Spatiotemporal Distribution Research Articles

Quasi-real-time earthquake relocation and monitoring in the northeastern Noto Peninsula

The seismicity rate markedly increased in the northeastern Noto Peninsula of Ishikawa Prefecture around the end of 2020, with an Mw6.2 event on 5 May, 2023, followed by many aftershocks. Previous earthquake relocation studies have detected upward migration of microearthquakes via multiple faults and clusters, suggesting the involvement of crustal fluids in this sequence. Since some active faults exist near the source region, there was concern that this sequence could lead to a larger earthquake; it became a reality with the Mw7.5 earthquake on 1 January 2024. This study aims to develop an algorithm to precisely relocate microearthquake hypocenters in quasi-real time for better monitoring. A fine view of seismicity requires relative relocation methods such as the double-difference (DD) method with numerous arrival time difference data precisely measured by the waveform correlation analysis. However, the standard DD method has the disadvantage of huge computational costs when data increase, making it unsuitable for real-time monitoring in such situations. We developed a quasi-real-time algorithm that relocates only new earthquakes using the DD method each time a new time window of data is added. The major improvement is that our method incorporates a traditional simple relative relocation and preserves constraints between different time windows; the relative locations of new events are constrained from reference events that were already relocated in the previous time windows. We tested a daily relocation algorithm on 11,546 events from 19 June, 2022, to 31 May, 2023, in the Noto Peninsula earthquake sequence. We found that our modification substantially reduced artificial hypocenter offsets between different time windows and succeeded in resolving the fine fault structures from the cloud-like distribution of initial hypocenters. If we do not impose constraints between different windows, the relocated hypocenters are scattered and do not show fine planar structures. Our algorithm greatly reduces the computational cost, allowing for quasi-real-time earthquake relocation and monitoring. We hope this algorithm will help monitor the spatio-temporal distribution of future earthquake sequences.Graphical

Machine Learning‐Driven Spatiotemporal Analysis of Ozone Exposure and Health Risks in China

AbstractAccurate and fine‐scaled prediction of ozone concentrations across space and time, as well as the assessment of associated human risks, is crucial for protecting public health and promoting environmental conservation. This paper introduces NetGBM, an innovative machine‐learning model designed to comprehensively model ozone levels across China's diverse topography and analyze the spatiotemporal distribution of ozone and exposure. Our model focuses on daily, weekly, and monthly predictions, achieving commendable coefficients of 0.83, 0.77, and 0.79, respectively. By constructing a gridded map of ozone and incorporating both land use and meteorological features into each grid, we achieved ozone prediction at a high spatiotemporal resolution, outperforming previous research in terms of performance and scale, particularly in regions with limited monitoring stations. The results can be further improved when applied to regional research using meteorological and ozone data from regional stations. Additionally, our research revealed that temperature is the most significant factor affecting ozone concentrations across China. In health risk assessment, we retrieved a high‐resolution spatial distribution of ozone‐attributed mortality for 5‐COD and daily ozone inhalation distributions during our study period. We concluded that ozone‐attributed mortality is predominantly caused by stroke and IHD, accounting for more than 70% of the total deaths in 2021, with the highest mortality rates in developed urban areas such as the NCP and the YRD. Our experiment demonstrated the potential of NetGBM in robustly modeling ozone across China with high spatiotemporal resolution and its applicability in measuring associated health risks.

Important fish diversity maintenance status of the tributaries in a hotspot fish conservation area in the upper Yangtze River revealed by eDNA metabarcoding

This study employed Environmental DNA (eDNA) barcoding technology to delve into the influence of the tributaries and mainstem on fish diversity and spatiotemporal distribution in a hotspot fish conservation area in the upper Yangtze River. A total of 123 fish species were detected, belonging to 7 orders, 19 families, and 77 genera. The composition of fish species in tributaries is similar to that in mainstem, with higher fish community diversity in tributaries during the spring and summer. Exploration of fish ecotypes revealed significant differences between mainstem and tributaries. The fish community is mainly influenced by key environmental factors such as water temperature, dissolved oxygen, electrical conductivity, and ammonia nitrogen, with a higher impact of these factors on tributaries than on mainstem. In conclusion, while tributaries and mainstem in the Jiangjin section exhibit similarities in fish community composition, there are notable differences in community structure and diversity. Therefore, the protection of not only mainstem but also tributaries and their associated fish habitats is crucial for promoting the overall health and sustainability.

