering cellulolytic bacteria or modification of commercial cellulases for industrial application. Major cellulosomal components are encoded by a 26 kb cip-cel gene operon named cip-cel. Two major large transcripts were detected when C. cellulolyticum was grown on cellulose. However, the abundance of 3’- transcript is much lower than the 5’- transcript. To increase the expression of the 3’- transcript of the cip-cel operon, we employed CRISPR-Cas9 editing system to insert a synthetic promoter (P4) and an endogenous promoter (P2) within cip-cel operon in Clostridium cellulolyticum. Both engineered strains increased the transcript abundance of downstream polycistronic genes and enhanced in vitro cellulolytic activities of isolated cellulosomes. Compared to the control strain, both engineered strains could degrade more cellulose and demonstrated a greater growth rate and a higher cell biomass yield. Our strategy, editing regulatory elements of catabolic gene clusters, provides new perspectives on improving cellulose bioconversion in microbes. Earlier studies have found that the accumulation of cellobiose could inhibit both cell growth and cellulase productions in the cellulolytic clostridia bacteria, such as Clostridium thermocellum and C. cellulolyticum, which would further decrease the efficiency of cellulose bioconversion. To overcome it, two strategies were applied to release the carbon catabolite repression caused by cellobiose. First, an exogenous β-glucosidase gene from C.cellulovorans was integrated into the upstream of the lactate hydrogenase gene (ccel_2485) of C. cellulolyticum genome for enhancing the enzymatic bioconversion of cellobiose to glucose. We found that the engineered strain could degrade 12% more cellulose than the WT at the final time point, accompanied with 25% more ethanol production. Second, the regulator for carbon catabolite repression (CCR) was inactivated in C. cellulolyticum. However, the mutant could not utilize the cellulose anymore, indicating that inactivation of CCR regulator is not an effective strategy for releasing the repression of cellobiose. Together, the integration of the exogenous β-glucosidase gene in the genome provides new perspectives on improving cellulose bioconversion in C. cellulolyticum, and also provides a new potential site in the genome of C. cellulolyticum for future integration and engineering. Finally, microbial decomposition of soil organic carbon (SOC), which are mainly derived from lignocellulose, has a strong impact on future atmospheric greenhouse gas concentrations, which serve as important feedbacks to climate warming. However, the underlying decomposition mechanisms remain poorly understood. In order to understand the microbial mechanisms of lignocellulose decomposition and how the active microbes respond to current global warming, we identified active taxa responsible for carbon (C) degradation in temperate grassland subjected to experimental warming. Using a stable-isotope probing incubation experiment with 13C-labeled straw to simulate grassland litter, a total of 56 active amplicon sequence variants (ASVs) were detected only in the warmed samples. Many ASVs belonged to fast-growing bacteria such as α-Proteobacteria, Bacillales, Actinobacteria, and Bacteroidetes, which were further verified by our observation that their relative abundances were increased (p < 0.050) by warming over consecutive seven years. Interestingly, warming increased the phylogenetic diversity of active bacterial communities and β-diversity among active bacterial communities. The carbon-degrading potentials of the active bacterial communities were also stimulated by warming. In summary, these results should provide essential support to future field and global scale simulations and enable more accurate predictions of feedbacks between climate change and carbon cycling. Overall, this dissertation provides valuable insights into engineering C. cellulolyticum for improving its lignocellulose bioconversion efficiency. Our strategies can be applied for engineering other clostridial cellulolytic bacteria, such as C.cellulovorans and C.thermocellum, to improve their lignocellulose bioconversion efficiency. Additionally, the newly identified active lignocellulose degraders in temperate grassland may also provide new insights into finding new industrial potential strain to produce lignocellulosic biofuels

