Effects of Soil Compaction and Organic Carbon Content on Preferential Flow in Loamy Field Soils

Abstract: Preferential flow and transport through macropores affect plant water use efficiency and enhance leaching of agrochemicals and the transport of colloids, thereby increasing the risk for contamination of groundwater resources. The effects of soil compaction, expressed in terms of bulk density (BD), and organic carbon (OC) content on preferential flow and transport were investigated using 150 undisturbed soil cores sampled from 15 × 15–m grids on two field sites. Both fields had loamy textures, but one site had significantly higher OC content. Leaching experiments were conducted in each core by applying a constant irrigation rate of 10 mm h−1 with a pulse application of tritium tracer. Five percent tritium mass arrival times and apparent dispersivities were derived from each of the tracer breakthrough curves and correlated with texture, OC content, and BD to assess the spatial distribution of preferential flow and transport across the investigated fields. Soils from both fields showed strong positive correlations between BD and preferential flow. Interestingly, the relationships between BD and tracer transport characteristics were markedly different for the two fields, although the relationship between BD and macroporosity was nearly identical. The difference was likely caused by the higher contents of fines and OC at one of the fields leading to stronger aggregation, smaller matrix permeability, and a more pronounced pipe-like pore system with well-aligned macropores.

Soil Nitrogen and Carbon Management Project, 2002

Report produced by Iowa Departmment of Agriculture and Land Stewardship

Soil fertility, organic carbon and fractions of the organic matter at different distances from eucalyptus stumps

Knowledge on variations in vertical, horizontal and temporal characteristics of the soil chemical properties under eucalyptus stumps left in the soil is of fundamental importance for the management of subsequent crops. The objective of this work was to evaluate the effect of eucalyptus stumps (ES) left after cutting on the spatial variability of chemical characteristics in a dystrophic Yellow Argisol in the eastern coastal plain region of Brazil. For this purpose, ES left for 31 and 54 months were selected in two experimental areas with similar characteristics, to assess the decomposition effects of the stumps on soil chemical attributes. Soil samples were collected directly around these ES, and at distances of 30, 60, 90, 120 and 150 cm away from them, in the layers 0-10, 10-20 and 20-40 cm along the row of ES, which is in-between the rows of eucalyptus trees of a new plantation, grown at a spacing of 3 x 3 m. The soil was sampled in five replications in plots of 900 m² each and the samples analyzed for pH, available P and K (Mehlich-1), exchangeable Al, Ca and Mg, total organic carbon (TOC) and C content in humic substances (HS) and in the free light fraction. The pH values and P, K, Ca2+, Mg2+ and Al3+ contents varied between the soil layers with increasing distance from the 31 and 54-monthold stumps. The highest pH, P, K, Ca2+ and Mg2+ values and the lowest Al3+ content were found in the surface soil layer. The TOC of the various fractions of soil organic matter decreased with increasing distance from the 31 and 54-month-old ES in the 0-10 and 10-20 cm layers, indicating that the root (and stump) cycling and rhizodeposition contribute to maintain soil organic matter. The C contents of the free light fraction, of the HS and TOC fractions were higher in the topsoil layer under the ES left for 31 months due to the higher clay levels of this layer, than in those found under the 54-month-old stumps. However, highest C levels of the different fractions of soil organic matter in the topsoil layer reflect the deposition and maintenance of forest residues on the soil surface, mainly after forest harvest.

Enzymatic activity and mineralization of carbon and nitrogen in soil cultivated with coffee and green manures

There are great concerns about degradation of agricultural soils. It has been suggested that cultivating different plant species intercropped with coffee plants can increase microbial diversity and enhance soil sustainability. The objective of this study was to evaluate enzyme activity (urease, arylsulfatase and phosphatase) and alterations in C and N mineralization rates as related to different legume cover crops planted between rows of coffee plants. Soil samples were collected in a field experiment conducted for 10 years in a sandy soil in the North of Paraná State, Brazil. Samples were collected from the 0-10 cm layer, both from under the tree canopy and in-between rows in the following treatments: control, Leucaena leucocephala, Crotalaria spectabilis, Crotalaria breviflora, Mucuna pruriens, Mucuna deeringiana, Arachis hypogaea and Vigna unguiculata. The soil was sampled in four stages of legume cover crops: pre-planting (September), after planting (November), flowering stage (February) and after plant residue incorporation (April), from 1997 to 1999. The green manure species influenced soil enzyme activity (urease, arylsulfatase and phosphatase) and C and N mineralization rates, both under the tree canopy and in-between rows. Cultivation of Leucaena leucocephala increased acid phosphatase and arilsulfatase activity and C and N mineralization both under the tree canopy and in-between rows. Intercropped L. leucocephala increased urease activity under the tree canopy while C. breviflora increased urease activity in-between rows.

