Articles | Volume 3, issue 3
https://doi.org/10.5194/soil-3-113-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/soil-3-113-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Original research article
| 
04 Aug 2017
Original research article |
| 04 Aug 2017
Decision support for the selection of reference sites using 137Cs as a soil erosion tracer
Laura Arata
Environmental Geosciences, Department of Environmental
Sciences, University of Basel, Basel, Switzerland
Katrin Meusburger
CORRESPONDING AUTHOR
Environmental Geosciences, Department of Environmental
Sciences, University of Basel, Basel, Switzerland
Alexandra Bürge
Environmental Geosciences, Department of Environmental
Sciences, University of Basel, Basel, Switzerland
Markus Zehringer
State Laboratory Basel-City, Basel, Switzerland
Michael E. Ketterer
Chemistry Department, Metropolitan State University of Denver,
Colorado, USA
Lionel Mabit
Soil and Water Management & Crop Nutrition Laboratory, FAO/IAEA
Agriculture & Biotechnology Laboratory, Vienna, Austria
Christine Alewell
Environmental Geosciences, Department of Environmental
Sciences, University of Basel, Basel, Switzerland
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Katrin Meusburger, Paolo Porto, Judith Kobler Waldis, and Christine Alewell
SOIL, 9, 399–409, https://doi.org/10.5194/soil-9-399-2023, https://doi.org/10.5194/soil-9-399-2023, 2023
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Quantifying soil redistribution rates is a global challenge. Radiogenic tracers such as plutonium, namely 239+240Pu, released to the atmosphere by atmospheric bomb testing in the 1960s are promising tools to quantify soil redistribution. Direct validation of 239+240Pu as soil redistribution is, however, still missing. Here, we used a unique sediment yield time series in southern Italy, reaching back to the initial fallout of 239+240Pu to verify 239+240Pu as a soil redistribution tracer.
Pedro V. G. Batista, Peter Fiener, Simon Scheper, and Christine Alewell
Hydrol. Earth Syst. Sci., 26, 3753–3770, https://doi.org/10.5194/hess-26-3753-2022, https://doi.org/10.5194/hess-26-3753-2022, 2022
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Patchy agricultural landscapes have a large number of small fields, which are separated by linear features such as roads and field borders. When eroded sediments are transported out of the agricultural fields by surface runoff, these features can influence sediment connectivity. By use of measured data and a simulation model, we demonstrate how a dense road network (and its drainage system) facilitates sediment transport from fields to water courses in a patchy Swiss agricultural catchment.
Lena Wohlgemuth, Pasi Rautio, Bernd Ahrends, Alexander Russ, Lars Vesterdal, Peter Waldner, Volkmar Timmermann, Nadine Eickenscheidt, Alfred Fürst, Martin Greve, Peter Roskams, Anne Thimonier, Manuel Nicolas, Anna Kowalska, Morten Ingerslev, Päivi Merilä, Sue Benham, Carmen Iacoban, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 19, 1335–1353, https://doi.org/10.5194/bg-19-1335-2022, https://doi.org/10.5194/bg-19-1335-2022, 2022
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Gaseous mercury is present in the atmosphere all over the globe. During the growing season, plants take up mercury from the air in a similar way as CO2. We investigated which factors impact this vegetational mercury uptake by analyzing a large dataset of leaf mercury uptake rates of trees in Europe. As a result, we conclude that mercury uptake is foremost controlled by tree-intrinsic traits like physiological activity but also by climatic factors like dry conditions in the air and in soils.
Lauren Zweifel, Maxim Samarin, Katrin Meusburger, and Christine Alewell
Nat. Hazards Earth Syst. Sci., 21, 3421–3437, https://doi.org/10.5194/nhess-21-3421-2021, https://doi.org/10.5194/nhess-21-3421-2021, 2021
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Mountainous grassland areas can be severely affected by soil erosion, such as by shallow landslides. With an automated mapping approach we are able to locate shallow-landslide sites on aerial images for 10 different study sites across Swiss mountain regions covering a total of 315 km2. Using a statistical model we identify important explanatory variables for shallow-landslide occurrence for the individual sites as well as across all regions, which highlight slope, aspect and terrain roughness.
Maral Khodadadi, Christine Alewell, Mohammad Mirzaei, Ehssan Ehssan-Malahat, Farrokh Asadzadeh, Peter Strauss, and Katrin Meusburger
SOIL Discuss., https://doi.org/10.5194/soil-2021-2, https://doi.org/10.5194/soil-2021-2, 2021
Revised manuscript not accepted
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Forest soils store carbon and therefore play an important role in mitigating climate change impacts. Yet again, deforestation for farming and grazing purposes has grown rapidly over the last decades. Thus, its impacts on soil erosion and soil quality should be understood in order to adopt sustainable management measures. The results of this study indicated that deforestation can prompt soil loss by multiple orders of magnitude and deteriorate the soil quality in both topsoil and subsoil.
