Soil Survey Research Articles

A Soil Analysis Approach to Assessing Potential Loss of Productive Lands Under Agricultural Land Conversion

Land provides physical space and is usually required for various sectoral developments needed to meet the needs of increasing population. Land is a finite natural resource; thus, conflict arises over land use and development. The strategic location of the municipality of Pura in Tarlac province, Philippines within the urban beltway of Central Luzon and the recent opening of the Tarlac–Pangasinan–La Union Expressway provide Pura excellent opportunities for urban and industrial development. However, the precursor to this is agricultural land conversion (ALC), which can change or reduce in the area of productive lands. This paper assessed the degree of productivity of the agricultural lands in the study area that are predisposed to ALC using FAO’s land suitability framework and the revised Storie index for soil productivity. Soil survey and composite soil sampling at 20 cm depth in the selected 34 sampling points were done to analyze the relevant soil physical and chemical properties. Five soil mapping units (SMU) were grouped based on the soil surface texture. The results show that the SMUs are only marginally suitable (S3f) for producing rice and other crops due to their current low soil organic carbon content. However, these SMUs can be highly suitable (S1) for crop production with appropriate soil management. Using the Storie index, the entire tract of land of Pura has an index rating of 58 percent, which corresponds to a grade 3 soil suitable for planting a number of crops with expected good results. The results of the land suitability evaluation and soil productivity assessment further show that the land in the municipality of Pura is productive, and thus can benefit both agricultural production and ALC. As such, whichever spatial strategy or policy direction for ALC that the municipal government chooses to adopt, the municipality of Pura will lose productive land.

AGRO-ECOLOGICAL CLASSIFICATION OF AGRICULTURAL LAND USING MACHINE LEARNING, GIS AND REMOTE SENSING DATA

The paper is devoted to agro-ecological classification of agricultural land using modern methods of geo-information data analysis and machine learning.
 Background. There are few works in the literature, which cover the issues of accuracy of machine learning (MLL) models for agro-ecological grouping of agricultural land. A large number of raster information layers are used to improve the accuracy of land classification from satellite images. This considerably increases the time of training and testing MMOs, producing thematic maps of agricultural land classification. This approach requires considerably high computing resources and a considerable amount of computer RAM. Raster GIS data models occupy a much larger volume than vector models. In this regard, research on automated agro-ecological (grouping, classification) of agricultural land using vector GIS models is of practical importance.
 Purpose. The aim of the study is to apply GIS methods, remote sensing (ERS) data and machine learning methods for agricultural land grouping.
 Materials and methods. The materials used were synthesized multispectral high spatial resolution Sentinel-2A images, maps of vegetation indices NDVI (Normalized Difference Vegetation Index), OSAVI (Optimized Soil Adjusted Vegetation Index), EVI2 (Enhanced Vegetation Index2), NDWI (Normalized Difference Water Index), SAVI, PVI, GDVI, MCARI, NDRE, TSAVI; topographic map, ALOS DSM (30 m/pixel) and ALOS PALSAR (12.5 m/pixel) satellite images, soil map and field survey results. Field measurements were carried out using the Triump-2 satellite geodetic receiver and included determination of coordinates of characteristic points of land plot boundaries, relief elements, and soil survey.
 Digital spatial model of land use was created using GIS ArcGIS and QGIS, Python engineering libraries were used in the machine learning process.
 Results. Agro-ecological grouping of lands was realized by the example of the farm "Zerno Sibiri" of Novosibirsk region using the following machine learning methods: Random Forest (RF) method, Decision Tree (DT), k-nearest neighbours method (KNN). The best accuracy is the RF machine learning model. The accuracy of the model averaged 97.9% (with training 99.9%, testing 98.8%, and cross validation 95.0%). The Root Mean Square Error (RMSE) is 0.006: for training sample 0.001; test sample 0.076; validation sample 0.123 respectively). The mean kappa coefficient was 0.97 (1.00 for the training sample; 0.982 for the test sample, and 0.927 for the validation sample). 
 Conclusion. The offered method of agro-ecological grouping of agricultural lands by means of GIS, RS data and machine learning methods enabled to distinguish informative quantitative indicators of the relief. The main essence of the proposed method is to create a machine learning model (MLM) based on a spatial dataset. The spatial dataset is formed using geoinformation analysis methods and includes: geomorphometric maps, maps of agrometeorological parameters, soil map, on-farm land management map and operational-territorial units of land classification. The application of vector data model allowed for agro-ecological grouping of agricultural lands in automated mode, to accelerate labor-intensive process of raster data recognition, to increase objectivity of the work. The suggested method of agro-ecological agro-ecological grouping of lands allows taking into account the totality of relief and soil-ecological conditions indicators with the help of geoinformation analysis methods, remote sensing and machine learning.

