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To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was conducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear implementation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale.
The precise and accurate assessment of carbon dioxide (CO2) exchange is crucial to identify terrestrial carbon (C) sources and sinks and for evaluating their role within the global C budget. The substantial uncertainty in disentangling the management and soil impact on measured CO2 fluxes are largely ignored especially in cropland. The reasons for this lies in the limitation of the widely used eddy covariance as well as manual and automatic chamber systems, which either account for short-term temporal variability or small-scale spatial heterogeneity, but barely both. To address this issue, we developed a novel robotic chamber system allowing for dozens of spatial measurement repetitions, thus enabling CO2 exchange measurements in a sufficient temporal and high small-scale spatial resolution. The system was tested from 08th July to 09th September 2019 at a heterogeneous field (100 m x 16 m), located within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The field is foreseen for a longer-term block trial manipulation experiment extending over three erosion induced soil types and was covered with spring barley. Measured fluxes of nighttime ecosystem respiration (R-eco) and daytime net ecosystem exchange (NEE) showed distinct temporal patterns influenced by crop phenology, weather conditions and management practices. Similarly, we found clear small-scale spatial differences in cumulated (gap-filled) R-eco, gross primary productivity (GPP) and NEE fluxes affected by the three distinct soil types. Additionally, spatial patterns induced by former management practices and characterized by differences in soil pH and nutrition status (P and K) were also revealed between plots within each of the three soil types, which allowed compensating for prior to the foreseen block trial manipulation experiment. The results underline the great potential of the novel robotic chamber system, which not only detects short-term temporal CO2 flux dynamics but also reflects the impact of small-scale spatial heterogeneity.
Remote sensing plays an increasingly key role in the determination of soil organic carbon (SOC) stored in agriculturally managed topsoils at the regional and field scales. Contemporary Unmanned Aerial Systems (UAS) carrying low-cost and lightweight multispectral sensors provide high spatial resolution imagery (<10 cm). These capabilities allow integrate of UAS-derived soil data and maps into digitalized workflows for sustainable agriculture. However, the common situation of scarce soil data at field scale might be an obstacle for accurate digital soil mapping. In our case study we tested a fixed-wing UAS equipped with visible and near infrared (VIS-NIR) sensors to estimate topsoil SOC distribution at two fields under the constraint of limited sampling points, which were selected by pedological knowledge. They represent all releva nt soil types along an erosion-deposition gradient; hence, the full feature space in terms of topsoils' SOC status. We included the Topographic Position Index (TPI) as a co-variate for SOC prediction. Our study was performed in a soil landscape of hummocky ground moraines, which represent a significant of global arable land. Herein, small scale soil variability is mainly driven by tillage erosion which, in turn, is strongly dependent on topography. Relationships between SOC, TPI and spectral information were tested by Multiple Linear Regression (MLR) using: (i) single field data (local approach) and (ii) data from both fields (pooled approach). The highest prediction performance determined by a leave-one-out-cross-validation (LOOCV) was obtained for the models using the reflectance at 570 nm in conjunction with the TPI as explanatory variables for the local approach (coefficient of determination (R-2) = 0.91; root mean square error (RMSE) = 0.11% and R-2 = 0.48; RMSE = 0.33, respectively). The local MLR models developed with both reflectance and TPI using values from all points showed high correlations and low prediction errors for SOC content (R-2 = 0.88, RMSE = 0.07%; R-2 = 0.79, RMSE = 0.06%, respectively). The comparison with an enlarged dataset consisting of all points from both fields (pooled approach) showed no improvement of the prediction accuracy but yielded decreased prediction errors. Lastly, the local MLR models were applied to the data of the respective other field to evaluate the cross-field prediction ability. The spatial SOC pattern generally remains unaffected on both fields; differences, however, occur concerning the predicted SOC level. Our results indicate a high potential of the combination of UAS-based remote sensing and environmental covariates, such as terrain attributes, for the prediction of topsoil SOC content at the field scale. The temporal flexibility of UAS offer the opportunity to optimize flight conditions including weather and soil surface status (plant cover or residuals, moisture and roughness) which, otherwise, might obscure the relationship between spectral data and SOC content. Pedologically targeted selection of soil samples for model development appears to be the key for an efficient and effective prediction even with a small dataset.
Processes driving the production, transformation and transport of methane (CH4 / in wetland ecosystems are highly complex. We present a simple calculation algorithm to separate open-water CH4 fluxes measured with automatic chambers into diffusion-and ebullition-derived components. This helps to reveal underlying dynamics, to identify potential environmental drivers and, thus, to calculate reliable CH4 emission estimates. The flux separation is based on identification of ebullition-related sudden concentration changes during single measurements. Therefore, a variable ebullition filter is applied, using the lower and upper quartile and the interquartile range (IQR). Automation of data processing is achieved by using an established R script, adjusted for the purpose of CH4 flux calculation. The algorithm was validated by performing a laboratory experiment and tested using flux measurement data (July to September 2013) from a former fen grassland site, which converted into a shallow lake as a result of rewetting. Ebullition and diffusion contributed equally (46 and 55 %) to total CH4 emissions, which is comparable to ratios given in the literature. Moreover, the separation algorithm revealed a concealed shift in the diurnal trend of diffusive fluxes throughout the measurement period. The water temperature gradient was identified as one of the major drivers of diffusive CH4 emissions, whereas no significant driver was found in the case of erratic CH4 ebullition events.
Processes driving the production, transformation and transport of methane (CH4) in wetland ecosystems are highly complex. We present a simple calculation algorithm to separate open-water CH4 fluxes measured with automatic chambers into diffusion- and ebullition-derived components. This helps to reveal underlying dynamics, to identify potential environmental drivers and, thus, to calculate reliable CH4 emission estimates. The flux separation is based on identification of ebullition-related sudden concentration changes during single measurements. Therefore, a variable ebullition filter is applied, using the lower and upper quartile and the interquartile range (IQR). Automation of data processing is achieved by using an established R script, adjusted for the purpose of CH4 flux calculation. The algorithm was validated by performing a laboratory experiment and tested using flux measurement data (July to September 2013) from a former fen grassland site, which converted into a shallow lake as a result of rewetting. Ebullition and diffusion contributed equally (46 and 55 %) to total CH4 emissions, which is comparable to ratios given in the literature. Moreover, the separation algorithm revealed a concealed shift in the diurnal trend of diffusive fluxes throughout the measurement period. The water temperature gradient was identified as one of the major drivers of diffusive CH4 emissions, whereas no significant driver was found in the case of erratic CH4 ebullition events.
