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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.
The open source computational fluid dynamics (CFD) wind model (CFD-WEM) for wind erosion research in the Xilingele grassland in Inner Mongolia (autonomous region, China) is compared with two open source CFD models Gerris and OpenFOAM. The evaluation of these models was made according to software technology, implemented methods, handling, accuracy and calculation speed. All models were applied to the same wind tunnel data set. Results show that the simplest CFD-WEM has the highest calculation speed with acceptable accuracy, and the most powerful OpenFOAM produces the simulation with highest accuracy and the lowest calculation speed. Gerris is between CFD-WEM and OpenFOAM. It calculates faster than OpenFOAM, and it is capable to solve different CFD problems. CFD-WEM is the optimal model to be further developed for wind erosion research in Inner Mongolia grassland considering its efficiency and the uncertainties of other input data. However, for other applications using CFD technology, Gerris and OpenFOAM can be good choices. This paper shows the powerful capability of open source CFD software in wind erosion study, and advocates more involvement of open source technology in wind erosion and related ecological researches.
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.
For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha(-1)) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance.
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.
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.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.
Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental conditions. Due to the immanent spatial soil variability, the transferability of results to larger areas, such as catchments, is therefore limited. However, the emergence of new technical features and increasing knowledge on details in Si cycling lead to a more complex picture at landscape and catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation but also its biomass distribution and related Si stocks. Maximum likelihood (ML) classification was applied to multispectral imagery captured by an unmanned aerial system (UAS) aiming at the identification of land cover classes (LCCs). Subsequently, the normalized difference vegetation index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si-accumulating plants (Calamagrostis epige-jos and Phragmites australis) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of C. epige-jos and P. australis to be surprisingly high (maxima of Si stocks reach values up to 98 g Sim(-2)), i.e. comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results, we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities, and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.
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.
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.
We hypothesized that at the very beginning of terrestrial ecosystem development, airborne testate amoebae play a pivotal role in facilitating organismic colonization and related soil processes. We, therefore, analyzed size and quantity of airborne testate amoebae and immigration and colonization success of airborne testate amoebae on a new land surface (experimental site "Chicken Creek", artificial post-mining water catchment). Within an altogether 91-day exposure of 70 adhesive traps, 12 species of testate amoebae were identified to be of airborne origin. Phryganella acropodia (51% of all individuals found, diameter about 35-45 mu m) and Centropyxis sphagnicola (23% of all individuals found, longest axis about 55-68 mu m), occurred most frequently in the adhesive traps. We extrapolated an aerial amoeba deposition of 61 individuals d(-1) m(-2) (living and dead individuals combined). Although it would be necessary to have a longer sequence (some additional years), our analysis of the "target substrate" of aerial immigration (catchment site) may point to a shift from a stochastic (variable) beginning of community assembly to a more deterministic (stable) course. This shift was assigned to an age of seven years of initial soil development. Although experienced specialists are necessary to conduct these time-consuming studies, the presented data suggest that terrestrial amoebae are suitable indicators for initial ecosystem development and utilization.
Erosion processes, aggravated by human activity, have a large impact on the spatial variation of soil and topographic properties. Knowledge of the topography prior to human-induced erosion (paleotopography) in naturally stable landscapes is valuable for identifying vulnerable landscape positions and is required as starting point for erosion modelling exercises. However, developing accurate reconstructions of paleotopography provide a major challenge for geomorphologists. Here, we present a set of paleotopographies for a closed kettle hole catchment in north-east Germany (4 ha), obtained through different reconstruction approaches. Current soil and colluvium thickness, estimated from a dataset of 264 soil descriptions using Ordinary Kriging, were used as input for a mass balance, or were compared with a set of undisturbed soil thicknesses to estimate the amount of erosion. The performance of the different approaches was assessed with cross-validation and the count of mispredicted eroded, depositional or stable landscape positions. The paleotopographic reconstruction approach based on the average thickness of undisturbed soils in the study area showed the best performance. This thickness (1.00 m) is comparable to the average undisturbed soil thickness in the region and in line with global correlations of soil thickness as a function of rainfall and initial CaCO3 content. The performance of the different approaches depended more on mispredictions of landscape position due to the assumption of a spatially constant initial soil depth than on small variations in this depth. To conclude, we mention several methodological and practical points of attention for future topography reconstruction studies, concerning data quality and availability, spatial configuration of data and other processes affecting topography. (C) 2017 Elsevier B.V. All rights reserved.
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.