Study on methodology for risk assessment of inorganic arsenic in rice

Objective To study the application of risk assessment in the prevention and control of health risk of inorganic arsenic in rice. Methods Taking the health effect assessment of inorganic arsenic from rice and the existing possible interventions or control measures on local population in A county as an example. The detection data, consumption survey data, bioavailability and dose-response relationship model were combined, and @ RISK 7.5 was used for probability assessment of the risk of bladder cancer and lung cancer in the general population in different scenarios. Results In the normal limit and consumption scenario, the number of new bladder and lung cancer cases after 25 years is 0.045 cases per 105 population per year. This was almost negligible (about 0.021 5%) compared with new cases by all causes after 25 years (about 209.2 cases per 105 population per year). The resulting loss in average life expectancy was approximately 0.000 529 years/0.193 1 days. Acceptable levels and the possible reintervention or control measures had little impact on the risk. Even assuming that both the inorganic arsenic limit and rice consumption were reduced by half, the incidence of lung cancer only fell by 2.16%. Conclusion The study showed that changing the consumption structure and/or national standard limits had little significance to reduce the risk of inorganic arsenic in rice, and the current hypothetical scenario also had great limitations and uncertainties, but provided a framework for integration, evaluation and application of new information in the public health

HAT: A Visual Transformer Model for Image Recognition Based on Hierarchical Attention Transformation

In the field of image recognition, Visual Transformer (ViT) has excellent performance. However, ViT, relies on a fixed self-attentive layer, tends to lead to computational redundancy and makes it difficult to maintain the integrity of the image convolutional feature sequence during the training process. Therefore, we proposed a non-normalization hierarchical attention transfer network (HAT), which introduces threshold attention mechanism and multi head attention mechanism after pooling in each layer. The focus of HAT is shifted between local and global, thus flexibly controlling the attention range of image classification. The HAT used the smaller computational complexity to improve it&#x2019;s scalability, which enables it to handle longer feature sequences and balance efficiency and accuracy. HAT removes layer normalization to increase the likelihood of convergence to an optimal level during training. In order to verify the effectiveness of the proposed model, we conducted experiments on image classification and segmentation tasks. The results shows that compared with classical pyramid structured networks and different attention networks, HAT outperformed the benchmark networks on both ImageNet and CIFAR100 datasets

Emerging multimodal memristors for biorealistic neuromorphic applications

The integration of sensory information from different modalities, such as touch and vision, is essential for organisms to perform behavioral functions such as decision-making, learning, and memory. Artificial implementation of human multi-sensory perception using electronic supports is of great significance for achieving efficient human–machine interaction. Thanks to their structural and functional similarity with biological synapses, memristors are emerging as promising nanodevices for developing artificial neuromorphic perception. Memristive devices can sense multidimensional signals including light, pressure, and sound. Their in-sensor computing architecture represents an ideal platform for efficient multimodal perception. We review recent progress in multimodal memristive technology and its application to neuromorphic perception of complex stimuli carrying visual, olfactory, auditory, and tactile information. At the device level, the operation model and undergoing mechanism have also been introduced. Finally, we discuss the challenges and prospects associated with this rapidly progressing field of research

Ethanolysis of Glucose into Biofuel 5-Ethoxymethyl-Furfural Catalyzed by NH4H2PO4 Modified USY Zeolite

5-Ethoxymethylfurfural (EMF) can be considered as a potential biofuel because of its excellent combustion properties, such as high energy density and low carbon smoke emissions. In this study, Ultra-stable Y (USY) zeolite was modified with NH4H2PO4 and then used as an efficient solid catalyst for the catalytic synthesis of EMF via ethanolysis of glucose First, the NH4H2PO4-modified USY was characterized by FT-IR, XRD, BET, and NH3-TPD. The effect of reaction temperature, reaction time, substrate concentration, and catalyst loading on the yield of EMF was investigated. The P0.2-USY optimal EMF yield was 39.6 mol%, which increased by 20.7% compared to USY, and still had better activity after being reused for 5 cycles. Moreover, the pseudo-homogeneous first-order kinetics model was developed to elucidate the kinetics of EMF formation from glucose, and the kinetics results showed that the activation energy of EMF formation (64.2 kJ⋅mol-1) was lower than that of humins formation (73.2 kJ⋅mol-1). Finally, the ethanolysis pathway was proposed based on the product distribution