Geoderma Regional最新文献

Soil aggregation controls several physical, chemical, and biological processes. Soil organic matter (SOM) and its stabilizing agents are regarded as the most important factors driving formation and stabilization of soil aggregates. However, aggregate stability in highly weathered soils may also be related to clay mineral composition and soil chemical properties. This study aims to evaluate the processes controlling soil aggregate stability and to understand the influence of soil chemical and clay mineral composition on the structural stability of highly weathered soils. Four Brazilian Oxisols were investigated: (P1) Xanthic Kandiustox, (P2) Rhodic Haplustox, (P3) Anionic Acrustox, and (P4) Typic Hapludox. Undisturbed and disturbed soil samples were collected from the Bw horizon under a native forest. Soil structural stability was evaluated using a variety of techniques and indices, including mean weight diameter (MWD) by hydraulic stress, mechanically-dispersible clay (MDC) by turbidimetry, tensile strength (TS) by crushing aggregates, and soil structural stability index (SSI) taking into account soil organic carbon (SOC). In general, P1 exhibited the highest MDC content (3.05 ± 0.54, Nephelometric Turbidity Unit, NTU/g L^‐−1), while P4 had the highest MWD (10.26 ± 0.24 mm) and the highest TS (80.42 ± 18.54 kPa) within the 8–4 mm aggregate size class. The TS for the 4–2 mm and 2–1 mm aggregate size classes was found to be equal for P2 and P4, with values ranging from 158.17 ± 24.70 kPa to 148.04 ± 38.50 kPa in the 4–2 mm class, and from 459.51 ± 189 kPa to 328.35 ± 78.22 kPa in the 2–1 mm one. The SSI was found to be inadequate for evaluating the structural stability of the Oxisols. In general, SOC was found to be the main stabilizing agent of larger aggregates, while clay mineral composition determined the stability of smaller aggregates. Goethite associated with gibbsite was more effective in increasing the structural stability of P2 and P4. Furthermore, kaolinites with low crystallinity, which are found in clayey Oxisols, resulted in a high specific surface area, particularly in Rhodic Haplustox and Typic Hapludox soils, which promoted more interactions with other clay minerals (e.g., goethite and gibbsite) and SOC, thereby increasing the tensile strength in these Oxisols. In fact, the formation and stabilization of aggregates in highly weathered soils depends on several factors, but the influence of clay mineral composition stands out as the most pronounced.

Soil salinization, impaired by climate change and poor management practices, poses a global threat, particularly in arid and semi-arid regions, leading to significant land degradation. This study aims to investigate the effects of different nitrogen (N) fertilizer sources (urea, ammonium-sulfate, and biogas waste) on CO₂, N₂O, and NH₃ emissions and soil enzyme activities in two soil types varying in salinity level (non-saline: EC = 1.15 dS m⁻¹, and saline: EC = 35.80 dS m⁻¹) in a robotized continuous-flow soil incubation system. Our results showed a sharp increase in N₂O and CO₂ emissions (up to 0.51 ± 0.02 g N₂O-N ha⁻¹ day⁻¹, 28.1 ± 3.9 kg CO₂-C ha⁻¹ day⁻¹) in non-saline soils following soil rewetting, attributed to bacterial denitrification. However, this pattern was not observed in saline soils, suggesting that salinity causes partial inhibition to the regeneration of soil organic matter mineralization and denitrification processes after rewetting. Although salinity did not alter the overall cumulative N₂O losses in any fertilizer treatment, it significantly delayed the evolution of N₂O peak during the incubation period. On the other hand, NH₃ volatilization was significantly higher in N-fertilized saline soils compared to non-saline soils (241% and 157% in ammonium-sulfate and biogas waste treatments, respectively), except for urea treatment, likely due to the decrease in nitrification rates. Furthermore, the study clearly showed lower soil enzyme activity levels for both nitrate reductase and urease activity. Interestingly, the lowest NH₃ emissions were measured in urea treatment in both soils. Overall, our findings highlight the complex interplay between soil salinity, nitrogen fertilizer sources, and microbial processes, significantly influencing gaseous nitrogen emissions and N cycling in agricultural soils. Identifying the specific fertilizer treatments that minimize or maximize gaseous nitrogen losses in varying soil salinity, may guide the selection of appropriate fertilization strategies for farmers and policymakers to mitigate environmental impacts of fertilizer use during agricultural production.

