Preliminary construction of a microecological evaluation model for uranium-contaminated soil.

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Soil quality assessment in low human activity disturbance zones: a study on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau, located at the Third Pole and known as the "Asian water tower," serves as a crucial ecological barrier for China. Grasping the soil quality on the Qinghai-Tibet Plateau holds paramount importance for the rational and scientific exploitation of soil resources within the region and is essential for vegetation restoration and ecological reconstruction. This study, conducted in Maqin County, Qinghai Province, collected 1647 soil samples (0-20 cm) within a study area of 6300 km2. Sixteen soil indicators were selected that were split into beneficial (N, P, S, and B), harmful (Cr, Hg, As, Pb, Ni, and Cd), and essential (Cu, Zn, Se, Ga, K, and Ca) elements. The Soil Quality Index (SQI) was computed to assess soil quality across diverse geological contexts, land cover classifications, and soil profiles. The results indicate that the overall SQI in the study area was comparatively high, with most regions having an SQI between 0.4 and 0.6, categorized as moderately to highly satisfactory. Among the different geological backgrounds, the highest SQI was found in the Quaternary alluvium (0.555) and the lowest in the Precambrian Jinshuikou Formation (0.481). Regarding different land-use types, the highest SQI was observed in glacier- and snow-covered areas (0.582) and the lowest in other types of grassland (0.461). The highest SQI was recorded in typical alpine meadow soil (0.521) and the lowest in leached brown soil (0.460). The evaluation results have significant reference value for the sustainable utilization and management of soil in Maqin County, Qinghai Province, China.

Bacteria not fungi drive soil chemical quality index in banana plantations with increasing years of organic fertilizer application.

BACKGROUND: Maintaining or improving soil chemical quality is critical for sustainable agricultural productivity and environmental safeguards. Organic fertilizer application, a common agricultural practice in banana cultivation, is often associated with greater microbial biomass and activity, which are linked to improvements in soil chemical quality. However, the effect of the duration of organic fertilizer application on soil chemical quality and whether it is microbially driven still needs to be investigated. We collected soil samples from banana plantations consistently applying organic fertilizers for 1 (Y1), 4 (Y4), 7 (Y7) and 10 (Y10) years. Soil chemical quality is expressed as total data set (TDS) and minimum data set (MDS) based on chemical indicators, and soil microorganisms are characterized by phospholipid fatty acid (PLFA). RESULTS: Based on TDS and MDS, the soil chemical quality indices in Y7 and Y10 treatments were significantly higher than that in Y1 and Y4 treatments. Soil total PLFA concentrations and the proportional abundance of fungi and arbuscular mycorrhizal fungi increased with prolonged banana cultivation. Total PLFA concentrations were significantly positive correlation with the soil chemical quality index. Soil gram-positive bacteria (G+), bacteria, protozoa and ratio of G+ to gram-negative bacteria (G-) were major drivers of soil chemical quality. CONCLUSION: The organic fertilizer application can significantly improve soil chemical quality, which is regulated by soil bacteria. Regular application of organic fertilizers is important in promoting soil quality and soil biological properties need to be incorporated into the assessment of soil health in banana plantations. © 2022 Society of Chemical Industry.

Spatial distribution and quantitative source identification of nutrients and beneficial elements in the soil of a typical suburban area, Beijing.

Source identification and quality monitoring of soil nutrients and beneficial elements (NBEs) are crucial for agricultural production and environmental protection. In this study, grid sampling (223 topsoil samples and 223 subsoil samples) was carried out in the Tongzhou District of Beijing. The concentration level of representative NBEs (N, P, K, Ca, Mg, Se, V, Ge, Mn, Zn) and some typical soil properties representing indicators (total organic carbon, TFe2O3, Al2O3/SiO2, and pH) in soils and their spatial distribution were analyzed. The major sources contributing to these NBEs were assessed by principal component analysis (PCA), redundancy analysis (RDA), and positive matrix factorization (PMF) analysis. The results suggested that the soil parent material contributed 40.09-69.84% to Zn, V, Ge, Mn, F, and K in soils; the local external source contributed 54.89-75.04% to N, Se, and TOC; and the hydrous system contributed 40.67-77.31% to Ca and Mg. The enrichment degree of each NBE was calculated using the standardized concentration ratio method. These indices exhibited the influence and mixing process of different sources on the target NBEs in topsoils. The individual concentrations of the target NBEs and the combined concentrations of N, P, and K were used to evaluate the soil quality. Our study estimated the relative contributions from dominant sources to NBEs in soils from a typical suburban area, providing a basis for agricultural activities and environmental protection.