SUBSTANTIVE-GENETIC PRINCIPLES OF SOIL CLASSIFICATION AND DIAGNOSTICS IN THE SCIENTIFIC HERITAGE OF NABOKIKH O.G.

Problem Statement and Purpose. Alexander Nabokikh (1874–1920), who criticized the model of soil classification and diagnostics by V. Dokuchaev and M. Sibirtsev, formulated the original water-mode concept of soil formation. This concept provided for the quantitative assessment of individual soil formation factors, as well as the classification and diagnosis of soils according to their characteristics and properties. Nabokikh ideas and methods were rejected by V. Dokuchaev’s students and have not been improved throughout the history of genetic soil science, but today they are clearly reflected in the «newest» substantive principles of soil diagnosis and classification. The methodological innovations of O. Nabokikh are far-sighted and relevant to this day and require a thorough study. Data & Methods. General scientific and historical methods were used. The research materials are the scientific works of O. Nabokikh, as well as archival materials of the Soil Museum of Odesa State Agrarian University. The maps of «selected major soil properties» of 1914–1916 were analyzed – detailed plans of organic matter content in the soils of the southern region of Ukraine. Results. O. G. Nabokikh proposed the Three-phase soil survey, which was based on methods of soil diagnostics by their properties, as well as the method of mapping the so-called “selected major soil properties”. Nabokikh foresaw the importance of detailed maps of the distribution of soil properties for soil monitoring. A comparative analysis of the data on organic matter content in the early twentieth century and in the early twenty-first century along two (n=94) of O. Nabokikh’s routes in the Odesa region revealed a decrease in organic matter in the surface layer of soils by an average of 0.6%. Nabokikh O. G. remained a supporter of the factor concept of soil formation, but modified it by identifying the “dominant factor” (an inseparable pair of precipitation and relief). In the matter of soil diagnostics and classification, he prefers the substantive principle. When identifying “variants of chernozems,” he cites the following substantive “main features of chernozems and the main modifications of these features”: uniformity of distribution of silicate minerals; accumulation of humus; illuvium of hydrates of one and a half oxides; illuvium of calcium carbonate salts; relict features. Determination of the main features of soils became the basis of the deep-profile method of soil research used by Nabokikh O. G.

Интродукция российских сортов люцерны в лесостепной зоне Монголии

There are two of commercial varieties of alfalfa (Medicago varia Mart.) ‘Vega 87’ and ‘Nakhodka’ originated from Russia, it are cultivated for introducing in Mongolian climate and ecological condition. Growth development of those varieties required from 136 to 143 days between regrowth in spring and the seed mature in the autumn. Wintering rate was 92.6% in ‘Nakhodka’ and 88.5% in ‘Vega 87’ in the first year and increased by 5.8 and 7.3% in the second year, respectively. Green biomass and hay yield of ‘Nakhodka’ were higher than ‘Vega 87’ and average green biomass of two years in ‘Nakhodka’ was 13.5 t/ha and 10.9 t/ha in ‘Vega 87’, the hay yield was 5.4 t/ha in ‘Nakhodka’ and 3.6 t/ha in ‘Vega 87’ at flowering stage. Moreover, humus content, phosphorus, potassium content and texture were determined in the depth of 0–10, 10–20, 20–30 cm in control and alfalfa cultivated areas. Humus content ranged between 3.1–3.6% in the depth of alfalfa cultivated areas while 2.8% in control area in the depth of 0–20 cm and humus content was increased by 9.36–14.5% (in relative terms) in alfalfa cultivated areas compared to the control. Then phosphorus content was 4.93 mg/100 g in ‘Nakhodka’ cultivated area, 4.11 mg/100 g in ‘Vega 87’ cultivated area and 3.70 mg/100 g in control area in the depth of 0–10 cm. Potassium content was ranged between 23.4–23.9 mg/100 g in alfalfa cultivated areas while it was 20.6 mg/100 g in 0–10 cm of depth. According to the soil survey result, there is no difference in soil texture between treatments (alfalfa cultivated areas and control area), but humus content and content of phosphorus, potassium had increased in alfalfa cultivated areas.