This study linked soil FT-NIR spectroscopy with soil organic carbon (SOC) and total nitrogen (TN) content in Saskatchewan (SK) agricultural soils, using a multivariate approach. Soil spectra were acquired along with laboratory measurements of SOC and TN from 1965 Saskatchewan soil samples. Spectral data were transformed using a variety of common pre-treatment approaches: Savitszky-Golay, first and second derivative, standard normal variate, multiplicative scatter correction and continuous wavelet transform. Models were next built using cubist regression tree (Cubist), support vector machine (SVM), and partial least square regression (PLSR) to evaluate the performance of the different pre-treatment/modelling approaches. The continuous wavelets transform was the best performing spectral treatment method for SK agricultural SOC and TN. For predictive model using an extensive dataset, the cubist model performed best for SOC and TN (R² = 0.80 and 0.85) followed by SVM (R² = 0.77 and 0.85) and PLSR (R² = 0.63 and 0.73). However, all models demonstrated the same correlation between predicted and observed values for SOC and TN (CCC = 0.87 and 0.93). The consistent model accuracy with extensive soil dataset suggests model's ability to generalize well beyond the data it was trained on. However, model accuracy varies if trained using different soil zones and Sk agricultural sites, and this suggest the need for careful selection of specific site or soil-zone on which model should be trained. Additionally, this study also underscores the influence of factors beyond sample size and spectra variability, such as coefficient of variation, on the accuracy of SOC and TN predictions.

In recent years, the importance of soils and soil functions has been recognised for supporting the delivery of ecosystem services and for the realisation of international initiatives, such as the UN Sustainable Development Goals. At the same time, Digital Soil Mapping (DSM) has emerged as a modelling technique that can satisfy increased end-user needs for new soil datasets by producing fine resolution soils and soil property maps to support complex digital soil and land evaluation assessments. Spatial disaggregation is a popular DSM technique that is used to transform legacy soil maps to more spatially-explicit soils datasets, which can also be used in conjunction with soil databases to generate digital soil property maps. In this study, we performed spatial disaggregation of the National Soil Map of Scotland (originally published at 1:250,000 scale) at the taxonomic level of Soil Series, with the specific objective to facilitate the production of harmonised digital soil property maps to support soil and land evaluation assessments in Scotland through linking to the Scottish Soil Database. We divided Scotland into Landscape Units of similar soil and landform characteristics and trained probability random forest models within each Landscape Unit using area-proportion random sampling of both single- and multiple- (complex) Soil Series map units and selected environmental covariates to produce Soil Series probability layers at 50 m grid resolution. The performance of the disaggregated Soil Series maps was evaluated using prediction uncertainties of individual soil types and independent soil profile classifications. Evaluation results indicated that the random forest algorithm was successful in promoting effective spatial disaggregation of both single soil and complex soil polygons and provided good prediction accuracies for most soil types with the exception of some of the least extensive soil types typically found within complex map units. This was attributed mainly to algorithm's tendency to favour dominant, more extensive classes, along with its difficulty to distinguish between similar soils within spatially diverse areas. However, training Soil Series models at a Landscape Unit level instead of nationally helped to limit both the underestimation of these minority soil types and the overestimation of the dominant ones. In addition, map evaluation results showed the usefulness of using the generated conditional Soil Series probabilities for exploring soil spatial variability, especially within complex areas such as river floodplains covered by multiple alluvial and non-alluvial soils. Overall, this study demonstrates the potential of using spatial disaggregation to extract pedological knowledge embedded in legacy soil maps and use it to generate new dynamic and harmonised soil and soil property maps by effectively using readily-available and easily-updated soils information from existing databases.

Given the natural fragility of sandy soils, Brazil's intensification of agricultural use of subtropical Acrisols must be carefully monitored. Nevertheless, reference values for microbiological properties have not yet been determined for these soils. Therefore, this study sought to determine the critical limits (CLs) and interpretative classes for soil microbiological properties, establish a minimum set of soil chemical and biological indicators based on statistical associations between these indicators and maize yield, and identify which management systems contribute to the quality of a subtropical Acrisol. Soil samples were collected from two experiments that were selected to evaluate the effects of tillage and cropping systems on maize production for >30 years. Principles to determine CLs for chemical properties were used to interpret microbiological properties, and a minimum data set was established by principal component analysis. Interpretative classes were determined for soil enzymes arylsulfatase and β-glucosidase, microbial biomass carbon and nitrogen, and soil basal respiration as a function of soil organic carbon content and maize yield. By analyzing the minimum data set, we were able to identify properties to compose a soil quality index (SQI) composed of arylsulfatase activity, microbial biomass carbon, total soil nitrogen, soil organic carbon, and pH in water. The SQI revealed that maize cultivation on subtropical Acrisols in Brazil is more sustainable under no-till and with legumes as cover crops.