Claudia Mignani, Jörg Wieder, Michael A. Sprenger, Zamin A. Kanji, Jan Henneberger, Christine Alewell, and Franz Conen
Atmos. Chem. Phys., 21, 657–664, https://doi.org/10.5194/acp-21-657-2021, https://doi.org/10.5194/acp-21-657-2021, 2021
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Most precipitation above land starts with ice in clouds. It is promoted by extremely rare particles. Some ice-nucleating particles (INPs) cause cloud droplets to already freeze above −15°C, a temperature at which many clouds begin to snow. We found that the abundance of such INPs among other particles of similar size is highest in precipitating air masses and lowest when air carries desert dust. This brings us closer to understanding the interactions between land, clouds, and precipitation.
Lena Wohlgemuth, Stefan Osterwalder, Carl Joseph, Ansgar Kahmen, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 17, 6441–6456, https://doi.org/10.5194/bg-17-6441-2020, https://doi.org/10.5194/bg-17-6441-2020, 2020
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Mercury uptake by trees from the air represents an important but poorly quantified pathway in the global mercury cycle. We determined mercury uptake fluxes by leaves and needles at 10 European forests which were 4 times larger than mercury deposition via rainfall. The amount of mercury taken up by leaves and needles depends on their age and growing height on the tree. Scaling up our measurements to the forest area of Europe, we estimate that each year 20 t of mercury is taken up by trees.
Miriam Groß-Schmölders, Pascal von Sengbusch, Jan Paul Krüger, Kristy Klein, Axel Birkholz, Jens Leifeld, and Christine Alewell
SOIL, 6, 299–313, https://doi.org/10.5194/soil-6-299-2020, https://doi.org/10.5194/soil-6-299-2020, 2020
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Degradation turns peatlands into a source of CO2. There is no cost- or time-efficient method available for indicating peatland hydrology or the success of restoration. We found that 15N values have a clear link to microbial communities and degradation. We identified trends in natural, drained and rewetted conditions and concluded that 15N depth profiles can act as a reliable and efficient tool for obtaining information on current hydrology, restoration success and drainage history.
José A. Gómez, Gema Guzmán, Arsenio Toloza, Christian Resch, Roberto García-Ruíz, and Lionel Mabit
SOIL, 6, 179–194, https://doi.org/10.5194/soil-6-179-2020, https://doi.org/10.5194/soil-6-179-2020, 2020
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The long-term evolution of soil organic carbon in an olive orchard (planted in 1856) was evaluated and compared to an adjacent undisturbed natural area. Total soil organic carbon in the top 40 cm of the soil in the orchard was reduced to 25 % of that in the undisturbed area. The deposition downslope in the orchard of sediment coming from the eroded upslope area did not increase the accumulation of organic carbon in soil, but it quadrupled available phosphorus and improved overall soil quality.
Pranav Hirave, Guido L. B. Wiesenberg, Axel Birkholz, and Christine Alewell
Biogeosciences, 17, 2169–2180, https://doi.org/10.5194/bg-17-2169-2020, https://doi.org/10.5194/bg-17-2169-2020, 2020
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Sediment input into water bodies is a prominent threat to freshwater ecosystems. We tested the stability of tracers employed in freshwater sediment tracing based on compound-specific isotope analysis during early degradation in soil. While bulk δ13C values showed no stability, δ13C values of plant-derived fatty acids and n-alkanes were stably transferred to the soil without soil particle size dependency after an early degradation in organic horizons, thus indicating their suitability as tracers.
Marlène Lavrieux, Axel Birkholz, Katrin Meusburger, Guido L. B. Wiesenberg, Adrian Gilli, Christian Stamm, and Christine Alewell
Biogeosciences, 16, 2131–2146, https://doi.org/10.5194/bg-16-2131-2019, https://doi.org/10.5194/bg-16-2131-2019, 2019
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A fingerprinting approach using compound-specific stable isotopes was applied to a lake sediment core to reconstruct erosion processes over the past 150 years in a Swiss catchment. Even though the reconstruction of land use and eutrophication history was successful, the observation of comparatively low δ13C values of plant-derived fatty acids in the sediment suggests their alteration within the lake. Thus, their use as a tool for source attribution in sediment cores needs further investigation.
Claudia Mignani, Jessie M. Creamean, Lukas Zimmermann, Christine Alewell, and Franz Conen
Atmos. Chem. Phys., 19, 877–886, https://doi.org/10.5194/acp-19-877-2019, https://doi.org/10.5194/acp-19-877-2019, 2019
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A snow crystal can be generated from an ice nucleating particle or from an ice splinter. In this study we made use of the fact that snow crystals with a particular shape (dendrites) grow within a narrow temperature range (−12 to −17 °C) and can be analysed individually for the presence of an ice nucleating particle. Our direct approach revealed that only one in eight crystals contained such a particle and was of primary origin. The other crystals must have grown from ice splinters.
Emiliano Stopelli, Franz Conen, Caroline Guilbaud, Jakob Zopfi, Christine Alewell, and Cindy E. Morris
Biogeosciences, 14, 1189–1196, https://doi.org/10.5194/bg-14-1189-2017, https://doi.org/10.5194/bg-14-1189-2017, 2017
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Based on the analysis of precipitation collected at high altitude, this study provides a relevant advancement in the assessment of the major factors responsible for the abundance and variability of airborne bacterial cells and Pseudomonas syringae in relation to ice nucleators. This is of prime importance to obtain a better understanding of the impact of ice-nucleation-active organisms on the development of precipitation and to determine the dispersal potential of airborne microorganisms.