Identifying the chemical mechanisms behind soil carbon bound in organo-mineral complexes is necessary to determine the degree to which soil organic carbon is stabilized belowground. Analysis of delta C-13 and delta N-15 isotopic signatures of stabilized OM fractions along with soil mineral characteristics may yield important information about OM-mineral associations and their processing history. We anlayzed the delta C-13 and delta N-15 isotopic signatures from two organic matter (OM) fractions along with soil mineral proxies to identify the likely binding mechanisms involved. We analyzed OM fractions hypothesized to contain carbon stabilized through organo-mineral complexes: (1) OM separated chemically with sodium pyrophosphate (OM(PY)) and (2) OM occluded in micro-structures found in the chemical extraction residue (OM(ER)). Because the OM fractions were separated from five different soils with paired forest and arable land use histories, we could address the impact of land use change on carbon binding and processing mechanisms. We used partial least squares regression to analyze patterns in the isotopic signature of OM with established mineral and chemical proxies indicative for certain binding mechanisms. We found different mechanisms predominate in each land use type. For arable soils, the formation of OM(PY)-Ca-mineral associations was identified as an important OM binding mechanism. Therefore, we hypothesize an increased stabilization of microbial processed OM(PY) through Ca2+ interactions. In general, we found the forest soils to contain on average 10% more stabilized carbon relative to total carbon stocks, than the agricultural counter part. In forest soils, we found a positive relationship between isotopic signatures of OM(PY) and the ratio of soil organic carbon content to soil surface area (SOC/SSA). This indicates that the OM(PY) fractions of forest soils represent layers of slower exchange not directly attached to mineral surfaces. From the isotopic composition of the OM(ER) fraction, we conclude that the OM in this fraction from both land use types have undergone a different pathway to stabilization that does not involve microbial processing, which may include OM which is highly protected within soil micro-structures.
Intensive grazing leads to land degradation and desertification of grassland ecosystems followed by serious environmental and social problems. The Xilingol steppe grassland in Inner Mongolia, China, which has been a sink area for dust for centuries, is strongly affected by the negative effects of overgrazing and wind erosion. The aim of this study is the provision of a wind erosion risk map with a spatial high resolution of 25 m to identify actual source and sink areas. In an integrative approach, field measurements of vegetation features and surface roughness length z0 were combined with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image data for a land use classification. To determine the characteristics of the different land use classes, a field observation (ground truth) was performed in April 2009. The correlation of vegetation height and z0 (R2 = 0.8, n = 55) provided the basis for a separation of three main classes, grassland, non-vegetation and other. The integration of the soil-adjusted vegetation index (SAVI) and the spectral information from the atmospheric corrected ASTER bands 1, 2 and 3 (visible to near-infrared) led to a classification of the overall accuracy (OA) of 0.79 with a kappa () statistic of 0.74, respectively. Additionally, a digital elevation model (DEM) was used to identify topographical effects in relation to the main wind direction, which enabled a qualitative estimation of potential dust deposition areas. The generated maps result in a significantly higher description of the spatial variability in the Xilingol steppe grassland reflecting the different land use intensities on the current state of the grassland less, moderately and highly degraded. The wind erosion risk map enables the identification of characteristic mineral dust sources, sinks and transition zones.
Questions remain about the exact ultrasonic energy level that is required to effectively disperse soil aggregates and to what extent this is accompanied by physical damage to individual soil particles. We found maximum aggregate dispersion at energy levels of 1500 J?cm3 and no evidence for the disintegration of particles < 20 mu m even at that energy level. Our findings suggest that sonication at energies much greater than those applied conventionally can disperse aggregates of high mechanical stability.
The detection of auto-fluorescence in phytogenic, hydrated amorphous silica depositions (phytoliths) has been found to be a promising approach to verify if phytoliths were burnt or not, especially in archaeological contexts. However, it is unknown so far at what temperature and how auto-fluorescence is induced in phytoliths. We used fluorescence microscopy, scanning electron microscope-energy dispersive X-ray spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy to analyze auto-fluorescence in modern phytoliths extracted from plant samples or in intact leaves of winter wheat. Leaves and extracted phytoliths were heated at different temperatures up to 600 degrees C. The aims of our experiments were i) to find out what temperature is needed to induce auto-fluorescence in phytoliths, ii) to detect temperature-dependent changes in the molecular structure of phytoliths related to auto-fluorescence, and iii) to derive a mechanistic understanding of auto-fluorescence in phytoliths. We found organic compounds associated with phytoliths to cause auto-fluorescence in phytoliths treated at temperatures below approx. 400 degrees C. In phytoliths treated at higher temperatures, i.e., 450 and 600 degrees C, phytolith auto-fluorescence was mainly caused by molecular changes of phytolith silica. Based on our results we propose that auto-fluorescence in phytoliths is caused by clusterization-triggered emissions, which are caused by overlapping electron clouds forming non-conventional chromophores. In phytoliths heated at temperatures above about 400 degrees C dihydroxylation and the formation of siloxanes result in oxygen clusters that serve as non-conventional chromophores in fluorescence events. Furthermore, SEM-EDX analyses revealed that extractable phytoliths were dominated by lumen phytoliths (62%) compared to cell wall phytoliths (38%). Our findings might be not only relevant in archaeological phytolith-based examinations, but also for studies on the temperature-dependent release of silicon from phytoliths and the potential of long-term carbon sequestration in phytoliths.
To better assess ecosystem C budgets of croplands and understand their potential response to climate and management changes, detailed information on the mechanisms and environmental controls driving the individual C flux components are needed. This accounts in particular for the ecosystem respiration (R-eco) and its components, the autotrophic (R-a) and heterotrophic respiration (R-h) which vary tremendously in time and space. This study presents a method to separate R-eco into R-a [as the sum of R-a (shoot) and R-a (root)] and R-h in order to detect temporal and small-scale spatial dynamics within their relative contribution to overall R-eco. Thus, predominant environmental drivers and underlying mechanisms can be revealed. R-eco was derived during nighttime by automatic chamber CO2 flux measurements on plant covered plots. R-h was derived from CO2 efflux measurements, which were performed in parallel to R-eco measurements on a fallow plot using CO2 sampling tubes in 10 cm soil depth. R-a (root) was calculated as the difference between sampling tube CO2 efflux measurements on a plant covered plot and R-h. R-a (shoot) was calculated as R-eco - R-a (root) - R-h. Measurements were carried out for winter wheat (Triticum aestivum L.) during the crop season 2015 at an experimental plot located in the hummocky ground moraine landscape of NE Germany. R-eco varied seasonally from < 1 to 9.5 g C m(-2) d(-1), and was higher in adult (a) and reproductive (r) than juvenile (j) stands (gC m(-2) d(-1): j = 1.2, a = 4.6, r = 5.3). Observed R-a and R-h were in general smaller compared to the independently measured R-eco, contributing in average 58% and 42% to R-eco. However, both varied strongly regarding their environmental drivers and particular contribution throughout the study period, following the seasonal development of soil temperature and moisture (R-h) as well as crop development (R-a). Thus, our results consistently revealed temporal dynamics regarding the relative contribution of R-a (root) and R-a (shoot) to R-a, as well as of R-a and R-h to R-eco. Based on the observed results, implications for partitioning of R-eco in croplands are given.
