Distribution Of Stocks Research Articles

Soil biocrusts affect metabolic response to hydration on dunes in west Queensland, Australia

Soil biocrusts, formed from communities of microbes and their extracellular products are a common feature of dryland soil surfaces. Biocrust organisms are only intermittently metabolically active, but due to their ubiquity they make a significant contribution to the carbon cycle. Quantification of the controls and insights into the interlinked process of photosynthesis and respiration are essential to enhancing our understanding of the carbon cycle in the world’s drylands. Yet, there have been relatively few field studies investigating controls on both biocrust photosynthesis and respiration. We undertook field-based experiments at two dune sites during the dry season in Diamantina National Park in Queensland, Australia to determine how biocrust hydration and illumination affect soil CO2 flux and photosynthesis. Static chambers and an infra-red gas analyser were used to quantify soil CO2 flux, and a fluorometer and a CFImager were used to determine a range of photosynthetic parameters in the field and laboratory respectively. When dry, biocrust photosynthetic activity was not detected and soil CO2 flux was very low irrespective of biocrust cover. Hydration led to a large and immediate increase in CO2 flux, which was more pronounced in the presence of biocrusts and on the dune with thinner biocrusts. Hydration also initiated the onset of photosynthesis in some biocrusts, which was greatest under low light conditions and sustained with further hydration. There were only infrequent periods of net CO2 uptake to the soil, occurring when CO2 uptake due to photosynthetic activity was less than background soil CO2 flux. Chlorophyll fluorescence imaging indicated biocrust spatial heterogeneity was evident at the cm scale where microtopography creates a myriad of environments for different crust organisms. Our findings demonstrate that biocrusts are highly spatially heterogenetic at both landscape and small scale, which suggests the maintenance of biocrust spatial diversity is likely to be key to imparting resilience to changing climate and disturbance. As well as reaffirming the importance of biocrusts for the carbon cycle in dryland dune soils the study demonstrates that biocrust respiration and photosynthesis respond differently to hydration and shading. This adds an unpredictability to the distribution of soil carbon stocks and the gaseous exchanges of CO2 between the surface and atmosphere. Future changes to precipitation and increased temperatures are likely to reduce soil moisture across much of the Australian interior and consequently biocrusts may experience a decline in biomass, structure, and function which could have significant repercussions beyond carbon stocks.

Spatial 3D mapping of forest soil carbon stocks in Hesse, Germany

AbstractBackgroundForest soils are an important reservoir of organic carbon (OC) and a potential source or sink for atmospheric CO2. Prediction of OC stock changes under ongoing climatic and management changes requires a spatial explicit base. Knowledge of the vertical distribution of OC stocks is very important, since varying soil layers may be affected differently by environmental change.AimThree‐dimensional regionalization of OC stocks of the forest floor (FFC) and 5 cm depth increments of the mineral soil (SOC) of Hesse, Germany.MethodsDatasets of the second National Forest Soil Inventory (NFSI II) were used for parametrization of hierarchical generalized additive models (hGAM). Validation was performed by a 10 times repeated 10‐fold cross‐validation, and spatial model uncertainty was assessed.ResultsDepth‐dependent validation indicated that model performance was best between 15 and 60 cm (amount of variance explained ≈ 0.5). All covariates showed plausible partial effects. FFC stocks were predicted to be highest under coniferous forest with a high influence of N deposition. Climate and potential cation exchange capacity affected SOC stocks markedly, whereas soil class and parent material were most important for the depth distribution. Overall, average predicted OC stocks were between 78.0 and 92.5 t ha−1, amounting to 67.6 to 80.1 Mt for all forest soils of Hesse. Between 16% and 24% were stored in the forest floor. Sixty‐eight percent to 69% of predicted SOC stocks were stored in the upper 30 cm. Model uncertainty was highest at locations with high elevation or ground water influence.ConclusionsThis work provides the first spatial explicit database for OC stocks of forest soils in Hesse at an intermediate scale. Stocks can be assessed flexibly for varying depth from the forest floor down to 100 cm. Uncertainty analysis informs about locations, where the model results have to be handled with care.