Simon Schmidt, Christine Alewell, Panos Panagos, and Katrin Meusburger
Hydrol. Earth Syst. Sci., 20, 4359–4373, https://doi.org/10.5194/hess-20-4359-2016, https://doi.org/10.5194/hess-20-4359-2016, 2016
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We present novel research on the seasonal dynamics of the impact of rainfall (R-factor) on the mobilization of topsoil as soil erosion by water for Switzerland. A modeling approach was chosen that enables the dynamical mapping of the R-factor. Based on the maps and modeling results, we could investigate the spatial and temporal distribution of that factor, which is high for Switzerland. With these results, agronomists can introduce selective erosion control measures.
Emiliano Stopelli, Franz Conen, Cindy E. Morris, Erik Herrmann, Stephan Henne, Martin Steinbacher, and Christine Alewell
Atmos. Chem. Phys., 16, 8341–8351, https://doi.org/10.5194/acp-16-8341-2016, https://doi.org/10.5194/acp-16-8341-2016, 2016
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Knowing the variability of ice nucleating particles (INPs) helps determining their role in the formation of precipitation. Here we describe and predict the concentrations of INPs active at −8 °C in precipitation samples collected at Jungfraujoch (CH, 3580 m a.s.l.). A high abundance of these INPs can be expected whenever a coincidence of high wind speed and first precipitation from an air mass occurs. This expands the set of conditions where such INPs could affect the onset of precipitation.
Christine Alewell, Axel Birkholz, Katrin Meusburger, Yael Schindler Wildhaber, and Lionel Mabit
Biogeosciences, 13, 1587–1596, https://doi.org/10.5194/bg-13-1587-2016, https://doi.org/10.5194/bg-13-1587-2016, 2016
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Origin of suspended sediments in rivers is of crucial importance for optimization of catchment management. Sediment source attribution to a lowland river in central Switzerland with compound specific stable isotopes analysis (CSIA) indicated that 65 % of the suspended sediments originated from agricultural land during base flow, while forest was the dominant source during high flow. We achieved significant differences in CSIA signature from land uses dominated by C3 plant cultivation.
S. Osterwalder, J. Fritsche, C. Alewell, M. Schmutz, M. B. Nilsson, G. Jocher, J. Sommar, J. Rinne, and K. Bishop
Atmos. Meas. Tech., 9, 509–524, https://doi.org/10.5194/amt-9-509-2016, https://doi.org/10.5194/amt-9-509-2016, 2016
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Human activities have increased mercury (Hg) cycling between land and atmosphere. To define landscapes as sinks or sources of Hg we have developed an advanced REA system for long-term measurements of gaseous elemental Hg exchange. It was tested in two contrasting environments: above Basel, Switzerland, and a peatland in Sweden. Both landscapes showed net Hg emission (15 and 3 ng m−2 h−1, respectively). The novel system will help to advance our understanding of Hg exchange on an ecosystem scale.
J. P. Krüger, J. Leifeld, S. Glatzel, S. Szidat, and C. Alewell
Biogeosciences, 12, 2861–2871, https://doi.org/10.5194/bg-12-2861-2015, https://doi.org/10.5194/bg-12-2861-2015, 2015
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Biogeochemical soil parameters are studied to detect peatland degradation along a land use gradient (intensive, extensive, near-natural). Stable carbon isotopes, radiocarbon ages and ash content confirm peat growth in the near-natural bog but also indicate previous degradation. When the bog is managed extensively or intensively as grassland, all parameters indicate degradation and substantial C loss of the order of 18.8 to 42.9 kg C m-2.