Variation in soil organic carbon and thickness of soil horizons within a boreal forest stand - effect of trees and implications for sampling

Summary

Relationship between soil oxidizable carbon and physical, chemical and mineralogical properties of umbric ferralsols

The occurrence of Umbric Ferralsols with thick umbric epipedons (> 100 cm thickness) in humid Tropical and Subtropical areas is a paradox since the processes of organic matter decomposition in these environments are very efficient. Nevertheless, this soil type has been reported in areas in the Southeast and South of Brazil, and at some places in the Northeast. Aspects of the genesis and paleoenvironmental significance of these Ferralsols still need a better understanding. The processes that made the umbric horizons so thick and dark and contributed to the preservation of organic carbon (OC) at considerable depths in these soils are of special interest. In this study, eight Ferralsols with a thick umbric horizon (UF) under different vegetation types were sampled (tropical rain forest, tropical seasonal forest and savanna woodland) and their macromorphological, physical, chemical and mineralogical properties studied to detect soil characteristics that could explain the preservation of high carbon amounts at considerable depths. The studied UF are clayey to very clayey, strongly acidic, dystrophic, and Al-saturated and charcoal fragments are often scattered in the soil matrix. Kaolinites are the main clay minerals in the A and B horizons, followed by abundant gibbsite and hydroxyl-interlayered vermiculite. The latter was only found in UFs derived from basalt rock in the South of the country. Total carbon (TC) ranged from 5 to 101 g kg-1 in the umbric epipedon. Dichromate-oxidizable organic carbon represented nearly 75 % of TC in the thick A horizons, while non-oxidizable C, which includes recalcitrant C (e.g., charcoal), contributed to the remaining 25 % of TC. Carbon contents were not related to most of the inorganic soil variables studied, except for oxalate-extractable Al, which individually explained 69 % (P < 0.001) of the variability of TC in the umbric epipedon. Clay content was not suited as predictor of TC or of the other studied C forms. Bulk density, exchangeable Al3+, Al saturation, ECEC and other parameters obtained by selective extraction were not suitable as predictors of TC and other C forms. Interactions between organic matter and poorly crystalline minerals, as indicated by oxalate-extractable Al, appear to be one of the possible organic matter protection mechanisms of these soils.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Distribution and vertical stratification of carbon and nitrogen in soil under different managements in the pampean region of Argentina

One of the expected benefits of no-tillage systems is a higher rate of soil C sequestration. However, higher C retention in soil is not always apparent when no-tillage is applied, due e.g., to substantial differences in soil type and initial C content. The main purpose of this study was to evaluate the potential of no-tillage management to increase the stock of total organic C in soils of the Pampas region in Argentina. Forty crop fields under no-tillage and conventional tillage systems and seven undisturbed soils were sampled. Total organic C, total N, their fractions and stratification ratios and the C storage capacity of the soils under different managements were assessed in samples to a depth of 30 cm, in three layers (0-5, 5-15 and 15-30 cm). The differences between the C pools of the undisturbed and cultivated soils were significant (p < 0.05) and most pronounced in the top (0-5 cm) soil layer, with more active C near the soil surface (undisturbed > no-tillage > conventional tillage). Based on the stratification ratio of the labile C pool (0-5/5-15 cm), the untilled were separated from conventionally tilled areas. Much of the variation in potentially mineralizable C was explained by this active C fraction (R² = 0.61) and by total organic C (R² = 0.67). No-till soils did not accumulate more organic C than conventionally tilled soils in the 0-30 cm layer, but there was substantial stratification of total and active C pools at no till sites. If the C stratification ratio is really an indicator of soil quality, then the C storage potential of no-tillage would be greater than in conventional tillage, at least in the surface layers. Particulate organic C and potentially mineralizable C may be useful to evaluate variations in topsoil organic matter.

Changes in soil acidity and organic carbon in a sandy typic hapludalf after medium-term pig-slurry and deep-litter application

Successive applications of liquid swine waste to the soil can increase the contents of total organic carbon and nutrients and change acidity-related soil chemical properties. However, little information is available on the effects of swine waste application in solid form, as of swine deep-litter. The objective of this study was to evaluate alterations of organic carbon and acidity-related properties of a soil after eight years of pig slurry and deep-litter application. In the eighth year of a field experiment established in Braço do Norte, Santa Catarina (SC) on a sandy Typic Hapludalf samples were taken (layers 0-2.5; 2.5-5; 5-10; 10-15; 15-20 and 20-30 cm) from unfertilized plots and plots with pig slurry or deep-litter applications, providing the simple or double rate of N requirement of Zea mays and Avena strigosa in rotation. Soil total organic carbon, water pH, exchangeable Al, Ca and Mg, and cation exchange capacity (CECeffective and CECpH7.0), H+Al, base saturation, and aluminum saturation were measured. The application of pig slurry and deep-litter for eight years increased total organic carbon and CEC in all soil layers. The pig slurry and deep-litter applications reduced active acidity and aluminum saturation and increased base saturation down to a depth of 30 cm. Eight years of pig slurry application did not affect soil acidity.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

Soil aggregation and organic carbon of Oxisols under coffee in agroforestry systems