Effects of Long-Term Enclosing on Vertical Distributions of Soil Physical Properties and Nutrient Stocks in Grassland of Inner Mongolia

Enclosing plays a crucial role in vegetation and soil quality in grassland. The biomass of green plants, litter, and vertical distributions of soil physical properties and nutrient stocks were evaluated at plot enclosed long term for 38 years inside a fence and a long-term grazing plot outside a fence in a semi-arid grassland of Inner Mongolia. The results showed that dry matter of green plants and litter during the 38-year enclosing treatment was higher than in the grazing treatment (p < 0.01). The soil silt (2–50 μm) in the 38-year enclosing treatment was 5.9% higher than in the grazing treatment (p < 0.01) in 0–10 cm soil, and the fine sand (100–250 μm) was 6.0% lower (p < 0.05). The 38-year enclosing treatment slightly decreased the bulk density and significantly decreased the electrical conductivity in each soil layer (0–100 cm). The 38-year enclosing treatment significantly increased the stocks of soil organic carbon (SOC), available phosphorus (AP), and available potassium (AK) on the surface soil, and obviously decreased the stocks of total nitrogen (TN), total phosphorus (TP), calcium (Ca), magnesium (Mg), sulfur (S), and available nitrogen (AN) in each soil layer (0–100 cm). In conclusion, long-term enclosing improved grassland production, but decreased most nutrient stocks in soil.

The Abundance and Distribution of Hatchery and Naturally Produced Chinook Salmon in Columbia River Estuary Nearshore Habitat

AbstractColumbia River hatcheries release millions of juvenile Chinook Salmon Oncorhynchus tshawytscha to support fisheries and mitigate for historical productivity declines from dam construction and upriver habitat losses. Recent federal biological opinions for Federal Columbia River Power System operations also have mandated restoration of estuarine rearing habitats to mitigate for mortality of naturally produced (NP) salmon at main‐stem dams. We compared genetic stock compositions, distributions, abundances, and length frequencies of hatchery‐marked and unmarked Chinook Salmon to evaluate the extent of hatchery influence on nearshore estuarine habitat use and the potential for interactions between hatchery‐origin (HO) and NP salmon. Cumulative Chinook Salmon releases from all hatcheries in 2010 and 2011 dictated estuarine stock composition, abundance, and life histories during the spring–summer migration peak. Naturally produced salmon from the lower Columbia River populations, including many fry migrants, were most abundant, but larger HO juveniles also frequented nearshore sites, where their total biomass often equaled or exceeded that of NP fish. Large releases of a single stock of origin (Spring Creek Group fall run) in April and May created sharp pulses in the estuary entry timing of fingerling‐sized salmon and dominated abundance and stock composition at some sites. Successive releases from scores of hatcheries during spring and early summer ensured a consistent presence of HO salmon near shore, regardless of the habitat‐specific residence times of individual fish. Overall, the historical replacement of diverse wild populations with fewer hatchery stocks of a narrow size range and migration timing has intensified nearshore habitat use during the spring–summer migration peak and reduced life history variation of Columbia River Chinook Salmon. Such changes could undermine the fish conservation goals of both hatchery mitigation and estuary restoration programs.

A two-layer modelling framework for predicting passenger flow on trains: A case study of London underground trains

A model that anticipates the passenger flow on trains will help passengers to avoid overcrowded trains in their journey planning. Such a model will also help rail industry to understand the current use of train capacity and plan the distribution of rolling stock, personnel and facilities. However, the existing studies only developed the models for forecasting the passenger flow in stations, which cannot reflect the true passenger number on trains. In this paper, a hierarchical modelling framework for passenger flow prediction is proposed. It includes two layers of fuzzy models, where a global model is used to predict for ordinary circumstances and a number of local models are used to predict the variations in passenger number due to specific factors, such as events and weather. A new data sifting method is proposed to obtain the most informative and representative data for model training, which greatly improves the modelling efficiency. The proposed method is then validated using a case study of forecasting the passenger flow of London Underground trains.

Stock Size Assessment, Distribution and Biology of the Surf Clam Mactra stultorum (Mollusca: Bivalvia) Along the Sfax Coasts (Tunisia, Mediterranean Sea)

Stock Size Assessment, Distribution and Biology of the Surf Clam Mactra stultorum (Mollusca: Bivalvia) Along the Sfax Coasts (Tunisia, Mediterranean Sea)

Mapping the stock and spatial distribution of aboveground woody biomass in the native vegetation of the Brazilian Cerrado biome