K. Meusburger, G. Leitinger, L. Mabit, M. H. Mueller, A. Walter, and C. Alewell
Hydrol. Earth Syst. Sci., 18, 3763–3775, https://doi.org/10.5194/hess-18-3763-2014, https://doi.org/10.5194/hess-18-3763-2014, 2014
S. Stanchi, M. Freppaz, E. Ceaglio, M. Maggioni, K. Meusburger, C. Alewell, and E. Zanini
Nat. Hazards Earth Syst. Sci., 14, 1761–1771, https://doi.org/10.5194/nhess-14-1761-2014, https://doi.org/10.5194/nhess-14-1761-2014, 2014
J. P. Krüger, J. Leifeld, and C. Alewell
Biogeosciences, 11, 3369–3380, https://doi.org/10.5194/bg-11-3369-2014, https://doi.org/10.5194/bg-11-3369-2014, 2014
B. A. Hungate, B. D. Duval, P. Dijkstra, D. W. Johnson, M. E. Ketterer, P. Stiling, W. Cheng, J. Millman, A. Hartley, and D. B. Stover
Biogeosciences, 11, 3323–3337, https://doi.org/10.5194/bg-11-3323-2014, https://doi.org/10.5194/bg-11-3323-2014, 2014
E. Stopelli, F. Conen, L. Zimmermann, C. Alewell, and C. E. Morris
Atmos. Meas. Tech., 7, 129–134, https://doi.org/10.5194/amt-7-129-2014, https://doi.org/10.5194/amt-7-129-2014, 2014
K. Meusburger, L. Mabit, J.-H. Park, T. Sandor, and C. Alewell
Biogeosciences, 10, 5627–5638, https://doi.org/10.5194/bg-10-5627-2013, https://doi.org/10.5194/bg-10-5627-2013, 2013
K. Meusburger, G. Leitinger, L. Mabit, M. H. Mueller, and C. Alewell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-9505-2013, https://doi.org/10.5194/hessd-10-9505-2013, 2013
Preprint withdrawn
M. H. Mueller, R. Weingartner, and C. Alewell
Hydrol. Earth Syst. Sci., 17, 1661–1679, https://doi.org/10.5194/hess-17-1661-2013, https://doi.org/10.5194/hess-17-1661-2013, 2013
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SOIL, 8, 587–604, https://doi.org/10.5194/soil-8-587-2022, https://doi.org/10.5194/soil-8-587-2022, 2022
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István Dunkl and Mareike Ließ
SOIL, 8, 541–558, https://doi.org/10.5194/soil-8-541-2022, https://doi.org/10.5194/soil-8-541-2022, 2022
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Digital soil mapping (DSM) allows us to regionalize soil properties by relating them to environmental covariates with the help of an empirical model. Legacy soil data provide a valuable basis to generate high-resolution soil maps with DSM. We studied the usefulness of data-clustering methods to tackle potential sampling bias in legacy soil data while applying DSM for soil texture regionalization. Clustering has proved to be useful in various steps of the DSM process.
Ulrich Weller, Lukas Albrecht, Steffen Schlüter, and Hans-Jörg Vogel
SOIL, 8, 507–515, https://doi.org/10.5194/soil-8-507-2022, https://doi.org/10.5194/soil-8-507-2022, 2022
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Soil structure is of central importance for soil functions. It is, however, ill defined. With the increasing availability of X-ray CT scanners, more and more soils are scanned and an undisturbed image of the soil's structure is produced. Often, a qualitative description is all that is derived from these images. We provide now a web-based Soil Structure Library where these images can be evaluated in a standardized quantitative way and can be compared to a world-wide data set.
Brieuc Hardy, Nils Borchard, and Jens Leifeld
SOIL, 8, 451–466, https://doi.org/10.5194/soil-8-451-2022, https://doi.org/10.5194/soil-8-451-2022, 2022
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Soil amendment with artificial black carbon (BC; biomass transformed by incomplete combustion) has the potential to mitigate climate change. Nevertheless, the accurate quantification of BC in soil remains a critical issue. Here, we successfully used dynamic thermal analysis (DTA) to quantify centennial BC in soil. We demonstrate that DTA is largely under-exploited despite providing rapid and low-cost quantitative information over the range of soil organic matter.
Yuanyuan Yang, Zefang Shen, Andrew Bissett, and Raphael A. Viscarra Rossel
SOIL, 8, 223–235, https://doi.org/10.5194/soil-8-223-2022, https://doi.org/10.5194/soil-8-223-2022, 2022
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We present a new method to estimate the relative abundance of the dominant phyla and diversity of fungi in Australian soil. It uses state-of-the-art machine learning with publicly available data on soil and environmental proxies for edaphic, climatic, biotic and topographic factors, and visible–near infrared wavelengths. The estimates could serve to supplement the more expensive molecular approaches towards a better understanding of soil fungal abundance and diversity in agronomy and ecology.
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SOIL, 7, 693–715, https://doi.org/10.5194/soil-7-693-2021, https://doi.org/10.5194/soil-7-693-2021, 2021
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We present a soil mid-infrared library with over 1800 samples from central Africa in order to facilitate soil analyses of this highly understudied yet critical area. Together with an existing continental library, we demonstrate a regional analysis and geographical extrapolation to predict total carbon and nitrogen. Our results show accurate predictions and highlight the value that the data contribute to existing libraries. Our library is openly available for public use and for expansion.
Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021, https://doi.org/10.5194/soil-7-525-2021, 2021
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We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.
Kpade O. L. Hounkpatin, Johan Stendahl, Mattias Lundblad, and Erik Karltun
SOIL, 7, 377–398, https://doi.org/10.5194/soil-7-377-2021, https://doi.org/10.5194/soil-7-377-2021, 2021
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Forests store large amounts of carbon in soils. Implementing suitable measures to improve the sink potential of forest soils would require accurate data on the carbon stored in forest soils and a better understanding of the factors affecting this storage. This study showed that the prediction of soil carbon stock in Swedish forest soils can increase in accuracy when one divides a big region into smaller areas in combination with information collected locally and derived from satellites.
