Sustainable Management Of Soil Resources Research Articles

Maps of Soil Organic Carbon Sequestration Potential in the Russian Croplands

Adoption of the farming systems that aim to sequester carbon in agricultural soils is one of the ways to mitigate global climate change. This study focuses on the estimation of organic carbon sequestration potential of the Russian croplands in the upper (0–30 cm) soil layer by creating a set of maps using the data from global and national databases as the input data. The maps are generated within the FAO Global Soil Organic Carbon Sequestration Potential Map (GSOCseq) project according to the unified methodology using the RothC model to predict the rate of carbon sequestration in 2020–2040 under a business as usual scenario (BAU), as well as under sustainable soil management scenarios with additional different C input (+5, +10, and +20%) resulting from the use of sustainable soil management (SSM) scenarios. The total potential sequestration rate by the croplands of the Russian Federation in the 0–30-cm layer under a BAU scenario is assessed at 8.5 Mt/year and the estimate under SSM scenarios, up to 25.5 Mt/year. The carbon sequestration by the cropland of each soil ecological zone (except for the light chestnut (Eutric Cambisols (Protocalcic)) and brown semidesert (Luvic Calcisols) soils, where it is around zero) and on a national scale is positive. The Altai krai, Omsk oblast, Novosibirsk oblast, and Krasnoyarsk krai have the greatest potential for sequestration. Several subjects of the Russian Federation—Krasnodar krai, Republic of Crimea, Rostov oblast, Primorskii krai, Republic of Adygea, and Kaliningrad oblast—demand the adoption of sustainable management of soil resources.

High-performance soil class delineation via UMAP coupled with machine learning in Kurdistan Province, Iran

In response to the demand for spatial information on the soil to support the sustainable management of soil resources, this study applies a digital soil mapping approach to predict soil classes for a 7000 ha area, located in Kurdistan province, Iran. Based on a stratified random sampling design, 91 soil profiles were situated, described, and classified into soil great groups. Environmental covariates used for modelling soil classes included terrain derivatives, remote sensing data, distance-based rasters, and legacy geospatial information (e.g., geological map). To address the issue of data multi-collinearity among the predictors, three dimensionality reduction techniques were tested: the principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and the novel Uniform Manifold Approximation and Projection (UMAP). An initial suite of 160 environmental covariates was reduced to 10 for all the methods and used to train a Random Forest (RF) model. The most effective model coupled UMAP with the Random Forest (RF-UMAP) machine-learner, which yielded a kappa index and overall accuracy values of 0.73 and 0.80, respectively. Within Kurdistan, topography and parent material were the main soil-forming factors influencing the prediction of the soil classes. Overall, the use of UMAP outperformed PCA and t-SNE. This study demonstrates the value of using advanced dimension reduction methods to facilitate the handling of non-linear relationships among predictor variables when using RF.

Variation in Certain Soil Properties Based on Land Use Type, and Elevation in Arhavi Sub-Basin, Artvin, Turkiye