Geochemical soil survey for gold in Ogudu-Ogbagba Area, Osun State, southwestern Nigeria

Geochemical soil survey for gold in Ogudu-Ogbagba Area, Osun State, southwestern Nigeria

Geologic Map of the Bedford 30- x 60-minute Quadrangle, Indiana

The Geologic Map of the Bedford 30- x 60-minute Quadrangle shows the Mississippian and lower Pennsylvanian bedrock units and the overlying Pleistocene and Holocene deposits distributed over eight counties. The mapped area includes five physiographic divisions of the Southern Hills and Lowlands Region in south-central Indiana. Bedrock units and unconsolidated deposits were characterized by outcrop field observations, and new and archived borehole data. Bedrock data was consolidated into a single mapping database, which was then processed using gridding and contouring tools in ArcGIS Pro, resulting in rock formation contact lines, mappable at 1:100,000 scale. Additional information used to delineate contacts for unconsolidated deposits was based upon Indiana Department of Natural Resources water well database and soils data from the Soil Survey Geographic (SSURGO) database. Light detection and ranging (LiDAR) digital elevation models were also used to identify landforms and refine contacts between surficial units. The mapped bedrock units, from east to west, range in age from the Borden Group (lower Mississippian) to the Raccoon Creek Group (Lower Pennsylvanian) with the strike oriented generally from northwest to southeast. Quaternary deposits are found in river and stream valleys and filling the Wabash and Scottsburg lowlands with glacial deposits. Quaternary sediments were mostly deposited during the last two major advances of the Laurentide Ice Sheet into south-central Indiana. Brief summaries of all mapped bedrock units and unconsolidated deposits are listed on the map sheet, with more detailed descriptions in the accompanying pamphlet. Bedrock survey drill hole data points are also displayed on the map with corresponding links to expanded drill hole information for each of the survey drill holes listed in the pamphlet. In addition to the map and pamphlet, a composite spatial data set that conforms to the standardized database schema known as GeMS (Geologic Map Schema) is also available for download from this site. Both ESRI-licensed geodatabase and open shapefile versions of the spatial data set are available for download. Metadata records associated with each element within the spatial data set contain detailed descriptions of their purpose, constituent entities, and attributes. This geologic map was funded in part through the STATEMAP program supported by the U.S. Geological Survey under Cooperative Agreement No. G21AC10646.

Characterization and Classification of the Soils Tilth of Al-Rumaitha Area of Al-Muthanna Governorate

The study area was chosen within Al-Muthanna Governorate, with an area of approximately (11719) hectares, located between longitude 509000 E and 521000 E and latitude 3473000N and 3492000 N (UTM). The semi details soil survey was carried out to selected area for study through digged up 94 Augar holes using the grade soil system, which was determined geographically using the GPS device. According to the results of the field examination of the Augar holes, and the distribution & area of the diagnostic physiological units in the area, eight pedons location which represented for the region. Pedons were dissected and morphologically described, then disturbed samples which representing each diagnosed horizon was taken and transferred to the laboratory for analysis its some physical and chemical properties. The soil was classified to the level of series, also the soil tilth classified. The results of the soil tilth classes which was present in the case of dry condition consistency of the surface layer were very good (B), good (C), moderate (D) and weak tilth class (E), which occupied the lowest area of the study area by 1.7%, the good tilth class occupied the largest area, its reached 51.09%, while the two tilth classes, very good and moderately, reached 22.51% and 24.71%, respectively.