Hana Beitlerová, Jonas Lenz, Jan Devátý, Martin Mistr, Jiří Kapička, Arno Buchholz, Ilona Gerndtová, and Anne Routschek
SOIL, 7, 241–253, https://doi.org/10.5194/soil-7-241-2021, https://doi.org/10.5194/soil-7-241-2021, 2021
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This study presents transfer functions for a calibration parameter of the Green–Ampt infiltration module of the EROSION-2D/3D model, which are significantly improving the model performance compared to the current state. The relationships found between calibration parameters and soil parameters however put the Green–Ampt implementation in the model and the state-of-the-art parametrization method in question. A new direction of the infiltration module development is proposed.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
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In this study, we show that a soil spectral library (SSL) can be used to predict soil carbon at new and very different locations. The importance of this finding is that it requires less time-consuming lab work than calibrating a new model for every local application, while still remaining similar to or more accurate than local models. Furthermore, we show that this method even works for predicting (drained) peat soils, using a SSL with mostly mineral soils containing much less soil carbon.
Jennifer M. Rhymes, Irene Cordero, Mathilde Chomel, Jocelyn M. Lavallee, Angela L. Straathof, Deborah Ashworth, Holly Langridge, Marina Semchenko, Franciska T. de Vries, David Johnson, and Richard D. Bardgett
SOIL, 7, 95–106, https://doi.org/10.5194/soil-7-95-2021, https://doi.org/10.5194/soil-7-95-2021, 2021
Matthew A. Belanger, Carmella Vizza, G. Philip Robertson, and Sarah S. Roley
SOIL, 7, 47–52, https://doi.org/10.5194/soil-7-47-2021, https://doi.org/10.5194/soil-7-47-2021, 2021
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Soil health is often assessed by re-wetting a dry soil and measuring CO2 production, but the potential bias introduced by soils of different moisture contents is unclear. Our study found that wetter soil tended to lose more carbon during drying than drier soil, thus affecting soil health interpretations. We developed a correction factor to account for initial soil moisture effects, which future studies may benefit from adapting for their soil.
Wartini Ng, Budiman Minasny, Wanderson de Sousa Mendes, and José Alexandre Melo Demattê
SOIL, 6, 565–578, https://doi.org/10.5194/soil-6-565-2020, https://doi.org/10.5194/soil-6-565-2020, 2020
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The number of samples utilised to create predictive models affected model performance. This research compares the number of samples needed by a deep learning model to outperform the traditional machine learning models using visible near-infrared spectroscopy data for soil properties predictions. The deep learning model was found to outperform machine learning models when the sample size was above 2000.
José Padarian, Alex B. McBratney, and Budiman Minasny
SOIL, 6, 389–397, https://doi.org/10.5194/soil-6-389-2020, https://doi.org/10.5194/soil-6-389-2020, 2020
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In this paper we introduce the use of game theory to interpret a digital soil mapping (DSM) model to understand the contribution of environmental factors to the prediction of soil organic carbon (SOC) in Chile. The analysis corroborated that the SOC model is capturing sensible relationships between SOC and climatic and topographical factors. We were able to represent them spatially (map) addressing the limitations of the current interpretation of models in DSM.
Yosra Ellili-Bargaoui, Brendan Philip Malone, Didier Michot, Budiman Minasny, Sébastien Vincent, Christian Walter, and Blandine Lemercier
SOIL, 6, 371–388, https://doi.org/10.5194/soil-6-371-2020, https://doi.org/10.5194/soil-6-371-2020, 2020
Anders Bjørn Møller, Amélie Marie Beucher, Nastaran Pouladi, and Mogens Humlekrog Greve
SOIL, 6, 269–289, https://doi.org/10.5194/soil-6-269-2020, https://doi.org/10.5194/soil-6-269-2020, 2020
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Decision trees have become a widely adapted tool for mapping soil properties in geographic space. However, it is problematic to implement spatial relationships in the models. We present a new method which uses geographic coordinates along several axes tilted at oblique angles in the models. We test this method on four spatial datasets. The results show that the new method is at least as accurate as other proposed alternatives, has a computational advantage and is flexible and interpretable.
Anika Gebauer, Monja Ellinger, Victor M. Brito Gomez, and Mareike Ließ
SOIL, 6, 215–229, https://doi.org/10.5194/soil-6-215-2020, https://doi.org/10.5194/soil-6-215-2020, 2020
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Pedotransfer functions (PTFs) for soil water retention were developed for two tropical soil landscapes using machine learning. The models corresponding to these PTFs had to be adjusted by tuning their parameters. The standard tuning approach was compared to mathematical optimization. The latter resulted in much better model performance. The PTFs derived are of particular importance for soil process and hydrological models.
Dominika Lewicka-Szczebak and Reinhard Well
SOIL, 6, 145–152, https://doi.org/10.5194/soil-6-145-2020, https://doi.org/10.5194/soil-6-145-2020, 2020
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This study aimed at comparison of various experimental strategies for incubating soil samples to determine the N2 flux. Such experiments require addition of isotope tracer, i.e. nitrogen fertilizer enriched in heavy nitrogen isotopes (15N). Here we compared the impact of soil homogenization and mixing with the tracer and tracer injection to the intact soil cores. The results are well comparable: both techniques would provide similar conclusions on the magnitude of N2 flux.
