Temporal Heterogeneity Research Articles

Seasonal regulation of tidal creek burrow distribution: Unveiling the dynamic interplay of biotic and abiotic factors

Intertidal creek ecosystems in saltmarsh wetlands provide crucial ecological services, with burrows facilitating material exchange between these environments. Investigating burrow distribution in tidal creeks is essential, yet the underlying mechanisms remain poorly understood. Our study conducted field observations during two seasons, dividing the typical creek section into microhabitats: flat (F), gentle edge (GE), gentle slope (GS), steep slope (SS), and steep edge (SE). Comprehensive analysis of sediment samples encompassed assessments of water content, organic matter, particle size, and salinity. Burrow parameters were extracted using a deep learning method applied to sample images. Benthic biodiversity and community compositions were characterized through eDNA analysis. Our findings revealed significant variations in burrow distribution, sediment properties, and community compositions, both between and within creek sections. Temporal heterogeneity emerged as a substantial influencer of burrow characteristics, while the propensity of benthic communities to respond to topography and sediment properties constituted a chief determinant of burrow distribution. Utilizing a structural equation model based on field data, we illuminated four response pathways governing burrow distribution. Abiotic factors, especially under temporal heterogeneity, had a paramount impact, highlighting the need to explore relative biotic and abiotic influences, considering seasonal regulation. These findings establish a foundational understanding of burrow distribution and its driving mechanisms in creek ecosystems. They offer valuable insights for future field observations and research directions in this field.

Exploring RAS mutation incidence and temporal heterogeneity in metastatic colorectal cancer patients – a single-institution experience utilising circulating tumour DNA

Exploring RAS mutation incidence and temporal heterogeneity in metastatic colorectal cancer patients – a single-institution experience utilising circulating tumour DNA

The illusion of balance in the history of the biosphere.

Earth's surface has been irreversibly altered by the activity of organisms, a process that has accelerated as the power of the biosphere (the rate at which life extracts and deploys energy) has increased over time. This trend is incompatible with the expectation that the inputs to Earth's surface of life's materials from the crust and mantle be matched by export from Earth's surface to long-term reservoirs. Here, I suggest that the collective activity of organisms has always violated this balance. The biosphere's ability to extract, retain, recycle, and accumulate materials has allowed living biomass to increase and for exports to decrease over very long timescales. This collective metabolism implies a net transfer of materials from the planet's interior to its surface. The combination of metabolic innovations, competition, adaptive evolution, and the establishment of collaborative economic feedback in ecosystems created dynamic ecological stability despite great spatial and temporal heterogeneity in physical and biological inputs and export of nutrients into and out of the biosphere. Models of geochemical cycling must take the fundamental role of living organisms and the evolutionary changes in these roles into account to explain past and future conditions.

E-cadherin/CD34 double immunostaining in placental diagnosis.

Placental foetal vascular malperfusion (FVM) may be responsible for complicated foetal or neonatal condition. By highlighting endothelial fragmentation, thedouble E-cadherin/CD34 immunostain highlights distal villous endothelial fragmentation ofrecent FVM not seen on haematoxylin-eosin stained sections. We routinely perform thestain on agrossly unremarkable placental sections ofplacentas predominantly from pregnancies with mass-forming foetal anomalies and umbilical cord complications. Thestain can upgrade theFVM and/or reveal its temporal heterogeneity, both useful in establishing thecause offoetal death or poor neonatal condition. It also highlights thebasement membranes ofsyncytiotrophoblastic cells which, in conjunction with endothelial staining, is helpful in thediagnosis ofwidening thereof in distal villous hypomaturity. It can distinguish mineralised stem occluding thrombi from mineralised trophoblastic pseudo inclusions - theformer outlined by CD34, thelatter by E-cadherin - thus helping to differentiate FVM from placental aneuploidies. TheE-cadherin component helps in thediagnosis oftrophoblastic lesions ofshallow placental implantation featuring an increased number ofextravillous trophoblasts in placental membranes and chorionic disc. Therefore, thedouble immunostain is helpful in histological diagnosis ofplacental lesions and patterns ofinjury.

