A standardized soil quality index for diverse field conditions

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.

Modeling and digital mapping of soil quality indicators in different land uses (a case study: Ravansar-Sanjabi Plain, Kermanshah)

Identifying the spatial variability of soil quality indices is necessary to manage soil resources on a watershed scale. This study aimed to identify suitable indices for soil quality assessment at the watershed scale using various soil characteristics and modeling approaches. Another objective was to map soil quality variability in a representative area in the Qarasu watershed in Kermanshah province, west of Iran. Latin hypercube sampling method using the auxiliary variables used to select 163 sampling points based on land use, soil, and topographical variability in an area of about 57 thousand hectares. In the field operations, soil profiles were described, and samples were taken from different soil profile horizons. Soil properties such as texture, pH, salinity, available water, equivalent calcium carbonate, saturation percentage, soil organic carbon, nitrogen, available phosphorous, potassium, Fe, Zn, Cu and Mn, and soil aggregate stability (mean weight diameter (MWD), geometric mean diametric (GMD), and stable aggregates larger than 0.25 mm (WAS)) measured in the laboratory. Soil quality indices (productivity index (PI), soil quality index (SQI) and reduced dimension soil quality index using principal component analysis (SQI-PCA)) were calculated for each point using the measured soil properties. Soil quality indices were simulated using modeling with the random forest and support vector machine methods and auxiliary variables. Results showed that the range of soil characteristics and integrated soil quality indices was very high across the study area. Soil organic carbon percent varied from about 0.19 to 8.44%. The range of changes in PI in the study area was more than SQI and SQI-PCA indices. Quantities of all soil quality indices were higher in forest and rangeland than in agricultural lands. The spatial estimation accuracy of the SQI-PCA was higher than other soil quality indices and converged well with land use changes compared to PI and SQI.

Determination of Soil Quality Index of agricultural land adjacent to industrial sites of Jamuria C.D.Block, Paschim Bardhaman District, West Bengal

A healthy soil is crucial for food security, but human activities, particularly industrialization, are degrading the soil's quality. This study aims to assess and compare the Soil Quality Index (SQI) at three industrial sites: the iron and steel industry, the open cast coal mining industry, and the brick kiln industry, along with a control field. To measure the SQI, the weighted additive method was applied to the nine selected physico-chemical properties of soil: soil temperature, soil moisture, Bulk Density, pH, N, P, K, OC, and EC. Principal Component Analysis coupled with multiple correlation methods was used to determine the Minimum Data Set. The most dominant factors near the iron and steel industrial site are soil temperature, N, K, and EC, while N, OC, soil moisture, P, K, and EC are the most significant factors near the open cast coal mine. In the case of the brick kiln industrial site, soil moisture, OC, K, soil temperature, and P have the highest loadings. The calculated SQI indicates that the quality of soil is in better condition in the control field (0.6475), while the soil adjacent to the coal mining industrial site (0.1426) is in the worst state, followed by the iron and steel industrial site (0.1611) and the brick kiln industrial site (0.289). To attain sustainable agricultural practices in industrial landscapes, efficient management of nutrient contents and phytoremediation can be helpful.

Assessment of soil quality in an arid and barren mountainous of Shandong province, China

Forest soils are important components of forest ecosystems, and soil quality assessment as a decision-making tool to understand forest soil quality and maintain soil productivity is essential. Various methods of soil quality assessment have been developed, which have occasionally generated inconsistent assessment results between soil types. We assessed the soil quality of five communities (herb, shrub, Quercus acutissima, Pinus thunbergii, and Q. acutissima-P. thunbergii mixed plantation) using two common methods of dry and barren mountains in the Yimeng Mountain area, China. Sixteen soil physical, chemical and biological properties were analysed. The soil quality index was determined using the established minimum data set based on the selection results of principal component analysis and Pearson analysis. Silt, soil total phosphorus (P), soil total nitrogen (N), L-leucine aminopeptidase, acid phosphatase and vector length were identified as the most representative indicators for the minimum data set. Linear regression analysis showed that the minimum data set can adequately represent the total data set to quantify the impact of different communities on soil quality (P < 0.001). The results of linear and non-linear methods of soil quality assessment showed that the higher soil quality index was Pinus forest (0.59 and 0.54), and the soil quality index of mixed plantation (0.41 and 0.45) was lower, which was similar to the herb community (0.37 and 0.44). Soil quality was mostly affected by soil chemical properties and extracellular enzyme activities of different communities, and the different reasons for the low soil quality of mixed plantations were affected by soil organic carbon (C) and total C. Overall, we demonstrate that the soil quality index based on the minimum data set method could be a useful tool to indicate the soil quality of forest systems. Mixed plantations can improve soil quality by increasing soil C, which is crucial in ecosystem balance.

Soil quality index as a tool to assess biochars soil quality improvement in a heavy metal-contaminated soil

The assessment of soil quality improvement provided by biochars is complex and rarely examined. In this work, soil quality indices (SQIs) were produced to evaluate coffee industry feedstock biochars improvement on soil quality samples of a heavy metal-multicontaminated soil. Therefore, a 90-day incubation experiment was carried out with the following treatments: contaminated soil (CT), contaminated soil with pH raised to 7.0 (CaCO3), contaminated soil + 5% (m/m) coffee ground biochar, and contaminated soil + 5% (m/m) coffee parchment biochar (PCM). After incubation, chemical and biological attributes were analyzed, and the data were subjected to principal component analysis and Pearson correlation to obtain a minimum dataset (MDS), which explain the majority of the variance of the data. The MDS-selected attributes were dehydrogenase and protease activity, exchangeable Ca content, phytoavailable content of Cu, and organic carbon, which composed the SQI. The resulting SQI ranged from 0.50 to 0.56, with the highest SQI obtained for the PCM treatment and the lowest for the CT. The phytoavailable content Cu was the determining factor for differentiating PCM from the other treatments, which was a biochar original attribute and helped to improve soil quality based on the SQI evaluation, further than heavy metal immobilization due to the soil sample pH increase. Longer-term experiments may illustrate clearer advantages of using biochar to improve heavy metal-contaminated soil quality, as physical attributes may also respond, and more significant contributions to biological attributes could be obtained as biochar ages.