Knowledge of soil properties such as texture, bulk density, organic matter, soil reaction, soil electrical conductivity, and soil erodibility factor is fundamental to the sustainable management of soil resources. This study aimed to determine the changes in certain soil properties including texture, bulk density, organic matter, pH, electrical conductivity, and soil erodibility factor with different land uses, elevation zones and soil depths in the Arhavi Sub-basin, Artvin, Turkiye. For these purposes, a total of 618 soil samples (309 disturbed and 309 undisturbed) were taken from 155 sampling points located in areas with different land uses, including tea (33 sampling points), hazelnut (33 sampling points), forest (67 sampling points), and grassland (22 sampling points). The results of the statistical analysis revealed that the soils at depths of 0–15 cm and 15–30 cm showed significant differences according to the land use in terms of sand, clay, silt, bulk density, organic matter, and pH. There were significant positive correlations between elevation and soil bulk density (r = 0.495) at a soil depth of 0–15 cm in the tea areas. In the grassland areas, there were significant positive correlations between elevation and silt, bulk density, and the soil erodibility factor (r = 0.485, r = 0.794, and r = 0.442, respectively) at depths of 0–15 cm, and significant positive correlations between elevation and both silt and bulk density (r = 0.468 and r = 0.691, respectively) at depths of 15–30 cm. Similarly, there were significant positive correlations between elevation and both sand and organic matter at soil depths of 0–15 cm and 15–30 cm (sand: r = 0.351 and r = 0.638, respectively; organic matter: r = 0.277 and r = 0.587, respectively). On the other hand, significant negative correlations were found between elevation and silt, bulk density, pH, and the soil erodibility factor at depths of 0–15 cm and 15–30 cm (silt: r = −0.400 and r = −0.461, respectively; bulk density: r = −0.593 and r = −0.545, respectively; pH: r = −0.354 and r = −0.309, respectively; soil erodibility factor: r = −0.443 and r = −520, respectively). Soil acidity was found to be the most important problem threatening soil fertility in all land uses. The use of soil acidity-increasing fertilizers, such as ammonium sulfate, in tea gardens in the region should be eliminated to protect the fertility of soils in the future. The knowledge that this study provides might help farmers and foresters in the region in the proper management and fertilization of their lands. Moreover, this study will provide data to future studies related to soil acidification, soil erosion, and land use that are planned for the Arhavi Sub-basin.

Digital mapping of selected soil properties using machine learning and geostatistical techniques in Mashhad plain, northeastern Iran

Understanding the spatial variation of soil properties is essential for monitoring land capabilities as well as the sustainable management of soil resources. The aim of this study was to predict digital soil properties mapping using 23 environmental variables, i.e., terrain attributes and remote sensing (RS) indices, across 1500 km2 of Mashhad plain lands. To achieve this purpose, a total of 180 soil samples (0–10 cm) were taken. The random forest (RF) model combined with ordinary kriging (OK), as well as regression kriging (RK), were applied to relate environmental variables and the studied soil properties. The results revealed that RF-OK was the best model with R2 and RMSE for silt (0.89% and 0.10%), followed by calcium carbonate equivalent (0.88% and 3.30%), clay (0.87% and 2.26%), soil organic carbon (0.86% and 0.24%), sand (0.84% and 4.21%), and pH (0.82% and 5.42%). The RS covariates, including band 5 (B5), modified soil-adjusted vegetation index (MSAVI), difference vegetation index (DVI), band 2 (B2), carbonate rock index (CRI2), gypsum index (GI), and enhanced vegetation index (EVI), and terrain attributes, including topographic wetness index (TWI) and elevation (EL), and topographic position index (TPI), were the most important variables in modeling different soil properties. RF-OK showed the prediction and uncertainty maps related to high precision and low standard deviation in most study areas, which indicate low overfitting and overtraining in modeling processes. In general, the RF-OK model, with low cost and high accuracy, can be applicable to use for predicting different soil properties, as well as spatial information acquired from an effort to maps to managing agriculture in areas at different conditions. Finally, this method can be applied to other regions of similar properties and for similar purposes.