Comparative Assessment of The Climatological Conditions on The Biological Activity of Ampelocenoses Soils Cultivated in The Wine-Growing Regions of The Southern Coast of Crimea and The Eastern Part of The National Park “Fruska Gora”

Over the last years, research interest in the use of soil biological activity indicator for predicting the state and sustainability of natural and agroecosystems has increased significantly due to climatic changes altering the location and boundaries of established agroclimatic belts. These changes are characterized by unprecedented speed, as well as spatial and temporal heterogeneity. In this regard, the identification of regularities of influence of regional agroclimatic factors on soil microbiota as an indicator of soil health under different types of land use is of great relevance. In this paper, we tried to determine the climatic factors limiting the activity of soil microbiome functioning on the basis of calculation of climatic indices in two regions of grape cultivation close in temperature regime, but contrasting in humidity, located in the Republic of Crimea and the Republic of Serbia.

Decoupling Analysis of Urban Growth and Carbon Emissions in Wuhan, 2000-2020

The analysis of the coupling relationship between urban growth and carbon emissions and its synergistic change rule is of great significance to the sustainable development of cities. The BCI index method is used to extract the scope of built-up areas of Wuhan from 2000 to 2020, and the relationship between urban growth and carbon emissions is analyzed based on the Tapio decoupling model. The results show that: (i) The built-up areas of Wuhan City expanded from 2000 to 2020 in all directions with Wuchang, Hankou, and Hanyang as the center, forming a stable monocentric urban spatial structure. The growth of the built-up areas exhibited stage characteristics, including a clear start, acceleration, high-speed growth, and deceleration. (ii) The carbon emissions of Wuhan City from 2000 to 2020 showed an overall growth trend. Three districts, Jiangxia, Huangpi and Hongshan, become high-emission districts, three districts, Caidian, Dongxihu and Xinzhou, become higher-emission districts, and the other seven districts maintain a lower level of carbon emissions; (iii) The carbon emissions and expansion of built-up areas in Wuhan city districts from 2000 to 2020 show obvious spatial and temporal heterogeneity. They present a decoupling of aggregation in the central area and some regression in the periphery, but the overall trend is favorable. The study provides useful references for urban planning and policy making.

The incidence, and spatial trends of cholera in Sabah over 15 years: Repeated outbreaks in coastal areas.

Vibrio cholerae remains a notable public health challenge across Malaysia. Although the Malaysian state of Sabah is considered a cholera-affected area, gaps remain in understanding the epidemiological trends and spatial distribution of outbreaks. Therefore, to determine longitudinal and spatial trends in cholera cases data were obtained from the Sabah State Health Department for all notified cases of cholera between 2005-2020. A cholera outbreak is defined as one or more confirmed cases in a single locality with the evidence of local transmission. All records were geolocated to village level. Satellite-derived data and generalised linearized models were used to assess potential risk factors, including population density, elevation, and distance to the sea. Spatiotemporal clustering of reported cholera cases and zones of increased cholera risk were evaluated using the tau statistic (τ) at 550m, 5km and 10km distances. Over a 15-year period between 2005-2020, 2865 cholera cases were recorded in Sabah, with a mean incidence rate of 5.6 cases per 100,000 (95% CI: 3.4-7.9). From 2015-2020, 705 symptomatic cases and 727 asymptomatic cases were reported. Symptomatic cases primarily occurred in local Malaysian populations (62.6%, 441/705) and in children and adolescents under 15-years old (49.4%, 348/705). On average, cases were reported in areas with low population density (19.45 persons/km2), low elevations (19.45m) and near coastal areas. Spatiotemporal clustering of cholera cases was identified up to 3.5km, with increased village-level cholera risk within 500m and 5 days of initial case presentation to a health facility (Risk Ratio = 9.7, 95% CI: 7.5-12.4). Cholera incidence has high spatial and temporal heterogeneity within Sabah, with some districts experiencing repeated outbreaks. Cholera cases clustered across space and time, with village-level risk of cholera highest within 5 days and within close proximity to primary case villages, suggesting local transmission.