Superior improvement on soil quality by Pennisetum sinese vegetation restoration in the dry-hot valley region, SW China

Vegetation restoration is a good way to improve soil quality and reduce erosion. However, the impact of vegetation restoration on soil quality in the dry-hot valley region has been overlooked for many years. This study aimed to reveal the effects of Pennisetum sinese (PS) and natural vegetation (NV) on soil quality and then to explore the feasibility of introducing PS for the vegetation restoration of the dry-hot valley region. The PS and NV restoration areas deserted land evolving from cultivated land (CL) have been established since 2011. The results showed that the soil properties were obviously improved by PS from the dry to wet seasons, except for the soil available phosphorous. The comprehensive soil quality indexes of the three typical seasons (dry, dry-wet, and wet) were determined by using nonlinear weighted additive (NLWA) based on the total dataset, significant dataset and minimum dataset (MDS). The results indicated that the comprehensive minimum dataset soil quality index (MDS-SQI) of the three typical seasons evaluate soil quality well. The soil quality of PS was significantly greater than that of CL and NV (P < 0.05), as shown by the MDS-SQI. Additionally, PS could maintain a stable soil quality in the three typical seasons, while both CL and NV had obvious fluctuations. In addition, the result of the generalized linear mode suggested that the vegetation type had the greatest impact on the soil quality (44.51 %). Comprehensively, vegetation restoration in the dry-hot valley region has a positive impact on the soil properties and quality. PS is a great candidate species for the early vegetation restoration in the dry-hot valley region. This work provides a reference for vegetation restoration and rational utilization of soil resources in degraded ecosystems in dry-hot valleys and other soil erosion areas.

Long-term intensive management reduced the soil quality of a Carya dabieshanensis forest

The evaluation of soil quality can provide new insights into the sustainable management of forests. This study investigated the effects of three types of forest management intensities (non-management (CK), extensive management (EM), and intensive management (IM)), and five management durations (0, 3, 8, 15, and 20 years) on the soil quality of a Carya dabieshanensis forest. Further, minimum data sets (MDS) and optimized minimum data sets (OMDS) were established to evaluate the soil quality index (SQI). A total of 20 soil indicators representing its physical, chemical, and biological properties were measured for the 0-30 cm layer. Using one-way ANOVA and principal component analysis (PCA), the total data set (TDS), the minimum data set (MDS), and optimized minimum data set (OMDS) were established. The MDS and OMDS contained three (alkali hydrolyzed nitrogen (AN), soil microbial biomass nitrogen (SMBN), and pH) and four (total phosphorus (TP), soil organic carbon (SOC), AN, and bulk density (BD)) soil indicators, respectively. The SQI derived from the OMDS and TDS exhibited a stronger correlation (r = 0.94, p < 0.01), which was suitable for evaluating the soil quality of the C. dabieshanensis forest. The evaluation results revealed that the soil quality was highest during the early stage of intensive management (IM-3), and the SQI of each soil layer was 0.81 ± 0.13, 0.47 ± 0.11, and 0.38 ± 0.07, respectively. With extended management times, the degree of soil acidification increased, and the nutrient content decreased. Compared with the untreated forest land the soil pH, SOC, and TP decreased by 2.64-6.24%, 29.43-33.04%, and 43.63-47.27%, respectively, following 20 years of management, while the SQI of each soil layer decreased to 0.35 ± 0.09, 0.16 ± 0.02 and 0.12 ± 0.06, respectively. In contrast to extensive management, the soil quality deteriorated more rapidly under longer management and intensive supervision. The OMDS established in this study provides a reference for the assessment of soil quality in C. dabieshanensis forests. In addition, it is suggested that the managers of C. dabieshanensis forests should implement measures such as increasing the amount of P-rich organic fertilizer and restoring vegetation to increase soil nutrient resources for the gradual restoration of soil quality.

Correlations between forest soil quality and aboveground vegetation characteristics in Hunan Province, China

As a key component of terrestrial ecosystems, soil interacts directly with aboveground vegetation. Evaluating soil quality is therefore of great significance to comprehensively explore the interaction mechanism of this association. The purpose of this study was to fully understand the characteristics of aboveground vegetation, soil quality, and their potential coupling relationship among different forest types in Hunan Province, and to provide a theoretical basis for further exploring the mechanisms underlying soil-vegetation interactions in central China. We have set up sample plots of five kinds of forests (namely broad-leaved forest, coniferous forest, coniferous broad-leaved mixed forest, bamboo forest, and shrub forest) in Hunan Province. To explore the differences of vegetation characteristics and soil physical and chemical properties among the five stand types, variance analysis, principal component analysis, and regression analysis were used. Finally, we explored the coupling relationship between soil quality and aboveground vegetation characteristics of each forest. We found that there were significant differences in soil quality among the forest types, ranked as follows: shrub forest > bamboo forest > broad-leaved forest > mixed coniferous and broad-leaved forest > coniferous forest. In general, there was a negative correlation between vegetation richness and soil quality in the broad-leaved forest and the shrub forest, but they showed a positive correlation in the coniferous forest, the mixed coniferous and broad-leaved forest, and the bamboo forest. As a necessary habitat condition for aboveground vegetation, soil directly determines the survival and prosperity of plant species. These results indicated that for vegetation-soil dynamics in a strong competitive environment, as one aspect wanes the other waxes. However, in a weak competitive environment, the adverse relationship between vegetation and soil is less pronounced and their aspects can promote.