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

AbstractUnderstanding the vertical and lateral distribution of soil organic carbon (SOC) and soil organic carbon density (SOCD) is indispensable for soil use and environmental management because of their vital role in soil quality assessments. Primarily, they are needed in calculating soil organic carbon storage (SOCS). The objective of this research was to provide digital maps of SOC and SOCD variation as well as their uncertainties at multiple standardized depths (H1: 0–5, H2: 5–15, H3: 15–30, H4: 30–60 and H5: 60–100 cm) using a parsimonious model with optimized terrain‐related attributes and satellite‐derived data. SOCS were evaluated at soil subgroup levels. An area of about 808 km2 with varying elevation, plant cover and lithology from the Miandoab region, West Azerbaijan Province, Iran was selected as a case study area. A total of 386 soil samples were collected from 104 profiles comprising various soil genetic horizons. A continuous spline function was then fitted to the target properties in advance of creating a dataset at five standard depth intervals (following the GlobalSoilMap project). These were then grouped into three classes including top (H1), middle (H2, H3 and H4) and bottom (H5) depths to ease interpretation. Static and dynamic covariates (30‐m resolution) were derived from a digital elevation model (DEM) and a suite of Landsat‐8 spectral imageries, respectively. Four candidate models including stepwise multiple linear regression (SMLR), random forest (RF), cubist (CU) and extreme gradient boosting (XGBoost) Tree were tested in this study. Finally, the digital maps at 30‐m resolution of SOC and SOCD and their uncertainties were prepared using the best‐fit model and the bootstrapping method, respectively. Four soil subgroups (Gypsic Haploxerepts, Typic Calcixerepts, Typic Haploxerepts and Xeric Haplocalcids) were identified across the study area. The covariates had variable contributions on the evaluated models. The XGBoost Tree model generally outperformed other models for prediction of SOC and SOCD (R2 = 0.60, on average). Regardless of soil subgroups, the uncertainty analysis showed that the SOCD map had a low prediction interval range value indicating high accuracy. Additionally, the highest SOCS and SOCD was observed at the top followed by middle and bottom depths in the study area. All subgroups exhibited a decreasing trend of SOCD with increasing depth. A similar trend was also observed for SOCS. The highest SOCD (on average) was observed in Gypsic Haploxerepts (4.71 kg C/m2) followed by Typic Calcixerepts (4.46 kg C/m2), Typic Haploxerepts (4.45 kg C/m2) and Xeric Haplocalcids (4.40 kg C/m2). Overall, the SOCS normalized by area within soil order boundaries was greater in Inceptisols than Aridisols across the study area. The findings of this study provide critical information for sustainable management of soil resources in the area for agricultural production and environmental health in the Miandoab region of Iran.

Реалії українського чорнозему: сучасний стан, еволюція, охорона та стале управління

Goal. To present the results of research on monitoring, diagnostics, assessment of the current state, and study of directions of agrogenic evolution of chornozems of Ukraine to ensure their rational use and sustainable management. Methods: analysis, synthesis, theoretical generalization, expert, profile-analytical, cartographic. Results. The results of diagnostics and assessment of the current state of Ukrainian chornozems as a reference soil are presented. The characteristics of the agronomic properties of the studied soils according to the main agrophysical, chemical, and physicochemical indicators that determine their quality state are given. It is shown that the high level of agricultural development and plowing of the territory, and intensive unbalanced use of chornozems led to the development of many degradation processes, which requires the application of adapted measures for the preservation and effective use of soils. Currently, the ecological situation has worsened as a result of the armed aggression of the Russian Federation against Ukraine, which led to the destruction of the soil cover and increased manifestations of mechanical, physical, chemical, and biological degradation. A map of the influence of armed aggression on the soil cover of Ukraine is presented. Conclusions. To preserve especially valuable chornozem soils and reproduce their fertility, it is necessary to ensure the implementation of priority tasks on the sustainable management of soil resources at the national level. During the military operations, the Ukrainian chornozem is subjected to a powerful impact and destruction, which requires the use of measures for the preservation and reclamation of soils, and assessment of the damage caused to the land fund. Sustainable, balanced management of chornozem soils should be considered as one of the components for achieving the goals of sustainable development of the country within the framework of the integration of the provisions of the Rio de Janeiro Convention into the national policy.

Strategies for efficient estimation of soil organic content at the local scale based on a national spectral database

