Spatial heterogeneity of soil respiration after prescribed burning in Pinus koraiensis forest in China.

Soil respiration (RS) is crucial for releasing carbon dioxide (CO2) from terrestrial ecosystems to atmosphere. Prescribed burning (a common forest management tool), along with its important by-product pyrogenic carbon (PyC), can influence the carbon cycle of forest soil. However, few studies explore RS and PyC spatial correlation after prescribed burning. In this study, we investigated the spatial pattern of RS and its influencing factors by conducting prescribed burnings in a temperate artificial Pinus koraiensis forest. RS was measured 1 day (1 d) pre-prescribed burning, 1 d, 1 year (1 yr) and two years (2 yr) after prescribed burning. Significant decrease in RS were observed 1-2 yr After burning (reductions of 65.2% and 41.7% respectively). The spatial autocorrelation range of RS decreased pre-burning (2.72m), then increased post-burning (1 d: 2.44m; 1 yr: 40.14m; 2 yr: 9.8m), indicating a more homogeneous distribution of patch reduction. Pyrogenic carbon (PyC) in the soil gradually decreased in the short term after burning with reductions of 19%, 52%, and 49% (1d., 1 yr And 2 yr After the fire, respectively). However, PyC and RS exhibited a strong spatial positive correlation from 1 d.- 1 yr post-burning. The spatial regression model of dissolved organic carbon (DOC) on RS demonstrated significant positive spatial correlation in all measurements (pre- and post-burning). Microbial carbon to soil nitrogen ratio (MCN) notably influenced RS pre-burning and 1-2 yr post-burning. RS also showed significant spatial correlation in cross-variance with NH4+-N and NO3--N post-burning. The renewal of the PyC positively influenced RS, subsequently affecting its spatial distribution in 1d.- 1yr. Introducing PyC into RS studies helps enhances understanding of prescribed fire effects on forest soil carbon (C) pools, and provides valuable information regarding regional or ecosystem C cycling, facilitating a more accurate prediction of post-burning changes in forest soil C pools.

Temporal dynamics of soil dissolved organic carbon in temperate forest managed by prescribed burning in Northeast China.

Dissolved organic carbon (DOC) is an important function of soil organic carbon and sensitive to environmental disturbance. Few studies have explored the variations in soil DOC dynamics and effects on soil physicochemical properties following prescribed burnings. In this study, Pinus koraiensis plantation forests in Northeast China were selected and subjected to prescribed burning in early November 2018. Soil DOC and different soil physicochemical and biological properties in the 0-10 cm and 10-20 cm soil layers were sampled six times within two years after a prescribed burning. In this study, some soil physicochemical (SOC, TN, and ST) and microbial biomass properties (MBC) recovered within two years after a prescribed burning. Compared to the unburned control stands, the post-fire soil DOC concentrations in the upper and lower soil layers increased by 16% and 12%, respectively. Soil DOC concentrations varied with sampling time, and peaked one year after the prescribed burning. Our results showed that soil chemical properties (NH4+-N and pH) rather than biological properties (microbial biomass) were the main driving factors for changes in post-fire soil DOC concentrations. Current study provides an important reference for post-fire and seasonal soil C cycling in plantation forests of Northeast China.

Effects of biochar on soil carbon pool stability in the Dahurian larch (Larix gmelinii) forest are regulated by the dominant soil microbial ecological strategy.

Biochar is widely used in integrated soil management, and can directly alter the soil environment and drastically affect the soil microbial community. Given the important role of soil microorganisms in the carbon cycling of soils, it is important to understand how biochar alters the stability of soil organic carbon (SOC) pools in Dahurian larch (Larix gmelinii) forests through microbial pathways unburned and high-severity burned soils to guide comprehensive soil management and restore ecological functions in postfire soils. This study employed the r/K ecological strategy theory to quantify the ecological strategy propensities of soil microbial communities. The ratio of oligotrophic species to copiotrophic species was used to measure these propensities. The study aimed to establish a link between the ecological strategy choices of microbial communities and SOC pools. We found: that (1) biochar increases the mass of SOC regardless of whether the soil has experienced fire, (2) biochar addition to unburned stands makes the K-strategy dominant in microbial communities, significantly decreasing the mineral-associated organic carbon (MAOC) to SOC ratio and weakening the of SOC pool stability; (3) biochar addition to high-severity burned stands shifts the dominant microbial strategy to r-strategy, restoring the damaged microbial community to its preburned state. The MAOC/SOC ratio significantly increased, contributing to the restoration of the SOC pool stability and enhancing the soil carbon sequestration capacity. This study elucidates the effects of biochar addition on the dominant ecological strategy of microbial communities and alterations in the structure and stability of SOC pools, which is important for understanding how biochar affects SOC pools through biochemical pathways, and provides important references for unraveling the relation between microbial ecological strategies and soil carbon pools.