Are Iron Tailings Suitable for Constructing the Soil Profile Configuration of Reclaimed Farmland? A Soil Quality Evaluation Based on Chronosequences

Iron tailings used as soil substitute materials to construct reclaimed farmland soil can effectively realize the large-scale resource utilization of iron tailings and reduce environmental risks. It is vital to understand the mechanisms affecting reclaimed soil quality and determine the appropriate pattern for reclamation with iron tailings. Thus, a soil quality index (SQI) was developed to evaluate the soil quality of reclaimed farmland with iron tailings in a semi-arid region. Soil samples were collected from two reclamation measures (20 cm subsoil + 20 cm iron tailings + 30 cm topsoil and 20 cm subsoil + 20 cm iron tailings + 50 cm topsoil) with reclamation years of 3 (R3), 5 (R5), and 10 (R10) at three soil depths (0–10, 10–20, and 20–30 cm) to measure 13 soil physicochemical properties in western Liaoning, China. Adjacent normal farmland (NF) acted as a reference. Results indicated that iron tailings were suitable for constructing the soil profile configuration of reclaimed farmland. SQI of reclaimed soil increased with the reclamation year, but it has not reached the NF level after 3 years, while it was better than NF after 5 years. The nutrient content of reclaimed soil increased with the reclamation year, but it still did not reach the NF level after 10 years. SQI of R10 (with 50 cm topsoil) was also better than NF but slightly lower than R5 (with 30 cm topsoil). For the semi-arid region with sticky soil texture, the topsoil thickness of reclamation was not the thicker the better, and 30 cm topsoil covered on iron tailings in western Liaoning could achieve a better reclamation effect than 50 cm.

Succession law and model of reconstructed soil quality in an open-pit coal mine dump of the loess area, China

Studying the change laws of reconstructed soil quality and constructing succession models are the main components and tools of reconstructed soil quality evaluation for the supervision and management of reconstructed soil. However, the evaluation and management system of reconstructed soil quality suitable for the loess area needs to be improved. This paper aimed to clarify the succession law of reconstructed soil in an open-pit coal dump in the loess area on the temporal scale and to construct a succession model of reconstructed soil quality to evaluate and manage reconstructed soil. The Pingshuo coal mine, a representative open-pit coal mine in the loess area, is the study area. Field investigation and sampling, time-space substitution, and the combination of qualitative and quantitative research methods were used. The reconstructed soil quality succession model was constructed based on the soil quality index method. Results: (1) As the reclamation period increased, the physical and chemical properties of reconstructed soil significantly improved, and reconstructed soil quality generally reached the quality of the original landform after approximately 15 years of reclamation. However, after long-term reclamation, soil physical properties still limited the improvement of reconstructed soil quality to a certain extent. (2) After long-term reclamation, the difference in reconstructed soil quality between layers gradually decreased, and the reconstructed soil condition of the 0-10 cm soil layer was obviously better than that of the other layers. (3) We quantitatively constructed and verified the reconstructed soil quality succession model that is suitable for the loess area, which can be used in conjunction with adaptive management for the evaluation and management of reconstructed soil in the loess area. In conclusion, this study is of great significance to meet the real needs of dynamic evaluation and management of reconstructed soil quality in the loess area and to enrich the soil evaluation and management system at home and abroad.

Soil chemical quality assessment and spatial distribution of pomelo orchards in acidic red soil hilly regions of China

BACKGROUND

Soil quality assessment is a critical strategy for determining optimum fertilization in intensive pomelo production. In this study, we evaluated the soil quality status and mapped the spatial distribution of 347 soil samples collected from pomelo orchards in Pinghe County, southern China. We analyzed nine chemical parameters and an altitude indicator.

RESULTS

The mean soil quality index (SQI) was 0.355 in the total data set (TDS) and 0.292 in the minimum data set (MDS). Available Ca (Avail-Ca), pH value, organic matter and altitude were selected as indicators of soil quality in the MDS. The SQI in mature orchards (>10 years) was higher than that in young orchards (<10 years), while no differences between soil types and altitude gradients were identified. We detected a significant positive correlation between the SQI based on TDS (SQI_TDS ) and the SQI based on MDS (SQI_MDS ), and the spatial distribution of soil properties and SQI_TDS showed a uniform pattern, except for Avail-N, Avail-B and SQI_MDS . Overall, unfavorable soil quality indicators, including rich in Avail-P, deficient in Avail-Ca, -Mg and -B, soil acidification and high altitude, were considered to be limiting factors for pomelo production.

CONCLUSION

The soil chemical quality in pomelo orchards is generally low, indicating that integrated management by controlling acidification, reducing planting altitude, regulating fertilization and monitoring soil properties is required for sustainable pomelo production. © 2021 Society of Chemical Industry.

Effects of Thinning Intensity on Forest Floor and Soil Biochemical Properties in an Aleppo Pine Plantation after 13 Years: Quantity but Also Quality Matters

In order to quantify the impacts of silvicultural treatments in semiarid forests, it is necessary to know how they affect key aboveground processes and also properties characterizing the forest floor and mineral soil compartments. The general objective of this work is to study the mid-term effects of thinning intensity on forest floor and soil properties after 13 years following the intervention. The experimental design consisted of a randomized block design with four thinning treatments (3 thinning intensity plots plus a control or unmanaged plot) and three blocks or replicates. Several determinations, such as total organic carbon, dissolved organic carbon, or basal respiration, were performed for characterizing forest floor and mineral soil by considering three random sampling points per experimental plot. Thirteen years after thinning, total organic content, the different organic carbon fractions studied, and basal respiration were higher in the forest floor of the unmanaged plot. These results, however, were contrasted to those obtained for the mineral soil, where significant differences between the treatments were only observed in basal respiration and C/N ratio, while the different organic carbon fractions were not affected by thinning intensity. Our results suggest better soil quality where biological activity is enhanced as a consequence of improved environmental conditions and also litterfall input. The latter is especially important in forests with tree leaves of low biodegradability, where new understorey species promoted by thinning can provide higher nutrient availability for the remaining trees and, therefore, better forest resilience.

