Effect of nitrogen fertilization on central tendency and spatial heterogeneity of soil moisture, pH and dissolved organic carbon and nitrogen in two bioenergy croplands

Background Soil moisture, pH, dissolved organic carbon and nitrogen (DOC, DON) are important soil biogeochemical properties in switchgrass (SG) and gamagrass (GG) croplands. Yet their spatiotemporal patterns under nitrogen (N) fertilization have not been studied. Aims The objective of this study is to investigate the main and interactive effects of N fertilization and bioenergy crop type on central tendencies and spatial heterogeneity of soil moisture, pH, DOC and DON. Methods Based on a 3-year long fertilization experiment in Middle Tennessee, USA, 288 samples of top horizon soils (0–15 cm) under three fertilization treatments in SG and GG croplands were collected. The fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha−1 in urea) and high N input (HN: 168 kg N ha−1 in urea). Soil moisture, pH, DOC and DON were quantified. And their within-plot variations and spatial distributions were achieved via descriptive and geostatistical methods. Results Relative to NN, LN significantly increased DOC content in SG cropland. LN also elevated within-plot spatial heterogeneity of soil moisture, pH, DOC and DON in both croplands though GG showed more evident spatial heterogeneity than SG. Despite the pronounced patterns described above, great plot to plot variations were also revealed in each treatment. Conclusion This study informs the generally low sensitivity of spatiotemporal responses in soil biogeochemical features to fertilizer amendments in bioenergy croplands. However, the significantly positive responses of DOC under low fertilizer input informed the best practice of optimizing agricultural nutrient amendment

Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics

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., \u3e 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

Study on the damage law of coal rock affected by different alternating periods of cold and heat

Temperature is an important factor affecting the physical properties of coal and rock, and as a solid medium, coal and rock have the properties of thermal expansion and contraction. The alternation of cold and heat will cause irreversible damage to the coal rock due to deformation, which will eventually lead to the damage and destruction of the original fracture structure of the coal rock. In order to study the damage law of coal and rock affected by different alternating cycles of cold and heat, the long-flame coal in Fuxin area of Liaoning Province was selected to make a cube specimen with a size of 100 mm×100 mm×100 mm. The mechanical parameters and surface dimensions of the coal samples before and after the experiment were measured by using the research method of reciprocating the application of temperature loads in a low temperature storage box(–15 °C) and room temperature(20 °C). Furthermore, the expansion law and damage mechanism of the coal sample fracture structure with the alternating cycle of cooling and heating are revealed. The results show ① The coal sample cracks expand and expand under the alternating action of cold and heat, and the expansion amount and expansion rate of the cracks on the surface of the coal sample gradually increase with the cycle of the alternating cycle of cold and heat. ② The mechanical properties of coal samples are weakened under the action of multi-cycle temperature loads, the damage is serious, and the compressive strength of coal samples gradually decreases with the cycle of alternating cycles of cold and heat. ③ The damage mechanics model of coal sample structure is established by ABAQUS software, and the simulation results are in good agreement with the experimental results. The overall structural damage degree of the coal sample is aggravated, indicating that the alternating action of cold and heat is an important factor for the structural damage of the coal sample

Differential effects of warming and nitrogen fertilization on soil respiration and microbial dynamics in switchgrass croplands

The mechanistic understanding of warming and nitrogen (N) fertilization, alone or in combination, on microbially mediated decomposition is limited. In this study, soil samples were collected from previously harvested switchgrass (Panicum virgatum L.) plots that had been treated with high N fertilizer (HN: 67 kg N ha−1) and those that had received no N fertilizer (NN) over a 3-year period. The samples were incubated for 180 days at 15 °C and 20 °C, during which heterotrophic respiration, δ13C of CO2, microbial biomass (MB), specific soil respiration rate (Rs: respiration per unit of microbial biomass), and exoenzyme activities were quantified at 10 different collections time. Employing switchgrass tissues (referred to as litter) with naturally abundant 13C allowed us to partition CO2 respiration derived from soil and amended litter. Cumulative soil respiration increased significantly by 16.4% and 4.2% under warming and N fertilization, respectively. Respiration derived from soil was elevated significantly with warming, while oxidase, the agent for recalcitrant soil substrate decomposition, was not significantly affected by warming. Warming, however, significantly enhanced MB and Rs indicating a decrease in microbial growth efficiency (MGE). On the contrary, respiration derived from amended litter was elevated with N fertilization, which was consistent with the significantly elevated hydrolase. N fertilization, however, had little effect on MB and Rs, suggesting little change in microbial physiology. Temperature and N fertilization showed minimal interactive effects likely due to little differences in soil N availability between NN and HN samples, which is partly attributable to switchgrass biomass N accumulation (equivalent to ~53% of fertilizer N). Overall, the differential individual effects of warming and N fertilization may be driven by physiological adaptation and stimulated exoenzyme kinetics, respectively. The study shed insights on distinct microbial acquisition of different substrates under global temperature increase and N enrichment