Analysis of the Spatiotemporal Distribution Characteristics and Influencing Factors of High-Grade Cultural Heritage in the Region Surrounding Mount Song

Situated in central China, the region surrounding Mount Song is a pivotal area within the Central Plains, renowned for its extensive and high-grade cultural heritage. This study aims to analyze the spatiotemporal distribution of this heritage using advanced spatial pattern analysis methods, including the Average Nearest Neighbor Ratio and Kernel Density Estimation within ArcGIS. Our findings reveal a distinct continuity in temporal distribution and a pronounced clustering in spatial terms. By investigating the underlying factors such as the geographical setting, historical political capitals, cultural and religious influences, water transportation systems, and traditional Fengshan ceremonies, this research elucidates the dynamics shaping this distribution. This study’s outcomes provide essential insights for policymakers and stakeholders involved in the protection and revitalization of cultural heritage, ensuring informed decision making for sustainable cultural conservation.

Climate Change Effects on Spatiotemporal Distribution of Precipitation over West Central India: A Statistical Downscaling Approach

The long-term shifts in temperatures and weather patterns are referred to as climate change. Climate change not only leads to long-term shifts in average temperatures but also changes in the spatial and temporal distribution of rainfall over continents. This study aims to predict likely changes in the rainfall pattern induced by climate change over the West Central (WC) region of India. The approach uses a statistical downscaling technique that converts coarse-scale outputs of the global climate model (GCM) to high-resolution future precipitation projections giving refined distribution. The decision support tool that uses a robust statistical downscaling technique viz. statistical downscaling model (SDSM) is used for assessing local climate change impacts. The research includes the study of likely regional climate variability, by integrating historical observational data and empirical relationships between large-scale climate variables and local weather patterns. Historical data and the SDSM, version 4.2, are employed to forecast future rainfall trends. Rainfall data from the India Meteorological Department and the National Centre for Environmental Prediction (NCEP) from 1961 to 2001 are used along with outputs from general circulation models (GCMs), viz. Hadley Centre coupled model, version 3 (HadCM3), and coupled global climate model, version 3 (CGCM3), for the period 1961–2099. Rainfall scenarios are presented for three future time periods (2011–2040, 2041–2070, and 2071–2099). The study indicates a significant increase in the mean annual precipitation across the West Central India region, particularly in the 2050s and 2080s. Mean annual rainfall is projected to rise by 10–19.4% under HadCM3 A2 and B2 scenarios. The HadCM3 indicates the month of September as the month of the highest precipitation in later time periods, whereas it is the month of August, according to CGCM3 simulations. When comparing the results of the two models, HadCM3 gives better results, as indicated by better R2 value in validation. Thus, the analysis gives climate change-induced likely changes in the spatiotemporal distribution of precipitation over the West Central India region. The insight given by the work will be useful for decision making in many sectors like agriculture, water management, disaster risk reduction, and infrastructure planning.

Climate Change Drove the Decline in Yangtze Estuary Net Primary Production Over the Past Two Decades.

Net primary productivity (NPP) is highly sensitive to multiple stressors under progressive and intensifying climate change and anthropogenic impacts. The importance of understanding spatiotemporal distribution patterns and the associated driving factors that govern estuary NPP is paramount for regional carbon (C) budget assessments. Using a combined remote sensing and machine learning (ML) approach, the average NPP of the Yangtze Estuarine-offshore continuum (YEOC) was measured at 273.19 ± 21.26 mgC m-2 day-1 over the past two decades. Temporally, NPP exhibited a significant downward trend between 2002 and 2022. Climate factors (climate fluctuations, sea level rise, and discharge) drove phytoplankton biomass (Chl-a) while light conditions (PAR and Kd490) affected photosynthesis rates. Together, they can explain 65% of the NPP variation. Anthropogenic disturbances (i.e., damming and nutrient emissions) were not significant. Additionally, changes in NPP decreased phytoplankton C sequestration rates from 11.9 to 10.4 Tg C year-1, reducing the estuary's C sink capacity, which relies on biological C fixation. This study highlights the climate's influence on the spatiotemporal transformation of YEOC NPP while enhancing our understanding of the response of EOC C budgets to climate change and anthropogenic activities.