Soil Quality and Evaluation of Spatial Variability in a Semi-Arid Ecosystem in a Region of the Southeastern Iberian Peninsula (Spain)

In the last two decades, as the importance of soil has been recognized as a key component of any ecosystem, there has been an increased global demand to establish criteria for determining soil quality and to develop quantitative indices that can be used to classify and compare that quality in different places. The preliminary estimation of the attributes involved in soil quality was made taking into account the opinion of the experts and our own experience in a semi-arid ecosystem. In this study, 16 soil properties have been selected as potential indicators of soil quality, in a region between Campo de Montiel and Sierra de Alcaraz (Spain): sand and clay percentage, pH, electrical conductivity (EC), soil organic carbon (OC), extractables bases of change (Na, K, Ca and Mg), cationic exchange capacity (CEC), carbonate calcium equivalent (CCE), bulk density (BD), water retention at 33 kPa field capacity and 1500 kPa permanent wither point (GWC33 kPa and GWC1500 kPa), coefficient of linear extensibility (COLE) and factor of soil erodibility (K). The main objective has been to develop an adequate index to characterize the quality of the soils in a semi-arid Mediterranean ecosystem. The preliminary estimation of the attributes involved in soil quality was made considering the opinion of the experts and our own experience in semi-arid ecosystems. Two indicator selection approaches have been used to develop the Soil Quality Index (SQI) (total data set -TDS- and minimum data set -MDS-), scoring functions (linear -L- and nonlinear -NL-) and methods (additive -A-, additive weighted -W- and Nemoro -N-. The quality indices have been calculated, considering the properties of the soil control section (between 0 and 100 cm depth), using 185 samples, belonging to horizons A, B and C of 51 soil profiles. The results have shown that the election of the soil properties, both of the topsoil and subsoil, is an important help in establishing a good relationship between quality, soil functions and agricultural management. The Kriging method has been used to determinate the spatial distribution of the soil quality grades. The indices that best reflect the state of soil quality are the TDS-L-W and TDS-L-A should go as sub-indices, as they are the most accurate indices and provide the most consistent results. These indices are especially indicated when carrying out detailed or semi-detailed studies. However, the MDS-L-W and MDS-L-A should go as sub-indices, which use only a limited number of indicators, are best for large-scale studies. The indicators with the greatest influence on soil quality for different land uses and those developed on different rocks, using linear scoring functions, are the following: (Clay), (GWC1500 kPa) and (Ca). These results can also be expressed as follows: the best soils in this region are deep soils, with a clay texture, with high water retention and a neutral or slightly basic pH. However, the indicators with the greatest influence on soil quality, using nonlinear scoring functions, are: (OC Stock), (Ca) and (CaCO3). In other words, the most important indicator is the organic carbon content, which is not logical in the case of a region in which the soils have an excessively low SOC content (0.86%).

Evaluation of Soil Quality and Maize Growth in Different Profiles of Reclaimed Land with Coal Gangue Filling

Reclaiming subsidence and waterlogged zones caused by coal mining to maintain food and feed supplies is an urgent issue in China. Utilizing coal gangue (CG) as a filling matrix to construct different profiles of reclaimed land in coal mining subsidence has downsides, e.g., due to its low conservative capability of water-fertilizer and crop yield, its lack of quantitative evaluation of soil quality, and its limiting factors of crop growth. Quantifying the soil quality by principal component analysis (PCA), obtaining key soil indicators, and a scoring system can clarify the influence of the profile structure on soil quality and limiting productive factors of soil and ascertain the optimal profile. Soil quality was evaluated by the minimum data set (MDS) of soil quality index (SQI) obtained by PCA in seven different profiles of reclaimed plots constructed in a field with maize planting experiments. The agronomic traits of maize were analyzed and compared. The result shows that the pH value contributed highest in surface SQI value. Maximal and minimal SQI value is 0.57 and 0.18, respectively, the variation of SQI between different profiles reveals it increases with the increase in thickness of overburdens and decreases with the increase in soil interlayer depth of reclaimed land. SQI based on MDS has a correlation coefficient of 0.4280 with maize yield and the same sequence with comprehensive growth of maize in reclaimed plots. Agronomic traits of maize are positively correlated with the nutrient index and SM of the surface soil, and negatively correlated with pH, electrical conductivity (EC), and total salt content (TS). Choosing a thicker surface overburden and control pH of CG preceding filling can effectively augment soil quality and maize growth. This study provides the exploratory means and a scientific basis for the management and improvement of filling reclamation.

A critical review on performance indicators for evaluating soil biota and soil health of biochar-amended soils

Amendment of soil with biochar has been widely investigated for soil quality improvement in terms of biotic and abiotic functionalities. The performance of biochar-based amendment varies according to the site characteristics, biochar properties, and soil management targets. There is no existing review that summarizes a broad range of performance indicators to evaluate the health of biochar-amended soil. Based on the latest studies on soil amendment with biochar, this review critically analyzes the soil health indicators that reveal the potential impact of biochar amendment with respect to physicochemical properties, biological properties, and overall soil quality. It is found that soil pH, soil aggregate stability, and soil organic matter are the basic indicators that could influence most of the soil functions, which should be prioritized for measurement. Relevant functional indicators (e.g., erosion rate, crop productivity, and ecotoxicity) should be selected based on the soil management targets of biochar application in agricultural soils. With this review, it is expected that target-oriented performance indicators can be selected in future studies for field-relevant evaluation of soil amendment by biochar under different situations. Therefore, a more cost-effective and purpose-driven assessment protocol for biochar-amended soils can be devised by using relevant measurable attributes suggested in this review.

Improvements in soil quality with vegetation succession in subtropical China karst

Secondary vegetation succession can alter soil functions and quality. However, data on changes to soil quality at different stages of vegetation succession in karst areas of southwest China is limited. This study aimed to evaluate the effects of different vegetation succession on soil quality and further to identify the factors that influencing soil quality. Secondary forest, shrub, grass, and cropland (as a reference) were selected and sampled in the subtropical karst of southwest China. Soil quality index (SQI) was developed by two methods of Total Data Set (TDS) and Minimum Data Set (MDS). Based on principal component analysis (PCA), soil organic carbon, silt, available phosphorous, available potassium, soil thickness, and soil water content were identified as the most representative indicators for the MDS. Both methods showed that the highest SQI values were observed in secondary forest, followed by shrub and grass, and the cropland values were the lowest. This showed vegetation succession significantly influenced on soil physiochemical properties and thus on soil quality. MDS could adequately represent TDS to quantify the effects of vegetation succession on soil quality since similar SQI results were derived from the two methods (R² = 0.68, P < 0.01). The influencing factors explained about 75% of the total variation in SQI using a generalized linear model. Vegetation types accounted for the largest proportion of the SQI variability followed by restoration time, indicating these factors significantly affect soil quality during vegetation succession. In general, vegetation succession significantly influenced soil properties, and also has long-term and positive effects on soil quality during vegetation restoration. This study helps to understand the changes in soil quality during vegetation succession and provides guidance for the sustainable management of revegetation in subtropical karst regions in China.