Modeling Lithium Plating Onset on Porous Graphite Electrodes Under Fast Charging with Hierarchical Multiphase Porous Electrode Theory

Lithium plating during fast charging of porous graphite electrodes in lithium-ion batteries accelerates degradation and raises safety concerns. Predicting lithium plating is challenging due to the close redox potentials of lithium reduction and intercalation, obscured by the nonlinear dynamics of electrochemically driven phase separation in hierarchical pore structures. To resolve dynamical resistance of realistic porous graphite electrodes, we introduce a model of porous secondary graphite particles to the multiphase porous electrode theory (MPET), based on electrochemical nonequilibrium thermodynamics and volume averaging. The resulting computational framework of “hierarchical MPET” is validated and tested against experimental data over a wide range of fast charging conditions and capacities. With all parameters estimated from independent sources, the model is able to quantitatively predict the measured cell voltages, and, more importantly, the experimentally determined capacity for lithium plating onset at fast 2C to 6C rates. Spatial and temporal heterogeneities in the lithiation of porous graphite electrodes are revealed and explained theoretically, including key features, such as idle graphite particles and non-uniform plating, which have been observed experimentally.

'I think both of us drew strength from it': qualitative reflections from next of kin following the death and post-mortem brain donation of a loved one with brain cancer.

Glioblastoma, a high-grade primary brain cancer, has a median survival of approximately 14 months. Post-mortem brain donation provides insight to pathogenesis along with spatial and temporal heterogeneity. Post-mortem brain biobanking programs are increasing in number and the need to understand and improve the associated human experience is pressing. This study aims to qualitatively explore the experiences of next of kin (NOK) following the death and brain donation of a loved one and to understand the impact such programs have on NOK carers. We interviewed 29 NOK following the death of their loved one and subsequent brain donation. Thematic analysis was conducted on the transcribed, qualitative interviews. Four themes were identified; (1) Brain donation is a straightforward decision grounded in altruism and pragmatism; (2) Supporting donors is a source of comfort, pride and empowerment; (3) Brain donation can provide meaning for suffering and tragedy and (4) Perceptions of procedures and processes when supporting a loved one to donate. Insights into areas for improvement, for example transporting donors following a home death and the role of the body bag were also noted. Supporting a loved one to donate their brain can be a positive experience providing a source of hope, empowerment and purpose for NOK. Data indicating areas for consideration are broadly relevant for improving the delivery of brain donation programs for future donors and their loved ones.

Rapid change in plankton community structure during spring along the eastern Beagle Channel

In November 2019, a first joint Chilean–Argentinian research cruise was conducted along the eastern section of the Beagle Channel (BC). Here we present the results of the microbial plankton (2–200 μm cell size) abundance and composition analyses in relation to water masses and environmental variables, along a longitudinal transect characterized by contrasting hydrology. Plankton samples were analyzed within the photic zone along the channel and at two fixed stations during two short time series (a first one of 30 and a second one of 42 h). Results revealed a spatial zonation in the composition and structure of the plankton assemblages, related to bathymetry, water temperature and nutrient availability but also, a small-scale temporal variability due mainly to a rise in air and water temperature. The inner (westernmost) and outer sectors of the sampled area, west and east of Mackinlay Strait, respectively, were characterized by low plankton abundances, mostly dominated by nanoflagellates and some large diatoms. In contrast, the easternmost sector of BC, showed the highest total cell abundances, displaying a high diversity of small and large diatoms. Notably, in the inner BC (fixed station F1), chlorophyll-a (chl-a) concentrations almost doubled in 24 h, along with an increase in total plankton abundance and the dominance of small diatoms and nanoflagellates. Rapid changes in plankton relative abundance were also observed east to Mackinlay Strait. This highlights the large spatial (km) and temporal (hours to days) plankton heterogeneity along the eastern section of the BC, scales which should be considered for further sampling strategies.