José Padarian and Alex B. McBratney
SOIL, 6, 89–94, https://doi.org/10.5194/soil-6-89-2020, https://doi.org/10.5194/soil-6-89-2020, 2020
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Data sharing and collaboration are critical to solving large-scale problems. The prevailing soil data-sharing model is of a centralized nature and, consequently, results in the participants ceding control and governance over their data to the lead party. Here we explore the use of a distributed ledger (blockchain) to solve the aforementioned issues. We also describe the potential use case of developing a global soil spectral library between multiple, international institutions.
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 6, 35–52, https://doi.org/10.5194/soil-6-35-2020, https://doi.org/10.5194/soil-6-35-2020, 2020
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The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It is a difficult task to manually review all papers on the application of ML. This paper aims to provide a review of the application of ML aided by topic modelling in order to find patterns in a large collection of publications. The objective is to gain insight into the applications and to discuss research gaps. We found 12 main topics and that ML methods usually perform better than traditional ones.
Sören Thiele-Bruhn, Michael Schloter, Berndt-Michael Wilke, Lee A. Beaudette, Fabrice Martin-Laurent, Nathalie Cheviron, Christian Mougin, and Jörg Römbke
SOIL, 6, 17–34, https://doi.org/10.5194/soil-6-17-2020, https://doi.org/10.5194/soil-6-17-2020, 2020
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Soil quality depends on the functioning of soil microbiota. Only a few standardized methods are available to assess this as well as adverse effects of human activities. So we need to identify promising additional methods that target soil microbial function. Discussed are (i) molecular methods using qPCR for new endpoints, e.g. in N and P cycling and greenhouse gas emissions, (ii) techniques for fungal enzyme activities, and (iii) field methods on carbon turnover such as the litter bag test.
Jeroen H. T. Zethof, Martin Leue, Cordula Vogel, Shane W. Stoner, and Karsten Kalbitz
SOIL, 5, 383–398, https://doi.org/10.5194/soil-5-383-2019, https://doi.org/10.5194/soil-5-383-2019, 2019
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A widely overlooked source of carbon (C) in the soil environment is organic C of geogenic origin, e.g. graphite. Appropriate methods are not available to quantify graphite and to differentiate it from other organic and inorganic C sources in soils. Therefore, we examined Fourier transform infrared spectroscopy, thermogravimetric analysis and the smart combustion method for their ability to identify and quantify graphitic C in soils. The smart combustion method showed the most promising results.
Monja Ellinger, Ines Merbach, Ulrike Werban, and Mareike Ließ
SOIL, 5, 275–288, https://doi.org/10.5194/soil-5-275-2019, https://doi.org/10.5194/soil-5-275-2019, 2019
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Vis–NIR spectrometry is often applied to capture soil organic carbon (SOC). This study addresses the impact of the involved data and modelling aspects on SOC precision with a focus on the propagation of input data uncertainties. It emphasizes the necessity of transparent documentation of the measurement protocol and the model building and validation procedure. Particularly, when Vis–NIR spectrometry is used for soil monitoring, the aspect of uncertainty propagation becomes essential.
José Padarian and Ignacio Fuentes
SOIL, 5, 177–187, https://doi.org/10.5194/soil-5-177-2019, https://doi.org/10.5194/soil-5-177-2019, 2019
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A large amount of descriptive information is available in geosciences. Considering the advances in natural language it is possible to
rescuethis information and transform it into a numerical form (embeddings). We used 280764 full-text scientific articles to train a language model capable of generating such embeddings. Our domain-specific embeddings (GeoVec) outperformed general domain embedding tasks such as analogies, relatedness, and categorisation, and can be used in novel applications.
Cathelijne R. Stoof, Jasper H. J. Candel, Laszlo A. G. M. van der Wal, and Gert Peek
SOIL, 5, 159–175, https://doi.org/10.5194/soil-5-159-2019, https://doi.org/10.5194/soil-5-159-2019, 2019
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Teaching and outreach of soils is often done with real-life snapshots of soils and sediments in lacquer or glue peels. While it may seem hard, anyone can make such a peel. Illustrated with handmade drawings and an instructional video, we explain how to capture soils in peels using readily available materials. A new twist to old methods makes this safer, simpler, and more successful, and thus a true DIY (do-it-yourself) activity, highlighting the value and beauty of the ground below our feet.
Alexandre M. J.-C. Wadoux, José Padarian, and Budiman Minasny
SOIL, 5, 107–119, https://doi.org/10.5194/soil-5-107-2019, https://doi.org/10.5194/soil-5-107-2019, 2019
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 5, 79–89, https://doi.org/10.5194/soil-5-79-2019, https://doi.org/10.5194/soil-5-79-2019, 2019
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Digital soil mapping has been widely used as a cost-effective method for generating soil maps. DSM models are usually calibrated using point observations and rarely incorporate contextual information of the landscape. Here, we use convolutional neural networks to incorporate spatial context. We used as input a 3-D stack of covariate images to simultaneously predict organic carbon content at multiple depths. In this study, our model reduced the error by 30 % compared with conventional techniques.