Fine‐scale variation in the medium and large‐sized mammal assemblage composition in northeastern Amazon: Drivers of β‐diversity and species interactions

AbstractUnderstanding fine‐scale assemblage composition patterns of mammals is important to increase ecological knowledge and support conservation actions. We investigated whether β‐diversity of medium and large‐sized mammals and its components (replacement and richness difference) are related to distance to major rivers, height above the nearest drainage (HAND), and vegetation height; and whether species interactions shape their spatiotemporal distribution. We used camera traps to monitor the mammal assemblage of the Tumucumaque Mountains National Park, Northeastern Amazon. The difference (Δ) in distance to major rivers and geographic distance between sites affected positively the total β‐diversity and both its components. ΔVegetation height affected total β‐diversity and species replacement, while ΔHAND affected richness differences, and to a lower extent, species replacement. We found evidence that spotted pacas (Cuniculus paca) and ocelots (Leopardus pardalis) adjust their spatiotemporal dynamics to escape from predation and to overlap with abundant prey, respectively. However, we did not find evidence that competition affects the spatiotemporal distribution of any other species. Vegetation height, distance to rivers and HAND influenced mammal assemblages probably through shaping the quality and amount of resources. Predation risk seems to be important in shaping the use of time and space by prey, while the distribution of prey is important for the use of time and space for predators. Furthermore, other niche differentiation mechanisms may explain why competition did not affect the species' spatiotemporal dynamics. We highlight the need to include different environmental contexts within protected areas to promote mammal diversity and conservation.

Dynamics of the electromagnetic field near the edge of a stripe line during its charging

The spatiotemporal distribution of the electromagnetic field near the edge of the strip line when it is charged to a constant value of the voltage between the strips is studied by the methods of a computational experiment. The conditions under which a monopolar electromagnetic pulse is emitted into free space are revealed.

Real-time high-resolution microscopy reveals how single-cell lysis shapes biofilm matrix morphogenesis.

During development, multiscale patterning requires that cells organize their behavior in space and time. Bacteria in biofilms must similarly dynamically pattern their behavior with a simpler toolkit. Like in eukaryotes, morphogenesis of the extracellular matrix is essential for biofilm development, but how it is patterned has remained unclear. Here, we explain how the architecture of eDNA, a key matrix component, is controlled by single cell lysis events during Pseudomonas aeruginosa biofilm development. We extend single-cell imaging methods to capture complete biofilm development, characterizing the stages of biofilm development and visualizing eDNA matrix morphogenesis. Mapping the spatiotemporal distribution of single cell lysis events reveals that cell lysis is restricted to a specific biofilm zone. Simulations indicate that this patterning couples cell lysis to growth, more uniformly distributing eDNA throughout the biofilm. Finally, we find that patterning of cell lysis is organized by nutrient gradients that act as positioning cues.

Spatiotemporal topology of religious spread in a multi‐religious metropolis: A historical religious profile of Taipei City in Taiwan from 1660 to 2020

