Markus Steffens

Sensitivity of peatland carbon loss to organic matter quality

Peatland soils store substantial amounts of organic matter (OM). During peat formation, easily decomposable OM is preferentially lost and more recalcitrant moieties accumulate. In a peat profile, OM quality thus scales with depth. Drainage and ongoing climate change poses the risk of rapid OM loss when formerly anoxic peat layers oxidize. During peat decomposition, deeper, more recalcitrant peat is exposed to the oxygen-rich surface, which may influence the decomposition rate. We show that the soil respiration rate of a disturbed temperate peatland is strongly controlled by the peats quality and especially its polysaccharides content. The polysaccharide content of soil profiles in a wider range of peatland sites with differing degrees of disturbance was inferred by means of solid-state C-13 NMR and DRIFT spectroscopy. The data confirmed a strong decline in polysaccharide content with depth and a poor OM quality of surface peat in soils drained decades ago. We combined the evidence from respiration and spectroscopic measurements to deduce the sensitivity of peatland carbon loss with respect to OM quality by scaling measured quality to a 142-years record of peatland subsidence and carbon loss at one of the sites. According to the functional relationship between quality and respiration, the measured average annual carbon loss rate of 2.5 t C ha(-1) at that site was 20 t C ha(-1) at the onset of peatland drainage and dropped to less than 1 t C ha(-1) in recent times. Citation: Leifeld, J., M. Steffens, and A. Galego-Sala (2012), Sensitivity of peatland carbon loss to organic matter quality, Geophys. Res. Lett., 39, L14704, doi: 10.1029/2012GL051856. (Less)

Soil microbial diversity affects soil organic matter decomposition in a silty grassland soil

Soil microorganisms play a pivotal role in soil organic matter (SOM) turn-over and their diversity is discussed as a key to the function of soil ecosystems. However, the extent to which SOM dynamics may be linked to changes in soil microbial diversity remains largely unknown. We characterized SOM degradation along a microbial diversity gradient in a two month incubation experiment under controlled laboratory conditions. A microbial diversity gradient was created by diluting soil suspension of a silty grassland soil. Microcosms containing the same sterilized soil were re-inoculated with one of the created microbial diversities, and were amended with 13C labeled wheat in order to assess whether SOM decomposition is linked to soil microbial diversity or not. Structural composition of wheat was assessed by solid-state 13C nuclear magnetic resonance, sugar and lignin content was quantified and labeled wheat contribution was determined by 13C compound specific analyses. Results showed decreased wheat O-alkyl-C with increasing microbial diversity. Total non-cellulosic sugar-C derived from wheat was not significantly influenced by microbial diversity. Carbon from wheat sugars (arabinose-C and xylose-C), however, was highest when microbial diversity was low, indicating reduced wheat sugar decomposition at low microbial diversity. Xylose-C was significantly correlated with the Shannon diversity index of the bacterial community. Soil lignin-C decreased irrespective of microbial diversity. At low microbial diversity the oxidation state of vanillyl–lignin units was significantly reduced. We conclude that microbial diversity alters bulk chemical structure, the decomposition of plant litter sugars and influences the microbial oxidation of total vanillyl–lignins, thus changing SOM composition.

Grazing changes topography-controlled topsoil properties and their interaction on different spatial scales in a semi-arid grassland of Inner Mongolia, P.R. China

Semiarid steppe ecosystems account for large terrestrial areas and are considered as large carbon (C) sinks. However, fundamental information on topsoil sensitivity to grazing is lacking across different spatial scales including the effects of topography. Our interdisciplinary approach considering soil chemical, physical, and vegetation properties included investigations on pit scale (square-metre scale), plot scale (hectare scale), and the scale of a landscape section (several hectares). Five different sites, representing a grazing intensity gradient, ranging from a long-term grazing exclosure to a heavily grazed site were used. On the pit scale, data about aggregate size distribution, quantity of different soil organic carbon (SOC) pools, SOC mineralisation, hydraulic conductivity and shear strength was available for topsoil samples from representative soil profiles. Spatial variability of topographical parameters, topsoil texture, bulk density, SOC, water repellency, and vegetation cover was analysed on the basis of regular, orthogonal grids in differently grazed treatments by using two different grid sizes on the plot scale and landscape section. On the pit scale, intensive grazing clearly decreased soil aggregation and the amount of fresh, litter-like particulate organic matter (POM). The weak aggregation in combination with animal trampling led to an enhanced mineralisation of SOC, higher topsoil bulk densities, lower infiltration rates, and subsequently to a higher risk of soil erosion. On the plot scale, the effects of soil structure disruption due to grazing are enhanced by the degradation of vegetation patches and resulted in a texture-controlled wettability of the soil surface. In contrast, topsoils of grazing exclosures were characterised by advantageous mechanical topsoil characteristics and SOC-controlled wettability due to higher POM contents. A combined geostatistical and General Linear Model approach identified topography as the fundamental factor creating the spatial distribution of texture fractions and related soil parameters on the scale of a landscape section. Grazing strongly interfered with the topography-controlled particle relocation processes in the landscape and showed strongest effects on the aboveground biomass production and biomass-related soil properties like SOC stocks. We conclude that interdisciplinary multi-scale analyses are essential (i) to differentiate between topography- and grazing-controlled spatial patterns of topsoil and vegetation properties, and (ii) to identify the main grazing-sensitive processes on small scales that are interacting with the spatial distribution and relocation processes on larger scales.