Soil is an indispensable and important natural resource and it is necessary to manage and monitor soil quality with appropriate methods in order to ensure the sustainability of the soil. The aim of this study is to determine the current state of soil quality in different land uses where soil functions change. This study was carried out in the Karasu river watershed with an area of 19,178 ha where Entisols soil order is dominant, located Andırın, Kahramanmaraş. The Soil Management Assessment Framework (SMAF) method and Principal Component Analysis (PCA) was used to assess the dynamic soil quality in watershed scale. In the evaluation of soil quality, random samples were taken from a total of 360 topsoil layers (0−30) according to land use and physiography. Soil indicators such as bulk density, aggregate stability, total organic carbon, pH, electrical conductivity, available phosphorus (P), potassium (K), available water amount and water-filled pore volume were selected to create the minimum data set (MDS). The results showed that the productivity, environmental protection, waste recycling quality scores and general soil quality index of forest lands are higher than agricultural lands. According to expert opinion, general soil quality scores were found to be 0.86 in forest land, 0.78 in crop land and 0.83 in grassland, while in PCA, general soil quality scores were calculated as 0.85 in forest land, 0.79 in crop land and 0.78 in grassland. Contribution level of soil functions to management targets was observed in water relations function the most. The contribution levels of the water relations function to the productivity, environmental protection and waste recycling management targets are 0.38, 0.32 and 0.34 in forest lands, 0.42, 0.33 and 0.35 in croplands, respectively; It was showed that 0.40, 0.33 and 0.36 in grasslands. Contribution rates of productivity, environmental protection and waste recycling management targets to soil quality were 30%, 37% and 33%, respectively, in forest lands; 29%, 37% and 34% in crop lands; It has been determined as 30%, 36% and 34% in the grasslands. Negative effects such as heavy rainfall in the watershed, wrong agricultural practices (excessive fertilization and irrigation, improper tillage, and crop selection, etc.) and excessive grazing have led to soil degradation and erosion, reducing the soil function capacity of agricultural lands and meadows. In order to increase the functional capacity of the soil, a soil management approach aimed at protection, improvement and sustainability must be adopted and implemented.

Specific pedoclimatic conditions in tropical environments have a considerable impact on pesticide fate. Tropical volcanic soils result from specific pedogenesis processes linked to successive volcanic projections; they are characterised by acidic conditions, high organic matter content, a specific mineralogical composition and the presence of organo-mineral complexes. The retention of pesticides in these soils is therefore often high but variable depending on the associated molecules and soil properties. Nevertheless, knowledge of pesticide sorption in these soils remains limited, and knowledge of the desorption process is scarce. The objectives of this work were to study the variability of the sorption and desorption coefficient of four pesticides currently used in banana and sugarcane crops on a set of representative tropical soils developed on volcanic ash (Guadeloupe, French West Indies). Adsorption and desorption isotherms were analysed for three ionizable pesticides (2,4-D, mesotrione, glyphosate) and a hydrophobic pesticide (difenoconazole) on ten soil samples from five soil profiles: one silandic andosol, one vitric andosol, two nitisols and one ferralsol. For ionizable pesticides, soil pH appears to be a first-order discriminating factor of the sorption capacity, and the organic carbon content appears to have a lesser impact on 2,4-D. For a strongly hydrophobic pesticides such as difenoconazole, the organic carbon content plays a major role in sorption. Desorption hysteresis has been observed regardless of the soils and the molecules considered, and tropical volcanic soils seem to be conducive to adsorption but show low to moderate release. The silandic andosol, which has the greatest sorption, buffers the dissemination of pesticides towards surface and groundwaters but also increases the risk of long-term contamination in the case of molecules that degrade slowly. Moreover, our results highlight that agronomic practices, such as liming, have a major impact on the sorption coefficient of pesticides and must be considered for when predicting sorption in a tropical volcanic context.