AbstractSoil function degradation threatens the sustainable management of soil resources and soil organic matter (SOM) is a vital and important factor. Powerful measuring tools will become very important, especially in areas where data are poor or absent. The archive: China Soil Visible and Near Infrared (vis–NIR) Spectroscopy Library (CSSL) could help providea solution for less costly and fast measuring of SOM. The aim of this article was to compare SOM prediction performance according to three strategies: i) general global partial least squares regression (PLSR) using CSSL with and without spiking samples; ii) memory‐based learning (MBL) using CSSL with and without spiking samples; and iii) general PLSR using only spiking samples to predict soil organic matter in the target area. When using spiked subsets, we also investigated the prediction performance of the extra‐weighted (several copies) subsets. A series of spiking subsets were randomly selected from the total spiking samples, which were selected by conditioned Latin hypercube sampling (cLHS) from the target sites. We calculated only the mean squared Euclidean distance (msd) between the estimates density function (pds) of the principal components (PCs) of vis–NIR spectroscopy from the validation dataset and spiking subsets and statistically inferred the optimal sampling set size to be 30. Our study showed that global PLSR using CSSL spiked with the statistically optimal local samples can achieve higher predicted performance [with a mean root mean square error (RMSE) of 5.75]. MBL spiked with five extra‐weighted optimal spiking samples achieved the best accuracy with an RMSE of 3.98, an R2 of 0.70, a bias of 0.04, and an LCCC of 0.81. The msd is a simple and effective method to determine an adequate spiking set size using only vis–NIR data. These accurate predictions demonstrated the usefulness of statistically representative spiking and MBL for advanced large soil spectral libraries for SOM determination, which is currently lacking at large soil spectral libraries in use.

Amalgamation of Farmers' Bio-priming Knowledge in Integrated Nutrient Management for Sustainable Management of Red Cabbage Soil Under Middle Gangetic Plains, India.

Biotic stress management through bio-priming is a common practice among the farmers of the Indo-Gangetic Plains. However, this indigenous technology is less explored for the sustainable management of soil resources. Therefore, field-based experiments (2016-17 and 2017-18) were conducted in Varanasi to evaluate the combined effect of seedling bio-priming and fertilization on biochemical properties, microbiological properties, and fertility of red cabbage soil at harvest. Based on the farmers' fertilization practice, the recommended dose of fertilizers (RDF) of N:P2O5:K2O were applied @ 120:60:60 kg ha-1. Three compatible bio-agents, viz., Trichoderma harzianum, Pseudomonas fluorescens, and Bacillus subtilis were applied alone and in combination with 75% RDF. The effect of treatment combinations was also analyzed for carbon (C) mineralization by conducting an incubation experiment for 90 days. Bio-priming treatments recorded a higher richness of soil microflora and soil fertility than control and sole application of chemical fertilizers. Application of 75% RDF + T. harzianum + P. fluorescens resulted in highest urease and cellulase activities and soil organic C. Inclusion of dual-species bacterial consortium (P. fluorescens and B. subtilis) in integrated system resulted in highest dehydrogenase activity and available P. These priming agents also exhibited significantly higher CO2 fluxes and C mineralization in our incubation study. A microbial consortium of T. harzianum and B. subtilis increased the microbial biomass C and available K. Although application of triple-species consortium improved C mineralization in laboratory conditions, the positive effects lowered down in field conditions. As a bottom-up approach, customization of bio-priming technology among farmers will help in attaining the UN-Sustainable Development Goals.

Концептуальні положення сталого менеджменту добрив в Україні

The article presents the results of the analysis of the main national and international documents, which are evidence of how the global deterioration of the quality and state of soil resources catalyzed the process of awareness by the international community of the need to develop and implement mechanisms for preserving the productive and ecological functions of the soils of agrocenoses in order to achieve a neutral level of land degradation. One of the main blocks of sustainable management of soil resources is the sustainable management of fertilizers, the use of which significantly increases the productivity of agricultural crops, affects the quality of the soil, but may have certain environmental risks. The purpose of the research is to define conceptual approaches to sustainable fertilizer management that are harmonized with the requirements of the International Fertilizer Code and adapted to the conditions of Ukraine. The research was conducted using general scientific, structural-functional and abstract-logical methods. The analysis of the current national base of regulatory documents regarding the management of soil resources and fertilizers indicates its improvement, including through the ratification and implementation of international regulatory documents. Within the framework of the international integration of the country, a conceptual approach to the sustainable management of fertilizers in Ukraine is proposed, which is aimed at reorienting the vector of actions from "controlling the impact" to "preventing the impact", where the object of action is the soil, and the subject of action is fertilizers. Subjects of ensuring sustainable management of fertilizers - authorities, manufacturers of fertilizers, including from secondary raw materials, scientific institutions of the National Academy of Agrarian Sciences and the State Institution "Soil Protection Institute of Ukraine", higher educational institutions of agronomic and environmental specialties, organizations and associations of various forms of ownership , whose activities concern fertilizers, agrochemical laboratories and farms of various forms of ownership. Sustainable fertilizers management, harmonized with international guidelines, is based on such principles as objectivity, representativeness, regulation, scientificity, systematicity, causality, environmental friendliness, benchmarking and informativeness. Based on the results of the analysis, a set of measures to ensure the sustainable management of fertilizers in Ukraine is proposed, which consists of interconnected and complementary blocks – regulatory, organizational, informational and technological (fertilizer production and application), which have a number of relevant tasks aimed at ensuring a balanced and standardized application of fertilizers in the country's agriculture, preservation of productive and ecological functions of soils, prevention of the development of degradation processes in order to achieve their neutral level, guarantee of food stability and ecological security of the country.