Reconstructing rates and patterns of colluvial soil redistribution in agrarian (hummocky) landscapes
(2019)
Humans have triggered or accelerated erosion processes since prehistoric times through agricultural practices. Optically stimulated luminescence (OSL) is widely used to quantify phases and rates of the corresponding landscape change, by measuring the last moment of daylight exposure of sediments. However, natural and anthropogenic mixing processes, such as bioturbation and tillage, complicate the use of OSL as grains of different depositional ages become mixed, and grains become exposed to light even long after the depositional event of interest. Instead, OSL determines the stabilization age, indicating when sediments were buried below the active mixing zone. These stabilization ages can cause systematic underestimation when calculating deposition rates. Our focus is on colluvial deposition in a kettle hole in the Uckermark region, northeastern Germany. We took 32 samples from five locations in the colluvium filling the kettle hole to study both spatial and temporal patterns in colluviation. We combined OSL dating with advanced age modelling to determine the stabilization age of colluvial sediments. These ages were combined with an archaeological reconstruction of historical ploughing depths to derive the levels of the soil surface at the moment of stabilization; the deposition depths, which were then used to calculate unbiased deposition rates. We identified two phases of colluvial deposition. The oldest deposits (similar to 5 ka) were located at the fringe of the kettle hole and accumulated relatively slowly, whereas the youngest deposits (<0.3 ka) rapidly filled the central kettle hole with rates of two orders of magnitude higher. We suggest that the latter phase is related to artificial drainage, facilitating accessibility in the central depression for agricultural practices. Our results show the need for numerical dating techniques that take archaeological and soil-geomorphological information into account to identify spatiotemporal patterns of landscape change, and to correctly interpret landscape dynamics in anthropogenically influenced hilly landscapes. (c) 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons Ltd.
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.
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.
Silicon stable isotopes have emerged as a powerful proxy to investigate weathering because Si uptake from solution by secondary minerals or by the vegetation causes significant shifts in the isotope composition. In this study, we determined the Si isotope compositions of the principle Si pools within two small catchments located on sandstone and paragneiss, respectively, in the temperate Black Forest (Germany). At both settings, clay formation is dominated by mineral transformation preserving largely the signature of parental minerals with delta Si-30 values of around -0.7%. Bulk soils rich in primary minerals are similar to bulk parental material with delta Si-30 values close to -0.4%. Topsoils are partly different because organic matter degradation has promoted intense weathering leading to delta Si-30 values as low as -1.0%. Water samples expose highly dynamic weathering processes in the soil zone: 1) after spring snowmelt, increased release of DOC and high water fluxes trigger clay mineral dissolution which leads to delta Si-30 values down to -0.7% and 2) in course of the summer, Si uptake by the vegetation and secondary mineral formation drives dissolved Si to typical positive delta Si-30 values up to 1.1%. Groundwater with delta Si-30 values of around 0.4% records steady processes in bedrock reflecting plagioclase weathering together with kaolinite precipitation. An isotope mass balance approach reveals incongruent weathering conditions where denudation of Si is largely driven by physical erosion. Erosion of phytoliths contributes 3 to 21% to the total Si export flux, which is in the same order as the dissolved Si flux. These results elucidate the Si dynamics during weathering on catchments underlain of sedimentary origin, prevailing on the Earth surface and provide therefore valuable information to interpret the isotope signature of large river systems.
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.