Delimitation of supervision zones based on the soil property characteristics in a reclaimed opencast coal mine dump on the Loess Plateau, China

Supervision zones in a reclaimed coal mine refer to regions where soil properties are being slowly restored but further management is still urgently needed. The important roles of supervision zones in guiding the ecological restoration of degraded mining areas have been widely recognized, but the delimitation of supervision zones needs further examination. To delineate supervision zones for the restoration of poor soil properties, the soil available phosphorus (SAP), soil available potassium (SAK), soil total nitrogen (STN), soil organic matter (SOM), soil particle fractal dimension (SPD), soil electric conductivity (SEC), and soil pH (pH) at a depth of 0-20 cm were measured in a reclaimed dump in the Antaibao coal mine on the Loess Plateau of China. The spatial distribution of the soil properties was analyzed using geostatistical analysis, a fuzzy c-means clustering algorithm, and pedodiversity analysis. Then, the supervision zones were delimited based on the spatial characteristics of the reclaimed soil properties. The results revealed the following: (1) reclaimed soil in the study area was clustered into eight classes, and each soil class had one or more well-recovered soil properties, except for class I. Areas covered with only class I soil were delimited as poor-soil property regions. (2) The spatial distribution of the pedodiversity indexes of the reclaimed soil classes showed obvious aggregation characteristics, with extremely low values occurring mainly in the northeast and south of the study area. Two zones with low values of the Shannon index (H) were delimited as low-pedodiversity regions. (3) Four supervision zones with poor land reclamation effects were delimited based on the analysis of the poor-soil property regions and low-pedodiversity regions, and precise reclamation measures, including crop rotation, fertilization, neutralization, irrigation, and plowing, were proposed for each zone to improve the quality of the reclaimed soil.

Evaluating quality of soils formed on basement complex rocks in Kaduna State, northern Guinea savanna of Nigeria

A few investigations have been done regarding the soil quality index (SQI) for various locations, soil types, and states. Still, little has been reported regarding SQI for both surface and control sections, especially for the Northern Guinea Savanna of Nigeria. Due to the subsurface property pedogenic influence on soil function, it is crucial to assess SQI using surface and subsurface properties as both properties influence soil productivity. We investigated the potentials of choosing a minimum data set for soil quality indicators and assess soil quality (SQ), using both surface and entire soil pedon data for the soils on the basement complexes. Both additive and weighted soil quality indices and different scoring methods (linear and non-linear) were used in evaluating SQ. Out of the twenty-three soil properties subjected to PCA, eight indicators (TEB, clay, silt, K, EA, EC, BD, and Fe) were selected as the minimum data set (MDS). There was not much difference in the calculated soil quality using the non-linear additive (SQI-NLA), linear additive (SQI-LA), linear weighted (SQI-LW), and non-linear weighted (SQI-NLW) for the soils as they were all rated low (SQI < 0.55). The estimated SQI for the control section had relatively higher values than the surface soil, thus suggesting the need to incorporate both surface and entire soil profile properties in assessing SQ as both are important in integrating the relationship between soil properties and management goals which eventually provides complete information that affects the production of crops.

Assessment of Soil Quality under Different Soil Management Strategies: Combined Use of Statistical Approaches to Select the Most Informative Soil Physico-Chemical Indicators

Assessment of soil quality under different management practices is crucial for sustainable agricultural production and natural resource use. In this study, different statistical methods (principal component analysis, PCA; stepwise discriminant analysis, SDA; partial least squares regression with VIP statistics, PLSR) were applied to identify the variables that most discriminated soil status under minimum tillage and no-tillage. Data collected in 2015 from a long-term field experiment on durum wheat (Triticum durum Desf.) were used and twenty soil indicators (chemical, physical and biological) were quantified for the upper soil layer (0–0.20 m). The long-term iteration of different management strategies affected soil quality, showing greater bulk density, relative field capacity (RFC), organic and extractable carbon contents (TOC and TEC) and exchangeable potassium under no-tillage. PCA and SDA confirmed these results and underlined also the role of available phosphorous and organic carbon fractions as variables that most discriminated the treatments investigated. PLSR, including information on plant response (grain yield and protein content), selected, as the most important variables, plant nutrients, soil physical quality indicators, pH and exchangeable cations. The research showed the effectiveness of combining variable selection methods to summarize information deriving from multivariate datasets and improving the understanding of the system investigated. The statistical approaches compared provided different results in terms of variables selected and the ranking of the selected variables. The combined use of the three methods allowed the selection of a smaller number of variables (TOC, TEC, Olsen P, water extractable nitrogen, RFC, macroporosity, air capacity), which were able to provide a clear discrimination between the treatments compared, as shown by the PCA carried out on the reduced dataset. The presence of a response variable in PLSR considerably drove the feature selection process.

An Approach to Thresholds for Evaluating Post-Mining Site Reclamation

Here, a time-scale conceptual threshold model for assessing, evaluating, documenting, and monitoring post-mining sites reclamation progress was developed. It begins from initial state I0 down to degraded state D0 (which depends on the mining). Reclamation starts with soil reconstruction R−2 up to revegetation R−1 (red zones) to reach minimum threshold R0 (amber zone). Beyond R0 are green zones R1, R2, and R3 representing soil/abiotic conditions, biological, and improved threshold, respectively. The model also identifies potential drivers, land-use options, targets, and endpoints along the threshold reclamation ladder. It is applicable to all degraded ecosystems and adoptable in national and international laws. In this approach study, we identified threshold biotic/abiotic indicators for ascertaining success from R0, future work focuses on measurement and ascribing of threshold values to each of the threshold stage.