Comparative pathogenomic analysis reveals a highly tetanus toxin-producing clade of Clostridium tetani isolates in Japan.

C. tetani is a spore-forming, anaerobic bacterium that produces a toxin causing muscle stiffness and paralysis. Tetanus is preventable with the toxoid vaccine, but it remains a significant public health threat in regions with low vaccine coverage. However, there are relatively few isolates and limited genomic information available worldwide. In Japan, about 100 cases are reported each year, but there have been no nationwide surveys of isolates, and no genomic information from Japanese isolates has been published. In our study, we analyzed the genomes of 151 strains from a limited survey of soil in Kumamoto, Japan. Our findings revealed a high degree of genetic diversity, and we also identified a subset of strains that produced significantly more toxin, which provides new insights into the pathogenesis of tetanus. Our findings lay the foundation for future studies to investigate the distribution and evolution of C. tetani in Japan and neighboring countries.

Soil Survey Mapping and Classification of Engiz Sub Basin Soils

Bu çalışma, Samsun ili Ondokuzmayıs ilçesi arazisinin Aşağı Engiz Alt Havzası’nın detaylı toprak etüd haritalarının ve toprak sınıflarının belirlenmesi amacıyla yapılmıştır. Çalışma alanı, 4590000-4598000 K, 250000-258000 E (WGS-84, Zone37, UTMm) koordinatlarında yer almaktadır. 2021 yılı Temmuz ayında gerçekleştirilen çalışmanın alanı 4758 hektardır. Yıllık ortalama sıcaklık 13.8 °C ve toplam yıllık yağış miktarı 717.5 mm'dir. Alanın topoğrafya, jeoloji ve jeomorfik haritaları ve arazi gözlemleri incelenerek araştırma alanında 6 adet toprak profili açılmıştır. Yapılan analizler ve arazi gözlemlerinden elde edilen sonuçlar değerlendirilerek 6 farklı toprak serisi tanımlanmıştır. Düzköy, Dağköy, Çepinler, Esenyer, Ballıca ve Yukarıengiz serileri sırayla Toprak Taksonomisine göre Vertic Dystrustept, Vertic Haplustepts, Lithic Orthent, Lithic Orthent, Typic Ustifluvents ve Calcic Haplusterts; FAO/WRB’ye göre ise sırayla Dystric Vertic Cambisol, Colluvic Vertic Cambisol, Lithic Leptosol, Lithic Leptosol, Clayic Fulvisol ve Calcic Vertisol olarak belirlenmiştir. Araştırma alanında % 24.54 ile Ballıca serisi en fazla alana sahip iken, % 1.45 ile Esenyer serisi en az alana sahiptir. Çalışma alanından elde edilen sayısal toprak veri tabanı, sürdürülebilir arazi kullanımı ve doğal kaynakların korumasına yönelik yapılacak projelerde altlık olarak kullanılmasına olanak sağlanılmıştır.

Cadmium in topsoils of the European Union – An analysis based on LUCAS topsoil database

