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The identification of buried soil horizons in agricultural landscapes helps to quantify sediment budgets and erosion-related carbon dynamics. High-resolution mapping of buried horizons using conventional soil surveys is destructive and time consuming. Geoelectrical sensors can offer a fast and non-destructive alternative for determining horizon positions and properties. In this paper, we compare the suitability of several geoelectrical methods for measuring the depth to buried horizons (Apb, Ahb and Hab) in the hummocky ground moraine landscape of northeastern Germany. Soil profile descriptions were developed for 269 locations within a 6-ha experimental field "CarboZALF-D". A stepwise linear discriminant analysis (LDA) estimated the lateral position of the buried horizons using electromagnetic induction data and terrain attributes. To predict the depth of a buried horizon, multiple linear regression (MLR) was used for both a 120-m transect and a 0.2-ha pseudo-three-dimensional (3D) area. At these scales, apparent electrical conductivity (ECa), electrical resistivity (ER) and terrain attributes were used as independent variables. The LDA accurately predicted Apb- and Ahb-horizons (a correct classification of 93%). The LDA of the Hab-horizon had a misclassification of 24%, which was probably related to the smaller test set and the higher depth of this horizon. The MLR predicted the depth of the Apb-, Ahb- and Hab-horizons with relative root mean square errors (RMSEs) of 7, 3 and 13%, respectively, in the pseudo-3D area. MLR had a lower accuracy for the 2D transect compared to the pseudo-3D area. Overall, the use of LDA and MLR has been an efficient methodological approach for predicting buried horizon positions. Highlights The suitability of geoelectrical measurements for digital modelling of diagnostic buried soil horizons was determined. LDA and MLR were used to detect multiple horizons with geoelectrical devices and terrain attributes. Geoelectrical variables were significant predictors of the position of the target soil horizons. The use of these tested digital technologies gives an opportunity to develop high-resolution soil mapping procedures.
Separation of coarse organic particles from bulk surface soil samples by electrostatic attraction
(2009)
Different separation procedures are suggested for studying the stability and functionality of sod organic matter (OM). Density fractionation procedures using high-molarity, water-based salt solutions to separate organic particles may cause losses or transfers of C between particle and soluble OM fractions during separation, which may be a result of solution processes. The objective of this study was to separate coarse organic particles (>0.315 mm) from air- dried surface soil samples to avoid such solution processes as far as possible. Air-dried surface soil samples (<2 mm) from nine adjacent arable and forest sites were sieved into five soil particle size fractions (2-1.25, 1.25-0.8, 0.8- 0.5, 0.5-0.4, and 0.4-0.315 mm). Coarse organic particles were separated from each of these fractions using electrostatic attraction by a charged glass surface. The sum of the total dry matter content of the electrostatically separated coarse organic particles ranged from 0.05 to 140 g kg(-1). Scanning electron microscopy images and organic C (OC) analyses indicated, however, that the coarse organic particle fractions were also composed of 20 to 76% mineral particles (i.e., 200-760 g mineral kg(-1) fraction). The repeatability of the electrostatic attraction procedure falls within a range similar to that of accepted density fractionation methods using high-molarity salt solutions. Based on the similarity in repeatability, we suggest that the electrostatic attraction procedure will successfully remove coarse organic particles (>0.315 mm) from air-dried surface soil samples. Because aqueous solutions are not used, the electrostatic attraction procedure to separate coarse organic particles avoids C losses and transfers associated with solution-dependent techniques. Therefore, this method can be used as a pretreatment for subsequent density- or solubility-based soil OM fractionation procedures.
Land use and mineral characteristics affect the ability of surface as well as subsurface soils to sequester organic carbon and their contribution to mitigation of the greenhouse effect. There is less information about the effects of land use and soil properties on the amount and composition of organic matter (OM) for subsurface soils as compared with surface soils. Here we aimed to analyse the long-term (>= 100 years) impact of arable and forest land use and soil mineral characteristics on subsurface soil organic carbon (SOC) contents, as well as on amount and composition of OM sequentially separated by Na pyrophosphate solution (OM(PY)) from subsurface soil samples. Seven soils with different mineral characteristics (Albic and Haplic Luvisol, Colluvic and Haplic Regosol, Haplic and Vertic Cambisol, Haplic Stagnosol) were selected from within Germany. Soil samples were taken from subsurface horizons of forest and adjacent arable sites continuously used for > 100 years. The OM(PY) fractions were analysed for their OC content (OC(PY)) and characterized by Fourier transform infrared spectroscopy. Multiple regression analyses for the arable subsurface soils indicated significant positive relationships between the SOC contents and combined effects of the (i) exchangeable Ca (Ca(ex)) and oxalate-soluble Fe (Fe(ox)) and (ii) the Ca(ex) and Al(ox) contents. For these soils the increase in OC (OC(PY) multiplied by the relative C=O content of OM(PY)) and increasing contents of Ca(ex) indicated that OM(PY) mainly interacts with Ca2+. For the forest subsurface soils (pH < 5), the OC(PY) contents were related to the contents of Na-pyrophosphate-soluble Fe and Al. The long-term arable and forest land use seems to result in different OM(PY)-mineral interactions in subsurface soils. On the basis of this, we hypothesize that a long-term land-use change from arable to forest may lead to a shift from mainly OM(PY)-Ca2+ to mainly OM(PY)-Fe3+ and -Al3+ interactions if the pH of subsurface soils significantly decreases to < 5.