Effects of pyrogenic carbon addition after fire on soil carbon mineralization in the Great Khingan Mountains peatlands (Northeast China).

Wildfires play a critical role in regulating soil carbon (C) budgets in peatland ecosystems, and their frequency and intensity are increasing owing to climate change and human activities. Wildfires not only emit CO2 during the combustion process but also produce pyrogenic carbon (PyC), which accumulates in the soil C pool and influences soil C decomposition. However, the role of PyC after a fire in peatland soil C mineralization has rarely been examined. This study investigated the effects of PyC addition on peatland soil C mineralization and its potential driving mechanisms using an anaerobic/aerobic incubation experiment with peat soils collected from typical peatlands in the Great Khingan Mountains, Northeast China. The effect of PyC was more pronounced under aerobic conditions than under anaerobic conditions. The mean C- mineralization rates of soil were significantly increased by 45.2 ± 15.5 % and 87.6 ± 14.3 % with 10 % PyC250°C addition after the initial stage (D7) of aerobic and anaerobic incubation, but PyC600°C addition caused a to decrease. Compared with PyC600°C, PyC250°C addition significantly increased the available N content and altered the soil microbial activities, which may be the primary reason for the increase in C mineralization rates. Furthermore, adding a high concentration of PyC (10 %) reduced the concentration of phenolics but increased phenol oxidase activity, which promoted C mineralization rates. Thus, PyC250°C addition to peat soils mainly influences the microbial biomass C content through the accumulation of available N and phenolics, which ultimately positively affects C mineralization rates.

Prediction models of fire spread rate of Pinus koraiensis plantation's surface fuel.

Pinus koraiensis plantation has high fire risks due to high oil content in branches and leaves. The spread of surface fire is the main way of forest fire expansion. Understanding the surface fire spread rate can provide scientific guidance for fire fighting. We carried out a laboratory experiment with surface fuel of Pinus koraiensis plantation in Maoershan area of Heilongjiang Province. We set different levels of fuel moisture contents (5%, 15%, 25%), fuel loads (0.5, 0.7, 0.9, 1.1 kg·m-2), and slope (0°, 10°, 20°, 30°, 40°) to simulate the characteristics of fuel bed in the field, and quantified the spread rate by thermocouple method. We further compared and analyzed the prediction accuracy of Rothermel model, modified Rothermel model and random forest model, and evaluated the optimal model for predicting the surface fire spread rate of P. koraiensis plantation. The results showed that the overall efficacy of directly using the Rothermel model to predict the surface fire spread rate of P. koraiensis plantations was good, but the prediction result of the spread rate under the conditions of high slope and high moisture content was not satisfied. The Rothermel model after refitting the slope parameters and the random forest model had good prediction efficacy and similar prediction accuracy. The random forest model needed to be further evaluated and verified due to its own characteristics. The modified Rothermel model was more suitable for predicting the surface fire spread rate of P. koraiensis plantations at a slope range of 0°-40° than the others.

Prediction model of water content in surface dead fuel based on convolution neural network and meteoro-logical factors regression.

Water content of surface fuels is an important indicator of forest fire risk level and fire behavior, and the prediction model of which has a significant effect on fire risk prediction and management. Based on field meteorological factors of Quercus mongolica and Pinus sylvestris var. mongolica forests and water content data of dead fuels on the ground, we conducted the relative importance ranking of meteorological factors random forest and Pearson correlation analysis, and predicted water content of fuels using deeply learned convolutional neural network and meteorological factors regression. The results showed that water content of Q. mongolica fuels in the wild was significantly higher than that of P. sylvestris var. mongolica. The results of random forest showed that the factors that had significant effect on water content of fuel were humidity, temperature, rainfall, wind speed, and solar radiation, with the importance ranking from the largest to the smallest. Results of correlation analysis showed that temperature, humidity, and rainfall of current day had a significant impact on water content of fuels, and certain correlations were observed between meteorological factors. The prediction R2 of the convolutional neural network model for the surface fuel water content of Q. mongolica and P. sylvestris var. mongolica forest was 0.928 and 0.905, the mean absolute error (MAE) was 6.1% and 8.1%, and the mean relative error (MRE) was 8.9% and 4.2%, respectively. However, the R2, MAE, MRE of meteorological factors regression were 0.495 and 0.525, 30.5% and 39.5%, 52.1% and 32.6%, respectively. The precision of convolution neural network model was significantly higher than that of meteorological factors regression. Our results showed that the deeply learned convolutional neural network could provide some reference for the prediction of fuel water content in the future, and effectively support higher level forest fire management.