Silicon (Si) is the second-most abundant element in the earth's crust. In the pedosphere, however, huge spans of Si contents occur mainly caused by Si redistribution in soil profiles and landscapes. Here, we summarize the current knowledge on the different pools and fluxes of Si in soils and terrestrial biogeosystems. Weathering and subsequent release of soluble Si may lead to (1) secondarily bound Si in newly formed Al silicates, (2) amorphous silica precipitation on surfaces of other minerals, (3) plant uptake, formation of phytogenic Si, and subsequent retranslocation to soils, (4) translocation within soil profiles and formation of new horizons, or (5) translocation out of soils (desilication). The research carried out hitherto focused on the participation of Si in weathering processes, especially in clay neoformation, buffering mechanisms for acids in soils or chemical denudation of landscapes. There are, however, only few investigations on the characteristics and controls of the low-crystalline, almost pure silica compounds formed during pedogenesis. Further, there is strong demand to improve the knowledge of (micro)biological and rhizosphere processes contributing to Si mobilization, plant uptake, and formation of phytogenic Si in plants, and release due to microbial decomposition. The contribution of the biogenic Si sources to Si redistribution within soil profiles and desilication remains unknown concerning the pools, rates, processes, and driving forces. Comprehensive studies considering soil hydrological, chemical, and biological processes as well as their interactions at the scale of pedons and landscapes are necessary to make up and model the Si balance and to couple terrestrial processes with Si cycle of limnic, fluvial, or marine biogeosystems
The relevance of biological Si cycling for dissolved silica (DSi) export from terrestrial biogeosystems is still in debate. Even in systems showing a high content of weatherable minerals, like Cambisols on volcanic tuff, biogenic Si (BSi) might contribute > 50% to DSi (Gerard et al., 2008). However, the number of biogeosystem studies is rather limited for generalized conclusions. To cover one end of controlling factors on DSi, i.e., weatherable minerals content, we studied a forested site with absolute quartz dominance (> 95 %). Here we hypothesise minimal effects of chemical weathering of silicates on DSi. During a four year observation period (05/2007-04/2011), we quantified (i) internal and external Si fluxes of a temperate-humid biogeosystem (beech, 120 yr) by BIOME-BGC (version ZALF), (ii) related Si budgets, and (iii) Si pools in soil and beech, chemically as well as by SEM-EDX. For the first time two compartments of biogenic Si in soils were analysed, i.e., phytogenic and zoogenic Si pool (testate amoebae). We quantified an average Si plant uptake of 35 kg Si ha(-1) yr(-1) - most of which is recycled to the soil by litterfall - and calculated an annual biosilicification from idiosomic testate amoebae of 17 kg Si ha(-1). The comparatively high DSi concentrations (6 mg L-1) and DSi exports (12 kg Si ha(-1) yr(-1)) could not be explained by chemical weathering of feldspars or quartz dissolution. Instead, dissolution of a relictic, phytogenic Si pool seems to be the main process for the DSi observed. We identified canopy closure accompanied by a disappearance of grasses as well as the selective extraction of pine trees 30 yr ago as the most probable control for the phenomena observed. From our results we concluded the biogeosystem to be in a transient state in terms of Si cycling.
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.
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 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.
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.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Silicon (Si) speciation and availability in soils is highly important for ecosystem functioning, because Si is a beneficial element for plant growth. Si chemistry is highly complex compared to other elements in soils, because Si reaction rates are relatively slow and dependent on Si species. Consequently, we review the occurrence of different Si species in soil solution and their changes by polymerization, depolymerization, and condensation in relation to important soil processes. We show that an argumentation based on thermodynamic endmembers of Si dependent processes, as currently done, is often difficult, because some reactions such as mineral crystallization require months to years (sometimes even centuries or millennia). Furthermore, we give an overview of Si reactions in soil solution and the predominance of certain solid compounds, which is a neglected but important parameter controlling the availability, reactivity, and function of Si in soils. We further discuss the drivers of soil Si cycling and how humans interfere with these processes. The soil Si cycle is of major importance for ecosystem functioning; therefore, a deeper understanding of drivers of Si cycling (e.g., predominant speciation), human disturbances and the implication for important soil properties (water storage, nutrient availability, and micro aggregate stability) is of fundamental relevance.
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.
Leaching of dissolved C in arable hummocky ground moraine soil landscapes is characterized by a spatial continuum of more or less erosion-affected Luvisols, Calcaric Regosols at exposed positions, and Colluvic Regosols in depressions. Our objective was to estimate the fluxes of dissolved C in four differently eroded soils as affected by erosion-induced pedological and soil structural alterations. In this model study, we considered landscape position effects by adapting the water table as the bottom boundary condition and erosion effects by using pedon-specific soil hydraulic properties. The one-dimensional vertical water movement was described with the Richards equation using HYDRUS-1D. Solute fluxes were obtained by combining calculated water fluxes with concentrations of dissolved organic and inorganic C (DOC and DIC, respectively) measured from soil solution extracted by suction cups at biweekly intervals. In the 3-yr period (2010-2012), DOC fluxes in the 2-m soil depth were similar at the three non-colluvic locations with -0.8 +/- 0.1 g m(-2) yr(-1) (i.e., outflow) but were 0.4 g m(-2) yr(-1) (i.e., input) in the depression. The DIC fluxes ranged from -10.2 g m(-2) yr(-1) for the eroded Luvisol, -9.2 g m(-2) yr(-1) for the Luvisol, and -6.1 g m(-2) yr(-1) for the Calcaric Regosol to 3.2 g m(-2) yr(-1) for the Colluvic Regosol. The temporal variations in DOC and DIC fluxes were controlled by water fluxes. The spatially distributed leaching results corroborate the hypothesis that the effects of soil erosion influence fluxes through modified hydraulic and transport properties and terrain-dependent boundary conditions.