AbstractReligious identities play an important role in shaping migrants' experiences. Understanding the spatiotemporal distribution of religions enhances our knowledge of both religious expansion and religious cultures. This paper aims to leverage spatiotemporal analysis to characterise the topology of the spread of multiple religions in the Taipei metropolitan area from 1660 to 2020, including Folk Taoism (853 temples/altars, 55.39%), Christianity (306 churches, 19.87%) and Buddhism (332 temples, 21.56%). Three major factors affecting religious distribution are considered: the year of establishment of religious units (churches, temples or altars), the reclamation year of religious locations, and the economic index of religious sites. The results show that Folk Taoism and Buddhism have a long history of development in early reclamation regions with a hopping expansion pattern. However, Christianity expanded later in the later reclaimed and early reclaimed areas. The Christian religious units have highly concentrated spatial patterns and are located in the higher‐income districts, centralised in the core regions of the Taipei metropolis. Modern forms of highly institutionalised religion, such as Buddhism and Christianity, are more prevalent in the relatively higher‐income, later‐cultivated areas, which provide richer social resources for development. Folk Taoism, as a traditional religion, is maintained and developed by local communities. This macroscopic analysis helps to (1) identify the exact chronology of different growth waves and explain them in a historical context, and (2) elucidate the spatial distribution differences between institutionalised religions and folk religion. Our research shows the evolution of religious landscapes from an undeveloped city to a developed city, offering valuable insights for geographical and religious studies, and enhancing understanding of diffused and institutionalised religious expansion.

A Review of Satellite-Based CO2 Data Reconstruction Studies: Methodologies, Challenges, and Advances

Carbon dioxide is one of the most influential greenhouse gases affecting human life. CO2 data can be obtained through three methods: ground-based, airborne, and satellite-based observations. However, ground-based monitoring is typically composed of sparsely distributed stations, while airborne monitoring has limited coverage and spatial resolution; they cannot fully reflect the spatiotemporal distribution of CO2. Satellite remote sensing plays a crucial role in monitoring the global distribution of atmospheric CO2, offering high observation accuracy and wide coverage. However, satellite remote sensing still faces spatiotemporal constraints, such as interference from clouds (or aerosols) and limitations from satellite orbits, which can lead to significant data loss. Therefore, the reconstruction of satellite-based CO2 data becomes particularly important. This article summarizes methods for the reconstruction of satellite-based CO2 data, including interpolation, data fusion, and super-resolution reconstruction techniques, and their advantages and disadvantages, it also provides a comprehensive overview of the classification and applications of super-resolution reconstruction techniques. Finally, the article offers future perspectives, suggesting that ideas like image super-resolution reconstruction represent the future trend in the field of satellite-based CO2 data reconstruction.

Statistical Characteristics of Snowfall on the Tibetan Plateau Affected by TCs Over the Bay of Bengal: An Observational Analysis

ABSTRACTIn this study, the characteristics of tropical cyclones (TCs) over the Bay of Bengal (BoB) that affect snowfall on the Tibetan Plateau (TP) and spatiotemporal distribution of snowfall related to BoB TCs are statistically analysed by using multi‐sources data from 1981 to 2020, with partitioning TC‐influenced snowfall by tracking cloud clusters. The results show that 141 TCs formed during the 40‐year period of 1981–2020, of which about 35% (50 TCs) impacted snowfall at 83% of meteorological stations on the TP during their northward or westward movement, and the average distance between the TC centre and the snowfall stations is 1277 km. The proportion of snowfall‐related TC frequency shows a significantly decreasing trend with a predominant cycle of 10a. The TC‐influenced snowfall frequency (SF), precipitation amount (PA) on a snowfall day and snow depth (SD) during 1981–2020 all show a non‐significant weak decreasing trend, while TC‐influenced snowfall is significantly increased in the eastern and southern edges of Xizang, western Sichuan and the southern margin of Qinghai. PA and SD in December account for more than 75% and 55% of the monthly total, respectively. The spatial pattern of PA could be objectively categorised into west‐type (24%) and southeast‐type (76%). The moisture transported by the BoB TC and a southerly jet stream formed between the trough and the western Pacific subtropical high (WPSH), the convergence of cold air and warm–moist airstream over the TP and the change in position of the south Asian high in the upper troposphere are significant factors causing the different spatial distribution. The results can provide reference for TC‐related snowfall, SD prediction and disaster assessment on the TP.

