TY - JOUR A1 - Rasigraf, Olivia A1 - Wagner, Dirk T1 - Landslides BT - an emerging model for ecosystem and soil chronosequence research JF - Earth science reviews : the international geological journal bridging the gap between research articles and textbooks N2 - Erosion by landslides is a common phenomenon in mountain regions around the globe, affecting all climatic zones. Landslides facilitate bedrock weathering, pedogenesis and ecological succession, being key drivers of biodiversity. Landslide chronosequences have long been used for studies of vegetation succession in initial ecosystems, but they further offer ideal model systems for studies of soil development and microbial community succession. In this review we synthesize the state of knowledge on the role of landslides in ecosystems, their influence on element cycles and interactions with biota. Further, we discuss feedback mechanisms between global warming, landslide activity and greenhouse gas emissions. In the view of increasing anthropogenic influence and climate change, soils are becoming a critical resource. Due to their ubiquity, landslide chronosequences have the potential to provide critical insights into soil development under different climates and thereby contribute to future soil restoration efforts. KW - Landslides KW - Greenhouse gas emissions KW - Landslide chronosequences KW - Soil KW - microbial community KW - Erosion KW - Biodiversity KW - Microbial processes KW - Climate KW - change Y1 - 2022 U6 - https://doi.org/10.1016/j.earscirev.2022.104064 SN - 0012-8252 SN - 1872-6828 VL - 231 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Fournier, Bertrand A1 - Steiner, Magdalena A1 - Brochet, Xavier A1 - Degrune, Florine A1 - Mammeri, Jibril A1 - Carvalho, Diogo Leite A1 - Siliceo, Sara Leal A1 - Bacher, Sven A1 - Peña-Reyes, Carlos Andrés A1 - Heger, Thierry Jean T1 - Toward the use of protists as bioindicators of multiple stresses in agricultural soils BT - a case study in vineyard ecosystems JF - Ecological indicators : integrating monitoring, assessment and management N2 - Management of agricultural soil quality requires fast and cost-efficient methods to identify multiple stressors that can affect soil organisms and associated ecological processes. Here, we propose to use soil protists which have a great yet poorly explored potential for bioindication. They are ubiquitous, highly diverse, and respond to various stresses to agricultural soils caused by frequent management or environmental changes. We test an approach that combines metabarcoding data and machine learning algorithms to identify potential stressors of soil protist community composition and diversity. We measured 17 key variables that reflect various potential stresses on soil protists across 132 plots in 28 Swiss vineyards over 2 years. We identified the taxa showing strong responses to the selected soil variables (potential bioindicator taxa) and tested for their predictive power. Changes in protist taxa occurrence and, to a lesser extent, diversity metrics exhibited great predictive power for the considered soil variables. Soil copper concentration, moisture, pH, and basal respiration were the best predicted soil variables, suggesting that protists are particularly responsive to stresses caused by these variables. The most responsive taxa were found within the clades Rhizaria and Alveolata. Our results also reveal that a majority of the potential bioindicators identified in this study can be used across years, in different regions and across different grape varieties. Altogether, soil protist metabarcoding data combined with machine learning can help identifying specific abiotic stresses on microbial communities caused by agricultural management. Such an approach provides complementary information to existing soil monitoring tools that can help manage the impact of agricultural practices on soil biodiversity and quality. KW - Biomonitoring KW - Machine learning KW - Predictive model KW - Soil function KW - Soil KW - quality KW - Microbial ecology Y1 - 2022 U6 - https://doi.org/10.1016/j.ecolind.2022.108955 SN - 1470-160X SN - 1872-7034 VL - 139 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Vaidya, Shrijana A1 - Schmidt, Marten A1 - Rakowski, Peter A1 - Bonk, Norbert A1 - Verch, Gernot A1 - Augustin, Jürgen A1 - Sommer, Michael A1 - Hoffmann, Mathias