The Brazilian Cerrado biome consists of a highly heterogeneous tropical savanna, and is one of the world’s biodiversity hotspots. High rates of deforestation, however, place it as the second-largest source of carbon emissions in Brazil. Due to its heterogeneity, biomass and carbon stocks in the Cerrado vegetation are highly variable, and mapping and monitoring these stocks are not a trivial effort. To address this challenge, we built an aboveground woody biomass (AGWB) model for the Cerrado biome using 30-m resolution optical satellite imagery (Landsat-5 and Landsat-8), 25-m resolution SAR imagery (ALOS and ALOS-2), and a set of plot-based and LiDAR-derived AGWB estimates (n = 1858) from a wide network of researchers in Brazil. We implemented both a Classification and Regression Tree (CART) and a Random Forest (RF) algorithm to model AGWB over the native vegetation in the year 2019 (as classified by MapBiomas) in the Cerrado. The RF algorithms resulted in a slightly better result (R2 = 53%; rel. RMSE = 57%) than the CART model (R2 = 45%; rel. RMSE = 63%), but our map shows an underestimation of very high AGWB (negative bias over 200 t ha−1) and a slight overestimation of low AGWB (positive bias), especially in the RF model (bias of 1.19 t ha−1 against 0.86 t ha−1 for the CART model). We believe we have contributed to knowledge on the woody biomass stocks in the biome, especially in the predominant savanna woodlands, which is where the highest current rates of conversion take place in the Cerrado.

The assessment and management of data limited fisheries: Future directions

Most fisheries in the world do not collect the relatively rich data streams necessary for formal stock assessment. Expanding and improving the current suite of data limited stock evaluation methods will be critical for ensuring that more of the world’s fisheries are managed on the basis of scientific stock status evaluations. Here I offer perspectives on three emerging ways to help achieve this goal: (1) making use of data streams that are not usually used for stock evaluation; (2) extracting more information relevant to fisheries management from stock evaluations by scaling the use of adaptive management frameworks; and (3) using human-centered design processes to deploy appropriate technologies to dramatically increase the amount of data that even resource-limited fisheries can collect, analyze, and apply to management. Because climate change is already altering fish stock distribution and abundance patterns and these changes will likely become more profound over time, I also offer a perspective on the need for data limited approaches for anticipating these changes in order to facilitate fishery planning and adaptive management.

Carbon Stocks, Species Diversity and Their Spatial Relationships in the Yucatán Peninsula, Mexico

Integrating information about the spatial distribution of carbon stocks and species diversity in tropical forests over large areas is fundamental for climate change mitigation and biodiversity conservation. In this study, spatial models showing the distribution of carbon stocks and the number of species were produced in order to identify areas that maximize carbon storage and biodiversity in the tropical forests of the Yucatan Peninsula, Mexico. We mapped carbon density and species richness of trees using L-band radar backscatter data as well as radar texture metrics, climatic and field data with the random forest regression algorithm. We reduced sources of errors in plot data of the national forest inventory by using correction factors to account for carbon stocks of small trees (<7.5 cm DBH) and for the temporal difference between field data collection and imagery acquisition. We created bivariate maps to assess the spatial relationship between carbon stocks and diversity. Model validation of the regional maps obtained herein using an independent data set of plots resulted in a coefficient of determination (R2) of 0.28 and 0.31 and a relative mean square error of 38.5% and 33.0% for aboveground biomass and species richness, respectively, at pixel level. Estimates of carbon density were influenced mostly by radar backscatter and climatic data, while those of species richness were influenced mostly by radar texture and climatic variables. Correlation between carbon density and species richness was positive in 79.3% of the peninsula, while bivariate maps showed that 39.6% of the area in the peninsula had high carbon stocks and species richness. Our results highlight the importance of combining carbon and diversity maps to identify areas that are critical—both for maintaining carbon stocks and for conserving biodiversity.

Modeling long-term attainable soil organic carbon sequestration across the highlands of Ethiopia

The objectives of this study across the highlands of Ethiopia were: (i) to characterize the association between soil organic carbon (SOC) stocks and biophysical variables and (ii) to model and map attainable SOC sequestration associated with five improved land management practices. The spatial distribution of the SOC stock was studied using a multiple linear regression model driven by eight biophysical predictors. A widely used SOC model (RothC) was then used to model changes in SOC over the next 20–50 years of improved land management. Simulations were driven by the derived SOC stocks, pH and clay contents that are available in the ISRIC soils database at 250 m resolution and climate data from the “Enhancing National Climate Services Initiative” database. Organic carbon inputs to the model were estimated from the “Improved Crop Varieties Yield Register” of the Ministry of Agriculture and Livestock Resource and the Central Statistics Authority. After 50 years of conservation tillage with 80% of available manure applied to cultivated land, the total SOC stock increased by 169,182,174 t, which is 2.8 times higher than the stock increase with only 50% of available manure applied. Introduction of improved pasture species and measures to control soil erosion was an important source of net carbon sequestration in grasslands. Afforestation and reforestation of degraded landscapes and protection of natural ecosystems further increased soil carbon. This highlights the importance of improved land management practices to SOC sequestration, which in turn could enhance agricultural productivity, food security and sustainable development.