Intestinal distribution of anionic, cationic, and neutral polymer-stabilized nanocarriers measured with a lanthanide (europium) tracer assay

Nanocarriers, more commonly called nanoparticles (NPs), have found increasing use as delivery vehicles which increase the oral bioavailability of poorly water-soluble and peptide therapeutics. Therapeutic bioavailability is commonly assessed by measuring plasma concentrations that reflect the absorption kinetics. This bioavailability is a convolution of the gastrointestinal distribution of the NP vehicle, the release rate of the encapsulated therapeutic cargo, and the absorption-metabolism-distribution kinetics of the released therapeutic. The spatiotemporal distribution of the NP vehicle in the gastrointestinal tract is not well studied and is a buried parameter in PK studies used to measure the effectiveness of an NP formulation. This work is a study of the intestinal distribution and fate of orally dosed NPs in male CD-1 mice over 24 h. NPs have identical hydrophobic cores – composed of poly(styrene) homopolymer, a naphthalocyanine dye, and oleate-coated europium oxide colloids – with one of four different surface stabilizers: neutral poly(styrene)-block-poly(ethylene glycol) (PS-b-PEG), moderately negative hydroxypropyl methylcellulose acetate succinate (HPMCAS), highly negative poly(styrene)-block-poly(acrylic acid) (PS-b-PAA), and highly cationic adsorbed chitosan HCl on PS-b-PAA stabilized NPs. NP hydrodynamic diameters are all below 200 nm, with some variation attributable to the molecular properties of the stabilizing polymer. The encapsulated hydrophobic europium oxide colloids do not release soluble europium ions, enabling the use of highly sensitive inductively coupled plasma mass spectrometry (ICP-MS) to detect NP concentrations in digested biological tissues.Highly anionically-charged PAA and cationically-charged chitosan stabilized NPs showed statistically significant increased retention compared to the neutral PEG-stabilized NPs at p < 0.05 significance and (1-β) > 0.95 power. HPMCAS-stabilized NPs showed statistically insignificant greater retention than PEG-stabilized NPs, and all NP formulations showed clearance from the intestines within 24 h. Different surface charges preferentially reside in different segments of the intestines, where cationic chitosan-stabilized NPs showed increased retention in the small intestines (ileum) and anionic PAA-stabilized NPs in the large intestines (caecum and colon). Modifying the surface charge of a NP can be used to modulate mucoadhesion, total retention, and intestinal segment specific retention, which enables the rational design of delivery vehicles that maximize residence times in appropriate locations.

Mangroves Invaded by Spartina alterniflora Loisel: A Remote Sensing-Based Comparison for Two Protected Areas in China

Mangroves are one of the world’s most productive and ecologically important ecosystems, and they are threatened by the widespread invasion of Spartina alterniflora Loisel in China. As few studies have examined the spatial pattern differences of S. alterniflora invasion and the nearby mangroves in different latitudes, we chose the Zhangjiang Estuary and the Dandou Sea, two representative mangrove–salt marsh ecotones in the north and south of the Tropic of Cancer, as the study areas for comparison. The object-based image analysis and visual interpretation methods were combined to construct fine-scale mangrove and S. alterniflora maps using high-resolution satellite imagery from 2005 to 2019. We applied spatial analysis, centroid migration, and landscape indexes to analyze the spatio–temporal distribution changes of mangroves and S. alterniflora in these two ecotones over time. We used the landscape expansion index to investigate the S. alterniflora invasion process and expansion patterns. The annual change rates of mangrove and S. alterniflora areas in the Zhangjiang Estuary showed a continuous growth trend. However, the mangrove areas in the Dandou Sea showed a fluctuating trend of increasing, decreasing, and then increasing again, while S. alterniflora areas kept rising from 2005 to 2019. Spartina alterniflora showed larger annual change rates compared with mangroves, indicating rapid S. alterniflora invasion in the intertidal zones. The opposite centroid migration directions of mangroves and S. alterniflora and the decreasing distances between the mangrove and S. alterniflora centroids indirectly revealed the fierce competition between mangroves and S. alterniflora for habitat resources. Both regions saw a decrease in mangrove patch integrality and connectivity. The integrality of mangrove patches in the Zhangjiang Estuary was always higher than those in the Dandou Sea. We observed the growth stage (2011–2014) and outbreak stage (2014–2019) of S. alterniflora expansion in the Zhangjiang Estuary and the outbreak stage (2005–2009) and plateau stage (2009–2019) of S. alterniflora expansion in the Dandou Sea. The expansion pattern of S. alterniflora varies in time and place. Since the expansion of S. alterniflora in the outbreak stage is rapid, with a large annual change rate, early warning of S. alterniflora invasion is quite important for the efficient and economical removal of the invasive plant. Continuous and accurate monitoring of S. alterniflora is highly necessary and beneficial for the scientific management and sustainable development of coastal wetlands.