An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

n insufficient functional relationship between adjustment factors and saturation flow rate (SFR) in the U.S. Highway Capacity Manual (HCM) method increases an additional prediction bias. The error of SFR predictions can reach 8%&ndash 10%. To solve this problem, this paper proposes a comprehensive adjusted method that considers the effects of interactions between factors. Based on the data from 35 through lanes in Beijing and 25 shared through and left-turn lanes in Washington, DC, the interactions between lane width and percentage of heavy vehicles and proportion of left-turning vehicles were analyzed. Two comprehensive adjustment factor models were established and tested. The mean absolute percentage error (MAPE) of model 1 (considering the interaction between lane width and percentage of heavy vehicles) was 4.89% smaller than the MAPE of Chinese National Standard method (Standard Number is GB50647) at 13.64%. The MAPE of model 2 (considering the interaction between lane width and proportion of left-turning vehicles was 33.16% smaller than the MAPE of HCM method at 14.56%. This method could improve the accuracy of SFR prediction, provide support for traffic operation measures, alleviate the traffic congestion, and improve sustainable development of cities. Document type: Articl

Soil extracellular enzyme activities, soil carbon and nitrogen storage under nitrogen fertilization: A meta-analysis

Nitrogen (N) fertilization affects the rate of soil organic carbon (SOC) decomposition by regulating extracellular enzyme activities (EEA). Extracellular enzymes have not been represented in global biogeochemical models. Understanding the relationships among EEA and SOC, soil N (TN), and soil microbial biomass carbon (MBC) under N fertilization would enable modeling of the influence of EEA on SOC decomposition. Based on 65 published studies, we synthesized the activities of α-1,4-glucosidase (AG), β-1,4-glucosidase (BG), β-d-cellobiosidase (CBH), β-1,4-xylosidase (BX), β-1,4-N-acetyl-glucosaminidase (NAG), leucine amino peptidase (LAP), urease (UREA), acid phosphatase (AP), phenol oxidase (PHO), and peroxidase (PEO) in response to N fertilization. The proxy variables for hydrolytic C acquisition enzymes (C-acq), N acquisition (N-acq), and oxidative decomposition (OX) were calculated as the sum of AG, BG, CBH and BX; AG and LAP; PHO and PEO, respectively. The relationships between response ratios (RRs) of EEA and SOC, TN, or MBC were explored when they were reported simultaneously. Results showed that N fertilization significantly increased CBH, C-acq, AP, BX, BG, AG, and UREA activities by 6.4, 9.1, 10.6, 11.0, 11.2, 12.0, and 18.6%, but decreased PEO, OX and PHO by 6.1, 7.9 and 11.1%, respectively. N fertilization enhanced SOC and TN by 7.6% and 15.3%, respectively, but inhibited MBC by 9.5%. Significant positive correlations were found only between the RRs of C-acq and MBC, suggesting that changes in combined hydrolase activities might act as a proxy for MBC under N fertilization. In contrast with other variables, the RRs of AP, MBC, and TN showed unidirectional trends under different edaphic, environmental, and physiological conditions. Our results provide the first comprehensive set of evidence of how hydrolase and oxidase activities respond to N fertilization in various ecosystems. Future large-scale model projections could incorporate the observed relationship between hydrolases and microbial biomass as a proxy for C acquisition under global N enrichment scenarios in different ecosystems

Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning

Sound events in daily life carry rich information about the objective world. The composition of these sounds affects the mood of people in a soundscape. Most previous approaches only focus on classifying and detecting audio events and scenes, but may ignore their perceptual quality that may impact humans’ listening mood for the environment, e.g. annoyance. To this end, this paper proposes a novel hierarchical graph representation learning (HGRL) approach which links objective audio events (AE) with subjective annoyance ratings (AR) of the soundscape perceived by humans. The hierarchical graph consists of fine-grained event (fAE) embeddings with single-class event semantics, coarse-grained event (cAE) embeddings with multi-class event semantics, and AR embeddings. Experiments show the proposed HGRL successfully integrates AE with AR for AEC and ARP tasks, while coordinating the relations between cAE and fAE and further aligning the two different grains of AE information with the AR

Effects of nitrogen fertilization and bioenergy crop species on central tendency and spatial heterogeneity of soil glycosidase activities

Extracellular glycosidases in soil, produced by microorganisms, act as major agents for decomposing labile soil organic carbon (e.g., cellulose). Soil extracellular glycosidases are significantly affected by nitrogen (N) fertilization but fertilization effects on spatial distributions of soil glycosidases have not been well addressed. Whether the effects of N fertilization vary with bioenergy crop species also remains unclear. Based on a 3-year fertilization experiment in Middle Tennessee, USA, a total of 288 soil samples in topsoil (0–15 cm) were collected from two 15 m2 plots under three fertilization treatments in switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.) using a spatially explicit design. Four glycosidases, α-glucosidase (AG), β-glucosidase (BG), β-xylosidase (BX), cellobiohydrolase (CBH), and their sum associated with C acquisition (Cacq) were quantified. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha−1 year−1 in urea) and high N input (HN: 168 kg N ha−1 year−1 in urea). The descriptive and geostatistical approaches were used to evaluate their central tendency and spatial heterogeneity. Results showed significant interactive effects of N fertilization and crop type on BX such that LN and HN significantly enhanced BX by 14% and 44% in SG, respectively. The significant effect of crop type was identified and glycosidase activities were 15–39% higher in GG than those in SG except AG. Within-plot variances of glycosidases appeared higher in SG than GG but little differed with N fertilization due to large plot-plot variation. Spatial patterns were generally more evident in LN or HN plots than NN plots for BG in SG and CBH in GG. This study suggested that N fertilization elevated central tendency and spatial heterogeneity of glycosidase activities in surficial soil horizons and these effects however varied with crop and enzyme types. Future studies need to focus on specific enzyme in certain bioenergy cropland soil when N fertilization effect is evaluated

Nitrogen Fertilization Restructured Spatial Patterns of Soil Organic Carbon and Total Nitrogen in Switchgrass and Gamagrass Croplands in Tennessee USA

Nitrogen (N) fertilizers can potentially alter spatial distribution of soil organic carbon (SOC) and total nitrogen (TN) concentrations in croplands such as switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.), but it remains unclear whether these effects are the same between crops and under different rates of fertilization. 13C and 15N are two important proxy measures of soil biogeochemistry, but they were rarely examined as to their spatial distributions in soil. Based on a three-year long fertilization experiment in Middle Tennessee, USA, the top mineral horizon soils (0–15 cm) were collected using a spatially explicit design within two 15-m2 plots under three fertilization treatments in SG and GG croplands. A total of 288 samples were collected based on 12 plots and 24 samples in each plot. The fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha−1 in urea) and high N input (HN: 168 kg N ha−1 in urea). The SOC, TN, SOC/TN (C: N), δ13C and δ15N were quantified and their within-plot variations and spatial distributions were achieved via descriptive and geostatistical methods. Results showed that SG generally displayed 10~120% higher plot-level variations in all variables than GG, and the plot-level variations were 20~77% higher in NN plots than LN and HN plots in SG but they were comparable in unfertilized and fertilized plots in GG. Relative to NN, LN and HN showed more significant surface trends and spatial structures in SOC and TN in both croplands, and the fertilization effect appeared more pronounced in SG. Spatial patterns in C: N, δ13C and δ15N were comparable among different fertilization treatments in both croplands. The descending within-plot variations were also identified among variables (SOC \u3e TN \u3e δ15N \u3e C: N \u3e δ13C). This study demonstrated that N fertilizations generally reduced the plot-level variance and simultaneously re-established spatial structures of SOC and TN in bioenergy croplands, which little varied with fertilization rate but was more responsive in switchgrass cropland