Impact of River fluvial processes on arsenic enrichment in Mid Gangetic Plains: The coining of arsenic confirming pollution markers

The present study traces the geochemical occurrence of arsenic and heavy metals along the active oxbow formations of river Ganga in MGP. A total of 31 groundwater samples were collected, specifically in close proximity to the river profile section, to understand the high spatial enrichment pattern of arsenic. The bivariate plots reveal strong influence of silicate weathering and anthropogenic leaching of fertilizers occurring concurrently with pyrite oxidation, leading to high arsenic vulnerability. The bicarbonate enrichment plays a major role in the replacement of adsorbed arsenic while most of the carbonate minerals remain in a state of oversaturation, causing their ultimate precipitation. The steep changes in river directional profile as evident through the high bulk density of the soil (1587 kg/m3) near the oxbow formations of the river has caused high sediment deposition which is coherent with the spatial distribution of soil organic carbon stock (8–33 tons/hectare). Further, high concentration of arsenic (~100 ppb) traces the high availability of the clay content (18–40 %) and moderate iron concentration of the soil confirming the role of river led recharge in promoting oxidizing conditions. Low cation exchange capacity (9–52 mmol. c.kg−1), indicative of illite as the dominant clay mineral, further supports our concern for groundwater vulnerability in terms of enhanced cation retention in the soil. Our study is a pioneering work in understanding arsenic spatial vulnerability under fluvial forcing through developing indicators which trace the arsenic mobilizing chemistry in a more coherent and direct ways.

Accounting for soil architecture and microbial dynamics in microscale models: Current practices in soil science and the path ahead

AbstractMacroscopic models of soil organic matter (SOM) turnover have faced difficulties in reproducing SOM dynamics or in predicting the spatial distribution of carbon stocks. These models are based on a largely inadequate linear response of soil microorganisms to bulk concentrations of nutrients and it is clear that a new approach to SOM modelling is required. Introducing explicit microbial activity and organic matter (OM) reactivity in macroscopic models represents a challenge because of the fine spatial scales at which the processes occur. To get a better grasp on interactions that take place at the microscale, a new generation of SOM models have been developed at the spatial scale of the soil microenvironments where microorganisms evolve. These models are well adapted to challenge traditional hypotheses about the influence of soil architecture on soil microbial activity. Soil architecture provides the stage for a dynamic spatial accessibility of resources to microbes and the emergence of interactions between the actors in SOM decomposition. In this context, we review microscale models of microbial activity that have been designed for soils and soil analogues. To understand how these models account for spatial accessibility, we look in detail at how soil microenvironments are described in the different approaches and how microbial colonies are spatialized in these microenvironments. We present the advantages and disadvantages of the developed strategies and we discuss their limits.HighlightsWe review the state of the art in the development of microscale models of soil microbial processes.Microscale models have integrated the tremendous progress in knowledge of OM cycling in soils.We categorize modelling approaches by how they deal with complexity of soil architecture.Modelling benchmarks are required to properly balance complexity and data uncertainty.

Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data

Abstract. The status of the soil organic carbon (SOC) stock at any position in the landscape is subject to a complex interplay of soil state factors operating at different scales and regulating multiple processes resulting either in soils acting as a net sink or net source of carbon. Forest landscapes are characterized by high spatial variability, and key drivers of SOC stock might be specific for sub-areas compared to those influencing the whole landscape. Consequently, separately calibrating models for sub-areas (local models) that collectively cover a target area can result in different prediction accuracy and SOC stock drivers compared to a single model (global model) that covers the whole area. The goal of this study was therefore to (1) assess how global and local models differ in predicting the humus layer, mineral soil, and total SOC stock in Swedish forests and (2) identify the key factors for SOC stock prediction and their scale of influence. We used the Swedish National Forest Soil Inventory (NFSI) database and a digital soil mapping approach to evaluate the prediction performance using random forest models calibrated locally for the northern, central, and southern Sweden (local models) and for the whole of Sweden (global model). Models were built by considering (1) only site characteristics which are recorded on the plot during the NFSI, (2) the group of covariates (remote sensing, historical land use data, etc.) and (3) both site characteristics and group of covariates consisting mostly of remote sensing data. Local models were generally more effective for predicting SOC stock after testing on independent validation data. Using the group of covariates together with NFSI data indicated that such covariates have limited predictive strength but that site-specific covariates from the NFSI showed better explanatory strength for SOC stocks. The most important covariates that influence the humus layer, mineral soil (0–50 cm), and total SOC stock were related to the site-characteristic covariates and include the soil moisture class, vegetation type, soil type, and soil texture. This study showed that local calibration has the potential to improve prediction accuracy, which will vary depending on the type of available covariates.