Previous studies have recognized the influence of crop cover and agricultural management on variables (soil temperature, soil moisture, and root biomass) that influence soil respiration. However, despite the influence of plant density and row spacing on these variables in the maize crop (Zea mays L.), their impact on soil respiration has received little attention. Thus, the aims of this study were (i) to investigate whether reducing plant density and row spacing influences soil respiration, and (ii) to identify the controlling variables (soil temperature and soil moisture) underlying this response. We conducted field experiments in Balcarce, Argentina, over two seasons. Treatments included (i) maize crops at high plant density (≈8 plants m⁻²) and narrow rows (0.52 cm, HDN), and (ii) maize crops at low plant density (≈6.5 plants m⁻²) and wide row spacing (0.70 cm; LDW). Leaf area index (LAI), soil CO₂ fluxes, soil superficial temperature, and moisture (characterized by the water-filled pore space, WFPS) were assessed throughout the growing season. Grain yield and cumulative soil CO₂ emissions were determined at the final harvest. Major findings relevant to understanding the influence of reducing plant density and wider row spacing on instant CO₂ fluxes include: (i) LAI reductions were related to higher superficial soil moisture, which was consistent at LAI ≥ 3; suggesting higher decreases in water uptake than increases in soil evaporation, and in turn (ii) increments in soil moisture were associated with higher CO₂ fluxes. While lower plant density and wider row spacing had notable short-term effects on WFPS and soil respiration fluxes, they did not significantly affect cumulative soil respiration throughout the growing season. However, the combination of this practice with low-yield potential genotypes that exhibit low stability to changes in resource availability can increase CO₂ emissions per unit of grain yield. These findings contribute to a better understanding of the impacts of management practices on soil respiration and, consequently, on carbon cycling within agricultural ecosystems.

Characterization of soil organic carbon (SOC) in terms of size, storage inside aggregates and chemical recalcitrance is vital to understand mechanisms of its stabilization and to devise climate smart agricultural management practices. Tillage and residue retention are known to influence carbon (C) storage within soil aggregates and its accumulation as particulate organic matter as well as organomineral complexes. However, the effect of tillage and crop residue retention on C stabilization in coarse textured soils through various mechanisms is not well understood. We studied the effect of conservation agriculture involving no tillage with surface residue mulch (NTM) in maize-wheat sequence on particulate (POC) and mineral associated organic C (MinOC), C storage within aggregates and acid non-hydrolysable C (NHC) in a sandy loam soil. Compared to conventional tillage without residue retention (CTM₀), the NTM improved SOC stocks by 23% in top 15-cm soil and significantly increased coarse POC (∼92 to 284%) and fine POC (67 to 123%) with relatively little effect on MinOC. This indicated that MinOC had relatively small contribution towards SOC stabilization in coarse textured sandy loam soils with limited potential to form organomineral complexes. The results further showed that the effects of NTM were brought about by improved aggregate stability and C preservation inside macroaggregates of size >1 mm. Furthermore, greater amount of SOC (2.64 g C kg⁻¹) and macroaggregate associated C (0.35–0.59 g C kg⁻¹) occurred in recalcitrant forms (NHC) under NTM compared to conventional (CT) and deep tillage (DT). The NTM also impacted the belowground C input through improved root length density (RLD) and development of fibrous roots expressed as specific root length (SRL), which influenced SOC build-up and stabilization. It is concluded that compared to the existing practice of CTM₀, the conservation agriculture involving NT with residue retention leads to SOC sequestration in coarse textured soils. Its large scale adoption, besides helping in climate change mitigation will lead to soil health improvement.

Water scarcity and soil erosion are global problems with socioeconomic consequences for small-scale farmers, especially in semiarid areas. Small-scale farmers scarcely consider techniques for reversing this situation due to uncertain outcomes and high costs. In this study, we hypothesized that contour furrowing, a simple and accessible technique, would effectively increase soil moisture and mitigate soil erosion. In addition, we hypothesized that vegetation is also a contributing factor. We performed a field experiment to evaluate the effect of four treatments on soil moisture (until 1 m depth) and soil loss: bare and unmanaged soils (CON); bare soils managed with contour furrowing (CF); soils with shrub cover (VEG); and CF + VEG. Each treatment was monitored on six hillslopes of agricultural communities in a semiarid area of central Chile for one year. We found that the minimal soil water content recorded in the soil profiles of the CF, VEG, and CF + VEG plots was significantly greater than in the CON plots (with increases of 16%, 22%, and 13%, respectively, compared to CON). The CF and VEG treatments conserved soil moisture during the dry season and demonstrated more effective soil–water recharge after the first rain. However, the combined CF + VEG treatment retained less water in the soil profile than the single treatments. On the other hand, all treated plots showed lower soil loss than the CON treatment (mean of 0.68 t ha⁻¹ year⁻¹). We concluded that contour furrowing effectively enhances soil and soil-water conservation on bare hillslopes. Moreover, it is a low-cost technique that engaged those farmers looking to enhance sustainability and productivity on their lands.