Hydrological Modeling to Unravel the Spatiotemporal Heterogeneity and Attribution of Baseflow in the Yangtze River Source Area, China

Revealing the spatiotemporal variation in baseflow and its underlying mechanisms is critical for preserving the health and ecological functions of alpine rivers, but this has rarely been conducted in the source region of the Yangtze River (SRYR). Our study employed the Soil and Water Assessment Tool (SWAT) model coupled with two-parameter digital filtering and geostatistical approaches to obtain a visual representation of the spatiotemporal heterogeneity characteristics of the baseflow and baseflow index (BFI) in the SRYR. The SWAT model and multiple linear regression model (MLR) were used to quantitatively estimate the contribution of climate change and human activities to baseflow and BFI changes. The results underscore the robust applicability of the SWAT model within the SRYR. Temporally, the precipitation, temperature, and baseflow exhibited significant upward trends, and the baseflow and BFI showed contrasting intra-annual distribution patterns, which were unimodal and bimodal distribution, respectively. Spatially, the baseflow increased from northwest to southeast, and from the watershed perspective, the Tongtian River exhibited higher baseflow values compared to other regions of the SRYR. The baseflow and BFI values of the Dangqu River were greater than those of other tributaries. More than 50% of the entire basin had an annual BFI value greater than 0.7, which indicates that baseflow was the major contributor to runoff generation. Moreover, the contributions of climate change and human activities to baseflow variability were 122% and −22%, and to BFI variability, 60% and 40%. Specifically, precipitation contributed 116% and 60% to the baseflow and BFI variations, while the temperature exhibited contributions of 6% and 8%, respectively. Overall, it was concluded that the spatiotemporal distributions of baseflow and the BFI are controlled by various factors, and climate change is the main factor of baseflow variation. Our study offers valuable insights for the management and quantitative assessment of groundwater resources within the SRYR amidst climate change.

Intercomparison of gross primary productivity in spatio-temporal distribution over a typical tropical region based on different datasets.

Gross Primary Productivity (GPP) plays a vital role in the carbon cycle of terrestrial ecosystems. For the purpose of assessing the performance of various GPP products in a typical tropical area, this study conducted an intercomparison of seven different GPP products over Hainan Island, China, and analyzed spatiotemporal characteristics of GPP in different elevation regions and vegetation types over study area. The results showed that although the GPP spatial distribution pattern over Hainan Island, as presented by different GPP products, is similar- showing that GPP values in the southwest are higher than those in the northeast- there are significant differences in the spatial distributions and magnitudes of each GPP product. The multi-annual mean GPP values from the seven GPP products exhibited similar temporal variation trends, with GOSIF being obviously higher than other GPP products. The GPP products indicated significant differences in different elevation and vegetation type groups. The GPP gap between GLASS AVHRR and BESS V2 decreases slightly with the increase in elevation. Most GPP products show a consistent change trend over time. There were also significant differences in the results of significance tests for the change trends of GPP products. Though GOSIF is significantly higher than other GPP products, it demonstrated a relatively high correlation with all GPP products, while AGPP exhibited relatively low correlations with all GPP products. The quantitatively comparative analysis of seven different GPP products in this study is valuable for improving GPP retrieval models and can also serve as a scientific reference for the application of GPP products in tropical region vegetation studies.

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. The results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

Event Stream Denoising Method Based on Spatio-Temporal Density and Time Sequence Analysis.