T1 - A novel robotic chamber system allowing to accurately and precisely determining spatio-temporal CO2 flux dynamics of heterogeneous croplands JF - Agricultural and forest meteorology N2 - 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. KW - Automatic chamber KW - Net ecosystem exchange (NEE) KW - Gross primary KW - productivity (GPP) KW - Ecosystem respiration (R-eco) KW - Soil erosion KW - Soil KW - heterogeneity Y1 - 2021 U6 - https://doi.org/10.1016/j.agrformet.2020.108206 SN - 0168-1923 SN - 1873-2240 VL - 296 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rühlmann, Madlen A1 - Büchele, Dominique A1 - Ostermann, Markus A1 - Bald, Ilko A1 - Schmid, Thomas T1 - Challenges in the quantification of nutrients in soils using laser-induced breakdown spectroscopy BT - a case study with calcium JF - Spectrochimica Acta Part B: Atomic Spectroscopy N2 - The quantification of the elemental content in soils with laser-induced breakdown spectroscopy (LIBS) is challenging because of matrix effects strongly influencing the plasma formation and LIBS signal. Furthermore, soil heterogeneity at the micrometre scale can affect the accuracy of analytical results. In this paper, the impact of univariate and multivariate data evaluation approaches on the quantification of nutrients in soil is discussed. Exemplarily, results for calcium are shown, which reflect trends also observed for other elements like magnesium, silicon and iron. For the calibration models, 16 certified reference soils were used. With univariate and multivariate approaches, the calcium mass fractions in 60 soils from different testing grounds in Germany were calculated. The latter approach consisted of a principal component analysis (PCA) of adequately pre-treated data for classification and identification of outliers, followed by partial least squares regression (PLSR) for quantification. For validation, the soils were also characterised with inductively coupled plasma optical emission spectroscopy (ICP OES) and X-ray fluorescence (XRF) analysis. Deviations between the LIBS quantification results and the reference analytical results are discussed. KW - Laser-induced breakdown spectroscopy (LIBS) KW - Soil KW - Multivariate data analysis KW - Principal component analysis (PCA) KW - Partial least squares regression (PLSR) Y1 - 2018 U6 - https://doi.org/10.1016/j.sab.2018.05.003 SN - 0584-8547 VL - 146 SP - 115 EP - 121 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Maass, Stefanie A1 - Daphi, Daniel A1 - Lehmann, Anika A1 - Rillig, Matthias C. T1 - Transport of microplastics by two collembolan species JF - Environmental pollution N2 - Plastics, despite their great benefits, have become a ubiquitous environmental pollutant, with micro-plastic particles having come into focus most recently. Microplastic effects have been intensely studied in aquatic, especially marine systems; however, there is lack of studies focusing on effects on soil and its biota. A basic question is if and how surface-deposited microplastic particles are transported into the soil. We here wished to test if soil microarthropods, using Collembola, can transport these particles over distances of centimeters within days in a highly controlled experimental set-up. We conducted a fully factorial experiment with two collembolan species of differing body size, Folsomia candida and Proisotoma minuta, in combination with urea-formaldehyde particles of two different particle sizes. We observed significant differences between the species concerning the distance the particles were transported. F. candida was able to transport larger particles further and faster than P. minuta. Using video, we observed F candida interacting with urea-formaldehyde particles and polyethylene terephthalate fibers, showing translocation of both material types. Our data clearly show that microplastic particles can be moved and distributed by soil microarthropods. Although we did not observe feeding, it is possible that microarthropods contribute to the accumulation of microplastics in the soil food web. (C) 2017 Elsevier Ltd. All rights reserved. KW - Microplastics KW - Soil KW - Collembolans KW - Transport KW - Pollution Y1 - 2017 U6 - https://doi.org/10.1016/j.envpol.2017.03.009 SN - 0269-7491 SN - 1873-6424 VL - 225 SP - 456 EP - 459 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Schulz, Katharina