Cadmium (Cd) is a naturally occurring element that can accumulate in the soil through the application of fertilisers containing cadmium and as a waste of industrial processes. Cadmium inputs in the soil have increased significantly (+50 %) during the 20th century as a result of the application of fertilisers and sewage sludge, and also due to local contamination (e.g. waste dumping, mining) and industrial emissions (e.g. zinc smelters).Using the 21,682 soil samples from the LUCAS soil survey, we aim to estimate the spatial distribution of the concentration of Cd in the European Union (EU) and UK topsoil. Out of the total, 72.6 % of the samples have Cd values <0.07 mg kg−1, 21.6 % in the range 0.07–1 mg kg−1 and the remaining 5.5 % higher than the threshold of 1 mg kg−1, which is generally considered the limit for risk assessment. The mean Cd value in the EU topsoils is 0.20 mg kg−1, slightly higher in grasslands (0.24 mg kg−1) compared to croplands (0.17 mg kg−1).Applying an ensemble of machine learning models supported by a variety of environmental descriptors, we created maps of Cd distribution at a resolution of 100 m. The ensemble approach included five models and increased the prediction accuracy to R2 of 0.45 (an increase of 0.1 compared to best single model performance). The approach used resulted in a high predictive power for the general Cd distribution, while also identifying hotspots of Cd contamination. Natural factors influencing Cd levels include soil properties (pH, clay), topography, soil erosion, and leaching. As anthropogenic factors, we identified phosphorus inputs to agricultural lands as the most important for Cd levels. The application of the EU Fertiliser Directive should further limit Cd inputs and potentially the Cd content in soils.

Digital soil characteristics mapping for aiding site-specific management practices in the West Nile Delta, Egypt

Soil survey system is the key word for sustainable soil use and management. This study aimed to generate a digital soil mapping (DSM) using various spatial resolutions of freely available digital elevation models (DEMs) i.e., (30 m ALOS “Advanced Land Observing Satellite”, 12.5 m ALOS, 30 m SRTM “Shuttle Radar Topography Mission”, and 90 m SRTM) to assess the spatial variability of soil physio-chemical characteristics in El-Beheira Province, Western Nile Delta. A total of 196 geo-referenced soil profiles were collected from agricultural fields, and the soil's contents of total nitrogen (TN), potassium (K), available phosphorous (P), calcium (Ca), sulfur (S), magnesium (Mg), zinc (Zn), copper (Cu), manganese (Mn), and boron (B) were analyzed. The study revealed that the soil's contents of TN, P, S, B, and Cu were low, and Mg was suspected to be higher than K, leading to an Mg-induced K shortage. The study also found wide-ranging spatial variability structures of inverse distance weight (IDW) interpolated maps for several soil physio-chemical characteristics. The DSM further revealed that poor status was present in 85.4% of TN, 91.7% of P, 76.9% of S, and 87% of both B and Cu. The conclusion is that soil variability, as demonstrated in DSM, outweighs uniform treatment, and this discovery will assist extension workers, scientists, and decision-makers in implementing site-specific nutrient management strategies. Validation of the DSM is recommended for crop and variety-specific nutrient treatment rates. Understanding the geographical variance in the soil is critical for long-term nutrient management and higher output.

Spatial distribution and driving factors of soil organic carbon in the Northeast China Plain: Insights from latest monitoring data

Soil organic carbon (SOC) is a critical component of soil fertility and plays a crucial role in the global carbon cycle. Despite the widespread reports of a decrease in SOC content and stock in the Northeast China Plain in recent decades, the current status and driving factors of its content and distribution are unclear. In this study, the surface soil (0–20 cm) SOC content data of 1920 sampling points within the Northeast China Plain covering an area of 2.6 × 105 km2 were obtained based on the Land Quality Geochemical Monitoring Network established in 2018. Random forest model and correlation analysis were used to identify the main driving factors of SOC distribution. The results showed that the SOC content, soil organic carbon density (SOCD), and soil organic carbon storage (SOCS) in the Northeast China Plain were 13.48 g·kg−1, 3.45 kg·C·m−2, and 898.95 Tg, respectively. SOC content in paddy land was the highest among different land use types, which reached 18.77 g·kg−1. SOC content showed strong spatial dependence and gradually increased from southwest to northeast in the monitoring area. The results of the random forest analysis showed that the SiO2, mean annual temperature, and Fe2O3 explained 39.4 %, 18.9 %, and 12.8 % of the spatial variation of SOC, respectively. Although the SOCS (0–20 cm) in the Northeast China Plain has decreased by 8.68 % in the last 40 years compared to the Second National Soil Survey (1980), it's important to note that the SOCS has transitioned from a decreasing trend between 1980 and 2006 to an increasing trend from 2006 to 2018.This study provides important information for decision-makers on the spatiotemporal changes of SOC and its driving factors in the Northeast China Plain, which has a great significance for soil carbon sequestration and the development of management strategies to maintain soil fertility.