Mapping Permanent Gullies in an Agricultural Area Using Satellite Images: Efficacy of Machine Learning Algorithms

Gullies are responsible for detaching massive volumes of productive soil, dissecting natural landscape and causing damages to infrastructure. Despite existing research, the gravity of the gully erosion problem underscores the urgent need for accurate mapping of gullies, a first but essential step toward sustainable management of soil resources. This study aims to obtain the spatial distribution of gullies through comparing various classifiers: k-dimensional tree K-Nearest Neighbor (k-d tree KNN), Minimum Distance (MD), Maximum Likelihood (ML), and Random Forest (RF). Results indicated that all the classifiers, with the exception of ML, achieved an overall accuracy (OA) of at least 0.85. RF had the highest OA (0.94), although it was outperformed in gully identification by MD (0% commission), but the omission error was 20% (MD). Accordingly, RF was considered as the best algorithm, having 13% error in both adding (commission) and omitting pixels as gullies. Thus, RF ensured a reliable outcome to map the spatial distribution of gullies. RF-derived gully density map reflected the agricultural areas most exposed to gully erosion. Our approach of using satellite imagery has certain limitations, and can be used only in arid or semiarid regions where gullies are not covered by dense vegetation as the vegetation biases the extracted gullies. The approach also provides a solution to the lack of laser scanned data, especially in the context of the study area, providing better accuracy and wider application possibilities.

ҐРУНТОВІ РЕСУРСИ УКРАЇНИ: СТАН, ПРОБЛЕМИ І СТРАТЕГІЯ СТАЛОГО УПРАВЛІННЯ

The purpose of this study is to propose the concept of a strategy for sustainable management of soil resources in Ukraine based on the analysis of the dynamics and current state of soils and their fertility. In this study, we used such main methods: analysis, synthesis, monographic, expert assessments, calculation-and-analytical, abstract-and-logic, cartographic. Despite the intensification of soil degradation (losses of humus and nutrients, especially phosphorus and potassium, erosional losses of the upper fertile layer, physical degradation of soils; acidification of soils, especially in the Polissya and in the Carpathian region; secondary alkalinization and salinization of irrigated soils), there is a reduction in funding for soil protection measures. The area of degraded and infertile soils in Ukraine is over 8 mln ha, and direct annual losses of income only from crop failure due to the main types of soil degradation reach about 33.6 bln UAH in the country as a whole. The novelty of the study is that the provisions on the strategy of sustainable management of soil resources of Ukraine were further developed, in particular, in terms of a holistic macroeconomic approach to the scale of soil degradation and its environmental-and-economic consequences, and a holistic solution through a set of strategic measures of soil fertility reproduction. One of the first attempts to substantiate the strategy of sustainable management of soil resources of Ukraine from the standpoint of an interdisciplinary approach, which provides for: improvement of legislative and regulatory support; improving information and institutional support; effective international cooperation; technological and financial support of sustainable soil management, as well as forecast economic, environmental and social effects of solving the problem of soil degradation. The practical value of the obtained results is that their application should help increase the efficiency and performance of sustainable management of soil resources and achieve land degradation neutrality in Ukraine.

