Potential Soil Quality Indicators Research Articles

Assessing the Alteration of Soil Quality under Long-Term Fertilization Management in Farmland Soil: Integrating a Minimum Data Set and Developing New Biological Indicators

The key role of soil quality improvement in achieving sustainable agricultural development based on highly intensive use of farmland is increasingly being recognized, as is the ponderance of suitable evaluation of the soil quality. The overarching goal of this study was to determine an accurate assessment framework by the comparison of the scoring function (linear and non-linear) and integration method (area and weighted additive), which integrally evaluates the soil quality of an eleven-year field fertilization experiment (including CK, no fertilizer; CF, conventional fertilization; SF, formulated fertilization; SFO, SF with organic fertilizer). Thirty-three properties, including eighteen physiochemical-related and fifteen biological-related properties, associated with soil functions were measured as potential soil quality indicators, and the soil multifunctionality (SMF) was applied to validate the soil quality indices (SQIs). Principal component analysis and relationship analysis were used with indicators sensitive to management to determine a minimum data set (MDS). The results showed that the electrical conductivity, large macroaggregate-associated total nitrogen, small macroaggregate-associated organic carbon, carbon fixation, and enzyme activities of phenol oxidase and cellulase were chosen as the MDS. All the SQIs were significantly correlated with the SMF (p < 0.05). The fertilization strategies affected most indicators in different ways, and the index developed using the non-linear function and weighted additive integration method (SQI-NL) had the best sensibility and discriminability. The SQI value with the SQI-NL-MDS method was higher following the fertilization treatments than that of no fertilizer (p < 0.05), and the treatment of the organic fertilizer had the highest SQI value (0.66). Soil quality evaluation in long-term fertilized farmland suggested that the soil quality constraints between treatments of synthetic and organic fertilizer are related to the soil functions of nutrient cycling and sustain biological activity due to their higher contribution rates to the SQI in the organic fertilizer treatment, which provides insights into ways to reduce the gap in soil quality. The framework method can provide an accurate quantitative tool for the evaluation of soil quality from the target indicators by bridging management objectives and field-level actions.

Effect of Different Levels of Sodicity on Soil Enzymes, Soil Microbial Biomass Carbon and Activity of Antioxidant Enzymes in Different Rice Varieties under Semi-arid Conditions

Background: Soil sodicity is a major abiotic stress for crop production in many parts of the world. Soil enzymes have been proposed as potential indicators of soil quality due to their connection to soil biology, ease of measurement and quick responsiveness to changes in soil management. Concerning that how different levels of sodicity affects the activity of soil enzymes, soil MBC and antioxidant enzymes in different rice varieties will promote us to understand the mechanism behind the tolerant varieties and to find out the ways to improve the tolerance mechanism. Methods: A field experiment was conducted at Anbil Dharmalingam Agricultural College and Research Institute, Tiruchirappalli, Tamil Nadu during late samba season. Different rice varieties viz., TRY 1, CO 43, TRY 2, CSR 27, TRY 3 and white ponni (WP) were grown at different levels of Exchangeable Sodium Percentage (ESP) ie., 8, 16, 24, 32, 40 and 48 under field condition. The soil samples were collected at flowering stage and analyzed for urease, alkaline phosphatase (APH), dehydrogenase (DHG) and soil microbial biomass carbon (MBC). The plant samples collected at flowering stage were examined for activity of antioxidant enzymes like catalase (CAT), peroxidase (POX) and superoxide dismutase (SOD). Result: The growth and yield decreases with increasing sodicity levels. The soil enzyme and microbial biomass carbon found to be decreased with increasing ESP levels. The antioxidant enzyme increases with increase in sodicity levels in tolerant varieties and decreases at high ESP levels in susceptible varieties. Overall TRY 3 outperformed under increasing sodicity levels compared to other varieties.