Intensive land use can lead to a loss of soil physical quality with negative impacts on soil aggregates, resistance to root penetration, porosity, and bulk density. Organic and agroforestry management systems can represent sustainable, well-balanced alternatives in the agroecosystem for promoting a greater input of organic matter than the conventional system. Based on the hypothesis that an increased input of organic matter improves soil physical quality, this study aimed to evaluate the impact of coffee production systems on soil physical properties in two Red-Yellow Oxisols (Latossolos Vermelho-Amarelos) in the region of Caparaó, Espirito Santo, Brazil. On Farm 1, we evaluated the following systems: primary forest (Pf1), organic coffee (Org1) and conventional coffee (Con1). On Farm 2, we evaluated: secondary forest (Sf2), organic coffee intercropped with inga (Org/In2), organic coffee intercropped with leucaena and inga (Org/In/Le2), organic coffee intercropped with cedar (Org/Ced2) and unshaded conventional coffee (Con2). Soil samples were collected under the tree canopy from the 0-10, 10-20 and 20-40 cm soil layers. Under organic and agroforestry coffee management, soil aggregation was higher than under conventional coffee. In the agroforestry system, the degree of soil flocculation was 24 % higher, soil moisture was 80 % higher, and soil resistance to penetration was lower than in soil under conventional coffee management. The macroaggregates in the organic systems, Org/In2, Org/In/Le2, and Org/Ced2 contained, on average, 29.1, 40.1 and 34.7 g kg-1 organic carbon, respectively. These levels are higher than those found in the unshaded conventional system (Con2), with 20.2 g kg-1.

Assessment of pedotransfer functions for estimating soil water retention curves for the amazon region

Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

DISTRIBUTION OF ORGANIC CARBON IN DIFFERENT SOIL FRACTIONS IN ECOSYSTEMS OF CENTRAL AMAZONIA

Organic matter plays an important role in many soil properties, and for that reason it is necessary to identify management systems which maintain or increase its concentrations. The aim of the present study was to determine the quality and quantity of organic C in different compartments of the soil fraction in different Amazonian ecosystems. The soil organic matter (FSOM) was fractionated and soil C stocks were estimated in primary forest (PF), pasture (P), secondary succession (SS) and an agroforestry system (AFS). Samples were collected at the depths 0-5, 5-10, 10-20, 20-40, 40-60, 60-80, 80-100, 100-160, and 160-200 cm. Densimetric and particle size analysis methods were used for FSOM, obtaining the following fractions: FLF (free light fraction), IALF (intra-aggregate light fraction), F-sand (sand fraction), F-clay (clay fraction) and F-silt (silt fraction). The 0-5 cm layer contains 60 % of soil C, which is associated with the FLF. The F-clay was responsible for 70 % of C retained in the 0-200 cm depth. There was a 12.7 g kg-1 C gain in the FLF from PF to SS, and a 4.4 g kg-1 C gain from PF to AFS, showing that SS and AFS areas recover soil organic C, constituting feasible C-recovery alternatives for degraded and intensively farmed soils in Amazonia. The greatest total stocks of carbon in soil fractions were, in decreasing order: (101.3 Mg ha-1 of C - AFS) > (98.4 Mg ha-1 of C - FP) > (92.9 Mg ha-1 of C - SS) > (64.0 Mg ha-1 of C - P). The forms of land use in the Amazon influence C distribution in soil fractions, resulting in short- or long-term changes.

Soil Aggregation, Organic Carbon Concentration, and Soil Bulk Density As Affected by Cover Crop Species in a No-Tillage System

Soil aggregation and the distribution of total organic carbon (TOC) may be affected by soil tillage and cover crops. The objective of this study was to determine the effects of crop rotation with cover crops on soil aggregation, TOC concentration in the soil aggregate fractions, and soil bulk density under a no-tillage system (NTS) and conventional tillage system (CTS, one plowing and two disking). This was a three-year study with cover crop/rice/cover crop/rice rotations in the Brazilian Cerrado. A randomized block experimental design with six treatments and three replications was used. The cover crops (treatments) were: fallow, Panicum maximum, Brachiaria ruziziensis, Brachiaria brizantha, and millet (Pennisetum glaucum). An additional treatment, fallow plus CTS, was included as a control. Soil samples were collected at the depths of 0.00-0.05 m, 0.05-0.10 m, and 0.10-0.20 m after the second rice harvest. The treatments under the NTS led to greater stability in the soil aggregates (ranging from 86.33 to 95.37 %) than fallow plus CTS (ranging from 74.62 to 85.94 %). Fallow plus CTS showed the highest number of aggregates smaller than 2 mm. The cover crops affected soil bulk density differently, and the millet treatment in the NTS had the lowest values. The cover crops without incorporation provided the greatest accumulation of TOC in the soil surface layers. The TOC concentration was positively correlated with the aggregate stability index in all layers and negatively correlated with bulk density in the 0.00-0.10 m layer.