Quaternary Geology of the Washington-Jasper Area

"Quaternary Geology of the Washington-Jasper Area" was created to present basic quaternary geologic information that contributes to the characterization of potential aggregate resources, characterization of bedrock aquifer systems, and analysis of the overlying predominantly glacial deposits. This map is based on data compiled from project field observations and project exploratory borings, complemented with IGWS cartographic (e.g., Gray, 1989) and archive borehole data, select Indiana Department of Natural Resources water well logs, and United States Department of Agriculture soil survey maps. Expert knowledge of fluvial, glacifluvial and ice-marginal environments was used to draw contacts between units. This geologic map was funded in part through the STATEMAP program supported by the U.S. Geological Survey under Cooperative Agreement No. G21AC10646. "Quaternary Geology of the Washington-Jasper Area" is a composite geodata set that conforms to "GeMS (Geologic Map Schema)--a standard format for the digital publication of geologic maps," available at http://ngmdb.usgs.gov/Info/standards/GeMS/. Metadata records associated with each element within the geodata set contain more detailed descriptions of their purposes, constituent entities, and attributes. An OPEN shapefile version of the data set is also available. It consists of shapefiles, DBF files, and delimited text files and retains all information in the native geodatabase, but some programming will likely be necessary to assemble these components into usable formats.

Significant opportunities for tree crop expansion on marginal lands in the Midwest, USA

AbstractIntroductionTree crop orchards can help diversify the monocropping practices in agricultural lands such as the Midwestern region of the United States which is currently dominated by corn‐soybean rotation. These crops can not only expand farm income but also help stabilize soil, purify water, and provide other ecosystem services. Despite these benefits, tree crops as agroforestry systems are not widely established in the region. Identifying marginal land that is more suitable for tree crops over row crops can help the growers and the environment.Materials and MethodsUsing the case of Missouri, USA, this study mapped marginal land for nut‐producing tree crops using a three‐step process. The first step includes the identification of marginal land suitable for a wide variety of tree crops. The second step involved GIS‐based multicriteria analysis of biophysically suitable areas for three commercially viable tree species, that is, eastern black walnut, pecan, and Chinese chestnut. The final step maps the marginal land for tree crops based on their suitability to grow under different environmental vulnerabilities, mainly flooding, erosion, and sloped conditions. The Gridded Soil Survey Geographic Database developed by the United States Department of Agriculture provided information on soil biophysical and environmental characteristics.ResultsThe spatial analysis showed that Missouri has around 16,000 sq. km of land suitable for Black walnut, followed by 10,801 sq. km and 4587 sq. km for pecan and Chinese chestnut, respectively. The study found very few tree crop orchards on these marginal lands.ConclusionThere are ample opportunities to expand tree crops on marginal cropland. Converting these lands to tree crops could provide communities with economic, human health, and environmental benefits. This multistep methodology could serve as a screening tool to identify tree‐cropping areas for environmental improvement and rural America's economic revitalization.

Site History’s Role in Urban Agriculture: A Case Study in Kisumu, Kenya, and Ouagadougou, Burkina Faso

Urban agriculture (UA) is a widespread practice often considered low-profit, taking place on marginal lands. This is supported by the lack of quantitative data on UA’s contributions to food security and employment, yet contradicted by prevalence and high participation rates. This case study of six UA sites in Kisumu, Kenya and Ouagadougou, Burkina Faso explores the relationship between prior land use and current management and soil quality. A soil survey is performed determining the soil macronutrient and soil mineral composition. Agricultural management, ownership, and prior land use are investigated through interviews, satellite imagery, and historic publications. Results show three UA sites predating surrounding urban development, and data on soil nutrient content show that sites likely were chosen for their soil. The three younger sites are smaller and less embedded in the local economy, but soil analysis shows medium-rich to rich agricultural soils. We conclude that one cannot assume that UA is practiced on marginalized soils. Consequently, both value attribution to and the sustainable agricultural management of UA soils must be based on their characteristics, such as mineralogy and nutrient status, to prevent valuable soil resources from being lost. Through this, the more accurate value attribution of UA can be achieved, lending weight to the value attributed to UA by local communities.