Multiple soil quality assessment methods for evaluating effects of organic fertilization in wheat-maize rotation system

Soil degradation is a common phenomenon in smallholder farmlands in Asia and Africa. To mitigate soil degradation and the subsequent elevation in agricultural productivity, it is crucial to improve soil quality using a low-cost and time-saving organic fertilization technique. Although the soil quality index (SQI) has been widely used to assess and monitor soil quality in degenerative farmlands, studies comparing SQI calculation methods are rare. The specific objectives of this study were to (1) compare the differences in SQIs calculated using principal component analysis, factor analysis, discriminant analysis, partial least squares discriminant analysis (PLS-DA), and hierarchical clustering; (2) analyze the effects of organic fertilization on soil quality in smallholdings; and (3) determine the correlations among organic fertilizer rate, soil quality, and crop yield. We analyzed 37 soil physical, chemical, and biological properties under three organic fertilization groups [high organic fertilizer group (HOF), low organic fertilizer group (LOF), and no organic fertilizer group (NOF)] as potential soil quality indicators by using multiple assessment methods in the wheat-maize rotation system in Quzhou County, North China Plain, China. SQIs calculated using PLS-DA and the nonlinear scoring method had the best discrimination ability. Compared with the NOF group, the HOF and LOF groups exhibited an increase in SQIs by 6.93–36.99% and 3.98–26.76%, respectively. The high rate of application of organic fertilizers improved soil quality and enhanced crop yield. Moreover, soil quality was positively correlated with crop yield. These results confirmed the feasibility of using organic fertilizers for soil quality improvement and implied PLS-DA to be an effective method for selecting the minimum dataset for soil quality assessment.

Establishing a soil quality index to evaluate soil quality after afforestation in a karst region of Southwest China

The improvement of soil quality (SQ) evaluation tools can contribute to more precise and efficient monitoring of SQ changes under different management practices. This study aimed to establish an effective and accurate soil quality index (SQI) using different indicator selecting methods (MDS, minimum data set; RMDS, revised minimum data set) and different weighted additive approaches (variance and communality weighted) to assess the effect of the conversion of farmland (FL) to three land use types (BA, bamboo forest; LAT, landscape tree planting; ORO, orange orchard) converted from similar farmland on SQ in a karst region of Southwest China. Six physical indicators, nine chemical indicators and seven biological indicators were measured at the 0–20 cm depth as potential SQ indicators. Four chemical indicators, including the very labile carbon fraction (LCF), macroaggregate-associated organic carbon, total potassium (TK) and available phosphorus, were identified as the MDS using principal component analysis. However, one physical indicator (sand), two chemical indicators (LCF and TK) and one biological indicator (bacterial Shannon diversity index) were retained in the RMDS. The average sensitivity index value of the SQIs calculated using the RMDS was 39.54% higher than that of the SQIs determined using the MDS. The range (max.-min.) of weighting values calculated by variance (0.55 and 0.10 for the MDS and RMDS, respectively) among the chosen soil indicators was greater than that calculated by communality (0.07 and 0.02 for the MDS and RMDS, respectively). The high sensitivity index value and great range of weighting values indicated that the SQI calculated by the RMDS and variance weighted exhibited better performance and discrimination in the evaluation of SQ than other SQIs. The SQI value under BA was the highest, followed by that under ORO and FL, and LAT had the lowest SQI value. In conclusion, land use changes significantly alter the SQ in Southwest China, and the SQI developed using the RMDS approach and the variance weighted method is recommended as a sensitive and effective tool for SQ evaluation under different land uses in Southwest China and other regions.

Response of Potential Indicators of Soil Quality to Land-Use and Land-Cover Change under a Mediterranean Climate in the Region of Al-Jabal Al-Akhdar, Libya

Conversion of native lands into agricultural use, coupled with poor land management practices, generally leads to changes in soil properties. Understanding the undesirable effects of land-use and land-cover (LULC) changes on soil properties is essential when planning for sustainable land management. This study was conducted in Al Jabal Al Akhdar region, Libya, to assess the effects of land-use and land-cover changes on soil quality inferred by analyzing the relative changes in 17 chemical, physical, and biological soil properties in the upper layer (0–20 cm) of disturbed and undisturbed soil systems. Soil samples were collected from 180 sampling sites with 60 from each of the three types of LULC prevalent in the study area: natural Mediterranean forests (NMF), rainfed agriculture (RA), and irrigated crops (IC). The soil properties of the two agricultural land uses were compared with soil properties under an adjacent natural forest, which served as a control to assess changes in soil quality resulting from the cultivation of deforested land. The results indicate significant reductions in most soil quality indicators under rainfed agriculture as compared to native forest land. Under irrigated agriculture, there were significant changes (p ≤ 0.05) in most of the soil quality indicators, generally, indicating a significant reduction in soil quality, except for improvement of nitrogen and phosphorus levels due to frequent fertilizer application. Our data support the notion that changes in land use and land cover, in the absence of sustainable management measures, induce deterioration of soil properties and ultimately may lead to land degradation and productivity decline.