The early marine distribution of Atlantic salmon in the North‐east Atlantic: A genetically informed stock‐specific synthesis

AbstractThe survival of Atlantic salmon (Salmo salar), an increasingly rare anadromous species, has declined dramatically during its marine phase, with disproportionate impacts on the poorly understood early post‐smolt period. Logistical constraints on collecting oceanic data to inform this issue pose a formidable obstacle. To advance understanding of post‐smolt distributional ecology in the North‐east Atlantic, a comprehensive analysis of existing information was undertaken. Data were synthesized from 385 marine cruises, 10,202 individual trawls, and 9,269 captured post‐smolts, spanning three decades and ~4.75 million km2 of ocean, with 3,423 individuals genetically assigned to regional phylogeographic origin. The findings confirm major migrational post‐smolt aggregations on the continental shelf‐edge off Ireland, Scotland and Norway, and an important marine foraging area in the Norwegian Sea. Genetic analysis shows that aggregational stock composition does not simply reflect distance to natal rivers, with northern phylogeographic stock groups significantly under‐represented in sampled high‐seas aggregations. It identifies a key foraging habitat for southern European post‐smolts located in international waters immediately west of the Vøring Plateau escarpment, potentially exposing them to a high by‐catch mortality from extra‐territorial pelagic fisheries. Evidence of the differential distribution of regional stocks points to fundamental differences in their migration behaviours and may lead to inter‐stock variation in responses to environmental change and marine survival. The study shows that understanding of post‐smolt marine ecology, as regards to stock‐specific variations in habitat utilization, biological performance and exposure to mortality factors, can be significantly advanced by data integration across studies and exploiting genetic approaches.

Variance gamma for stock model performance with excess kurtosis

The Geometric Brownian Motion (GBM) model is used widely for model the dynamic of asset price movement. One of the company’s assets is a stock. The distribution of stock data that is normally distributed can be modeled using the Geometric Brownian Motion model. However, the distribution of stock data showed excess kurtosis and tail when using the Brown Geometry Motion model was less precise. One model for data showing excess kurtosis and tail was Variance Gamma (VG). In this research, the sample used was the stock data of PT Bank Danamon Indonesia Tbk for the period April 25 th , 2018 to April 24 th , 2020. The data sample was divided into two parts, namely training data and testing data. Based on the result of the stock description statistics, the value of skewness = -2.105417 and kurtosis = 22.16438 was obtained, while hypothesis testing concluded that the stock distribution did not spread normally. The resulting parameters for the VG model were σ = 0.08071, v = 8.00500 and θ = 0.01976. Based on the results of testing on the last 38 observations, the MAPE value was = 6.97560%. These results gave the conclusion that the VG model provided excellent forecasting results.

Ensuring the chatter stability of milling by optimizing the workpiece stock

The paper considers a new technique for increasing the dynamic stability of the dynamics of milling flexible parts. The technique is based on the formation of a uniform stock of the workpiece for the finish milling. The paper proposes an optimization algorithm for the automated calculation of the stock distribution based on the sensitivity analysis method. The ratio of the natural frequencies of the flexible workpiece is used as the objective function of the optimization algorithm. The developed technique was tested on a numerical example.