A1 - Voigt, Karsten A1 - Beusch, Christine A1 - Almeida-Cortez, Jarcilene S. A1 - Kowarik, Ingo A1 - Walz, Ariane A1 - Cierjacks, Arne T1 - Grazing deteriorates the soil carbon stocks of Caatinga forest ecosystems in Brazil JF - Forest ecology and management N2 - Grazing by domestic ungulates can have substantial impacts on forests in arid and semi-arid regions, possibly including severe loss of carbon from the soil. Predicting net livestock impacts on soil organic carbon stocks remains challenging, however, due to the dependence on animal loads and on soil and environmental parameters. The objective of this study was to better understand grazing effects on soil organic carbon in seasonal tropical dry forests of north-eastern Brazil (Caatinga) by quantifying carbon stocks of the upper soil profile (0–5 cm depth) and greater soil depths (>5 cm depth down to bedrock) along a gradient of grazing intensity while accounting for other influencing factors such as soil texture, vegetation, landscape topography, and water availability. We analysed soil organic carbon, soil clay content, altitude above sea level, soil depth to bedrock, distance to the nearest permanent water body, species diversity of perennial plants and aboveground biomass on 45 study plots located in the vicinity of the Itaparica Reservoir, Pernambuco, Brazil. Livestock (mainly goats and cattle) are unevenly distributed in the studied ecosystem, thus grazing intensity was accounted for based on the weight of livestock droppings per square metre and classified as no or light, intermediate, or heavy grazing. The mean soil organic carbon in the area was 16.86 ± 1.28 Mg ha−1 C with approximately one-quarter found in the upper 5 cm of the soil profile (4.14 ± 0.43 Mg ha−1 C) and the remainder (12.57 ± 0.97 Mg ha−1 C) in greater soil depths (>5 cm). Heavy grazing led to significantly lower soil organic carbon stocks in the upper 5 cm, whereas no effect on soil organic carbon of the soil overall or in greater soil depths was detectable. The soil’s clay content and the altitude proved to be the most relevant factors influencing overall soil organic carbon stocks and those in greater soil depths (>5 cm). Our findings suggest that grazing causes substantial release of carbon from Brazilian dry forest soils, which should be addressed through improved grazing management via a legally compulsory rotation system. This would ultimately contribute to the conservation of a unique forest system and associated ecosystem services. KW - Carbon cycle KW - Degradation KW - Desertification KW - Livestock KW - Semi-arid KW - Soil Y1 - 2016 U6 - https://doi.org/10.1016/j.foreco.2016.02.011 SN - 0378-1127 SN - 1872-7042 VL - 367 SP - 62 EP - 70 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Aichner, Bernhard A1 - Bussian, Bernd M. A1 - Lehnik-Habrink, Petra A1 - Hein, Sebastian T1 - Regionalized concentrations and fingerprints of polycyclic aromatic hydrocarbons (PAHs) in German forest soils JF - Environmental pollution N2 - Samples of 474 forest stands in Germany were analysed for concentrations of polycyclic aromatic hydrocarbons (PAHs) in three sampling depths. Enhanced concentrations were mainly found at spots relatively close to densely industrialized and urbanized regions and at some topographically elevated areas. Average enrichment factors between mineral soil and humic layer depend on humus type i.e. decrease from mull via moder to more Based on their compound-patterns, the observed samples could be assigned to three main clusters. For some parts of our study area a uniform assignment of samples to clusters over larger regions could be identified. For instance, samples taken at vicinity to brown-coal strip-mining districts are characterized by high relative abundances of low-molecular-weight PAHs. These results suggest that PAHs are more likely originated from local and regional emitters rather than from long-range transport and that specific source-regions can be identified based on PAH fingerprints. (C) 2015 Elsevier Ltd. All rights reserved. KW - Organic pollutants KW - PAHs KW - Soil KW - Emissions KW - Long-range transport KW - Enrichment factor KW - Humic layer KW - Mineral soil KW - O horizon Y1 - 2015 U6 - https://doi.org/10.1016/j.envpol.2015.03.026 SN - 0269-7491 SN - 1873-6424 VL - 203 SP - 31 EP - 39 PB - Elsevier CY - Oxford ER -