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%).

Soil quality assessment via the factor analysis of karst rocky desertification areas in Hunan, China

AbstractQuantitative evaluation of soil quality (SQ) is of paramount importance to provide a basis for restoring degraded land that affects the living conditions of people in these degraded areas. Amongst land degradation types, karst rocky desertification (KRD) is caused by human disturbance on a fragile karst geo‐ecological environment. However, SQ evaluations have not been widely and correctly used in KRD soil systems due to the complex soil conditions and lack of uniform standards. SQ evaluation can be qualitatively and quantitatively calculated. Soil quality index (SQI) can be used more frequently due to its simplicity and quantitative flexibility. To quantitatively analyse the SQ of four KRD grades in Hunan Province in China, 25 soil properties at 0–20 cm were identified as potential SQ indicators. SQ was assessed via SQI based on a total data set (TDS) and a minimum data set (MDS). Similar to grey relational analysis (GRA), the SQI was ranked as follows: potential KRD>moderate KRD>light KRD>intensive KRD. Total phosphorus, pH, calcium, clay, capillary porosity, biomass nitrogen and microbial biomass phosphorus were selected into the MDS, and they were sensitive to SQ. However, available phosphorus and soil organic carbon were not selected in the MDS. Soil quality in KRD areas could be quantitatively evaluated using SQI via factor analysis. SQ assessment based on the MDS can represent TDS to reduce labour intensity and detection costs. The quantification of SQ under different KRD grades can provide reference for improving SQ in limestone rocky desertification areas.

Assessment of Soil Quality under Different Agricultural Land Use Systems: A Case Study of the Ibadan Farm Settlement

Soil quality in an agroecosytem is considerably influenced by land use and management practices. Twenty two potential soil quality indicators were used to assess the effects of five different land use types (arable land, plantation, agroforestry, marginal land and native forest) on soil quality in Akufo and Atan farm settlements in Ibadan, southwestern Nigeria. A total of sixty-two fields were selected from which soil samples were taken at a depth of 0-15 cm and subjected to laboratory analysis. Majority of the evaluated physicochemical properties varied significantly among the land uses and whereas native land performed relatively better for most of the observed attributes, arable and marginal lands performed worse. Due to the moderate to strong significant correlation among the potential indicators, they were subjected to principal component analysis and only seven indicators were selected to compute the soil quality index (SQI). In both Akufo and Atan, native land had the highest SQI (0.8250 and 0.860 respectively) which was significantly different (P = .05) from all the agricultural land uses, except plantation (0.739 and 0.750 respectively). Whereas marginal field in Atan was most degraded (SQI = 0.455), it was closely followed by arable fields in both locations. This study indicates that the current agricultural land use and soil management practices in Akufo and Atan farm settlements have negatively impacted soil quality; however, the degree of degradation was strongly influenced by the concentration of soil organic carbon in the understudied land use systems. It also emphasizes the need to promote the use of sustainable management practices among agricultural land users, so as to increase soil organic carbon stock, and improve soil quality and land productivity.