Mario Guevara, Guillermo Federico Olmedo, Emma Stell, Yusuf Yigini, Yameli Aguilar Duarte, Carlos Arellano Hernández, Gloria E. Arévalo, Carlos Eduardo Arroyo-Cruz, Adriana Bolivar, Sally Bunning, Nelson Bustamante Cañas, Carlos Omar Cruz-Gaistardo, Fabian Davila, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo Tacona, Fernando Fontes, José Antonio Hernández Herrera, Alejandro Roberto Ibelles Navarro, Veronica Loayza, Alexandra M. Manueles, Fernando Mendoza Jara, Carolina Olivera, Rodrigo Osorio Hermosilla, Gonzalo Pereira, Pablo Prieto, Iván Alexis Ramos, Juan Carlos Rey Brina, Rafael Rivera, Javier Rodríguez-Rodríguez, Ronald Roopnarine, Albán Rosales Ibarra, Kenset Amaury Rosales Riveiro, Guillermo Andrés Schulz, Adrian Spence, Gustavo M. Vasques, Ronald R. Vargas, and Rodrigo Vargas
SOIL, 4, 173–193, https://doi.org/10.5194/soil-4-173-2018, https://doi.org/10.5194/soil-4-173-2018, 2018
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We provide a reproducible multi-modeling approach for SOC mapping across Latin America on a country-specific basis as required by the Global Soil Partnership of the United Nations. We identify key prediction factors for SOC across each country. We compare and test different methods to generate spatially explicit predictions of SOC and conclude that there is no best method on a quantifiable basis.
Louis-Pierre Comeau, Derrick Y. F. Lai, Jane Jinglan Cui, and Jenny Farmer
SOIL, 4, 141–152, https://doi.org/10.5194/soil-4-141-2018, https://doi.org/10.5194/soil-4-141-2018, 2018
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To date, there are still many uncertainties and unknowns regarding the soil respiration partitioning procedures. This study compared the suitability and accuracy of five different respiration partitioning methods. A qualitative evaluation table of the partition methods with five performance parameters was produced. Overall, no systematically superior or inferior partition method was found and the combination of two or more methods optimizes assessment reliability.
Jacqueline R. England and Raphael A. Viscarra Rossel
SOIL, 4, 101–122, https://doi.org/10.5194/soil-4-101-2018, https://doi.org/10.5194/soil-4-101-2018, 2018
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Proximal sensing can be used for soil C accounting, but the methods need to be standardized and procedural guidelines developed to ensure proficient measurement and accurate reporting. This is particularly important if there are financial incentives for landholders to adopt practices to sequester C. We review sensing for C accounting and discuss the requirements for the development of new soil C accounting methods based on sensing, including requirements for reporting, auditing and verification.
Madlene Nussbaum, Kay Spiess, Andri Baltensweiler, Urs Grob, Armin Keller, Lucie Greiner, Michael E. Schaepman, and Andreas Papritz
SOIL, 4, 1–22, https://doi.org/10.5194/soil-4-1-2018, https://doi.org/10.5194/soil-4-1-2018, 2018
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This paper presents an extensive evaluation of digital soil mapping (DSM) tools. Recently, large sets of environmental covariates (e.g. from analysis of terrain on multiple scales) have become more common for DSM. Many DSM studies, however, only compared DSM methods using less than 30 covariates or tested approaches on few responses. We built DSM models from 300–500 covariates using six approaches that are either popular in DSM or promising for large covariate sets.
R. Murray Lark, Elliott M. Hamilton, Belinda Kaninga, Kakoma K. Maseka, Moola Mutondo, Godfrey M. Sakala, and Michael J. Watts
SOIL, 3, 235–244, https://doi.org/10.5194/soil-3-235-2017, https://doi.org/10.5194/soil-3-235-2017, 2017
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An advantage of geostatistics for mapping soil properties is that, given a statistical model of the variable of interest, we can make a rational decision about how densely to sample so that the map is sufficiently precise. However, uncertainty about the statistical model affects this process. In this paper we show how Bayesian methods can be used to support decision making on sampling with an uncertain model, ensuring that the probability of meeting certain levels of precision is high enough.
Madlene Nussbaum, Lorenz Walthert, Marielle Fraefel, Lucie Greiner, and Andreas Papritz
SOIL, 3, 191–210, https://doi.org/10.5194/soil-3-191-2017, https://doi.org/10.5194/soil-3-191-2017, 2017
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Digital soil mapping (DSM) relates soil property data to environmental data that describe soil-forming factors. With imagery sampled from satellites or terrain analysed at multiple scales, large sets of possible input to DSM are available. We propose a new statistical framework (geoGAM) that selects parsimonious models for DSM and illustrate the application of geoGAM to two study regions. Straightforward interpretation of the modelled effects likely improves end-user acceptance of DSM products.
Hannes Keck, Bjarne W. Strobel, Jon Petter Gustafsson, and John Koestel
SOIL, 3, 177–189, https://doi.org/10.5194/soil-3-177-2017, https://doi.org/10.5194/soil-3-177-2017, 2017
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Several studies have shown that the cation adsorption sites in soils are heterogeneously distributed in space. In many soil system models this knowledge is not included yet. In our study we proposed a new method to map the 3-D distribution of cation adsorption sites in undisturbed soils. The method is based on three-dimensional X-ray scanning with a contrast agent and image analysis. We are convinced that this approach will strongly aid the development of more realistic soil system models.