Spatial variability of soil properties under different landuse in Koupendri catchment, Benin

The spatial distribution of soil properties especially saturated hydraulic conductivity (Ksat), Bulk density (BD), soil organic carbon (SOC), total nitrogen (TN) and available phosphorus (Avail.P) is fundamental to sustainable management of soil resources. About 291 surface soil (0-20 cm) samples were collected across three land use types (maize-sorghum (MS), rice field and fallow shrub-grassland (FSG) in Koupendri, north-west Benin using a grid sampling of 25 m x 25 m supplemented with samplings at 5 m x 5 m. Data obtained were subjected to classical and spatial statistics, Pearson’s correlation and analysis of variance using GENSTAT. The soil properties showed normal and non-normal distribution, variation was high (75-126.7 %) for Ksat, moderate (29-45 %) for SOC, C/N and Avail.P, and low (7-15) for BD and TN across the land use. Land use had significant (P < 0.05) effect on all the soil properties evaluated except C/N. The highest values of Ksat (151.6 cm/d), SOC (1.26 %), BD (1.79 g/cm<sup>3</sup>), TN (0.105 %), Avail.P (4.66 ppm) and C/N (12.14) were obtained under the MS cropland whereas porosity was highest (43.7 %) in the rice field. High significant correlation (P < 0.01) was observed among the soil properties irrespective of land use. The correlation length (65-300 m) and nugget effect ratio indicates high variation and strong spatially dependent soil properties. However, TN, BD, Avail.P and C/N were weakly spatially dependent. The variograms were fitted with mostly exponential and spherical models. The interpolation map could help in delineating different management zones and for making good agronomic decisions.

Comparing laboratory and airborne hyperspectral data for the estimation and mapping of topsoil organic carbon: Feature selection coupled with random forest

Rapid monitoring of soil organic carbon (SOC) with fine sampling resolution is vital for further understanding of the global carbon cycle and sustainable management of soil resources. Proximal visible and near-infrared (Vis–NIR) spectroscopy is an effective approach to analyze SOC. However, this technique can only be used for point-to-point monitoring and not for grid pixels evenly spread throughout the area. Airborne hyperspectral imagery with high-spectral- and spatial-resolution provides a promising tool for mapping topsoil SOC at a fine scale, but suffers from the interference of some external factors. Using 45 topsoil samples collected from an agricultural field in the United States, this study aimed to compare the potential of airborne hyperspectral image in estimating and mapping of bare topsoil SOC with that derived from proximal laboratory Vis–NIR spectral data. Random forest (RF) along with two advanced feature selection algorithms, namely, continuous wavelet transform (CWT) and competitive adaptive reweighted sampling (CARS), was applied to optimize the performance of the prediction models. Results showed that laboratory and airborne spectra presented similar spectral shapes and strengths, but laboratory spectral curves were smoother than airborne spectral curves, which were noisier. Laboratory spectra (R2 = 0.79–0.87) performed better than airborne hyperspectral imagery (R2 = 0.49–0.76) in cross-validation, regardless of feature selection algorithms. The CWT-RF models resulted in the highest cross-validation results for laboratory (R2 = 0.87) and airborne (R2 = 0.76) spectra, suggesting their robustness in SOC prediction. The SOC maps retrieved from full-spectrum-RF, CWT-RF, and CARS-RF models all exhibited similar spatial distribution patterns. With airborne hyperspectral imagery serving as a valuable data source at pixel level for digital soil mapping, the methodological framework proposed in this paper could improve the accuracy and reduce the prediction uncertainty of SOC maps by selecting and adopting the optimal subset of spectral variables.

Biostimulant Action of Dissolved Humic Substances From a Conventionally and an Organically Managed Soil on Nitrate Acquisition in Maize Plants.

