Effects of erosion and deposition on particle size distribution of deposited farmland soils on the chinese loess plateau

Particle size distribution (PSD) in the soil profile is strongly related to erosion, deposition, and physical and chemical processes. Water cycling and plant growth are also affected by PSD. Material sedimented upstream of the dam constructions formed large areas of deposited farmland (DF) soils on the Chinese Loess Plateau (CLP), which has been the site of the most severe soil erosion in the world. Two DFs without tillage on the CLP were chosen to study the combined effect of erosion and check dams on PSD. Eighty-eight layers (each 10 cm thick) of filled deposited farmland (FDF) soils and 22 layers of silting deposited farmland (SDF) soils of each studied soil profile were collected and 932 soil samples were investigated using laser granulometry. The particle sizes were stratified in both DFs based on soil properties and erosion resistance. The obtained results of clay and silt fractions showed similar horizontal distribution, indicating parallel characteristics of erosion and deposition processes. Fine sand represented the largest fraction, suggesting the preferential detachment of this fraction. The most erodible range of particle sizes was 0.25-0.5 mm, followed by 0.2-0.25 mm in the studied soil profiles. The correlation between particle size and soil water contents tended to increase with increasing water contents in FDF. Due to the abundant shallow groundwater, the relationship between particle size and soil water content in SDF was lost. Further studies on PSD in the DF area are needed to enhance the conservation management of soil and water resources in this region.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

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.

Animal manure phosphorus characterization by sequential chemical fractionation, release kinetics and 31P-NMR analysis

Phosphate release kinetics from manures are of global interest because sustainable plant nutrition with phosphate will be a major concern in the future. Although information on the bioavailability and chemical composition of P present in manure used as fertilizer are important to understand its dynamics in the soil, such studies are still scarce. Therefore, P extraction was evaluated in this study by sequential chemical fractionation, desorption with anion-cation exchange resin and 31P nuclear magnetic resonance (31P-NMR) spectroscopy to assess the P forms in three different dry manure types (i.e. poultry, cattle and swine manure). All three methods showed that the P forms in poultry, cattle and swine dry manures are mostly inorganic and highly bioavailable. The estimated P pools showed that organic and recalcitrant P forms were negligible and highly dependent on the Ca:P ratio in manures. The results obtained here showed that the extraction of P with these three different methods allows a better understanding and complete characterization of the P pools present in the manures.

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.

SEQUENTIAL EXTRACTION OF PHOSPHORUS BY MEHLICH-1 AND ION EXCHANGE RESIN FROM B HORIZONS OF FERRIC AND PERFERRIC LATOSOLS (OXISOLS)

In general, Latosols have low levels of available P, however, the influence of the parent material seems to be decisive in defining the pool and predominant form of P in these soils. This study evaluated P availability by extraction with Mehlich-1 (M-1) and Ion Exchange Resin (IER), from samples of B horizons of Ferric and Perferric Latosols developed from different parent materials. To this end, in addition to the physical and chemical characterization of soils, 10 sequential extractions were performed with M-1 and IER from samples of B horizons (depth between 0.8 and 1.0 m). Total contents of Ca, P, Fe, Al, and Ti were determined after digestion with nitric, hydrofluoric and perchloric acids. The effects of sequential P extractions on Fe oxides were also evaluated from the analyses of dithionite-citrate-bicarbonate and ammonium acid oxalate. The high similarity between contents of P accumulated after sequential extractions with M-1 and IER in soils developed on tuffite indicated a predominance of P-Ca. Higher contents of P after a single IER extraction show greater efficiency in P removal from highly weathered soils, as from the Latosols studied here. The P contents also show the high sensitivity of extractant M-1 in highly buffered soils. Furthermore, a single extraction with extractant M-1 or IER is not sufficient to estimate the amount of labile P in these soils.