Soil quality response to organic amendments on dryland red soil in subtropical China

Organic fertilizer applications can increase soil fertility and productivity and reduce chemical fertilizer use. However, few experimental studies have focused on effects of organic fertilizers on soil quality in a field ecosystem. The overarching goal of this study was to develop a soil quality index (SQI) for fertilization management in red soil farmland in China. The specific objectives were to determine 1) appropriate soil quality indicators, 2) a suitable weight assignment method (PCA, principal component analysis or MRA, multiple regression analysis) and 3) the optimal scoring function (standard or linear or non-linear). We analyzed 40 soil physical, chemical, biochemical and biological properties under nine fertilization treatments (CK (no fertilizer), CF (chemical fertilizer), RF (60% chemical fertilizer), CFS (chemical fertilizer + straw), RFS (60% chemical fertilizer + straw), CFB (chemical fertilizer + biochar), RFB (60% chemical fertilizer + biochar), RFP (60% chemical fertilizer + pig manure), RFV (60% chemical fertilizer + vermicompost)) as potential soil quality indicators. Principal component analysis and correlation analysis were applied to determine the indicators responsive to management and for the confirmation of the six SQIs. Available phosphorous, nitrogen, potassium and gram-positive bacteria were chosen as the minimum data set from the total of 40 soil indictors. Management of organic and inorganic fertilizers affected each soil property in different ways, and the index based on the minimum data set, calculated using standard scoring function and weight assignment method of multiple regression analysis, was most accurate and sensitive. Application of a pig manure or vermicompost significantly increased SQI values relative to other treatments, followed by straw or biochar treatments which were higher than a single application of chemical fertilizer. These results indicate that the addition of organic fertilizers will not only improve soil quality, but also enhance rapeseed and sweet potato yield compared to chemical fertilizers. Additionally, the SQI method can provide a practical and quantitative tool for the evaluation of soil quality.

Quantifying soil quality in a horticultural-cover cropping system

Understanding and interpretation of soil quality is crucial to strategize land management practices for sustaining agricultural productivity while mitigating environmental degradation. A medium-term cover crop (CC) trial, established in 2007 and repeated in 2008, at Ridgetown, Ontario was used to evaluate the comprehensive assessment of soil health (CASH), to develop a weighted soil quality index (WSQI), and to compare scores of CASH, Haney soil health test (HSHT), and WSQI in surface soil (15 cm) in 2015 and 2016 (herein referred to as site-years). Out of 25 potential soil quality indicators, 19 soil indicators were responsive to CC treatments and represented a total dataset. Using principal component analysis (PCA) of the total dataset, a minimum dataset (five indicators; pH, organic matter (OM), Solvita labile amino N (SLAN), Solvita CO2-burst, and water extractable organic C (WEOC)) was identified to calculate a WSQI. The WSQI and CASH scores were equivalent in detecting CC treatment differences in site-year 2015, but CASH detected greater magnitude (12.1%) of treatment differences than WSQI (5.7%) in site-year 2016. Cereal rye and a mixture of oilseed radish and rye (OSR + Rye) led to greater soil quality values than other tested CCs. Our results indicate the potential of CCs in significantly improving soil quality in the medium-term (6 years). This study is the first independent evaluation of CASH in a horticultural system in a humid, temperate climate, and first study to compare WSQI with commercial soil quality tests. Even though CASH and WSQI differentiated between CC treatments for soil quality evaluation in both site-years, we recommend WSQI as a valuable and practical tool (lesser number of indicators; five vs. 15), for quantifying soil quality in similar production regions and climatic conditions.

Minimum data set for evaluation of stand density effects on soil quality in Larix principis-rupprechtii plantations in North China

Soil quality index (SQI) was an important tool for evaluating soil quality (SQ). The aim of the study was to evaluate the stand density effects on SQ for Larix principis-rupprechtii plantations in North China. After eight years of thinning, SQ evaluation was used a SQI method to provide targeted and theoretical basis for the reasonable management and soil restoration. The study was conducted on twelve experimental sample plots classified by four levels of stand density (CK, HD, MD, LD), which were formed by 0%, 14%, 28% and 42% thinning, respectively. Thirty-nine soil physical, chemical and biological properties were measured at 0–20 and 20–40 cm depths as potential SQ indicators. The SQI was calculated using a minimum data set (MDS), the non-linear scoring method, followed by weighted additive (SQIw) and nemoro (SQIn) integration. Fungi, OM (soil organic matter) and G+:G− (the concentration ratio of Gram-positive bacteria to Gram-negative bacteria) were identified as the MDS. Both SQIw and SQIn performed well, with significant differences (P < 0.001, at both soil depths) among four stand densities after 8 years of thinning. However, the SQIw was superior to the SQIn for showing differences among the four stand densities due to the higher F values and larger coefficient of variance. The results showed that decrease of stand density (caused by thinning) resulted in a positive effect on SQ, and the highest values of SQI occurred in MD stands. Density management of around 1495 trees ha−1 (MD) was beneficial to the maintenance of SQ for Larix principis-rupprechtii plantations in North China. Additionally, the SQI method could provide a practical, quantitative tool for evaluating SQ in plantations, and provide reference for other tree species or other regions.