Christopher Poeplau, Cora Vos, and Axel Don
SOIL, 3, 61–66, https://doi.org/10.5194/soil-3-61-2017, https://doi.org/10.5194/soil-3-61-2017, 2017
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This paper shows that three out of four frequently used methods to calculate soil organic carbon stocks lead to systematic overestimation of those stocks. Stones, which can be assumed to be free of carbon, have to be corrected for in both bulk density and layer thickness. We used data of the German Agricultural Soil Inventory to illustrate the potential bias and suggest a unified and unbiased calculation method for stocks of soil organic carbon, which is the largest terrestrial carbon pool.
Jan M. van Mourik, Thomas V. Wagner, J. Geert de Boer, and Boris Jansen
SOIL, 2, 299–310, https://doi.org/10.5194/soil-2-299-2016, https://doi.org/10.5194/soil-2-299-2016, 2016
Ranjith P. Udawatta, Clark J. Gantzer, Stephen H. Anderson, and Shmuel Assouline
SOIL, 2, 211–220, https://doi.org/10.5194/soil-2-211-2016, https://doi.org/10.5194/soil-2-211-2016, 2016
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Soil compaction degrades soil structure and affects water, heat, and gas exchange as well as root penetration and crop production. The objective of this study was to use X-ray computed microtomography (CMT) techniques to compare differences in geometrical soil pore parameters as influenced by compaction of two different aggregate size classes.
B. Reidy, I. Simo, P. Sills, and R. E. Creamer
SOIL, 2, 25–39, https://doi.org/10.5194/soil-2-25-2016, https://doi.org/10.5194/soil-2-25-2016, 2016
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This study reviews pedotransfer functions from the literature for different soil and horizon types. It uses these formulae to predict bulk density (ρb) per horizon using measured data of other soil properties. These data were compared to known pb per horizon and recalibrated. These calculations were used to fill missing horizon data in the Irish soil database. This allowed the generation of a pb map to 50 cm. These pb data are at horizon level allowing more accurate estimation of C with depth.
J. J. Keizer, M. A. S. Martins, S. A. Prats, L. F. Santos, D. C. S. Vieira, R. Nogueira, and L. Bilro
SOIL, 1, 641–650, https://doi.org/10.5194/soil-1-641-2015, https://doi.org/10.5194/soil-1-641-2015, 2015
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In this study, a novel plastic optical fibre turbidity sensor was exhaustively tested with a large set of runoff samples, mainly from a recently burnt area. The different types of samples from the distinct study sites revealed without exception an increase in normalized light loss with increasing sediment concentrations that agreed (reasonably) well with a power function. Nevertheless, sensor-based predictions of sediment concentration should ideally involve site-specific calibrations.
C. Rasmussen, R. E. Gallery, and J. S. Fehmi
SOIL, 1, 631–639, https://doi.org/10.5194/soil-1-631-2015, https://doi.org/10.5194/soil-1-631-2015, 2015
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There is a need to understand the response of soil systems to predicted climate warming for modeling soil processes. Current experimental methods for soil warming include expensive and difficult to implement active and passive techniques. Here we test a simple, inexpensive in situ passive soil heating approach, based on easy to construct infrared mirrors that do not require automation or enclosures. Results indicated that the infrared mirrors yielded significant heating and drying of soils.
E. Nadal-Romero, J. Revuelto, P. Errea, and J. I. López-Moreno
SOIL, 1, 561–573, https://doi.org/10.5194/soil-1-561-2015, https://doi.org/10.5194/soil-1-561-2015, 2015
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Geomatic techniques have been routinely applied in erosion studies, providing the opportunity to build high-resolution topographic models.The aim of this study is to assess and compare the functioning of terrestrial laser scanner and close range photogrammetry techniques to evaluate erosion and deposition processes in a humid badlands area.
Our results demonstrated that north slopes experienced more intense and faster dynamics than south slopes as well as the highest erosion rates.
L. M. Thomsen, J. E. M. Baartman, R. J. Barneveld, T. Starkloff, and J. Stolte
SOIL, 1, 399–410, https://doi.org/10.5194/soil-1-399-2015, https://doi.org/10.5194/soil-1-399-2015, 2015
B. A. Miller, S. Koszinski, M. Wehrhan, and M. Sommer
SOIL, 1, 217–233, https://doi.org/10.5194/soil-1-217-2015, https://doi.org/10.5194/soil-1-217-2015, 2015
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There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research was to compare these two approaches for mapping SOC stocks from multiple linear regression models applied at the landscape scale via spatial association. Although the indirect approach had greater spatial variation and higher R2 values, the direct approach had a lower total estimated error.
W. Eugster and L. Merbold
SOIL, 1, 187–205, https://doi.org/10.5194/soil-1-187-2015, https://doi.org/10.5194/soil-1-187-2015, 2015
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The eddy covariance (EC) method has become increasingly popular in soil science. The basic concept of this method and its use in different types of experimental designs in the field are given, and we indicate where progress in advancing and extending the field of applications is made. The greatest strengths of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes and (2) spatial integration over
small-scale heterogeneity in the soil.
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