Assessment of pathological grade and variants of bladder cancer with a continuous-time random-walk diffusion model.

To evaluate the efficacy of high b-value diffusion-weighted imaging (DWI) with a continuous-time random-walk (CTRW) diffusion model in determining the pathological grade and variant histology (VH) of bladder cancer (BCa). A total of 81 patients (median age, 70 years; range, 35-92 years; 18 females; 66 high grades; 30 with VH) with pathologically confirmed bladder urothelial carcinoma were retrospectively enrolled and underwent bladder MRI on a 3.0T MRI scanner. Multi-b-value DWI was performed using 11 b-values. Three CTRW model parameters were obtained: an anomalous diffusion coefficient (D) and two parameters reflecting temporal (α) and spatial (β) diffusion heterogeneity. The apparent diffusion coefficient (ADC) was calculated using b0 and b800. D, α, β, and ADC were statistically compared between high- and low-grade BCa, and between pure urothelial cancer (pUC) and VH. Comparisons were made using the Mann-Whitney U test between different pathological states. Receiver operating characteristic curve analysis was used to assess performance in differentiating the pathological states of BCa. ADC, D, and α were significantly lower in high-grade BCa compared to low-grade, and in VH compared to pUC (p < 0.001), while β showed no significant differences (p > 0.05). The combination of D and α yielded the best performance for determining BCa grade and VH (area under the curves = 0.913, 0.811), significantly outperforming ADC (area under the curves = 0.823, 0.761). The CTRW model effectively discriminated pathological grades and variants in BCa, highlighting its potential as a noninvasive diagnostic tool.

Identifying urban, transportation, and socioeconomic characteristics across US zip codes affecting CO2 emissions: A decision tree analysis

Understanding the factors contributing to CO2 emissions is pivotal for informed policy-making and sustainable urban development. This study probes the interconnections between urban attributes, transportation patterns, and socioeconomic factors concerning CO2 emissions using Decision Tree analysis across a substantial dataset of US zip codes. The dataset was carefully prepared to ensure accuracy and relevance, considering temporal, geographical, and socioeconomic heterogeneity. The Decision Tree algorithm was applied iteratively to evaluate variable interactions and identify critical thresholds that influence carbon emissions. The findings of this study shed light on the key drivers of CO2 emissions across US zip codes. The analysis reveals significant variations in the relative importance of different factors in different regions, emphasizing the need for localized and tailored strategies to address carbon reduction targets effectively. The research provides a more holistic understanding that can drive effective urban planning and energy policies, ultimately contributing to the global effort to reduce carbon emissions and combat climate change. The findings from this research underscore the importance of multidisciplinary approaches in addressing environmental challenges and highlight the necessity for continuous innovation in analytical methodologies to keep pace with the evolving urban landscapes.

Immunotherapy guided precision medicine in solid tumors.

Cancer is no longer recognized as a single disease but a collection of diseases each with its defining characteristics and behavior. Even within the same cancer type, there can be substantial heterogeneity at the molecular level. Cancer cells often accumulate various genetic mutations and epigenetic alterations over time, leading to a coexistence of distinct subpopulations of cells within the tumor. This tumor heterogeneity arises not only due to clonal outgrowth of cells with genetic mutations, but also due to interactions of tumor cells with the tumor microenvironment (TME). The latter is a dynamic ecosystem that includes cancer cells, immune cells, fibroblasts, endothelial cells, stromal cells, blood vessels, and extracellular matrix components, tumor-associated macrophages and secreted molecules. The complex interplay between tumor heterogeneity and the TME makes it difficult to develop one-size-fits-all treatments and is often the cause of therapeutic failure and resistance in solid cancers. Technological advances in the post-genomic era have given us cues regarding spatial and temporal tumor heterogeneity. Armed with this knowledge, oncologists are trying to target the unique genomic, epigenetic, and molecular landscape in the tumor cell that causes its oncogenic transformation in a particular patient. This has ushered in the era of personalized precision medicine (PPM). Immunotherapy, on the other hand, involves leveraging the body's immune system to recognize and attack cancer cells and spare healthy cells from the damage induced by radiation and chemotherapy. Combining PPM and immunotherapy represents a paradigm shift in cancer treatment and has emerged as a promising treatment modality for several solid cancers. In this chapter, we summarise major types of cancer immunotherapy and discuss how they are being used for precision medicine in different solid tumors.