Forest fire risk estimation in a typical temperate forest in Northeastern China using the Canadian forest fire weather index: case study in autumn 2019 and 2020.

China's forest cover has increased by approximately 10% as a result of sustainable forest management since the late 1970s. The forest ecosystem area affected by fire is increasing at an alarming rate of approximately 600,000 ha per year. The northeastern part of China, with a forest cover of 41.6%, has the greatest percentage of acres affected by forest fires. This study combines field and satellite weather data to determine factors that influence dead fuel moisture content (FMC). It assesses the use of the Canadian forest fire weather index to determine the daily forest fire danger in a typical temperate forest in Northeastern China during autumn. Based on the Wilcoxon test for paired samples, the observed and predicted values of FMC showed similar variation in eight of eleven sampling sites (72.7%), with a p value > 0.05. Three sampling plots presented lower predicted values of FMC than observed values (27.3%), with a p value < 0.05. The calculation of fire risk using the Canadian Forest Fire Weather Rating System (CFFDRS) in Maoer Mountain forest ecosystems presented low, medium or high risk; thus, the CFFDRS is suitable for determining fire danger in our study region. Along with these results, this study served to compare the use of FMC-metre field data and China Weather Station data to evaluate fire danger. The results of this study led us to suggest the multiplication of meteorological stations in fire-prone regions.

Association of leukocyte counts in the first trimester with glucose intolerance during pregnancy.

AIMS/INTRODUCTION: We investigated the association between leukocyte counts and glucose challenge test (GCT) level during pregnancy. MATERIALS AND METHODS: We collected prenatal information of women who had their first clinic visit in early pregnancy. Women underwent GCT at 24-28 gestational weeks, and a result of ≥7.8 mmol/L was considered positive. Participants were divided into quartiles of leukocyte counts, and association with GCT results and positive rate were analyzed by logistic regression. RESULTS: Among 20,707 pregnant women, the median of leukocyte counts was higher in the positive group than the normal group (8.5 × 109 /L vs 8.2 × 109 /L, P < 0.01). There was a linear trend in GCT results and positive rate with increasing leukocyte quartiles. Compared with the lowest quartile, the highest leukocyte quartile (>9.70 × 109 /L) was significantly associated with positive GCT results (adjusted odds ratio 1.378, 95% confidence interval 1.246-1.524), and the linear relationship between increased risk of positive result and increasing leukocyte quartiles persisted (P for linear trend <0.01). In multivariable analysis, the risk of a positive result increased by 2.2% with each 1-unit increase in leukocyte counts (adjusted odds ratio 1.022, 95% confidence interval 1.011-1.033). CONCLUSIONS: Elevated leukocyte counts in early pregnancy were independently and linearly associated with the risk of positive GCT levels, indicating that inflammation might play an important role in the development of gestational diabetes mellitus.

[Pyrolysis and gas emissions characteristics of six tree species in Heilongjiang Province, China]. / 黑龙江省6种乔木叶片热解特性及气体释放特征.