Influence of Tillage Practices, Organic Manures and Extrinsic Factors on β-Glucosidase Activity: The Final Step of Cellulose Hydrolysis

β-glucosidase is a key enzyme in the C-cycle, and its activity is strongly influenced by soil management practices and by extrinsic factors such as weather conditions. However, the variability of β-glucosidase activity (BGa) over time and how this variability is affected by tillage and organic fertilization remain poorly elucidated. We investigated how contrasting tillage practices (zero, minimum, conventional or deep) and organic amendment application (dairy cattle slurry or green compost) govern BGa. Strong correlations (r = −0.98; p &lt; 0.001) were found between BGa and preceding cumulative rainfall for soil without crops. Under cropped soil conditions, BGa was 53% greater under zero and minimum tillage than under ploughed treatments (p &lt; 0.05) six years after their applications. These differences could be explained by associated effects of tillage on organic matter content, electrical conductivity and water stable aggregates. The separated organic residue experiment showed that BGa was 36% greater in soil amended with slurry than in soil amended with compost (p &lt; 0.05) five years after their applications. Finally, the response ratio of BGa was calculated in order to study the effect size of each treatment at each sampling period. This simple strategy mitigated the variation on BGa measurements between two sampling periods, and may be applied in future studies to improve the interpretation of other potential soil quality indicators that are sensitive to seasonal changes.

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.

CHEMICAL AND MICROBIOLOGICAL ATTRIBUTES UNDER DIFFERENT SOIL COVER

ABSTRACT A challenge for the environmental recovery of degraded areas is the search for soil data. In this process, the microbiological parameters and soil chemicals are potential indicators of soil quality. This study aimed to evaluate soil quality based on microbiological and chemical soil attributes in different areas involving environmental recovery, sugarcane cultivation and remnants of native vegetation located in a rural private property farm in State of Mato Grosso do Sul, Brazil, in Hapludox Eutrophic soil. The microbiological (microbial biomass carbon, basal respiration, microbial quotient and metabolic quotient) and chemical parameters (organic matter, carbon, pH, cationic exchange capacity, sum of bases, potassium, phosphorus, magnesium, calcium, saturation base and potential acidity) were assessed. Data were assessed by variance and multivariate analysis (Principal Component Analysis and cluster analysis). Overall, the results showed highest alteration in the chemical and microbiological characteristics of the soil in sugarcane cultivation area in comparison with other areas. Considering the studied recovery areas, REC1, REC5 and REC7 show chemical and microbiological conditions with most similarity to native vegetation. Despite the short period of the resilience enhancement of environmental recovery areas, the development of vegetation cover and establishment of the microbial community were determined to be important factors for improving soil quality and environmental recovery in several of the areas studied.

Quantitative soil quality indexing of temperate arable management systems

Soil quality assessment can provide a practical approach for early detection of adverse influences of management practices. Our objective was to develop soil quality indices (SQI) for assessing the effects of current arable management practices on soil quality for temperate maritime soils. The study was conducted on twenty arable sites with conventional or minimum tillage and mono-cropping or crop rotation. Twenty-two soil properties were measured as potential indicators of soil quality, and those indicators that were responsive to management were considered as a total data set. Principal component analysis was used to determine a minimum data set (MDS), and four indices of soil quality were calculated using linear/non-linear scoring functions and additive/weighted additive methods. Visual evaluation of soil structure (VESS) was used to validate these indices. Total nitrogen, carbon nitrogen ratio, magnesium, aggregate size distribution, bulk density, penetration resistance and soil respiration were identified as the MDS (independent variables with r<0.7). All four SQI differed significantly by VESS class (P<0.05), but the linear additive index showed the best discrimination by management practices (P<0.05). The study indicated the positive influences of minimum tillage in combination with crop rotation on soil quality in Ireland, and indicated a detrimental effect of mono-cropping. The method developed in this study can provide a practical, quantitative tool for assessing soil quality under agricultural management systems.