A method for robust estimation of snow seasonality metrics from Landsat and Sentinel-2 time series data over Atlas Mountains scale using Google Earth Engine

Seasonal snow cover provides the majority of freshwater supplies for human society and natural ecosystems especially in semi-arid regions. For water resource managers, precise data regarding the spatiotemporal variability of snow cover and snow phenology is of paramount importance. Owing to the great spatial and temporal heterogeneity of the snowpack and the inaccessibility of high mountainous areas, gapless satellite remote sensing presents an unprecedented opportunity to monitor snow cover effectively and affordably on a fine scale, from different aspects, and with regular revisit time. This study derives the snow seasonality metrics (first day of snowfall, last day of snow melt; and snow cover duration) over a large semi-arid region in Morocco’s Atlas Mountains. We calculate these metrics by combining over 10,000 images from Landsat 8 and Sentinel 2 satellites for four hydrological years (2016–2021) to create a harmonized product with a time interval of about 3 days using the Google Earth Engine (GEE) platform. This dense and large time series facilitates a gap-filling method to minimize and overcome the effect of cloud cover, and its assessment shows a positive correlation between the masked pixels and the interpolated ones. These methods allowed us to realize a map of the snow cover area and extract a homogeneous Normalized Difference Snow Index (NDSI) profile over the four years whereby we were able to determine the optimal threshold to separate the presence of snow from its absence. The results showed that derived snow cover metrics provide considerable variation in both time and space, where an increase in snowpack measurement values at higher elevations can be noted. Overall, the snow duration ranges between November and April depending on the characteristics of each hydrological year. The retrieved Landsat 8 and Sentinel 2 snow dates had a high level of agreement with in-situ data observations with almost a day-and-a-half delay with an overall accuracy equal to 0.96. The analysis of snow cover dynamics via GEE has offered the ability to calculate the first day of snowfall, last day of snowmelt, and snow cover duration annually at a pixel level, providing the user with the ability to track the seasonal and interannual variability in the timing of snowmelt toward a better understanding of how the hydrological cycles of higher latitude and mountainous regions are responding to climate change.

Unravelling spatial and temporal heterogeneity associated with the blood-brain barrier in glioblastoma multiforme

Unravelling spatial and temporal heterogeneity associated with the blood-brain barrier in glioblastoma multiforme

Microfluidics-based patient-derived disease detection tool for deep learning-assisted precision medicine.

Cancer spatial and temporal heterogeneity fuels resistance to therapies. To realize the routine assessment of cancer prognosis and treatment, we demonstrate the development of an Intelligent Disease Detection Tool (IDDT), a microfluidic-based tumor model integrated with deep learning-assisted algorithmic analysis. IDDT was clinically validated with liquid blood biopsy samples (n = 71) from patients with various types of cancers (e.g., breast, gastric, and lung cancer) and healthy donors, requiring low sample volume (∼200 μl) and a high-throughput 3D tumor culturing system (∼300 tumor clusters). To support automated algorithmic analysis, intelligent decision-making, and precise segmentation, we designed and developed an integrative deep neural network, which includes Mask Region-Based Convolutional Neural Network (Mask R-CNN), vision transformer, and Segment Anything Model (SAM). Our approach significantly reduces the manual labeling time by up to 90% with a high mean Intersection Over Union (mIoU) of 0.902 and immediate results (<2 s per image) for clinical cohort classification. The IDDT can accurately stratify healthy donors (n = 12) and cancer patients (n = 55) within their respective treatment cycle and cancer stage, resulting in high precision (∼99.3%) and high sensitivity (∼98%). We envision that our patient-centric IDDT provides an intelligent, label-free, and cost-effective approach to help clinicians make precise medical decisions and tailor treatment strategies for each patient.