Conversion of conventional farming (CF) to organic farming (OF) is claimed to allow a sustainable management of soil resources, but information on changes induced on dissolved organic matter (DOM) are scarce. Among DOM components, dissolved humic substances (DHS) were shown to possess stimulatory effects on plant growth. DHS were isolated from CF and OF soil leacheates collected from soil monolith columns: first in November (bare soils) and then in April and June (bare and planted soils). DHS caused an enhancement of nitrate uptake rates in maize roots and modulated several genes involved in nitrogen acquisition. The DHS from OF soil exerted a stronger biostimulant action on the nitrate uptake system, but the first assimilatory step of nitrate was mainly activated by DHS derived from CF soil. To validate the physiological response of plants to DHS exposure, real-time RT-PCR analyses were performed on those genes most involved in nitrate acquisition, such as ZmNRT2.1, ZmNRT2.2, ZmMHA2 (coding for two high-affinity nitrate transporters and a PM H+-proton pump), ZmNADH:NR, ZmNADPH:NR, and ZmNiR (coding for nitrate reductases and nitrite reductase). All tested DHS fractions induced the upregulation of nitrate reductase (NR), and in particular the OF2 DHS stimulated the expression of both tested transcripts encoding for two NR isoforms. Characteristics of DHS varied during the experiment in both OF and CF soils: a decrease of high molecular weight fractions in the OF soil, a general increase in the carboxylic groups content, as well as diverse structural modifications in OF vs. CF soils were observed. These changes were accelerated in planted soils. Similarity of chemical properties of DHS with the more easily obtainable water-soluble humic substance extracted from peat (WEHS) and the correspondence of their biostimulant actions confirm the validity of studies which employ WEHS as an easily available source of DHS to investigate biostimulant actions on agricultural crops.

Mapping soil organic carbon and total nitrogen in croplands of the Corn Belt of Northeast China based on geographically weighted regression kriging model

Understanding the spatial distributions of soil organic carbon (SOC) and total nitrogen (TN) in croplands is necessary for the sustainable management of soil resources. In this study, a geographically weighted regression kriging (GWRK) model was applied to investigate spatial variabilities of SOC and TN in croplands of the Corn Belt of Northeast China (CBNC). Based on this, a map of the ratio of SOC and TN (C:N) was obtained. Results of geostatistical analysis showed that the best-fit variogram models for SOC and TN were spherical and exponential, respectively; the spatial dependence structures of SOC and TN were strong. The variabilities of SOC and TN were explained by GWRK model having a relatively high R2, and low root mean square error (RMSE) and mean absolute error (MAE) indices. These indices showed the potential applications of GWRK model on a large scale when environmental variables are quite different and the global trend is weak. The area under the curve (AUC) –receiver operating characteristic (ROC) curve exhibited that the prediction of SOC has a general performance whereas that of TN exhibited a good performance. Annual mean temperature had the largest impact on the prediction of SOC and TN in the CBNC. Mediated by topographic and climatic variables, remote sensing-derived variables did not play prominent roles as other studies for the explanation of the distributions of SOC and TN. SOC and TN contents reduced from northeast to southeast of the CBNC, and the average predicted contents were 13.22 g kg−1 and 1.28 g kg−1, respectively. The total level of C:N ratio was relatively low, suggesting high rates of decomposition. Our study results indicated that the influence of human activities on croplands of the CBNC should not be ignored. It also recommended that the improvement of agricultural management was an approach to re-configure the spatial distributions of SOC and TN in the CBNC of China.

Policy instruments for soil protection among the EU member states: A comparative analysis

Many factors threaten European Soils, and currently, all the Member States (MS) are introducing many types of soil protection measures. Erosion, pollution, sealing and decline of the organic matter are just some of the threats that affect one of the primary non-removable resources of the planet. Soils play a vital role in the biodiversity and are the provider of numerous Ecosystem Services that support human life on Earth.Following the withdrawal of the Soil Framework Directive proposal by the European Commission, we investigate how the different MS of the European Union (EU) address sustainable soil management under the pressures of different threats.The methodology used is based on a gap analysis applied to the instruments and/or policies adopted by the MS to contrast the various threats according to their specific level of intensity. The study presents for the first time a systematic review of the current EU policies covering all the regulatory instruments, the economic instruments, the information tools, the monitoring systems, and the research and innovation activities.The comparative analysis of the different approaches adopted by MS reveals the absence of a common EU strategy to address soil protection and the inefficacy of the subsidiary principle in the sustainable management of soil resources especially in the view of addressing the Sustainable Development Goals achieving the targets by 2030.Results show how the lack of a Soil Framework Directive has weakened the possibility to have strong coordination among the MS for soil protection. Each Country is adopting an autonomous legislative framework which reveals a huge dis-homogeneity and un-coherences among approaches.