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.
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.
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.
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.
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.
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.
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.
Biogenic silicon (BSI) pools influence Si cycling in terrestrial ecosystems. As research has been focused mainly on phytogenic BSi pools until now, there is only little information available on quantities of other BSi pools. There are no systematic studies on protozoic Si pools - here represented by idiosomic testate amoebae (TA) - and abiotic and biotic influences in temperate forest ecosystems. We selected ten old forests along a strong gradient in soil forming factors (especially parent material and climate), soil properties and humus forms. We quantified idiosomic Si pools, corresponding annual biosilicification, plant-available and amorphous Si fractions of topsoil horizons. Furthermore, we analyzed the potential influences of abiotic factors (e.g. soil pH) and earthworms on idiosomic Si pools.
While idiosomic Si pools were relatively small (up to 5 kg Si ha(-1)), annual biosilicification rates of living TA (17-80 kg Si ha(-1)) were comparable to or even exceeded reported data of annual Si uptake by trees. Soil pH exerted a strong, non-linear control on plant-available Si. Surprisingly, no relationship between Si supply and idiosomic Si pools could be found (no Si limitation). Instead, idiosomic Si pools showed a strong, negative relationship to earthworm biomasses, which corresponded to humus forms. We concluded that earthworms control idiosomic Si pools in forest soils by direct (feeding, competition) and/or indirect mechanisms (e.g. change of habitat structure). Earthworms themselves were strongly influenced by soil pH: Below a threshold of pH 3.8 no endogeic or anecic earthworms existed. As soil pH is a result of weathering and acidification idiosomic Si pools are indirectly, but ultimately controlled by soil forming factors, mainly parent material and climate. (C) 2014 Elsevier B.V. All rights reserved.
Landscapes can be viewed as spatially heterogeneous areas encompassing terrestrial and aquatic domains. To date, most landscape carbon (C) fluxes have been estimated by accounting for terrestrial ecosystems, while aquatic ecosystems have been largely neglected. However, a robust assessment of C fluxes on the landscape scale requires the estimation of fluxes within and between both landscape components. Here, we compiled data from the literature on C fluxes across the air–water interface from various landscape components. We simulated C emissions and uptake for five different scenarios which represent a gradient of increasing spatial heterogeneity within a temperate young moraine landscape: (I) a homogeneous landscape with only cropland and large lakes; (II) separation of the terrestrial domain into cropland and forest; (III) further separation into cropland, forest, and grassland; (IV) additional division of the aquatic area into large lakes and peatlands; and (V) further separation of the aquatic area into large lakes, peatlands, running waters, and small water bodies These simulations suggest that C fluxes at the landscape scale might depend on spatial heterogeneity and landscape diversity, among other factors. When we consider spatial heterogeneity and diversity alone, small inland waters appear to play a pivotal and previously underestimated role in landscape greenhouse gas emissions that may be regarded as C hot spots. Approaches focusing on the landscape scale will also enable improved projections of ecosystems’ responses to perturbations, e.g., due to global change and anthropogenic activities, and evaluations of the specific role individual landscape components play in regional C fluxes. WIREs Water 2016, 3:601–617. doi: 10.1002/wat2.1147
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.
Humidity is an important determinant of the mycotoxin production (DON, ZEA) by Fusarium species in the grain ears. From a landscape perspective humidity is not evenly distributed across fields. The topographically-controlled redistribution of water within a single field rather leads to spatially heterogeneous soil water content and air humidity. Therefore we hypothesized that the spatial distribution of mycotoxins is related to these topographically-controlled factors. To test this hypothesis we studied the mycotoxin concentrations at contrasting topographic relief positions, i.e. hilltops and depressions characterized by soils of different soil moisture regimes, on ten winter wheat fields in 2006 and 2007. Maize was the preceding crop and minimum tillage was practiced in the fields. The different topographic positions were associated with moderate differences in DON and ZEA concentrations in 2006, but with significant differences in 2007, with six times higher median ZEA and two times higher median DON detected at depression sites compared to the hilltops. The depression sites correspond to a higher topographic wetness index as well as redoximorphic properties in soil profiles, which empirically supports our hypothesis at least for years showing wetter conditions in sensitive time windows for Fusarium infections.
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.
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.
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.
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.