[Comprehensive evaluation of soil quality of different land use types on the northeastern margin of the Qinghai-Tibet Plateau, China]. / 青藏高原东北缘不同土地利用类型土壤质量综合评价.

Soil quality evaluation is an important prerequisite for the rational soil resource utilization. We collected soil samples from forest (n=9), grassland (n=18) and cropland (n=38) in Tianzhu County, Gansu Province, which is located on the northeastern edge of the Qinghai-Tibet Plateau. Soil quality was evaluated based on thirteen soil physical and chemical indicators, including soil bulk density, field capacity, and organic matter. A minimum data set (MDS) was constructed using principal component analysis and correlation analysis to establish a soil qua-lity evaluation index (SQI) system, which was used in the soil quality evaluation for the three land-use types. The results showed that total porosity, capillary porosity, field capacity, capillary water capacity, saturated water content, organic matter, total nitrogen and available potassium content were significantly higher in forest than those in grassland and cropland. The SQI system of forest was based on field capacity, organic matter, total nitrogen, available nitrogen, and available potassium, and the SQI ranged between 0.329 to 0.678, with a mean value of 0.481. Grassland SQI system was based on field capacity and available nitrogen, with the SQI ranging between 0.302 to 0.703 and a mean value of 0.469. Cropland SQI system was based on capillary water capacity, non-capillary porosity, available nitrogen, available phosphorus, and available potassium, and the SQI ranged from 0.337 to 0.616 with a mean value of 0.462. The most important barriers to soil quality improvement in forest, grassland, and cropland were available potassium, field capacity, and capillary water capacity, respectively. The MDS-based SQI enabled an accurate evaluation of soil quality across different land-use types in the study area, which was best in forest followed by grassland and cropland. The evaluation results would provide important reference for sustainable soil management in the local area.

Soil quality assessment of coastal salt-affected acid soils of India.

Soil salinity and acidity are some of the major causes of land degradation and have a negative impact on agricultural productivity. Assessing soil quality (SQ) of soils affected by soil salinity and acidity is required for their sustainable utilization for agricultural production. The aim of the present study was to evaluate the SQ of the salt-affected acid soils of the Indian West Coastal region using the additive and weighted soil quality indices (SQIs). The SQIs were developed using a total dataset (TDS) and a minimum dataset (MDS). The TDS comprised of 15 different soil properties as electrical conductivity (EC), pH, bulk density, soil available nitrogen (N), phosphorus (P), potassium (K), sulfur (S), boron (B), iron (Fe), manganese (Mn), copper (Cu), zinc (Zn) and exchangeable calcium (Ca), magnesium (Mg), and sodium (Na) measured on 300 soil samples (depth 0-0.15 m). Based on principal component analysis and correlation analysis, an MDS with soil properties like soil pH, EC, Na, Cu, Mn, and BD was formed. Using two approaches (additive and weighted), two datasets (TDS and MDS), and two scoring methods (linear and non-linear), eight SQIs were developed. The MDS-based linear weighted and non-linear weighted SQI found suitable to evaluate SQ of salt-affected acid soils and SQI had a significant and negative correlation of - 0.83 and - 0.70 (p < 0.01) with EC, respectively. Thus, it is clear that the SQ considerably reduces with an increase in soil salinity. The performance of the MDS-based SQIs was better than the TDS to discriminate different soil salinity classes. The agreement between the linear and non-linear scoring method of SQI had a linear relationship with a coefficient of determination (R2) of 0.91-0.96. Thus, assessing the SQ of salt-affected acid soils using MDS, linear scoring, and weighted approach of the soil quality indexing could save the time and cost involved.