Content and binding forms of heavy metals, aluminium and phosphorus in bog iron ores from Poland
(2009)
Bog iron ores are widespread in Polish wetland soils used as meadows or pastures. They are suspected to contain high concentrations of heavy metals, which are precipitated together with Fe along a redox gradient. Therefore, soils with bog iron ore might be important sources for a heavy metal transfer from meadow plants into the food chain. However, this transfer depends on the different binding forms of heavy metals. The binding forms were quantified by sequential extraction analysis of heavy metals (Fe, Mn, Cr, Co, Ni, Cd, Pb) as well as Al and P on 13 representative samples of bog iron ores from central and southwestern Poland. Our results showed total contents of Cr, Co, Ni, Zn, Cd, and Pb not to exceed the natural values for sandy soils from Poland. Only the total Mn was slightly higher. The highest contents of all heavy metals have,been obtained in iron oxide fractions V (occluded in noncrystalline and poorly crystalline Fe oxides) and VI (occluded in crystalline Fe oxides). The results show a distinct relationship between the content of Fe and the quantity of Zn and Pb as well R Water soluble as well as plant available fractions were below the detection limit in most cases. From this we concluded bog iron ores not to be an actual, important source of heavy metals in the food chain. However, a remobilization of heavy metals might occur due to any reduction of iron oxides in bog iron ores, for example, by rising groundwater levels.
Aggregate formation in poly(3-hexylthiophene) depends on molecular weight, solvent, and synthetic method. The interplay of these parameters thus largely controls device performance. In order to obtain a quantitative understanding on how these factors control the resulting electronic properties of P3HT, we measured absorption in solution and in thin films as well as the resulting field effect mobility in transistors. By a detailed analysis of the absorption spectra, we deduce the fraction of aggregates formed, the excitonic coupling within the aggregates, and the conjugation length within the aggregates, all as a function of solvent quality for molecular weights from 5 to 19 kDa. From this, we infer in which structure the aggregated chains pack. Although the 5 kDa samples form straight chains, the 11 and 19 kDa chains are kinked or folded, with conjugation lengths that increase as the solvent quality reduces. There is a maximum fraction of aggregated chains (about 55 +/- 5%) that can be obtained, even for poor solvent quality. We show that inducing aggregation in solution leads to control of aggregate properties in thin films. As expected, the field-effect mobility correlates with the propensity to aggregation. Correspondingly, we find that a well-defined synthetic approach, tailored to give a narrow molecular weight distribution, is needed to obtain high field effect mobilities of up to 0.01 cm2/Vs for low molecular weight samples (=11 kDa), while the influence of synthetic method is negligible for samples of higher molecular weight, if low molecular weight fractions are removed by extraction.
Due to the fact that silicon (Si) increases the resistance of plants against diverse abiotic and biotic stresses, Si nowadays is categorized as beneficial substance for plants. However, humans directly influence Si cycling on a global scale. Intensified agriculture and corresponding harvest-related Si exports lead to Si losses in agricultural soils. This anthropogenic desilication might be a big challenge for modern agriculture. However, there is still only little knowledge about Si cycling in agricultural systems of the temperate zone, because most studies focus on rice and sugarcane production in (sub)tropical areas. Furthermore, many studies are performed for a short term only, and thus do not provide the opportunity to analyze slow changes in soil-plant systems (e.g., desilication) over long periods. We analyzed soil and plant samples from an ongoing long-term field experiment (established 1963) in the temperate zone (NE Germany) to evaluate the effects of different nitrogen-phosphoruspotassium (NPK) fertilization rates and crop straw recycling (i.e., straw incorporation) on anthropogenic desilication in the long term. Our results clearly show that crop straw recycling not only prevents anthropogenic desilication (about 43-60% of Si exports can be saved by crop straw recycling in the long term), but also replenishes plant available Si stocks of agricultural soil-plant systems. Furthermore, we found that a reduction of N fertilization rates of about 69% is possible without considerable biomass losses. This economy of the need for N fertilizers potentially can be combined with the benefits of crop straw recycling, i.e., enhancement of carbon sequestration via straw inputs and prevention of anthropogenic desilication of agricultural soil-plant systems. Thus crop straw recycling might have the potential to act as key management practice in sustainable, low fertilization agriculture in the temperate zone in the future.
Testate amoebae with self-secreted siliceous shell platelets ("idiosomes") play an important role in terrestrial silicon (Si) cycles. In this context, Si-dependent culture growth dynamics of idiosomic testate amoebae are of interest. Clonal cultures of idiosomic testate amoebae were analyzed under three different Si concentrations: low (50 mu mol L-1), moderate/site-specific (150 mu mol L-1) and high Si supply (500 mu mol L-1). Food (Saccharomyces cerevisiae) was provided in surplus. (i) Shell size of four different clones of idiosomic testate amoebae either decreased (Trinema galeata, Euglypha filifera cf.), increased (E. rotunda cf.), or did not change (E. rotunda) under the lowest Si concentration (50 mu mol Si L-1). (ii) Culture growth of idiosomic Euglypha rotunda was dependent on Si concentration. The more Si available in the culture medium, the earlier the entry into exponential growth phase. (iii) Culture growth of idiosomic Euglypha rotunda was dependent on origin of inoculum. Amoebae previously cultured under a moderate Si concentration revealed highest sustainability in consecutive cultures. Amoebae derived from cultures with high Si concentrations showed rapid culture growth which finished early in consecutive cultures. (iv) Si (diluted in the culture medium) was absorbed by amoebae and fixed in the amoeba shells resulting in decreased Si concentrations. (C) 2016 Elsevier GmbH. All rights reserved.
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.
Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (Delta SOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in Delta SOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal Delta SOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of Delta SOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot / were used. To verify our method, results were compared with Delta SOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of Delta SOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual Delta SOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of Delta SOC.
Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (Delta SOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in Delta SOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal Delta SOC patterns but lack small-scale spatial resolution.
To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of Delta SOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot / were used. To verify our method, results were compared with Delta SOC observed by soil resampling.
Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of Delta SOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual Delta SOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of Delta SOC.
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.
Dynamic C and N stocks
(2015)
The drainage and cultivation of fen peatlands create complex small-scale mosaics of soils with extremely variable soil organic carbon (SOC) stocks and groundwater levels (GWLs). To date, the significance of such sites as sources or sinks for greenhouse gases such as CO2 and CH4 is still unclear, especially if the sites are used for cropland. As individual control factors such as GWL fail to account for this complexity, holistic approaches combining gas fluxes with the underlying processes are required to understand the carbon (C) gas exchange of drained fens. It can be assumed that the stocks of SOC and N located above the variable GWL - defined as dynamic C and N stocks - play a key role in the regulation of the plant- and microbially mediated CO2 fluxes in these soils and, inversely, for CH4. To test this assumption, the present study analysed the C gas exchange (gross primary production - GPP; ecosystem respiration - R-eco; net ecosystem exchange - NEE; CH4) of maize using manual chambers for 4 years. The study sites were located near Paulinenaue, Germany, where we selected three soil types representing the full gradient of GWL and SOC stocks (0-1 m) of the landscape: (a) Haplic Arenosol (AR; 8 kg C m(-2)); (b) Mollic Gleysol (GL; 38 kg C m(-2)); and (c) Hemic Histosol (HS; 87 kg C m(-2)). Daily GWL data were used to calculate dynamic SOC (SOCdyn) and N (N-dyn) stocks.
Average annual NEE differed considerably among sites, ranging from 47 +/- 30 g C m(-2) yr(-1) in AR to -305 +/- 123 g C m(-2) yr(-1) in GL and -127 +/- 212 g C m(-2) yr(-1) in HS. While static SOC and N stocks showed no significant effect on C fluxes, SOCdyn and N-dyn and their interaction with GWL strongly influenced the C gas exchange, particularly NEE and the GPP : R-eco ratio. Moreover, based on nonlinear regression analysis, 86% of NEE variability was explained by GWL and SOCdyn. The observed high relevance of dynamic SOC and N stocks in the aerobic zone for plant and soil gas exchange likely originates from the effects of GWL-dependent N availability on C formation and transformation processes in the plant-soil system, which promote CO2 input via GPP more than CO2 emission via R-eco.
The process-oriented approach of dynamic C and N stocks is a promising, potentially generalisable method for system-oriented investigations of the C gas exchange of groundwater-influenced soils and could be expanded to other nutrients and soil characteristics. However, in order to assess the climate impact of arable sites on drained peatlands, it is always necessary to consider the entire range of groundwater-influenced mineral and organic soils and their respective areal extent within the soil landscape.
The drainage and cultivation of fen peatlands create complex small-scale mosaics of soils with extremely variable soil organic carbon (SOC) stocks and groundwater levels (GWLs). To date, the significance of such sites as sources or sinks for greenhouse gases such as CO2 and CH4 is still unclear, especially if the sites are used for cropland. As individual control factors such as GWL fail to account for this complexity, holistic approaches combining gas fluxes with the underlying processes are required to understand the carbon (C) gas exchange of drained fens. It can be assumed that the stocks of SOC and N located above the variable GWL - defined as dynamic C and N stocks - play a key role in the regulation of the plant- and microbially mediated CO2 fluxes in these soils and, inversely, for CH4. To test this assumption, the present study analysed the C gas exchange (gross primary production - GPP; ecosystem respiration - R-eco; net ecosystem exchange - NEE; CH4) of maize using manual chambers for 4 years. The study sites were located near Paulinenaue, Germany, where we selected three soil types representing the full gradient of GWL and SOC stocks (0-1 m) of the landscape: (a) Haplic Arenosol (AR; 8 kg C m(-2)); (b) Mollic Gleysol (GL; 38 kg C m(-2)); and (c) Hemic Histosol (HS; 87 kg C m(-2)). Daily GWL data were used to calculate dynamic SOC (SOCdyn) and N (N-dyn) stocks.
Average annual NEE differed considerably among sites, ranging from 47 +/- 30 g C m(-2) yr(-1) in AR to -305 +/- 123 g C m(-2) yr(-1) in GL and -127 +/- 212 g C m(-2) yr(-1) in HS. While static SOC and N stocks showed no significant effect on C fluxes, SOCdyn and N-dyn and their interaction with GWL strongly influenced the C gas exchange, particularly NEE and the GPP : R-eco ratio. Moreover, based on nonlinear regression analysis, 86% of NEE variability was explained by GWL and SOCdyn. The observed high relevance of dynamic SOC and N stocks in the aerobic zone for plant and soil gas exchange likely originates from the effects of GWL-dependent N availability on C formation and transformation processes in the plant-soil system, which promote CO2 input via GPP more than CO2 emission via R-eco.
The process-oriented approach of dynamic C and N stocks is a promising, potentially generalisable method for system-oriented investigations of the C gas exchange of groundwater-influenced soils and could be expanded to other nutrients and soil characteristics. However, in order to assess the climate impact of arable sites on drained peatlands, it is always necessary to consider the entire range of groundwater-influenced mineral and organic soils and their respective areal extent within the soil landscape.
The size and dynamics of biogenic silicon (BSi) pools influence silicon (Si) fluxes from terrestrial to aquatic ecosystems. The research focus up to now was on the role of plants in Si cycling. In recent studies on old forests annual biosilicification rates of idiosomic testate amoebae (i.e. TA producing self-secreted silica shells) were shown to be of the order of Si uptake by trees. However, no comparable data exist for initial ecosystems. We analyzed the protozoic BSi pool (idiosomic TA), corresponding annual biosilicification rates and readily available and amorphous Si fractions along a 10-year chronosequence in a post-mining landscape in Brandenburg, Germany.
Idiosomic Si pools ranged from 3 to 680 g Si ha(-1) and were about 3-4 times higher at vegetated compared to uncovered spots. They increased significantly with age and were related to temporal development of soil chemical properties. The calculation of annual biosilicification resulted in maxima between 2 and 16 kg Si ha(-1) with rates always higher at vegetated spots. Our results showed that the BSi pool of idiosomic TA is built up rapidly during the initial phases of ecosystem development and is strongly linked to plant growth. Furthermore, our findings highlight the importance of TA for Si cycling in young artificial ecosystems. (C) 2014 Elsevier B.V. All rights reserved.
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 landscape of the semiarid Pampa in central Argentina is characterized by late Pleistocene aeolian deposits, covering large plains with sporadic dune structures. Since the current land use changed from extensive livestock production within the Caldenal forest ecosystem to arable land, the wind erosion risk increased distinctly. We measured wind erosion and deposition patterns at the plot scale and investigated the spatial variability of the erosion processes. The wind-induced mass-transport was measured with 18 Modified Wilson and Cooke samplers (MWAC), installed on a 1.44 ha large field in a 20 x 40 m grid. Physical and chemical soil properties from the upper soil as well as a digital elevation model were recorded in a 20 x 20 m grid. In a 5-month measuring campaign data from seven storms with three different wind directions was obtained. Results show very heterogeneous patterns of erosion and deposition for each storm and indicate favoured erosion on windward and deposits on leeward terrain positions. Furthermore, a multiple regression model was build, explaining up to 70% of the spatial variance of erosion by just using four predictors: topsoil thickness, relative elevation, soil organic carbon content and slope direction. Our findings suggest a structure-process-structure complex where the landscape structure determines the effects of recent wind erosion processes which again slowly influence the structure, leading to a gradual increase of soil heterogeneity.
Mineral topsoils possess large organic carbon (OC) contents but there is only limited knowledge on the mechanisms controlling the preservation of organic matter (OM) against microbial decay. Samples were taken from the uppermost mineral topsoil horizon (0 to 5 cm) of seven sites under mature deciduous forest showing OC contents between 69 and 164 g kg(-1) and a wide range in mineral characteristics. At first, organic particles and the water-extractable OM were removed from the soil samples. Thereafter, Na-pyrophosphate extractable organic matter (OM(PY)), assumed to be indicative for OM bound via cation mediated interactions, and the OM remaining in the extraction residue (OM(ER)), supposed to be indicative for OM occluded in mechanically highly stable micro-aggregates, were sequentially separated and quantified. The composition of OM(PY) and OM(ER) was analyzed by FTIR and their stability by C-14 measurements. The OC remaining in the extraction residues accounted for 38 to 59% of the bulk soil OC (SOC) suggesting a much larger relevance of OM(ER) for the OM dynamic in the analyzed soils as compared with OM(PY) that accounted for 1.6 to 7.5% of the SOC. The FUR analyses revealed a lower relative proportion of C=O groups in OM(ER) compared to OM(PY) indicating differences in the degree of microbial processing between these fractions. Correlation analyses suggest an increase in the stability of OM(PY) with the soil pH and contents of Na-pyrophosphate soluble Fe, Al, and Mg and an increase in the stability of OM(ER) with the soil pH and the contents of clay and oxalate-soluble Fe and Al. Despite the detected influence of soil mineral characteristics on the turnover of OM(PY) and OM(ER), the Delta C-14 signatures indicated mean residence times less than 100 years. The presence of less stabilized OM in these fractions can be derived from methodological uncertainties and/or the fast cycling compartment of mineral-associated OM. (C) 2015 Elsevier B.V. All rights reserved.
The significance of phytoliths for the control of silicon (Si) fluxes from terrestrial to aquatic ecosystems has been recognized as a key factor. Humankind actively influences Si fluxes by intensified land use, i.e., agriculture and forestry, on a global scale. We hypothesized phytolith distribution and assemblages in soils of agricultural and forestry sites to be controlled by vegetation (which is directed by land use) with direct effects on extractable Si fractions driven mainly by phytolith characteristics, i.e., dissolution status (dissolution signs) and morphology (morphotype proportions). To test our hypothesis we combined different chemical extraction methods (calcium chloride, ammonium oxalate, Tiron) for the quantification of different Si fractions (plant available Si, Si adsorbed to/occluded in pedogenic oxides/hydroxides, amorphous Si) and microscopic techniques (light microscopy, confocal laser scanning microscopy, scanning electron microscopy) for detailed analyses of phytoliths extracted using gravimetric separation (physical extraction) from exemplary loess soils of agricultural (arable land and grassland/meadow) and forestry (beech and pine) sites in Poland. We found differences in dissolution signs, morphotype proportions, and vertical distribution of phytoliths in soil horizons per site. In general, dominant morphotypes of assignable phytoliths in the studied soil profiles were elongate phytoliths and short cells, both of which are typical for grass-dominated vegetation. However, the organic layers of forest soils were dominated by globular phytoliths, which are typical indicators for mosses. As expected soil horizons under different vegetation generally were characterized by differences in extractable Si fractions, especially in the upper soil horizons. However, phytogenic Si pools counter-intuitively showed no correlations with chemically extracted Si fractions and soil pH at all. Our findings indicate that it is necessary to combine microscopic analyses and Si extraction techniques for examinations of Si cycling in biogeosystems, because extractions of Si fractions alone do not allow drawing any conclusions about phytolith characteristics or interactions between phytolith pools and chemically extractable Si fractions and do not necessarily reflect phytogenic Si pool quantities in soils and vice versa.
The role of soil erosion in terrestrial carbon (C) sequestration and release remains one of the most important uncertainties in our attempts to determine the potential of soils to mediate climate change. Despite its widely recognized importance for terrestrial C sequestration, to date, no Earth System Model (ESM) implements soil erosion effects on carbon cycling in sufficient detail. So far, available studies have mostly investigated the magnitude of erosional C transport and in-situ measurements of vertical C fluxes on the catchment or regional scale. Recognizing the need to adequately represent C erosion processes and controls in ESMs, we provide a comprehensive cross-disciplinary review on lateral C redistribution in the landscape and discuss the implications for bio-geochemical cycling of carbon. We present current knowledge on the role of erosional C distribution in controlling the stabilization and release of C in soils, taking into consideration the important geomorphic, ecological, hydrologic, pedologic and micro-climatic processes and controls that affect soil organic carbon (SOC) stock, fluxes, and persistence in dynamic landscapes. Further, we provide an overview on latest experimental and modelling approaches that are being used to investigate the role of erosion in the carbon cycle. Finally, to advance our understanding of the role of soil redistribution in biogeochemical cycles of essential elements, we discuss the most promising topics for future research in this field. (C) 2015 Elsevier B.V. All rights reserved.
Silicon (Si) is considered as a quasiessential element for higher plants as its uptake increases plant growth and resistance against abiotic as well as biotic stresses. Foliar application of fertilizers generally is assumed to be a comparably environment-friendly form of fertilization because only small quantities are needed. The interest in foliar fertilization and the use of Si as a fertilizer in general increased significantly within the last decades, but there are only few publications dealing with the foliar application of Si at all. In the present review, the effects of Si foliar fertilization, including nano-Si fertilizers, on the three most important crops on a global scale, that is, maize, rice, and wheat, are summarized. Additionally, different pathways (i.e., cuticular pathways, stomata, and trichomes) of foliar uptake and functioning of Si foliar fertilizers against biotic (i.e., fungal diseases and harmful insects), as well as abiotic (i.e., water stress, macronutrient imbalance, and heavy metal toxicity) stressors are discussed. Future research should especially focus on (1) the gathering of empirical data from field and greenhouse experiments, (2) the intensification of co-operations between practitioners and scientists, (3) interdisciplinary research, and (4) the analysis of results from multiple studies (meta-analysis, big data) to fully understand effects, uptake, and functioning of Si foliar fertilizers and to evaluate their potential in modern sustainable agriculture concepts.
From gustiness to dustiness
(2022)
This study delivers the first empirical data-driven analysis of the impact of turbulence induced gustiness on the fine dust emissions from a measuring field. For quantification of the gust impact, a new measure, the Gust uptake Efficiency (GuE) is introduced. GuE provides a percentage of over- or under-proportional dust uptake due to gust activity during a wind event. For the three analyzed wind events, GuE values of up to 150% could be found, yet they significantly differed per particle size class with a tendency for lower values for smaller particles. In addition, a high-resolution correlation analysis among 31 particle size classes and wind speed was conducted; it revealed strong negative correlation coefficients for very small particles and positive correlations for bigger particles, where 5 mu m appears to be an empirical threshold dividing both directions. We conclude with a number of suggestions for further investigations: an optimized field experiment setup, a new particle size ratio (PM1/PM0.5 in addition to PM10/PM2.5), as well as a comprehensive data-driven search for an optimal wind gust definition in terms of soil erosivity.
Soilscapes of the post-glacial morainic regions of the youngest glaciation are characterized by small hydrological kettle hole catchments forming hummocky soil landscapes. The spatial heterogeneity of subsurface structures as well as erosion-controlled pedogenesis under arable land use may complicate hydrological modeling. Our aim was to generate a soil landscape model for a small representative kettle hole catchment based on geoelectrical exploration and soil profile information. For a 1-ha catchment located in the northeastern German lowlands near the town of Prenzlau, electrical resistivity transects were determined by a multi electrode system (IMPETUS 12 Fs) and electrical conductivity (ECa) was mapped by using the electromagnetic induction (EMI) device EM38DD in both the vertical and horizontal modes. The 1-m digital elevation model (DEM) was obtained by kriging from high resolution manual elevation data determined with a leveling device (ZEISS Ni 40). Soil profile data from 26 boreholes distributed radially around the central pond were used to identify boundaries between soil horizons. The soil is characterized by varying topography and morphology of diagnostic horizons such as M- (colluvium), Bt- (clay illuviation), and C- (parent glacial till). By EMI mapping we identified (i) the boundary between erosive and colluvial areas around the kettle hole, and modeled (ii) the subsurface morphology of loamy horizons. Electrical resistivity tomography results coincide with these findings and allow for distinguishing between sandy and loamy dominated areas both in vertical and horizontal direction, respectively. This soil model of soil textural properties could be used for hydrological modeling.
A detailed analysis of horizontal and vertical particulate matter (PM) fluxes during wind erosion has been done, based on measurements of PM smaller than 10, 2.5, and 1.0 mu mm, at windward and leeward positions on a measuring field. The three fractions of PM measurement are differently influenced by the increasing wind and shear velocities of the wind. The measured concentrations of the coarser fractions of the fine dust, PM10, and PM2.5, increase with wind and shear velocity, whereas the PM1.0 concentrations show no clear correlation to the shear velocity. The share of PM2.5 on PM10 depends on the measurement height and wind speed and varies between 4 and 12 m/s at the 1 m height ranging from 25% to 7% (average 10%), and at the 4 m height from 39% to 23% (average 30%). Although general relationships between wind speed, PM concentration, and horizontal and vertical fluxes could be found, the contribution of the measuring field was very low, as balances of incoming and outgoing fluxes show. Consequently, the measured PM concentrations are determined from a variety of sources, such as traffic on unpaved roads, cattle drives, tillage operations, and wind erosion, and thus, represent all components of land use and landscape structure in the near and far surroundings of the measuring field. The current results may reflect factors from the landscape scale rather than the influence of field-related variables. The measuring devices used to monitor PM concentrations showed differences of up to 20%, which led to considerable deviations when determining total balances. Differences up to 67% between the calculated fluxes prove the necessity of a previous calibration of the devices used. (c) 2022 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion Research.
The significance of biogenic silicon (BSi) pools as a key factor for the control of Si fluxes from terrestrial to aquatic ecosystems has been recognized for decades. However, while most research has been focused on phytogenic Si pools, knowledge of other BSi pools is still limited. We hypothesized that different BSi pools influence short-term changes in the water-soluble Si fraction in soils to different extents. To test our hypothesis we took plant (Calamagrostis epigejos, Phragmites australis) and soil samples in an artificial catchment in a post-mining landscape in the state of Brandenburg, Germany. We quantified phytogenic (phytoliths), protistic (diatom frustules and testate amoeba shells) and zoogenic (sponge spicules) Si pools as well as Tironextractable and water-soluble Si fractions in soils at the beginning (t(0)) and after 10 years (t(10)) of ecosystem development. As expected the results of Tiron extraction showed that there are no consistent changes in the amorphous Si pool at Chicken Creek (Huhnerwasser) as early as after 10 years. In contrast to t(0) we found increased water-soluble Si and BSi pools at t(10); thus we concluded that BSi pools are the main driver of short-term changes in water-soluble Si. However, because total BSi represents only small proportions of water-soluble Si at t(0) (< 2 %) and t(10) (2.8-4.3 %) we further concluded that smaller (< 5 mu m) and/or fragile phytogenic Si structures have the biggest impact on short-term changes in water-soluble Si. In this context, extracted phytoliths (> 5 mu m) only amounted to about 16% of total Si con-tents of plant materials of C. epigejos and P. australis at t(10); thus about 84% of small-scale and/or fragile phytogenic Si is not quantified by the used phytolith extraction method. Analyses of small-scale and fragile phytogenic Si structures are urgently needed in future work as they seem to represent the biggest and most reactive Si pool in soils. Thus they are the most important drivers of Si cycling in terrestrial biogeosystems.
The significance of biogenic silicon (BSi) pools as a key factor for the control of Si fluxes from terrestrial to aquatic ecosystems has been recognized for decades. However, while most research has been focused on phytogenic Si pools, knowledge of other BSi pools is still limited. We hypothesized that different BSi pools influence short-term changes in the water-soluble Si fraction in soils to different extents. To test our hypothesis we took plant (Calamagrostis epigejos, Phragmites australis) and soil samples in an artificial catchment in a post-mining landscape in the state of Brandenburg, Germany. We quantified phytogenic (phytoliths), protistic (diatom frustules and testate amoeba shells) and zoogenic (sponge spicules) Si pools as well as Tironextractable and water-soluble Si fractions in soils at the beginning (t(0)) and after 10 years (t(10)) of ecosystem development. As expected the results of Tiron extraction showed that there are no consistent changes in the amorphous Si pool at Chicken Creek (Huhnerwasser) as early as after 10 years. In contrast to t(0) we found increased water-soluble Si and BSi pools at t(10); thus we concluded that BSi pools are the main driver of short-term changes in water-soluble Si. However, because total BSi represents only small proportions of water-soluble Si at t(0) (< 2 %) and t(10) (2.8-4.3 %) we further concluded that smaller (< 5 mu m) and/or fragile phytogenic Si structures have the biggest impact on short-term changes in water-soluble Si. In this context, extracted phytoliths (> 5 mu m) only amounted to about 16% of total Si con-tents of plant materials of C. epigejos and P. australis at t(10); thus about 84% of small-scale and/or fragile phytogenic Si is not quantified by the used phytolith extraction method. Analyses of small-scale and fragile phytogenic Si structures are urgently needed in future work as they seem to represent the biggest and most reactive Si pool in soils. Thus they are the most important drivers of Si cycling in terrestrial biogeosystems.
The hummocky ground moraine soil landscape forms a spatial continuum of more or less eroded and depositional soils developed from glacial till under intensive agricultural cultivation. Measurements of soil hydraulic properties in the laboratory on soil cores are mostly limited to some characteristic horizons. However, these horizons can vary in thickness or structural and pedological development depending on relief position. This paper compares soil hydraulic properties of the same soil horizons sampled at different relief positions in a single field representing various degrees of soil erosion/deposition. Water retention curves were determined from undisturbed core samples using sand and kaolin beds with hanging water column and pressure chambers, and the unsaturated hydraulic conductivity using the double-membrane apparatus. Data were fitted to the van Genuchten-Mualem function (VGM) using the nonlinear curve fitting program RETC. The desorption water retention curves for the soil horizons were different and depended on the soil structural development that could be related with the intensity of erosion history at each landscape position. The greatest differences in hydraulic functions were found for the E, Bt, and C horizons. The fitted soil water retention curves reflected these differences mainly in the values of the VGM curve parameters n and theta(s). The landscape features that have the strongest differentiating effect are related to erosion and distance towards the water table. The results can help improving pedotransfer approaches for the estimation of spatially distributed hydraulic parameters for modelling the water movement in hummocky soil landscapes as basis for establishing landscape scale water and element balances.
In order to identify the areas in the Xilingele grassland which are sensitive to wind erosion, a computational fluid dynamics model (CFD-WEM) was used to simulate the wind fields over a region of 37 km(2) which contains different topography and land use types. Previous studies revealed the important influences of topography and land use on wind erosion in the Xilingele grassland. Topography influences wind fields at large scale, and land use influences wind fields near the ground. Two steps were designed to implement the CFD wind simulation, and they were respectively to simulate the influence of topography and surface roughness on the wind. Digital elevation model (DEM) and surface roughness length were the key inputs for the CFD simulation. The wind simulation by CFD-WEM was validated by a wind data set which was measured simultaneously at six positions in the field. Three scenarios with different wind velocities were designed based on observed dust storm events, and wind fields were simulated according to these scenarios to predict the sensitive areas to wind erosion. General assumptions that cropland is the most sensitive area to wind erosion and heavily and moderately grazed grasslands are both sensitive etc. can be refined by the modelling of CFD-WEM. Aided by the results of this study, the land use planning and protection measures against wind erosion can be more efficient. Based on the case study in the Xilingele grassland, a method of regional wind erosion assessment aided by CFD wind simulation is summarized. The essence of this method is a combination of CFD wind simulation and determination of threshold wind velocity for wind erosion. Because of the physically-based simulation and the flexibility of the method, it can be generalised to other regions.
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.
Hummocky soil landscapes are characterized by 3D spatial patterns of soil types that result from erosion-affected pedogenesis. Due to tillage and water erosion, truncated profiles have been formed at steep and mid slopes and colluvial soils at hollows, while intact profiles remained at plateau positions. Pedogenetic variations in soil horizons lead to spatial differences in the soil water balance at hillslope positions. Here, possible interactions between erosion affected soil properties, the water balances, and the crop growth and feedback effects of erosion on the leaching rates were assumed. The hypothesis was tested by water balance simulations comparing uniform with hillslope position-specific crop and root growths for soils at plateau, flat mid slope, steep slope, and hollow using the Hydrus-1D program. The boundary condition data were monitored at the CarboZALF-D experimental field site, which was cropped with perennial lucerne (Medicago sativa L.) in 2013 and 2014. Crop and root growth at the four hillslope positions was assumed proportional to observed leaf area index (LAI). Fluxes of dissolved organic and inorganic carbon (DOC, DIC) were obtained from simulated water fluxes and measured DOC and DIC concentrations. For the colluvic soil at hollow, the crop growth was initially highest and later limited by an increasing water table; here the predominately upward flow led to a net input in DIC and DOC. For the truncated soils at steep slopes, simulations support the hypothesis that reduced crop growth caused an increase in percolation and DIC leaching from the subsoil horizons, which in turn led to accelerated soil development and more soil variations along eroding hillslopes in arable soil landscapes. (C) 2015 Elsevier B.V. All rights reserved.
The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To facilitate in-depth evaluations of the effects of climate and land use changes and to separate the effects of natural and anthropogenic drivers in the region, six sites were chosen for comprehensive monitoring. In addition, at selected sites, geoarchives were used to substantially extend the instrumental records back in time. It is this combination of diverse disciplines working across different time scales that makes the observatory TERENO-NE a unique observation platform. We provide information about the general characteristics of the observatory and its six monitoring sites and present examples of interdisciplinary research activities at some of these sites. We also illustrate how monitoring improves process understanding, how remote sensing techniques are fine-tuned by the most comprehensive ground-truthing site DEMMIN, how soil erosion dynamics have evolved, how greenhouse gas monitoring of rewetted peatlands can reveal unexpected mechanisms, and how proxy data provides a long-term perspective of current ongoing changes.
Precision farming needs management rules to apply spatially differentiated treatments in agricultural fields. Digital soil mapping (DSM) tools, for example apparent soil electrical conductivity, corrected to 25A degrees C (EC25), and digital elevation models, try to explain the spatial variation in soil type, soil properties (e.g. clay content), site and crop that are determined by landscape characteristics such as terrain, geology and geomorphology. We examined the use of EC25 maps to delineate management zones, and identified the main factors affecting the spatial pattern of EC25 at the regional scale in a study area in eastern Germany. Data of different types were compared: EC25 maps for 11 fields, soil properties measured in the laboratory, terrain attributes, geological maps and the description of 75 soil profiles. We identified the factors that influence EC25 in the presence of spatial autocorrelation and field-specific random effects with spatial linear mixed-effects models. The variation in EC25 could be explained to a large degree (R (2) of up to 61%). Primarily, soil organic matter and CaCO3, and secondarily clay and the presence of gleyic horizons were significantly related to EC25. Terrain attributes, however, had no significant effect on EC25. The geological map unit showed a significant relationship to EC25, and it was possible to determine the most important soil properties affecting EC25 by interpreting the geological maps. Including information on geology in precision agriculture could improve understanding of EC25 maps. The EC25 maps of fields should not be assumed to represent a map of clay content to form a basis for deriving management zones because other factors appeared to have a more important effect on EC25.
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.
Provisioning a sufficient stable source of food requires sound knowledge about current and upcoming threats to agricultural production. To that end machine learning approaches were used to identify the prevailing climatic and soil hydrological drivers of spatial and temporal yield variability of four crops, comprising 40 years yield data each from 351 counties in Germany. Effects of progress in agricultural management and breeding were subtracted from the data prior the machine learning modelling by fitting smooth non-linear trends to the 95th percentiles of observed yield data. An extensive feature selection approach was followed then to identify the most relevant predictors out of a large set of candidate predictors, comprising various soil and meteorological data. Particular emphasis was placed on studying the uniqueness of identified key predictors. Random Forest and Support Vector Machine models yielded similar although not identical results, capturing between 50% and 70% of the spatial and temporal variance of silage maize, winter barley, winter rapeseed and winter wheat yield. Equally good performance could be achieved with different sets of predictors. Thus identification of the most reliable models could not be based on the outcome of the model study only but required expert's judgement. Relationships between drivers and response often exhibited optimum curves, especially for summer air temperature and precipitation. In contrast, soil moisture clearly proved less relevant compared to meteorological drivers. In view of the expected climate change both excess precipitation and the excess heat effect deserve more attention in breeding as well as in crop modelling.
Carbon (C) stored in soils represents the largest C pool of terrestrial ecosystems and consequently plays a crucial role in the global C cycle. So far, it is widely unclear to what extent different land uses and land use change influence soil C storage. The hummocky ground moraine landscape of northeastern Germany is characterized by distinct small-scale soil heterogeneity on the one hand, and intensive energy crop cultivation on the other. Both factors are assumed to significantly influence gaseous C exchange; as such, they likely drive soil organic carbon (SOC) stock dynamics in terrestrial agricultural ecosystems. To date, it is not clear to what extent N fertilization forms, which are associated with energy crop cultivation (e.g., application of biogas fermentation residues) and soil type relative to soil erosion state, influence soil C dynamics, nor is it clear whether one of these factors is more important than the other. To investigate the influence of soil erosion state and N fertilization form on soil C dynamics, we present dynamic and seasonal net ecosystem carbon balances (NECB) as a proxy for changes in soil organic carbon stocks. Measurements were conducted for maize (Zea mays L.) at five sites in the "CarboZALF-D" experimental field during the 2011 growing season. Measurement sites represent different soil erosion states (non-eroded Albic Luvisols, extremely eroded Calcaric Regosols and depositional Endogleyic Colluvic Regosols) and N fertilization forms (100% mineral fertilizer, 50% mineral and 50% organic fertilizer, and 100% organic fertilizer). Fertilization treatments were established on the Albic Luvisol. Net ecosystem CO2 exchange (NEE) and ecosystem respiration (R-eco) were measured every four weeks using a dynamic flow-through non-steady-state closed manual chamber system. Gap filling was performed based on empirical temperature and PAR dependency functions and was used to derive daily NEE values. In parallel, daily above-ground biomass production (NPFshoot) was estimated using a logistic growth equation, fitted on periodic biomass samples. Finally, C dynamics were calculated as the balance of daily NEE and NPPshoot based on the initial C input due to organic fertilization. Resulting NECB varied from pronounced soil C losses at the Endogleyic Colluvic Regosol (592 g C m(-2)) to soil C gains at the Calcaric Regosol (-124 g C m(-2)). Minor to modest C losses were observed for the Albic Luvisol. Compared to N fertilization forms, soil erosion states generally had a stronger impact on derived NECB. However, interannual variations in plant phonology and interactions between soil erosion states and fertilization forms might result in different NECB values over multiple years. Hence, long-term measurements of different fertilization treatments on characteristic soil landscape elements are needed.
This study presents the first Si isotope data of the principle Si pools in soils determined by a UV femtosecond laser ablation system coupled to a multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS). This method reveals accurate and precise Si isotope data on bulk materials, and at high spatial resolution, on the mineral scale. The following Si pools have been investigated: a) the Si source to soils on all major silicate minerals on thin sections from bedrock fragments in the soil profiles; b) bulk soils (particle size <2 mm) after fusion to glass beads with an iridium-strip heater or pressed into powder pellets: c) separated clay fractions as pressed powder pellets and e) separated phytoliths as pressed powder pellets. Multiple analyses of three rock standards, BHVO-2, AGV-1 and RGM-1 as fused glass beads and as pressed powder pellets, reveal delta(30)Si values within the expected range of igneous rocks. The MPI-DING reference glass KL2-G exhibits the same Si isotope composition after remelting by an iridium-strip heater showing that this technique does not alter the isotope composition of the glass.
We used this approach to investigated two immature Cambisols developed on sandstone and paragneiss in the Black Forest (Germany), respectively. Bulk soils show a largely uniform Si isotope signature for different horizons and locations, which is close to those of primary quartz and feldspar with delta(30)Si values around -0.4 parts per thousand. Soil clay formation is associated with limited Si mobility, which preserves initial Si isotope signatures of parental minerals. An exception is the organic horizon of the paragneiss catchment where intense weathering leads to a high mobility of Si and significant negative isotope signatures as low as to -1.00 parts per thousand in bulk soils. Biogenic opal in the form of phytoliths, exhibits negative Si isotope signatures of about -0.4 parts per thousand. These results demonstrate that UV femtosecond laser ablation MC-ICP-MS provides a tool to characterize the Si isotope signature of the principle Si pools left behind after weathering and Si transport have altered soils. These results can now serve as a fingerprint of the residual solids that can be used to explain the isotope composition of dissolved Si in soil solutions and river water, which is mostly enriched in the heavy isotopes.
A common problem in ecology is identifying the relationship between relief and site properties obtainable only by point measurements. The method of Multi-Scale Landscape Analysis (MSLA) identifies such correlations. MSLA combines frequency filtering of the digital elevation model (DEM) with an estimation of the optimum filter coefficients using an optimization procedure. Tested using point data of soil decarbonation from a German young moraine landscape, MSLA provided significant results. Implemented within open source software SAMT. MSLA is comfortable and flexible to use, offering applications for numerous other spatial analysis problems.
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.
The ability of water to transport and transform soil materials is one of the main drivers of soil and landscape development. In turn, soil and landscape properties determine how water is distributed in soil landscapes. Understanding the complex dynamics of this co-evolution of soils, landscapes and the hydrological system is fundamental in adapting land management to changes in climate. Soil-Landscape Evolution Models (SLEMs) are used to simulate the development and evolution of soils and landscapes. However, many hydrologic processes, such as preferential flow and subsurface lateral flow, are currently absent in these models. This limits the applicability of SLEMs to improve our understanding of feedbacks in the hydro-pedo-geomorphological system. Implementation of these hydrologic processes in SLEMs faces several complications related to calculation demands, limited methods for linking pedogenic and hydrologic processes, and limited data on quantification of changes in the hydrological system over time. In this contribution, we first briefly review processes and feedbacks in soil-landscape-hydrological systems. Next, we elaborate on the development required to include these processes in SLEMs. We discuss the state-of-the-art knowledge, identify complications, give partial solutions and suggest important future development. The main requirements for incorporating hydrologic processes in SLEMs are: (1) designing a model framework that can deal with varying timescales for different sets of processes, (2) developing and implementing methods for simulating pedogenesis as a function of water flow, (3) improving and implementing knowledge on the evolution and dynamics of soil hydraulic properties over different timescales, and (4) improving the database on temporal changes and dynamics of flow paths.
Subsurface lateral flow in hillslope soils depends on lower permeability or texture-contrasting soil horizons. In the arable hummocky soil landscape, erosion processes caused glacial till appearance closer to the soil surface at upslope positions. The objective of this work was to quantify the potential for subsurface lateral flow depending on the erosion-affected spatial hydropedological complexity. The eroded Haplic Luvisol profile was studied due to the presence of a relatively dense C horizon that varied in depth, thickness, and sloping angle. A two-dimensional numerical modeling and sensitivity analysis for the saturated hydraulic conductivity (K-s) of the C horizon and the depth to C horizon (i.e., soil solum thickness) was performed for rainstorms in 2011 and 2012 using HYDRUS-2D. A K-s value of <2.5 cm d(-1) for the C horizon was required for lateral flow initiation. Lateral flow was (i) increasing with decreasing solum thickness, indicating an erosion-induced feedback on subsurface lateral flow, and (ii) dependent on the soil moisture regime prior to rainstorms. The effect of lateral flow on the movement of a conservative tracer was simulated in the form of a "virtual experiment". Simulation scenarios revealed only a relatively small lateral shift of the tracer plume caused by a local decoupling of water (already lateral) from subsequent tracer movement (still vertical). Longer term simulations suggested that, for the present conditions, lateral flow was limited mostly to occasional summer storm events. Even without considering preferential flow contribution to lateral flow, highly complex hydropedologic interactions are present in erosion-affected heterogeneous soil profiles.