An event camera is a neuromimetic sensor inspired by the human retinal imaging principle, which has the advantages of high dynamic range, high temporal resolution, and low power consumption. Due to the interference of hardware and software and other factors, the event stream output from the event camera usually contains a large amount of noise, and traditional denoising algorithms cannot be applied to the event stream. To better deal with different kinds of noise and enhance the robustness of the denoising algorithm, based on the spatio-temporal distribution characteristics of effective events and noise, an event stream noise reduction and visualization algorithm is proposed. The event stream enters fine filtering after filtering the BA noise based on spatio-temporal density. The fine filtering performs time sequence analysis on the event pixels and the neighboring pixels to filter out hot noise. The proposed visualization algorithm adaptively overlaps the events of the previous frame according to the event density difference to obtain clear and coherent event frames. We conducted denoising and visualization experiments on real scenes and public datasets, respectively, and the experiments show that our algorithm is effective in filtering noise and obtaining clear and coherent event frames under different event stream densities and noise backgrounds.

Community dynamics and assembly is driven by environmental microbiota mediated by spatiotemporal distribution: The case of Daqu fermentation

In almost all environments, microbial interaction is shaped by differences in environmental microbial transport, resulting in synergistic or antagonistic effects among community members. Unfortunately, the current understanding of how environmental microbiota affect spontaneous fermentation is very limited. Here, we selected Daqu workshops with different usage times (named X (60 years), Y (10 years), and Z (0 year)) as research model. The microbial contribution of raw material and environments to the microbiota of Daqu fermentation among workshops was compared, raw material microbiota contributed more bacterial genera (44.70 %–73.56 %) to the fermentation, and environmental microbiota contributed more fungal genera (10.09 %–99.76 %) to the fermentation. The deterministic assembly ratio and interaction intensity of workshop X were the highest, followed by Y and Z. We analyzed the relationship between environmental microbiota, fermentation microbiota, fermentation characteristics and flavor compounds. Environmental microbiota negatively drove the microbial diversity during fermentation (path coefficient = −1, P = 0.004), and further indirectly affected the community dynamics and assembly (path coefficient = −0.990, P < 0.001). Finally, community dynamics and assembly drove flavor compound diversity (path coefficient = 0.923, P < 0.001), it indicated the positive effect of environmental microbiota on flavor compound diversity. This work will help to understand the relationship between environmental microbiota and fermentation quality, supporting quality improvement of spontaneously fermented food in new workshop.

The divergent role of straw return in soil O2 dynamics elucidates its confounding effect on soil N2O emission

The divergent effects of straw returns on nitrous oxide (N2O) emissions from soil require elucidation of the underlying mechanisms and factors that explain the inconsistency in in-situ conditions. We conducted a field experiment based on a long-term trial under different regimes of nitrogen (N) fertilization and straw management, complemented by laboratory incubation experiments involving visualized O2 dynamics imaging. In the field trial, we performed hourly basis high-time-resolution measurements of soil matrix oxygen (O2), N2O concentrations and fluxes during N2O “hot moment” events. We found that straw return increased cumulative N2O emissions by 32.7% under conventional high N input (Ncon), but showed no effect on N2O emission under optimized N input (Nopt). In situ O2 content and further microcosm experiments with visualized O2 spatiotemporal distribution suggested that long-term straw return increases porosity and soil O2 content, which reduced N2O emission under low N substrate conditions by improving soil pore structure and aeration during “hot moment” events. By contrast, straw return increased N2O emission via creating short-term O2 depletion zone and triggering denitrification in anoxic microsites when excess N substrate was available. Although straw return showed inconsistent effects on N2O emission under different N application rates, it consistently decreased N2O concentration in the soil matrix during the "hot moment" events, suggesting that straw return increases the transport of the produced N2O in soil matrix to the soil surface. Our study underscores the multifaceted role of straw return in soil O2 dynamics, i.e., stimulating O2 consumption in a short-term microscale of soil, but increasing soil porosity in a long-term mesoscale of soil. This explains the confounding effects of straw management on the production and transportation of soil N2O in situ and emphasizes the importance of optimized N fertilization for reducing the “hot moment” N2O emissions when straw is incorporated.