The dataset in the present article provides information on protozoic silicon (Si) pools represented by euglyphid testate amoebae (TA) in soils of initial and forested biogeosystems. Protozoic Si pools were calculated from densities of euglyphid TA shells and corresponding Si contents. The article also includes data on potential annual biosilicification rates of euglyphid TA at the examined sites. Furthermore, data on selected soil parameters (e.g., readily-available Si, soil pH) and site characteristics (e.g., soil groups, climate data) can be found. The data might be interesting for researchers focusing on biological processes in Si cycling in general and euglyphid TA and corresponding protozoic Si pools in particular.
The dataset in the present article provides information on protozoic silicon (Si) pools represented by euglyphid testate amoebae (TA) in soils of initial and forested biogeosystems. Protozoic Si pools were calculated from densities of euglyphid TA shells and corresponding Si contents. The article also includes data on potential annual biosilicification rates of euglyphid TA at the examined sites. Furthermore, data on selected soil parameters (e.g., readily-available Si, soil pH) and site characteristics (e.g., soil groups, climate data) can be found. The data might be interesting for researchers focusing on biological processes in Si cycling in general and euglyphid TA and corresponding protozoic Si pools in particular.
Soil landscape research is faced with wide-ranging questions of soil erosion, precision farming, and agricultural risk management. Digital Soil Morphometrics is a powerful tool to provide respective answers or recommendations but requires soil data from the pedon-to-field scale with high horizontal and vertical resolutions, including the subsoil. We present an efficient sampling and measurement method for easily obtainable soil driving cores with low-destructive preparation. Elemental contents and soil organic and mineral matter composition were measured rapidly and in large numbers using a multi-sensor approach, i.e., visible and near infrared (Vis-NIR), diffuse reflectance infrared Fourier transform (DRIFT), and X-ray fluorescence (XRF) spectroscopy. The suitability of the approach with respect to three-dimensional soil landscape models was tested using soils along a slope representing different stages of erosion and deposition in a hummocky landscape under arable land use (Calcaric Regosols, Calcic Luvisols, Luvic Stagnosols, Gleyic-Colluvic Regosols). The combination of soil core sampling, pedological description, and three spectroscopic techniques enabled rapid determination and interpretation of horizontal and vertical spatial distributions of soil organic carbon (SOC), soil organic and mineral matter composition, as well as CaCO3, Fe, and Mn contents. Depth profiles for SOC, CaCO3, and Fe contents were suitable indicators for site-specific degrees of erosion and matter transport processes at the pedon-to-field scale. Fe and Mn profiles helped identifying zones of reductive and oxic domains in subsoils (gleyzation). Further methodical developments should implement plant-availability of nutrients, characterization of Fe oxides, and calibration of the spectroscopic techniques to field-moist samples.
Silicon is a beneficial element for many plants and is deposited in plant tissue as amorphous bio-opal called phytoliths. The biochemical processes of silicon uptake and precipitation induce isotope fractionation: the mass-dependent shift in the relative abundances of the stable isotopes of silicon. At the bulk scale, delta Si-30 ratios span from -2 to +6 parts per thousand. To further constrain these variations in situ, at the scale of individual phytolith fragments, we used femtosecond laser ablation multi-collector inductively coupled plasma-mass spectrometry (fsLA-MC-ICP-MS). A variety of phytoliths from grasses, trees and ferns were prepared from plant tissue or extracted from soil. Good agreement between phytolith delta Si-30 ratios obtained by bulk solution MC-ICP-MS analysis and in situ isotope ratios from fsLA-MC-ICP-MS validates the method. Bulk solution analyses result in at least twofold better precision for delta Si-30 (2s on reference materials <= 0.11 parts per thousand) over that found for the means of in situ analyses (2s typically <= 0.24 parts per thousand). We find that bushgrass, common reed and horsetail show large internal variations up to 2 parts per thousand in delta Si-30, reflecting the various pathways of silicon from soil to deposition. Femtosecond laser ablation provides a means to identify the underlying processes involved in the formation of phytoliths using silicon isotope ratios.
For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha(-1)) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance.
Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management (pest, weed and nutrient management and possible interactions with weather) explaining yield failures. Models to inform adaptation planning at farm, market or policy levels are here suggested to require consideration of cumulative resource capture and use, as well as effects of extreme events, the latter largely missing in process-based models. However, increasingly novel combinations of weather events under climate change may limit the extent to which data driven methods can replace process-based models in risk assessments.
Silicon (Si) is the second-most abundant element in the earth's crust. In the pedosphere, however, huge spans of Si contents occur mainly caused by Si redistribution in soil profiles and landscapes. Here, we summarize the current knowledge on the different pools and fluxes of Si in soils and terrestrial biogeosystems. Weathering and subsequent release of soluble Si may lead to (1) secondarily bound Si in newly formed Al silicates, (2) amorphous silica precipitation on surfaces of other minerals, (3) plant uptake, formation of phytogenic Si, and subsequent retranslocation to soils, (4) translocation within soil profiles and formation of new horizons, or (5) translocation out of soils (desilication). The research carried out hitherto focused on the participation of Si in weathering processes, especially in clay neoformation, buffering mechanisms for acids in soils or chemical denudation of landscapes. There are, however, only few investigations on the characteristics and controls of the low-crystalline, almost pure silica compounds formed during pedogenesis. Further, there is strong demand to improve the knowledge of (micro)biological and rhizosphere processes contributing to Si mobilization, plant uptake, and formation of phytogenic Si in plants, and release due to microbial decomposition. The contribution of the biogenic Si sources to Si redistribution within soil profiles and desilication remains unknown concerning the pools, rates, processes, and driving forces. Comprehensive studies considering soil hydrological, chemical, and biological processes as well as their interactions at the scale of pedons and landscapes are necessary to make up and model the Si balance and to couple terrestrial processes with Si cycle of limnic, fluvial, or marine biogeosystems