Soil environmental quality in Nanling commodity grain base based on equal intercept transformation radar chart

This paper introduces for the first time the equal intercept transformation radar chart—an improved form—to the assessment of soil environmental quality of Nanling commodity grain base. The equal intercept transformation radar chart, a visual graphical data analysis method, translates data from a numerical to graphical format. This visualization enables data presentation, analysis process and results stick out a mile and is capable of fully retaining information contained in data and excavating it in depth from geometry. Moreover, it overcomes pertinently the main defect of the conventional radar chart that the evaluation result depends heavily on the order of arrangement of indicators. The results indicated that the soil environmental quality at depths of 0–60 cm in the low mountain area of the Nanling commodity grain base was the second grade, while that in the hilly and plain areas were both first grade. The indicators of poor soil environmental quality in the low mountain area were exogenous Cd and endogenous As; those in the hilly area were exogenous Cd and endogenous As and Hg; and that in the plain area was exogenous Cd. The results were in line with the actual situation of the study area.

Digital technology dilemma: on unlocking the soil quality index conundrum

Knowledge of the interactions between soil systems, management practices, and climatic extremes are critical for prescription-based sustainable practices that reduce environmental pollution/footprints, disruption of food supply chains, food contamination, and thus improve socio-economic wellbeing. Soil quality status and dynamics under climate change present both a hazard which may not be remedied by simply adding chemicals or improved by crop varieties, and an opportunity (e.g., by indicating impact of a shift in land use) although the specifics remain debatable. This entry not only revisits the science of soil quality determination but also explicates on intricacies of monitoring using big data generated continuously and integrated using the "internet of things." Indeed, relaying credible soil quality information especially for heterogeneous soils at field scale is constrained by challenges ranging from data artifacts and acquisition timing differences, vague baselines, validation challenges, scarcity of robust standard algorithms, and decision support tools. With the advent of digital technology, modern communication networks, and advancement in variable rate technologies (VRT), a new era has dawned for developing automated scalable and synthesized soil quality metrics. However, before digital technology becomes the routine tool for soil quality sensing and monitoring, there is need to understand the issues and concerns. This contribution not only exemplifies a unique application of digital technology to detect residue cover but also deliberates on the following questions: (1) is digital agriculture the missing link for integrating, understanding the interconnectivity, and ascertaining the provenance between soil quality, agronomic production, environmental health, and climate dynamics? and (2) what are the technological gaps?

Abiotic Soil Health Indicators that Respond to Sustainable Management Practices in Sugarcane Cultivation

Soil quality (SQ) assessments are fundamental to design more sustainable land uses and management practices. However, SQ is a complex concept and there is not a universal approach to evaluate SQ across different conditions of climate, soil, and cropping system. Large-scale sugarcane production in Brazil is predominantly based on conventional tillage and high mechanization intensity, leading to SQ degradation. Thus through this study, we aim to assess the impact of sustainable management practices, including cover crops and less intensive tillage systems, in relation to the conventional system, using a soil quality index composed of abiotic indicators. Additionally, we developed a decision tree model to predict SQ using a minimum set of variables. The study was conducted in the municipality of Ibitinga, São Paulo, Brazil. The experimental design used was in strips, with four cover crops and three tillage systems. We evaluated three sugarcane cultivation cycles (2015/16, 2016/17, and 2017/18 crops). To calculate the SQ index, we selected five abiotic indicators: macroporosity, potassium content, calcium content, bulk density, and mean weight-diameter of soil aggregates. Based on our SQ index, our findings indicated that the soil quality was driven by the production cycle of sugarcane. Although a reduction of soil quality occurs between the plant cane and first ratoon cane cycles, from the second ratoon cane there is a trend of the gradual restoration of soil quality due to the recovery of both the soil’s physical and chemical attributes. Our study also demonstrated that the cultivation of sunn hemp and millet as cover crops, during the implementation of sugarcane plantation, enhanced soil quality. Due to the advantages provided by the use of these two cover crops, we encourage more detailed and long-term studies, aiming to test the efficiency of intercropping involving sunn hemp and millet during the re-planting of sugarcane.

Construction of a combined soil quality indicator to assess the effect of glyphosate application

Although the use of agrochemicals allowed increasing the crops productivity, in many cases led to soil deterioration. In this study, eight composite samples from different soils of two locations (San Martín and Anta) in Salta, Argentina, were collected and analyzed. All the samples were from loamy Entisols (0-20 cm depth) under reduced tillage without and with direct spray application of glyphosate. Twenty six variables were determined (physical, chemical, and biological soil quality indicators). From them, those of higher specificity and sensitivity to changes following glyphosate application were identified by a stepwise reduction of variables aided by statistical analysis. Samples were grouped regarding location and application of glyphosate, to identify differential effects upon variables, and glyphosate sensitive variables were selected by discarding those influenced by other factors. Thence, they were used to compose a first approximation to a combined soil quality indicator (CSQI) to assess the effect of glyphosate use in agriculture upon the soil. Overall, the set of physical variables showed the same discriminating structure as the biological set. Finally, two biological, two chemical, and two physical indicators resulted as the most specific to quality variations by the application of the herbicide, being the most sensitive the microbial biomass carbon and the (Aminomethyl)phosphonic acid concentration in soil. When these two were considered into a CSQI, it was possible to discriminate samples with the application of glyphosate (lower quality) from those without application (higher quality). To the best of our knowledge, this is the first attempt to propose a CSQI that could play an important role to prevent degradation in soils subjected to glyphosate application, as it could aid in the early detection of soil quality loss. This would provide to land managers a decision tool to let the land rest from glyphosate application, to ensure sustainable practices in agriculture.

Effect of reclamation treatments on microbial activity and phytotoxicity of soil degraded by the sulphur mining industry

The aim of the work was to determine the trend, intensity and changes of selected microbial and phytotoxic parameters of degraded soil in the area of former sulphur mine reclaimed by post-flotation lime (PFL), sewage sludge (SS), mineral wool (MW- mixed with soil, MWP-pad) and mineral fertilizer (NPK). The following parameters: number of proteolytic bacteria and fungi, ammonification, nitrification, activities of alkaline phosphatase and arylsulphatase Lepidium sativum growth index (GI) and phenolic compounds were analysed in the soil in second and third year of the experiment. The addition of the SS separately or in combination with other remediation agents was found to be the most valuable for the number of microorganisms, intensification of nitrification process and enzymatic activities. In objects where other materials were added without sewage sludge, the inhibition of fungal growth as well as alkaline phosphatase and arylsulphatase activities was observed, however the inhibitory effect declined with time. The observed increase of GI shows the long-term, positive effect of treatments on soil properties concerning plant growth. The use of lime and lime together with sewage sludge contributed to the decrease in the content of phenolic compounds in the reclaimed soil.