On the spatial variability and influencing factors of soil organic carbon and total nitrogen stocks in a desert oasis ecotone of northwestern China

Accurate assessments of soil organic carbon (SOC) and total nitrogen (TN) stocks and controlling factors are essential for understanding carbon and nitrogen sequestration in soil. In this study, we analyzed the spatial distribution and influencing factors of SOC and TN stocks to the depth of 3 m in a desert oasis ecotone of northwestern China. The study area has experienced large-scale transition of dunelands to irrigated croplands in the past 40–50 years. The results showed that the vertical distributions of SOC and TN stocks were well demonstrated by quadratic function forms. The SOC and TN stocks at 0–3 m depths in nabkha dunes were generally significantly higher than that in bare sand dunes. Additionally, after converting nabkha dunes to croplands, both SOC and TN stocks at the top 0.4 m depths increased with the extension of cultivation years, the mean SOC and TN stocks significantly increased from 0.396 to 0.992 kg·m−2 and from 0.053 to 0.096 kg·m−2, respectively. The strongest heterogeneity of SOC and TN generally appeared at top 0–0.4 m depths and decreased with the depth. The SOC and TN stocks in the nabkha dunes near the water areas were relatively higher, which may be suitable for croplands reclamation. It is noteworthy that land use brought a major influence of SOC and TN at top 0–0.4 m depths, whereas soil texture (clay and silt contents) was the main factor that controlled SOC and TN at deep soil depths (1–3 m). The results indicate that the nabkha dunes also increased carbon and nitrogen stocks throughout the entire 3 m soil profiles. While the demand for food is almost certain to increase in arid and semiarid China and other regions worldwide, the conversion from non-traditional croplands such as dunelands to croplands is likely going to continue.

The interaction of land-use history and tree species diversity in driving variation in the aboveground biomass of urban versus non-urban tropical forests

Understanding the drivers of aboveground biomass (AGB) variation in present-day tropical forests can contribute to management strategies that help mitigate against CO2-driven climate change and provide other services related to high AGB. Higher tree diversity can lead to higher woody productivity and carbon storage, but how diversity interacts with land-use history is less certain. We assessed variation in AGB across forests with different land-use histories and surrounding landscapes in southeastern Brazil and how AGB relates to tree diversity per se, while controlling for important factors such as mean functional trait values, stem density and soil fertility. Our findings indicate that aboveground biomass of forests is dependent on land-use history and the landscape matrix in which they occur (urban or non-urban). We found that tree diversity, measured as the average evolutionary divergence among close relatives, shows a strong positive relationship to AGB, but only in old-growth, non-urban forests. This suggests that higher niche complementarity leads to higher AGB in certain ecological contexts. Forests in an urban matrix, and those that regenerated from cropland (in an urban or non-urban matrix), showed weak or insignificant relationships between AGB and diversity, and forests that regenerated from completely denuded landscapes, including soil removal, actually showed a negative relationship between diversity and AGB. Meanwhile, across all forest classes, the abundance-weighted mean wood density of tree species present showed a consistent positive correlation with AGB, indicating the ubiquity of mass-ratio effects on AGB. Overall, our study suggests that strategies for conservation and restoration should account for past land-use and the matrix where forests are inserted, as the distribution of carbon stocks and biodiversity may need to be considered separately.

Inventory control and distribution of medicine stocks by using a just in time method based on interactive web applications

Management of an inventory data within an agency requires an interactive management system to provide ease and informative data presentation. Data processing using an interactive system makes it easy for users to understand and interact with data, especially if the agency concerned is an agency that is in charge of long-term data storage, complex data processing, data collection and data distribution processes, controlling inventory availability, and data collection conducted every day. Data storage and conventional data processing has several weaknesses such as high error rate in data processing, the system is not interactive so that it troubles and impedes the inventory data collection process by users, and can produce data ambiguity that can cause misinformation. By using the inventory control model Just-In-Time (JIT) Inventory method that allows the compilation of data collection and inventory stock requests as needed so that it can easily distribute and minimize wasted stock, the processing, storage, and data collection of a particular data inventory can be controlled well and can provide clearer information. As a result, implementing inventory control methods into a web application can provide web applications that have better functionality in processing, storing, and collecting data.

CATION EXCHANGE CAPACITY OF THE HUMUS PART OF THE WEST SIBERIAN TRANSECT SOILS

The article analyzes the change in the indicator of the cation exchange capacity (CEC) in the humus of the latitudinal series of soils in Western Siberia. It is shown that not all humus substances are able to perform the function of cation exchange and participate in the formation of the organic part of the soil EC. It is shown that the organic matter in the latitudinal range of soils in Western Siberia is distributed in accordance with the known geographical pattern of the distribution of the total humus stock and the main characteristics of this stock. An unconventional evaluation method for determining the EC is proposed using analytical data on the content of acidic functional groups in humic acids and the composition of humic substances, which allows us to separately assess the contribution of humic and fulvic acids in the composition of the EC of the soil.