Forest fuels are the basis of fire occurrences, while ground dead fuels are an important part of forest fuels. Undestanding the pyrolysis characteristics and gas emissions of forest fuels is of great significance to explore the effects of forest fire on atmospheric environment and carbon balance, as well as to prevent and combat forest fire. In this study, the thermogravimetric analysis and gas emission analysis were conducted on leaf litter of six tree species (Pinus sylvestris var. mongolica, Picea koraiensis, Fraxinus mandshurica, Juglans mandshurica, Quercus mongolica, Betula platyphylla) in Heilongjiang Province to explore the pyrolysis process and combustibility of forest fuels, to analyze their pyrolysis characteristics, pyrolysis kinetics characteristics, gas emission characteristics. A four-dimensional evaluation of their combustibility was conducted based on pyrolysis parameters. The results showed that the pyrolysis temperature of holocellulose in the leaves of those six tree species ranged in 143.31-180.48 ℃ at the beginning and 345.04-394.38 ℃ at the end, lignin pyrolysis temperature ranged in 345.04-394.38 ℃ at the beginning and 582.85-609.31 ℃ at the end. The pyrolysis of the six kinds of arbor blades during the pyrolysis process affected fuel ash content, quality and temperature of the total pyrolysis. The activation energies of two main pyrolysis stages of leaves of six tree species were 18.88-27.08 kJ·mol-1 and 13.25-27.54 kJ·mol-1, respectively, and the pre-exponential factors were 3.13-26.28 min-1 and 1.30-22.55 min-1. The holocellulose activation energy and pre-exponential factor of the pyrolysis stage for P. koraiensis, F. mandshurica, Q. mongolica, and B. platyphylla were greater than that of the lignin pyrolysis stage, while the opposite was true for P. sylvestris var. mongolica and J. mandshurica. The release amounts of CO and CO2 at the pyrolysis stage of the holocellulose was 535.16-880.11 mg·m-3 and 7004.97-10302.05 mg·m-3, and that at the pyrolysis stage of lignin was 240.31-1104.67 mg·m-3 and 20425.60-33946.68 mg·m-3, respectively. The release of CO and CO2 at the pyrolysis stage of healdellulose was less, but mass loss was greater than that at the pyrolysis stage of lignin. In the four-dimensional combustibility ranking of the six tree species leaves, B. platyphylla was the best ignitable, P. koraiensis was the most combustible, and P. sylvestris var. mongolica was the most sustainable and consumable. The ignitability was significantly positively correlated with pyrolysis kinetics parameters of the holocellulose, while the sustainability was negatively correlated with that of lignin.

Characterization of a Novel Bacteriophage Henu2 and Evaluation of the Synergistic Antibacterial Activity of Phage-Antibiotics.

Staphylococcus aureus phage Henu2 was isolated from a sewage sample collected in Kaifeng, China, in 2017. In this study, Henu2, a linear double-stranded DNA virus, was sequenced and found to be 43513bp long with 35% G + C content and 63 putative open reading frames (ORFs). Phage Henu2 belongs to the family Siphoviridae and possesses an isometric head (63 nm in diameter). The latent time and burst size of Henu2 were approximately 20 min and 7.8 plaque forming unit (PFU)/infected cells. The Henu2 maintained infectivity over a wide range of temperature (10-60 °C) and pH values (4-12). Phylogenetic and comparative genomic analyses indicate that Staphylococcus aureus phage Henu2 should be a new member of the family of Siphoviridae class-II. In this paper, Phage Henu2 alone exhibited weak inhibitory activity on the growth of S. aureus. However, the combination of phage Henu2 and some antibiotics or oxides could effectively inhibit the growth of S. aureus, with a decrease of more than three logs within 24 h in vitro. These results provide useful information that phage Henu2 can be combined with antibiotics to increase the production of phage Henu2 and thus enhance the efficacy of bacterial killing.

A combination therapy of Phages and Antibiotics: Two is better than one.

Emergence of antibiotic resistance presents a major setback to global health, and shortage of antibiotic pipelines has created an urgent need for development of alternative therapeutic strategies. Bacteriophage (phage) therapy is considered as a potential approach for treatment of the increasing number of antibiotic-resistant pathogens. Phage-antibiotic synergy (PAS) refers to sublethal concentrations of certain antibiotics that enhance release of progeny phages from bacterial cells. A combination of phages and antibiotics is a promising strategy to reduce the dose of antibiotics and the development of antibiotic resistance during treatment. In this review, we highlight the state-of-the-art advancements of PAS studies, including the analysis of bacterial-killing enhancement, bacterial resistance reduction, and anti-biofilm effect, at both in vitro and in vivo levels. A comprehensive review of the genetic and molecular mechanisms of phage antibiotic synergy is provided, and synthetic biology approaches used to engineer phages, and design novel therapies and diagnostic tools are discussed. In addition, the role of engineered phages in reducing pathogenicity of bacteria is explored.

Novel low-cost carboxymethyl cellulose microspheres with excellent fertilizer absorbency and release behavior for saline-alkali soil.