Indices for quantitative evaluation of soil quality under grassland management

ObjectiveThe objectives of this study are to determine appropriate indicators, the most appropriate scoring function (linear or non-linear) and integrating procedure (additive and weighted additive) for a soil quality index for typical temperate, maritime grassland management (e.g. livestock grazing and silage production). MethodsThe study was conducted on twenty grassland sites classified by three levels of management intensity. Twenty-one soil properties were measured as potential indicators of soil quality, and the visual evaluation of soil structure was applied to select indicators responsive to management and for the validation of the indices. Indices were calculated using linear and non-linear scoring, followed by additive and weighted additive integration. Principal component analysis used with the total dataset of indicators sensitive to management to determine a minimum dataset. ResultsSoil organic carbon (SOC), total nitrogen, aggregate size distribution, bulk density, bulk density of ≤2mm fraction, extractable potassium and carbon–nitrogen ratio (CN) were the indicators that comprised the total dataset, while SOC, CN and bulk density of ≤2mm fraction were the minimum dataset. The management intensity influenced each indicator in different ways, and the index calculated using minimum dataset and nonlinear weighted additive integration had the best discrimination ability. ConclusionsThe average soil quality index values were lower under higher intensity management, and indicated that management intensification was tending toward an adverse impact on soil quality under grassland systems in Ireland. PracticeThere was no evidence that current grassland management was having a long-term detrimental effect on soil quality for grassland production, but the trend suggested that increasing intensity might cause management difficulties due to soil limitations in the future. ImplicationsThe indexing approach in this study provides a practical, time and cost effective method for quantitative evaluation of soil quality under temperate maritime grassland management.

Soil quality response to long-term tillage and crop rotation practices

Soil quality is influenced by inherent and anthropogenic factors. This study was conducted to provide multiple groups guidance on how to achieve and maintain improved soil quality/health. Our hypothesis was that tillage intensity was the primary anthropogenic factor degrading soil quality, and our objective was to prove that hypothesis through an intensive 2005 sampling of a central Iowa, USA field study. Chisel plow, disk tillage, moldboard plow, ridge-till and no-till treatments, used for 31 years in a two-year, corn (Zea mays L.)/soybean [Glycine max (L.) Merr.] (C/S) rotation or for 26 years of continuous corn (CC) production, were evaluated by measuring 23 potential soil quality indicators. Soil samples from 0 to 5- and 5 to 15-cm depth increments were collected from 158 loam or clay loam sampling sites throughout the 10-ha study site. Nine of the indicators were evaluated by depth increment using the Soil Management Assessment Framework (SMAF) which has scoring functions for 13 soil biological, chemical, and physical measurements and can be used to compute individual indicator indices and an overall soil quality index (SQI). Water-stable aggregation (WSA), total organic carbon (TOC), microbial biomass carbon (MBC), and potentially mineralizable nitrogen (PMN) were all significantly lower for the 0 to 5-cm and generally lower for 5 to 15-cm increments after long-term moldboard plowing and its associated secondary tillage operations. This presumably reflected greater physical breakup and oxidation of above- and below-ground plant residues. Bray-P concentrations in moldboard plow plots were also significantly lower at both depth increments. Between soil texture groups, significant differences were found for WSA, Bray-P, TOC and MBC at both depth increments and for both cropping systems. When combined into an overall SQI, both soil texture groups were functioning at 82–85% of their potential at 0–5-cm and at 75% of their potential at the 5–15-cm depth. Our hypothesis that moldboard plowing would have the greatest negative effect on soil quality indicators was verified. Based on this assessment, we recommend that to achieve and maintain good soil health, producers should strive to adopt less aggressive tillage practices.