Electromagnetic danger of electric and hybrid vehicles

Problem statement. In electric and hybrid transport, passengers sit very close to the electrical system of considerable power, usually for a considerable time. People are concerned about the level of frequency, intensity of electromagnetic radiation, and the time spent in transport. The relatively high currents achieved in these systems and the short distances between power devices and passengers mean that the latter can be exposed to the corresponding magnetic fields. This means that there is a need to assess the electromagnetic environment inside these vehicles before they are put on the market. When designing electric and hybrid vehicles and their components, it is necessary to take into account the hazards of magnetic field exposure to drivers, passengers and the environment. The aim is to study the effect of electromagnetic radiation on people and improve the efficiency of vehicle operation by assessing the electromagnetic safety of electric and hybrid vehicles at the stage of their operation, as well as to improve methods for assessing electromagnetic radiation depending on operating conditions. Methodology. Methods are a systematic approach to research, protection against electromagnetic radiation in transport, conducting measurements of electromagnetic radiation in electric and hybrid transport, finding out the spatially strong inhomogeneity of the magnetic field and building 3D topology using numerous uniformly distributed magnetic field sensors in the vehicle interior, i.e. by a differential phase-gradient method for the study of ultra-low frequency amplifiers from 0.001 - 100 Hz of geomagnetic variations, a method of testing magnetic fields. This method allows using three three-component magnetic sensors arranged in a triangle at a short distance from each other (magnetic gradiometer) to construct a vector of gradients and phase velocities of magnetic variations for any of the three components of magnetic fields. As a result, the phase-gradient method has found its application for measuring magnetic fields in electric and hybrid vehicles, as well as for detecting the topology of magnetic fields, taking into account their extreme spatial heterogeneity, the sensors in the cabin should be located quite densely, i.e., the number of sensors should be at least 10-20 (evenly at a distance of ten centimeters at floor level, at head level of drivers and passengers, etc.). Scientific novelty: the study of electrical equipment in electric and hybrid transport has shown that the source of electromagnetic fields, which have a strong temporal and spatial heterogeneity in the frequency range from 0 to hundreds of megahertz, that they are a superposition of fields from many sources (from electric motors, traction batteries, live elements, various electrical equipment (starting and braking resistance, group switches, rheostat units, electrical circuits for ventilation, lighting, heating, etc.). Practical relevance. The problems of determining the moment of occurrence of electromagnetic hazards in electric and hybrid vehicles are considered. It is established that electronic devices on board are usually higher in frequency than magnetic fields, which is associated with changes in traffic modes. Safety measures against electromagnetic radiation in electric and hybrid modes of transport are presented.

Feature Engineering and Supervised Machine Learning to Forecast Biogas Production during Municipal Anaerobic Co-Digestion.