Saline-alkali soil and fertilizer loss severely restrict agriculture on the Songnen Plain in China. To resolve this problem, carboxymethyl cellulose immobilized slow-release fertilizer microspheres (CFM) with homogeneity pore structure, high porosity, biodegradable biological macromolecules and excellent fertilizer absorbency were synthesized by the combination of inverse emulsion polymerization and microfluidic method. By optimizing the synthesis conditions, the water absorption of CFM reached 8725 g g-1 in deionized water. The absorbency behaviors of CFM were highly sensitive to pH, ionic strength, and ionic species. In 5 g L-1 urea solution, the adsorption capacity of CFM was 3342.84 g g-1. The CFM showed excellent urea retention at 80 °C for 5 h and sustained release performance in soil. Besides, degradation rate of CFM was closed to 98.2% in Aspergillus niger at the third day. CFM had the advantages of high pH sensitivity, salt resistance, and good fertilizer absorbency and retention. Therefore, it will be prospecting fertilizer sustained release agent in agriculture.

Long-term effects of post-fire restoration types on nitrogen mineralisation in a Dahurian larch (Larix gmelinii) forest in boreal China.

Fire is an important disturbance agent in Chinese boreal forests but the long-term effects of wildfires on soil nitrogen (N) net mineralisation rates (Rmin) in natural versus human-assisted restorations are not well understood. In this study, we analysed upper (0-10cm) and lower layer (10-20cm) soil samples from natural restoration and afforestation plots in a Dahurian larch (Larix gmelinii) forest in north-eastern China 29years after a mega fire disturbance. Our results showed that the soil inorganic N (NH4+-N and NO3--N) pool of the upper and lower layers of the regenerated plots remained significantly lower than in unburned control plots. This suggests that the effects of a high burn severity fire on soil N availability were still significant almost 30years after the event. Restoration type (natural restoration versus afforestation) also had significant effects on upper layer soil N availability; compared with afforestation, natural restoration was more beneficial for the accumulation of soil inorganic N and the recovery of Rmin after fire disturbance. Specifically, the concentration of inorganic N and the mean Rmin in upper layer soils in the natural restoration plots were approximately 41% greater and 3.6 times greater, respectively, than in the afforestation plots. The differences in soil N availability between the two restoration types were attributed to differences in soil water content (SWC), soil microbial biomass nitrogen (MBN), and the recovery of vegetation after the fire disturbance. Our study demonstrates that natural restoration has proved more successful than afforestation in countering soil N losses in boreal forests in China resulting from a high burn severity fire disturbance.

Effects of fire disturbance on soil respiration in the non-growing season in a Larix gmelinii forest in the Daxing'an Mountains, China.

In boreal forests, fire is an important part of the ecosystem that greatly influences soil respiration, which in turn affects the carbon balance. Wildfire can have a significant effect on soil respiration and it depends on the fire severity and environmental factors (soil temperature and snow water equivalent) after fire disturbance. In this study, we quantified post-fire soil respiration during the non-growing season (from November to April) in a Larix gmelinii forest in Daxing'an Mountains of China. Soil respiration was measured in the snow-covered and snow-free conditions with varying degrees of natural burn severity forests. We found that soil respiration decreases as burn severity increases. The estimated annual C efflux also decreased with increased burn severity. Soil respiration during the non-growing season approximately accounted for 4%-5% of the annual C efflux in all site types. Soil temperature (at 5 cm depth) was the predominant determinant of non-growing season soil respiration change in this area. Soil temperature and snow water equivalent could explain 73%-79% of the soil respiration variability in winter snow-covering period (November to March). Mean spring freeze-thaw cycle (FTC) period (April) soil respiration contributed 63% of the non-growing season C efflux. Our finding is key for understanding and predicting the potential change in the response of boreal forest ecosystems to fire disturbance under future climate change.

Soil Respiration of the Dahurian Larch (Larix gmelinii) Forest and the Response to Fire Disturbance in Da Xing'an Mountains, China.

Despite the high frequency of wildfire disturbances in boreal forests in China, the effects of wildfires on soil respiration are not yet well understood. We examined the effects of fire severity on the soil respiration rate (Rs) and its component change in a Dahurian Larch (Larix gmelinii) in Northeast China. The results showed that Rs decreased with fire burning severity. Compared with the control plots, Rs in the low burning severity plots decreased by 19%, while it decreased by 28% in the high burning severity plots. The Rs decrease was mainly due to a decreased autotrophic respiration rate (Ra). The temperature sensitivity (Q 10) of Rs increased after the low severity fire disturbances, but it decreased after the high severity fire disturbance. The Rs were triggered by the soil temperature, which may explain most of the Rs variability in this area. Our study, for the first time, provides the data-based foundation to demonstrate the importance of assessing CO2 fluxes considering both fire severity and environmental factors post-fire in boreal forests of China.