Arbuscular Mycorrhizal Fungi and Glomalin‐Related Soil Protein as Potential Indicators of Soil Quality in a Recuperation Gradient of the Atlantic Forest in Brazil

AbstractThis study aimed at surveying arbuscular mycorrhizal fungi (AMF) species and glomalin‐related soil protein (GRSP) to understand their role as presumable biological indicators of soil quality in an undisturbed forest site (NT) and three sites with different management histories, soil textures, and different ages of recovery after reforestation for 20 (R20), 10 (R10) and 5 years (R05). Our objective was to determine how physical, chemical and microbiological soil attributes influence AMF species distribution, total‐GRSP (T‐GRSP) and easily extractable‐GRSP (EE‐GRSP). Glomus and Acaulospora were related to impacted sites, Gigaspora rosea to sites R10 and R20 that have different management histories and soil textures and Glomus geosporum to sites NT and R10, suggesting some influence of texture on its distribution. Scutellospora pellucida and other species were found only in one season. Correlations between EE‐GRSP and T‐GRSP on the one hand and total carbon and nitrogen, dehydrogenase and urease activity, microbial biomass carbon and microbial biomass nitrogen, on the other, reached values of 40–70% and were especially strong in summer. Soil bulk density had a negative and macroporosity a positive effect only on EE‐GRSP, suggesting the necessity to choose either EE‐GRSP or T‐GRSP as biological indicator depending on the soil characteristics and management. This study demonstrates the effect of recovery age, seasonality and other soil attributes on AMF and GRSP distribution and shows that these biological attributes may be used as indicators of soil quality in the Atlantic forest in Brazil. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Determining minimum data set for soil quality assessment of typical salt-affected farmland in the coastal reclamation area

The need for understanding and assessing soil quality is getting increasingly important because of growing public interest in determining the effect of management practices on the sustainability of the soil resource base. Our objectives were to investigate the effect of consecutive cultivation and different rotation systems on potential soil quality indicators, to identify effective soil quality indicators and to establish a minimum data set that discriminate different rotation systems. This study was conducted in a typical coastal salt-affected farmland in north Jiangsu Province, China. A pool of 22 measured variables representing soil chemical and physical properties (0–10cm) and groundwater features at 60 sampling sites and 10 representative soil profiles were used. A specific emphasis was given to the impact of crop rotation systems on measured soil and groundwater properties because of the importance of cultivation to the sustainability of soil quality. One-way analysis of variance (ANOVA) showed that measured variables of SOM, SOCD, TN, AP, CEC, AK, ECe, Na and Cl were positively impacted by cultivation. In contrast to cotton–barley rotation, rice–rape rotation had significantly positive influence on SOM and SOCD, but adverse impact on AK, pH, ρb, Ks, WTg and ECg. Factor analysis grouped all measured variables into seven principal components explaining 78.5% of total variance: salinity (PC1), organic matter (PC2), water permeability (PC3), soil texture (PC4), ion exchange (PC5), soil alkalinity (PC6) and available nutrients (PC7). Discriminant analysis indicated that PC1 (Cl, Na and ECg), PC2 (SOM and SOCD) and PC7 (WTg) were the most powerful factors (indicators) to distinguish the two rotation systems. SOCD (SOM) and Cl offered the greatest potential for monitoring soil quality under different management practices. SOM not only had the strongest positive influence on crop biomass, but also contributed the greatest to distinguishing the effect of rotation systems on soil quality. Our study suggested that SOM may be considered as an indispensable factor to determine the sustainability of soil productivity for the salt-affected farmlands in coastal reclamation area.

SMAF: A Soil Health Assessment Tool

The Soil Management Assessment Framework (SMAF) was developed to help quantify soil quality/health effects of tillage, crop rotation, and other soil management practices. Our objective was to determine if the SMAF could detect soil health differences after growing a single winter triticale (X Triticosecale Wittmack) crop. Soil samples were collected from 0 to 7.5- and 7.5 to 15-cm depth increments during the 2003 – 2004 and 2004 – 2005 growing seasons near Ames and Lewis, IA, and analyzed for several potential soil quality indicators. The SMAF analysis showed higher soil quality ratings for surface than subsurface samples. It also showed that a single winter grain crop can significantly improve soil quality after either corn (Zea mays L.) or soybean (Glycine max [L.] Merr.). Finally, in response to increasing interest in soil health assessments, a detailed appendix is attached to provide guidance for future soil health assessments.