Articles | Volume 8, issue 2
https://doi.org/10.5194/soil-8-451-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-8-451-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
08 Jul 2022
Original research article |
| 08 Jul 2022
| 08 Jul 2022
Identification of thermal signature and quantification of charcoal in soil using differential scanning calorimetry and benzene polycarboxylic acid (BPCA) markers
Brieuc Hardy
CORRESPONDING AUTHOR
Sols, Eaux et Productions Intégrées, Département Durabilité, Systèmes et Prospectives, Walloon Agricultural Research Center, Gembloux, Belgium
Earth and Life Institute, Environmental Sciences, Université
Catholique de Louvain, Louvain-la-Neuve, Belgium
Nils Borchard
Competence Center Agriculture,
German Agricultural Society (DLG e.V.), Frankfurt, Germany
Faculty of Life Sciences, Humboldt University of Berlin, Berlin, Germany
Jens Leifeld
Climate and Agriculture Group, Agroscope, Zurich, Switzerland
Environmental Geosciences, Universität Basel, Basel, Switzerland
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Manon S. Ferdinand, Brieuc F. Hardy, and Philippe V. Baret
EGUsphere, https://doi.org/10.5194/egusphere-2025-2700, https://doi.org/10.5194/egusphere-2025-2700, 2025
This preprint is open for discussion and under review for SOIL (SOIL).
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We assessed three soil quality indicators across Walloon Conservation Agriculture (CA) fields, accounting for practice diversity within four CA-types. Soil indicators varied significantly among CA-types. Inclusion of temporary grasslands in the crop sequence emerged as the most influential factor. Our findings show that CA effects depend on the combination of practices, highlighting the need for a systemic, context-based evaluation of soil quality.
Frédéric Marie Vanwindekens and Brieuc François Hardy
SOIL, 9, 573–591, https://doi.org/10.5194/soil-9-573-2023, https://doi.org/10.5194/soil-9-573-2023, 2023
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Structural stability is critical for sustainable agricultural soil management. We invented a simple test to measure soil structural stability. The QuantiSlakeTest consists of a dynamic weighting of a dried soil sample in water. The test is rapid, does not require expensive equipment and provides a high density of information on soil structural properties. With an open-access programme for data management under development, the test has strong potential for adoption by a large community of users.
Manon S. Ferdinand, Brieuc F. Hardy, and Philippe V. Baret
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We assessed three soil quality indicators across Walloon Conservation Agriculture (CA) fields, accounting for practice diversity within four CA-types. Soil indicators varied significantly among CA-types. Inclusion of temporary grasslands in the crop sequence emerged as the most influential factor. Our findings show that CA effects depend on the combination of practices, highlighting the need for a systemic, context-based evaluation of soil quality.
Luisa I. Minich, Dylan Geissbühler, Stefan Tobler, Annegret Udke, Alexander S. Brunmayr, Margaux Moreno Duborgel, Ciriaco McMackin, Lukas Wacker, Philip Gautschi, Negar Haghipour, Markus Egli, Ansgar Kahmen, Jens Leifeld, Timothy I. Eglinton, and Frank Hagedorn
EGUsphere, https://doi.org/10.5194/egusphere-2025-2267, https://doi.org/10.5194/egusphere-2025-2267, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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We developed a framework using rates and 14C-derived ages of soil-respired CO2 and its sources (autotrophic, heterotrophic) to identify carbon cycling pathways in different land-use types. Rates, ages and sources of respired CO2 varied across forests, grasslands, croplands, and managed peatlands. Our results suggest that the relationship between rates and ages of respired CO2 serves as a robust indicator of carbon retention or destabilization from natural to disturbed systems.
Frédéric Marie Vanwindekens and Brieuc François Hardy
SOIL, 9, 573–591, https://doi.org/10.5194/soil-9-573-2023, https://doi.org/10.5194/soil-9-573-2023, 2023
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Structural stability is critical for sustainable agricultural soil management. We invented a simple test to measure soil structural stability. The QuantiSlakeTest consists of a dynamic weighting of a dried soil sample in water. The test is rapid, does not require expensive equipment and provides a high density of information on soil structural properties. With an open-access programme for data management under development, the test has strong potential for adoption by a large community of users.
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.
Cédric Bader, Moritz Müller, Rainer Schulin, and Jens Leifeld
Biogeosciences, 15, 703–719, https://doi.org/10.5194/bg-15-703-2018, https://doi.org/10.5194/bg-15-703-2018, 2018
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When drained, peatlands degrade and release large quantities of CO2, thereby contributing to global warming. Do land use or the chemical composition of peat control the rate of that release? We studied 21 sites from the temperate climate zone managed as croplands, grasslands, or forests and found that the CO2 release was high, but only slightly influenced by land use or peat composition. