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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.
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.
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 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.