Comprehensive assessment of paddy soil quality under land consolidation: a novel perspective of microbiology

Soil quality assessment is an important means to demonstrate how effective land consolidation is. However, the existing assessment system is not sufficient to reflect actual soil quality. So, the purpose of this study is to integrate abiological and biological indicators into a comprehensive assessment to evaluate the paddy soil quality under different land consolidation practices. Soil samples were collected from 35 paddy sites under different land consolidation practices including land merging, land leveling (LL), ditch construction (DC) and application of organic fertilizer (AO). A total of 10 paddy sites were selected under conventional tillage (CT) from non-land consolidation area as a control group in Y county, China. The results indicated that soil organic matter (OM), total nitrogen (TN), available phosphorus, bacterial functional diversity (BFD), bacterial and fungal abundances were significantly improved. Fields under LL, among all the land consolidation practices, might still face the risk of land degradation caused by low TN, OM and microbial diversity. High microbial biomass, BFD and OM were significantly higher in fields under AO in nutrient cycle. According to the results of comprehensive assessment, the samples with severe heavy metal contamination and low microbial diversity were generally concentrated in CT. These results indicated that land consolidation was an efficient technique to improve soil quality and could achieve higher quality of agricultural products.

Using a modified soil quality index to evaluate densely tilled soils with different yields in Northeast China

Northeastern China has long-term densely tilled soils that supply approximately 20% of the annual total national grains. There are very few reports on the agricultural soil quality subjecting to the predatory tillage. Here, the soil quality index (SQI) of a brunisolic soil was calculated using the minimum data set (MDS) and integrated quality index (IQI). The topsoil layer was divided into plow layer (11.9 ± 1.9 cm) and plow pan (11.4 ± 2.6 cm) in fields of high yields (HYB), medium yields (MYB), and low yields (LYB). Our results showed that the MDS of the topsoil layer only contained chemical indicators. The bulk density (BD), as one of the most important soil quality indicators, was found of no significant differences in the topsoil layers. In different layers (i.e., the topsoil layer, plow layer, and plow pan), the value of SQI presented a consistent tendency of HYB &gt; MYB &gt; LYB (p &lt; 0.05). The correlation between SQI and yield was higher in the plow layer (0.60) and plow pan (0.63) than the topsoil layer (0.47). This further verified the reasonability of using soil stratification for SQI calculation. Our findings indicate the potential of using soil quality assessments to examine soil productivity (e.g., fertilizer deficiency) in crop lands with soil stratification.

Island soil quality assessment and the relationship between soil quality and land-use type/topography

Information about the soil quality of different land-use types and topographies is essential for the sustainable development, utilization, and protection of soil resource in coastal areas. In this study, representative topsoil samples were collected from Liandao Island, China, and soil water content (SWC), soil bulk density (BD), total nitrogen (TN), soil organic matter (SOM), ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃^--N), available phosphorus (AP), available potassium (AK), soil salt content (SSC), and pH were recorded. The suitable minimum soil data set (MDS) was computed by principal component analysis (PCA) and the soil quality index (SQI) was then determined. The spatial distribution of the SQI was analyzed using ordinary kriging interpolation. The effects of topographical parameters (digital elevation model [DEM], slope, and aspect) and land-use types (vegetation [V], water resource conservancy land [WRC], sandy land [SL], unused land [UL], and built-up land [BL]) on SQI were then analyzed in detail. The parameters included in the MDS were TN, pH, and BD, which together accounted for 84.371% of the variation in soil quality. The SQI varied from 0.189 to 0.772 in the study area. The correlation coefficients between SQI and DEM, slope, and aspect were 0.498, 0.294, and 0.137, respectively (p < 0.01). The highest SQI score was found at an elevation of 110 m, with a slope of 68.2° and an aspect of 246.6, in the vegetation land-use type. Soil quality differed significantly (p = 0.0000) among the land-use types, with the following ranking: V > UL > SL > BL. Our results provide land managers with an important reference for the development, utilization, and protection of soil resource in coastal zones such as Liandao Island, China.

Integrating management information with soil quality dynamics to monitor agricultural productivity

Sustainably utilizing global resources is critical for ensuring soil security which is pertinent for biomass production, climate change mitigation, environmental quality, biodiversity conservation and thus human wellbeing. A plethora of soil quality assessment metrics encapsulated in different concepts exist, with each typically biased towards identifying the interrelationship between agricultural production and specific physical, chemical or biological soil attributes. Because of diversity in soil classifications and crop requirements, considerable variation exist between these metrics making it difficult for end-users to select a suitable method. Here, Partial Least Squares Regression (PLSR) method is used to integrate the physical and chemical soil properties into a Soil Quality Index (SQI) which is then used to evaluate soil quality dynamics vis-à-vis crop yields over two growing seasons. Field data was acquired from 5 sites under No-Till (NT), Conventional Till (CT) management and Natural Vegetation (NV) land use. This SQI was computed under the hypothesis that site specific soil physico-chemical attributes depended on soil type, management, and depth. Under CT management Pw (Pewamo silty clay loam) had the highest soil quality; KbA (Kibbie fine sandy loam) soils had higher quality under NT management; whereas CtA (Crosby Celina silt loams) had relatively higher quality under NV land use. Soil bulk density (ρb), Soil Organic Carbon (SOC), Available Water Content (AWC) and Electrical Conductivity (EC) were the significant soil parameters influencing soil quality. The correlation between SQI and corn (Zea mays) yields was 0.6, whereas SQI and Soybean (Glycine max (L.) Merr.) yield was 0.9. Future research will evaluate SQI dynamics vis-à-vis socio-economic indicators and key climate variables.