Mapping surface soil organic carbon density by combining different soil sampling data sources and prediction models in Yangtze River Delta, China

Soil organic carbon (SOC) is a crucial soil property governing various agricultural, ecological, and environmental processes in the terrestrial ecosystem. However, acquiring accurate and high resolution SOC density (SOCD) map remained a challenge in the current researches. Based on soil samples collected from soil survey and published literatures (952 samples), this study tested different approaches for generating high accuracy dataset of 0–20 cm SOCD with the spatial resolution of 90-m in the Yangtze River Delta. Two spatial prediction methods, including artificial neural network (ANN, represented non-linear), multiscale geographically weighted regression (MGWR, represented linear) were applied to generated the SOCD maps. Then three fusion models, including multiple linear regression fusion (MLR_F), ANN fusion (ANN_F) and a self-developed model (multiscale geographically normalize weighted fusion, MGNW_F), were applied to fuse the prediction results of spatial interpolation methods. Among spatial interpolation methods, the ANN performed better in capturing the SOCD spatial pattern, while the MGWR performed better in accuracy measures of mean square error, mean absolute error and coefficient of determination. After data fusing by the three models, improved accuracy measures than the ANN and MGWR were achieved. The predictions of fusion models also showed better reliability than the soil dataset of high resolution National Soil Information Grids of China, mainly due to that more soil samples were included in the prediction. Among these fusion models, the MGNW_F performed slightly better than the other two and had the strongest adaptability to the overall environment of the study area. Findings of this study highlighted the potentials of acquiring additional soil samples from existing literatures and fusing different methods for enhancing the accuracy in mapping SOCD.

The neglected roles of adjacent natural ecosystems in maintaining bacterial diversity in agroecosystems.

A central aim of community ecology is to understand how local species diversity is shaped. Agricultural activities are reshaping and filtering soil biodiversity and communities; however, ecological processes that structure agricultural communities have often overlooked the role of the regional species pool, mainly owing to the lack of large datasets across several regions. Here, we conducted a soil survey of 941 plots of agricultural and adjacent natural ecosystems (e.g., forest, wetland, grassland, and desert) in 38 regions across diverse climatic and soil gradients to evaluate whether the regional species pool of soil microbes from adjacent natural ecosystems is important in shaping agricultural soil microbial diversity and completeness. Using a framework of multiscales community assembly, we revealed that the regional species pool was an important predictor of agricultural bacterial diversity and explained a unique variation that cannot be predicted by historical legacy, large-scale environmental factors, and local community assembly processes. Moreover, the species pool effects were associated with microbial dormancy potential, where taxa with higher dormancy potential exhibited stronger species pool effects. Bacterial diversity in regions with higher agricultural intensity was more influenced by species pool effects than that in regions with low intensity, indicating that the maintenance of agricultural biodiversity in high-intensity regions strongly depends on species present in the surrounding landscape. Models for community completeness indicated the positive effect of regional species pool, further implying the community unsaturation and increased potential in bacterial diversity of agricultural ecosystems. Overall, our study reveals the indubitable role of regional species pool from adjacent natural ecosystems in predicting bacterial diversity, which has useful implication for biodiversity management and conservation in agricultural systems.