The Effects of Spectral Pretreatments on Chemometric Analyses of Soil Profiles Using Laboratory Imaging Spectroscopy

Laboratory imaging spectroscopy can be used to explore physical and chemical variations in soil profiles on a submillimetre scale. We used a hyperspectral scanner in the 400 to 1000 nm spectral range mounted in a laboratory frame to record images of two soil cores. Samples from these cores were chemically analyzed, and spectra of the sampled regions were used to train chemometric PLS regression models. With these models detailed maps of the elemental concentrations in the soil cores could be produced. Eight different spectral pretreatments were applied to the sample spectra and to the resulting images in order to explore the influence of these pre-treatments on the estimation of elemental concentrations. We found that spectral preprocessing has a minor influence on chemometry results when powerful regression algorithms like PLSR are used.

N balance and cycling of Inner Mongolia typical steppe: a comprehensive case study of grazing effects

Increasing grazing pressure and climate change affect nitrogen (N) dynamics of grassland ecosystems in the Eurasian steppe belt with unclear consequences for future delivery of essential services such as forage production, C sequestration, and diversity conservation. The identification of key processes responsive to grazing is crucial to optimize grassland management. In this comprehensive case study of a Chinese typical steppe, we present an in-depth analysis of grazing effects on N dynamics, including the balance of N gains and losses, and N cycling. N pools and fluxes were simultaneously quantified on three grassland sites of different long-term grazing intensities. Dust deposition, wind erosion, and wet deposition were the predominant but most variable processes contributing to N losses and gains. Heavy grazing increased the risk of N losses by wind erosion. Hay-making and sheep excrement export to folds during nighttime keeping were important pathways of N losses from grassland sites. Compared to the...

Spatial and temporal variation of soil moisture in dependence of multiple environmental parameters in semi-arid grasslands

Grazing of grasslands changes soil physical and chemical properties as well as vegetation characteristics, such as vegetation cover, species composition and biomass production. In consequence, nutrient allocation and water storage in the top soil are affected. Land use and management changes alter these processes. Knowledge on the impacts of grazing management on nutrient and water fluxes is necessary because of the global importance of grasslands for carbon sequestration. Soil water in semi-arid areas is a limiting factor for matter fluxes and the intrinsic interaction between soil, vegetation and atmosphere. It is therefore desirable to understand the effects of grazing management and stocking rate on the spatial and temporal distribution of soil moisture. In the present study, we address the question how spatio-temporal soil moisture distribution on grazed and ungrazed grassland sites is affected by soil and vegetation properties. The study took place in the Xilin river catchment in Inner Mongolia (PR China). It is a semi-arid steppe environment, which is characterized by still moderate grazing compared to other regions in central Inner Mongolia. However, stocking rates have locally increased and resulted in a degradation of soils and vegetation also in the upper Xilin River basin. We used a multivariate geostatistical approach to reveal spatial dependencies between soil moisture distribution and soil or vegetation parameters. Overall, 7 soil and vegetation parameters (bulk density, sand, silt and clay content, mean weight diameter, mean carbon content of the soil, vegetation cover) and 57 soil moisture data sets were recorded on 100 gridded points on four sites subject to different grazing intensities. Increasing stocking rates accelerated the influence of soil and vegetation parameters on soil moisture. However, the correlation was rather weak, except for a site with high stocking rate where higher correlations were found. Low nugget ratios indicate spatial dependency between soil or plant parameters and soil moisture on a long-term ungrazed site. However, the effect was not found for a second ungrazed site that had been excluded from grazing for a shorter period. Furthermore the most important soil and vegetation parameters for predicting soil moisture distribution varied between different grazing intensities. Therefore, predicting soil moisture by using secondary variables requires a careful selection of the soil or vegetation parameters.

Characterization, stability, and plant effects of kiln-produced wheat straw biochar.