A new method for soil health assessment based on Analytic Hierarchy Process and meta-analysis

Understanding soil health condition is essential to the sustainability and stability of the entire ecosystem of farmland. The primary objective of this study was to improve the soil health index (SHI) based on principle component analysis (PCA) and develop a new analysis method for soil health assessment based on Meta-Analytic Hierarchy Process (Meta-AHP), which provides consistent minimum data sets (MDS), weight and scoring function for different locations, studies and management. The thirteen variables of MDS that exhibited sensitivity to management between organic and conventional soil were selected by meta-analysis. The indicator weight was assigned by a combination of experts scoring, AHP and meta-analysis. To test the applicability and sensitivity of the soil health assessment by Meta-AHP, a sixteen-year long-term test was assessed by the conventional SHI method (cSHI) and Meta-AHP. The results showed that similar evaluation results and significant positive correlations (**P < 0.01, n = 9) between the two evaluated methods were observed, and the results calculated using Meta-AHP had the best discrimination under different plant systems due to the higher F values when compared with the cSHI. This study developed a sensitive and consistent SH assessment framework that can be used applied to a variety of location, study, and soil management systems.

Mapping soil organic matter in the Baranja region (Croatia): Geological and anthropic forcing parameters

Spatial mapping of soil organic matter (SOM) and evaluation of the related natural and anthropic influencing factors are crucial to monitor the extent of degraded land and the evolution of soil functions. The objective of this work is to study the spatial distribution of SOM in a highly exploited agricultural area in the Baranja Region (Croatia). The spatially dense dataset available (4825 top-soil samples from 0 to 30 cm) allowed to produce reliable SOM maps using geostatistical interpolation kriging algorithms and to study the relationships with possible influencing factors. The interpolation has been conducted by means of two approaches. In one approach, the overall data set is considered for computing a global variogram and performing a direct interpolation of SOM values. In the second approach, the data are stratified according to two different geological and morphogenetic domains, Holocene Domain (HD) and Pleistocene Domain (PD), and a distinct geostatistical analysis is performed in each domain. The results showed that average SOM in the studied region was 2.29%, indicating a future need for adopting sustainable soil management practices in this region. SOM was significantly higher in HD (2.64%) than PD (1.97%) domain. SOM in PD generally had a much lower global variability. Global dataset analysis reveals that regional intrinsic factors prevail over local intrinsic and extrinsic factors in determining SOM spatial patterns. In contrast, the stratified approach can filter the effect of regional variability related to the main geological and geomorphological setting. The structural spatial correlation in PD is weaker than in HD, as manifested by spatial patches of low and high SOM content with smaller extension in PD with respect to HD. The strong relationships between SOM spatial patterns and geological/geomorphological factors suggest the possibility of adopting finer subdivision criteria in future research.

Selecting the minimum data set and quantitative soil quality indexing of alkaline soils under different land uses in northeastern China

Understanding the influences of land use conversions on soil quality (SQ) and function are essential to adopt proper agricultural management practices for a specific region. The primary objective of this study was to develop soil quality indices (SQIs) to assess the short-term influences of different land uses on SQ in semiarid alkaline grassland in northeastern China. Land use treatments were corn cropland (Corn), alfalfa perennial forage (Alfalfa), monoculture Lyemus chinensis grassland (MG) and successional regrowth grassland (SRG), which were applied for five years. Twenty-two soil indicators were determined at 0-20cm depth as the potential SQ indicators. Of these, thirteen indicators exhibited treatment differences and were identified as the total data set (TDS) for subsequent analysis. Principal component analysis was used with the TDS to select the minimum data set (MDS), and four SQIs were calculated using linear/non-linear scoring functions and additive/weighted additive methods. Invertase, N:P ratio, water-extractable organic carbon and labile carbon were identified as the MDS. The four SQIs performed well, with significant positive correlations (P<0.001, n=16) among them. However, the SQI calculated using the non-linear weighted additive integration (SQI-NLWA) had the best discrimination under different land-use treatments due to the higher F values and larger coefficient of variance as compared to the other SQIs. The SQI value under the MG treatment was the highest, followed by that under the SRG and Alfalfa treatments, and all of these were significantly higher than that of Corn treatment. These results indicated that conversion of cropland to perennial forage or grassland can significantly improve the SQ in the Songnen grassland. In addition, SQI-NLWA can provide a better practical, quantitative tool for assessing SQ and is recommended for soil quality evaluation under different land uses in semiarid agroecosystems.

Soil Quality Indexing Strategies for Evaluating Sugarcane Expansion in Brazil

Increasing demand for biofuel has intensified land-use change (LUC) for sugarcane (Saccharum officinarum) expansion in Brazil. Assessments of soil quality (SQ) response to this LUC are essential for quantifying and monitoring sustainability of sugarcane production over time. Since there is not a universal methodology for assessing SQ, we conducted a field-study at three sites within the largest sugarcane-producing region of Brazil to develop a SQ index (SQI). The most common LUC scenario (i.e., native vegetation to pasture to sugarcane) was evaluated using six SQI strategies with varying complexities. Thirty eight soil indicators were included in the total dataset. Two minimum datasets were selected: one using principal component analysis (7 indicators) and the other based on expert opinion (5 indicators). Non-linear scoring curves were used to interpret the indicator values. Weighted and non-weighted additive methods were used to combine individual indicator scores into an overall SQI. Long-term conversion from native vegetation to extensive pasture significantly decreased overall SQ. In contrast, conversion from pasture to sugarcane had no significant impact on overall SQ at the regional scale, but site-specific responses were found. In general, sugarcane production improved chemical attributes (i.e., higher macronutrient levels and lower soil acidity); however it has negative effects on physical and biological attributes (i.e., higher soil compaction and structural degradation as well as lower soil organic carbon (SOC), abundance and diversity of macrofauna and microbial activity). Overall, we found that simple, user-friendly strategies were as effective as more complex ones for identifying SQ changes. Therefore, as a protocol for SQ assessments in Brazilian sugarcane areas, we recommend using a small number of indicators (e.g., pH, P, K, Visual Evaluation of Soil Structure -VESS scores and SOC concentration) and proportional weighting to reflect chemical, physical and biological processes within the soil. Our SQ evaluations also suggest that current approaches for expanding Brazilian sugarcane production by converting degraded pasture land to cropland can be a sustainable strategy for meeting increasing biofuel demand. However, management practices that alleviate negative impacts on soil physical and biological indicators must be prioritized within sugarcane producing areas to prevent unintentional SQ degradation over time.