The Pedological Variation in some of Soil Characteristics of Alkhaleej and Al-Aali Project in Al-Alam District / Iraq

The goal of research to study pedological heterogeneity in soil morphological and physical Characteristics in the Al-Khaleej and Al-Aali Al-Muwahed Project soils in Salahaldin Government. The (6) six soil pedon were chosen and their distribution based on the area of the soil series in study area. The soil morphologically properties were described according to soil survey staff, 2006. The soil physical properties (soil texture, Bulk density, and Compaction) were selected. The results show there is a variation in the morphological, where the thickness of the horizons differed and was the largest in the surface horizon at the peduns P1 and P3, while the color was found that all study sites are located within a page 10YR, which is the dominant wavelength for most Iraqi soils, while the soil texture was clayey and sandy in P1, P2, and P4, and mixed in P3, P5, and P6. The results showed that the soil texture ranged between admixture and admixture clay and sandy, and it was noted that the soil texture classes took the following order: sand > silt > clay, and it was noted that there was a predominance of sand content as it ranged between (417 and 722) g.kg-1 in the C2 horizon for each of P5 and P2 respectively, and a decrease was found in the bulk density in the surface horizons of the soils of the study sites and an increase in the average diameter weighted by the open ground.

Spatial prediction of lime requirements by adjusting aluminium saturation in Sub-Saharan Africa croplands

Acidic soils cover over 30 % of Sub-Saharan Africa cropland. Acidic soils deprive crops of calcium, magnesium, potassium, molybdenum, and phosphorus due to aluminium (Al), manganese, and iron toxicities. Thus, liming is required to adjust the level of exchangeable Al3+ to the desired level of Al saturation of the crops grown. Lime requirement (LR) was quantified using soil dataset from Africa soil information service (AfSIS). Spatial variations of LR of cereals, pulses and cash crops were predicted using random forest algorithm. Our results revealed that mean of LR Mg CaCO3 (1 Mg = 106 g) ha−1 for cereal crops were 6.34, 6.35, and 4.41 for maize, sorghum, and upland rice, respectively. Mean of LR (Mg ha−1) for pulses were 6.28, 5.19, and 4.90 for common beans, soybeans, and cowpeas, respectively. Mean of LR Mg CaCO3 (1 Mg = 106 g) ha−1 for cash crops were 3.41 and 6.29 for coffee and cotton, respectively. Spatial variation showed that LR in croplands was higher in tropical humid regions than in semi-arid and arid regions and ranged from 0 to 8.8 Mg ha−1. The results of 10-fold cross validation for high model performance of LR for tested crops were coefficient of determination (R2) of 0.61, a root mean square error (RMSE) of 0.5, and a mean absolute error (MAE) of 0.31, maize LR with RMSE = 0.9, MAE = 0.24, and R2 = 0.51, and cotton LR with RMSE = 0.5, MAE = 0.31, and R2 = 0.60. We recommend predicting lime requirement in acidic soils of Sub-Saharan Africa by adjusting Al saturation up to the tolerance of the grown crop, updating soil surveys in Sab Saharan Africa, and using digital soil mapping to monitor soil acidity and lime requirement.

Soil Fertility and Phosphorus Leaching in Irrigated Calcareous Soils of the Mediterranean Region

To ensure soil quality and soil health, it is necessary to improve fertilization practices while minimizing environmental impacts. The aim of this study was to record the state of the art on soil fertility related to fertilization management (organic and/or mineral) and to detect environmental challenges in highly productive fields. A soil survey was set up in a new irrigated area (c. 20 years old), in the north-eastern part of Spain, which is mainly devoted to double annual crop rotations of cereals and maize. The area also supports an important animal rearing activity. The survey covered 733 ha of calcareous soils, owned by 35 farmers. At each farm, fertilization management was recorded, and soil was analyzed for nutrients and heavy metals. Multivariate analyses were performed. Total N, P, Cu and Zn, and available P, Cu, Zn and Mn soil concentrations were associated to the use of organic amendments. Heavy metals concentrations were below established thresholds. Available P (Olsen-P) was identified as an indicator of the previously adopted fertilization management and of the potential of P leaching towards deeper soil layers. Regression analyses were performed. A displacement of available P from the uppermost layer (0–0.3 m) occurs in the breakpoint of 86 mg P kg−1 soil. Preventative actions might be established from 53 mg P kg−1 soil due to the slowdown in P immobilization. Our results reinforce the importance of setting up P threshold soil levels for best practices of fertilization, as a basis for sustainable agriculture intensification.