Biochar is a promising technology for improving soil quality and sequestering C in the long term. Although modern pyrolysis technologies are being developed, kiln technologies often remain the most accessible method for biochar production. The objective of the present study was to assess biochar characteristics, stability in soil, and agronomic effects of a kiln-produced biochar. Wheat-straw biochar was produced in a double-barrel kiln and analyzed by solid-state C nuclear magneticresonance spectroscopy. Two experiments were conducted with biochar mixed into an Ap-horizon sandy loam. In the first experiment, CO efflux was monitored for 3 mo in plant-free soil columns across four treatments (0, 10, 50, and 100 Mg biochar ha). In the second experiment, ryegrass was grown in pots having received 17 and 54 Mg biochar ha combined with four N rates from 144 to 288 kg N ha. Our kiln method generated a wheat-straw biochar with carbon content composed of 92% of aromatic structures. Our results suggest that the biochar lost <0.16% C as CO over the 90-d incubation period. Biomass yields were not significantly modified by biochar treatments, except for a slight decrease at the 144 kg N ha rate. Foliar N concentrations were significantly reduced by biochar application. Biochar significantly increased soil water content; however, this increase did not result in increased biomass yield. In conclusion, our kiln-produced biochar was highly aromatic and appeared quite recalcitrant in soil but had no overall significant impact on ryegrass yields.

Organic matter stabilization in two Andisols of contrasting age under temperate rain forest

Recent studies with Andisols show that the carbon (C) stabilization capacity evolves with soil age relative to the evolution of the mineral phase. However, it is not clear how soil mineralogical changes during pedogenesis are related to the composition of soil organic matter (SOM) and 14C activity as an indicator for the mean residence time of soil organic matter (SOM). In the present study, we analyzed the contribution of allophane and metal–SOM complexes to soil C stabilization. Soil organic matter was analyzed with solid-state 13C nuclear magnetic resonance spectroscopy. Additionally, the soil was extracted with Na-pyrophosphate (Alp, Fep) and oxalate (Alo, Sio, and Feo). Results supported the hypothesis that allophane plays a key role for SOM stabilization in deep and oldest soil, while SOM stabilization by metal (Al and Fe) complexation is more important in the surface horizons and in younger soils. The metal/Cp ratio (Cp extracted in Na-pyrophosphate), soil pH, and radiocarbon age seemed to be important indicators for formation of SOM–metal complexes or allophane in top- and subsoils of Andisols. Changes in main mineral stabilization agents with soil age do not influence SOM composition. We suggest that the combination of several chemical parameters (Alp, Fep and Cp, metal/Cp ratio, and pH) which change through soil age controls SOM stabilization.

Identification of Distinct Functional Microstructural Domains Controlling C Storage in Soil

The physical, chemical, and biological processes forming the backbone of important soil functions (e.g., carbon sequestration, nutrient and contaminant storage, and water transport) take place at reactive interfaces of soil particles and pores. The accessibility of these interfaces is determined by the spatial arrangement of the solid mineral and organic soil components, and the resulting pore system. Despite the development and application of novel imaging techniques operating at the micrometer and even nanometer scale, the microstructure of soils is still considered as a random arrangement of mineral and organic components. Using nanoscale secondary ion mass spectroscopy (NanoSIMS) and a novel digital image processing routine adapted from remote sensing (consisting of image preprocessing, endmember extraction, and a supervised classification), we extensively analyzed the spatial distribution of secondary ions that are characteristic of mineral and organic soil components on the submicrometer scale in an intact soil aggregate (40 measurements, each covering an area of 30 μm × 30 μm with a lateral resolution of 100 nm × 100 nm). We were surprised that the 40 spatially independent measurements clustered in just two complementary types of micrometer-sized domains. Each domain is characterized by a microarchitecture built of a definite mineral assemblage with various organic matter forms and a specific pore system, each fulfilling different functions in soil. Our results demonstrate that these microarchitectures form due to self-organization of the manifold mineral and organic soil components to distinct mineral assemblages, which are in turn stabilized by biophysical feedback mechanisms acting through pore characteristics and microbial accessibility. These microdomains are the smallest units in soil that fulfill specific functionalities.

Hotspots of soil organic carbon storage revealed by laboratory hyperspectral imaging

Subsoil organic carbon (OC) is generally lower in content and more heterogeneous than topsoil OC, rendering it difficult to detect significant differences in subsoil OC storage. We tested the application of laboratory hyperspectral imaging with a variety of machine learning approaches to predict OC distribution in undisturbed soil cores. Using a bias-corrected random forest we were able to reproduce the OC distribution in the soil cores with very good to excellent model goodness-of-fit, enabling us to map the spatial distribution of OC in the soil cores at very high resolution (~53 × 53 µm). Despite a large increase in variance and reduction in OC content with increasing depth, the high resolution of the images enabled statistically powerful analysis in spatial distribution of OC in the soil cores. In contrast to the relatively homogeneous distribution of OC in the plough horizon, the subsoil was characterized by distinct regions of OC enrichment and depletion, including biopores which contained ~2–10 times higher SOC contents than the soil matrix in close proximity. Laboratory hyperspectral imaging enables powerful, fine-scale investigations of the vertical distribution of soil OC as well as hotspots of OC storage in undisturbed samples, overcoming limitations of traditional soil sampling campaigns.