Municipalities with excess anaerobic digestion capacity accept offsite wastes for co-digestion to meet sustainability goals and create more biogas. Despite the benefits inherent to co-digestion, the temporal and compositional heterogeneity of external waste streams creates operational challenges that lead to upsets or conservative co-digestion. Given the complex microbial bioprocesses occurring during anaerobic digestion, prediction and modeling of the outcomes can be challenging, and machine learning has the potential to improve understanding and control of co-digestion processes. Biogas flows are a surrogate for process health, and here, we predicted biogas production from historical data collected by a water resource recovery facility (WRRF) during normal operation. We tested a daily lab and operational data set (n = 1089 after cleaning) and a minute-by-minute supervisory control and data acquisition (SCADA) operational data set (n = 491,761 after cleaning) to determine if forecasting biogas flow for a 24 h time horizon is feasible without collecting additional data. We found that a multilayer perceptron (MLP) neural network model outperformed tree-based and multiple linear regression models. Using a high-resolution SCADA data set for the first time, we showed that MLP neural networks could predict biogas production with an adjusted coefficient of determination (R2) of 0.78 and a mean absolute percentage error of 13.4% on a holdout test set. Adding daily laboratory analyses to the model did not appreciably improve the prediction of biogas flows. Feature engineering was essential to an accurate prediction, and 11 of the 15 most important features in the SCADA model were calculated from raw SCADA outputs. In summary, this paper demonstrates that minute-scale SCADA information collected at a municipal co-digestion facility can forecast biogas production, as a first step toward a digital twin model, without additional data collection.

Temporal and Spatial Changes of Agriculture Green Development in Beijing’s Ecological Conservation Developing Areas from 2006 to 2016

As an irreplaceable ecological barrier, an ecological conservation developing area (ECDA) is vital for the integrated construction of urban and rural areas and the optimization and adjustment of industrial structures. However, few empirical studies have been conducted on the spatiotemporal variations of agricultural green development (AGD) in the ECDAs of large cities. Based on the green agricultural traits of Beijing and the accessible data, we evaluated the AGD and analyzed its spatial and temporal heterogeneity in Beijing’s ECDAs by constructing a framework with 13 indicators. The results stated that energy consumption is a vital factor in green agriculture production and that the agricultural output value per unit of arable land area is the key to green agricultural revenue. From 2006 to 2016, the AGD index of the ECDA had an increasing trend, until 2012 when it followed a decreasing tendency. The AGD index of the northern region was higher than in the southern ECDA. The obstacle degree model was used to verify the AGD limiting factors, where poor infrastructure, slow agritourism, low labor productivity, and low resource use efficiency varied by districts in the ECDA. Given these findings, our study is conducive to AGD evaluation at the district (county) level for the ECDAs of large cities and provides important policy implications.

Сравнительный анализ лимитирующих функционирование почвенного микробиома факторов при культивировании винограда в условиях Южного берега Крыма и Автономного края Воеводина Республики Сербия

Research interest in the use of soil biological activity indicator for predicting the state and sustainability of natural and agroecosystems has increased significantly in recent years due to climatic changes changing the location and boundaries of established agroclimatic belts. Distinctive features of these changes are unprecedented speed, as well as spatial and temporal heterogeneity. In this regard, the identification of regularities of influence of regional agroclimatic factors on soil microbiota as an indicator of soil health under different types of land use is of great relevance. In this work, an attempt was made to determine the climatic factors limiting the activity of soil microbiome functioning on the basis of calculation of climatic indices in two regions of grape cultivation close in temperature regime but contrasting in humidity. The results of the research showed that the value of basal respiration in the soils of ampelocenoses of the Autonomous Province of Vojvodina of the Republic of Serbia was 6-11 times higher than in the soils of ampelocenoses of the South Coast of Crimea, which is probably due to a sharp deficit of moisture in the latter (moisture coefficient 0.39 vs. 1.13 in Vojvodina). Regardless of the geographical location of wineries, basal respiration of soils in organic vineyards was twice as high as in soils of farms practicing the traditional system of grape cultivation, indicating more favorable conditions for the functioning of the soil microbial community. Keywords: BASAL RESPIRATION, BIOCLIMATIC INDICES, VINEYARDS, AMPELOCENOSIS, WINKLER THERMAL INDEX, HUGLIN HELIOTHERMAL INDEX, SELYANINOV HYDROTHERMAL HUMIDIFICATION COEFFICIENT, HUMIDIFICATION COEFFICIENT