Науково-методичні підходи до сталого управління ґрунтовими ресурсами Степу України в умовах зрошення

Науково-методичні підходи до сталого управління ґрунтовими ресурсами Степу України в умовах зрошення

Sustainable management of soil resources for adaptation to climate change

The questions of sustainable management of soil resources are shown. It is directed to the neutral level of soil degradation and agro-climatic adaptation of agriculture to climate change, promote rational use of resources, conservation and restoration of biodiversity. It is necessary to regulate the load on soils and take into account their ability to self-healing. Unbalanced use leads to a deterioration of the soil quality, water sources, loss of biodiversity, reduced environmental sustainability and ecosystem services which they provide. This question is especially actual with climate changes. Adoption of the three conventions of the United Nations is showing it. Degradation is one of the most important problems in the world. Its causes and unresolved problems of the soil resources management in Ukraine are indicated. In global climate change, the role of adaptive farming systems increases. It contributes to an increase in land productivity and sustainable use. Reducing the soil moisture content reduces mobility and availability of nutrients for plants. It requires the optimization of plant root nutrition through the mineral fertilizers. Measures for adaptation of agriculture should be integrated and cover all possible agricultural practices which can improve the plant growth. It is proposed to grow crops hybrids which resistant to temperature changes and water deficiency, to optimize the fertilizer system (by nitrogen, phosphorus, potash fertilizers, microfertilizers), moisture-saving soil cultivation systems. The use of irrigation and the expansion of irrigated land are essential for maintaining the “climate optimized” agriculture. Key words: adaptation, soil resources, degradation, fertilizers, irrigation, climate.

Research of Soil Resources Degradation Processes in Georgia

Proper exploitation of soil resourses is one of the significant problem of the adverse impact of climate change. Soil formation is a long process, while its degradation develops much faster. Soil degradation means the process of deterioration of soil resources fertility, as a result of both natural and anthropogenic impact. Significant impact on soil resources take place in East and West Georgia. The results of the present study show that the main reasons of soil resources degradation in Georgia are: salinization, erosion processes and natural disasters impact. In the work the following issues are overviewed, namely: i. The climate components regime and their connection with modern ecological processes. In particular, the temperature and precipitation trends and their possible impact on chemical data are researched. The regression relation between global warming intensity and soil chemical data are revealed. ii. In selected degraded soils total amount of easily soluble salts, the main ions composition for the determination of saline soil’s quality, humus and soluble forms of nutrient elements aiming soil fertility definition. iii. The mechanical analysis of the soil referring to research soil physical properties and salt migration in the ground. Natural disasters impact on the soil degradation is considered. Research results defined the territories and types of soils degradation in Georgia. The recommendations to improve the soil fertility are created. The received results could promote the socio-economic development of the districts/ regions in Georgia and introduce considerable material and economic effects, assist the sustainable management of soil resources and alleviation of poverty.

Harmonisation of the soil map of Africa at the continental scale

In the context of major global environmental challenges such as food security, climate change, fresh water scarcity and biodiversity loss, the protection and the sustainable management of soil resources in Africa are of paramount importance. To raise the awareness of the general public, stakeholders, policy makers and the science community to the importance of soil in Africa, the Joint Research Centre of the European Commission has produced the Soil Atlas of Africa. To that end, a new harmonised soil map at the continental scale has been produced. The steps of the construction of the new area-class map are presented, the basic information being derived from the Harmonized World Soil Database (HWSD). We show how the original data were updated and modified according to the World Reference Base for Soil Resources classification system. The corrections concerned boundary issues, areas with no information, soil patterns, river and drainage networks, and dynamic features such as sand dunes, water bodies and coastlines. In comparison to the initial map derived from HWSD, the new map represents a correction of 13% of the soil data for the continent. The map is available for downloading.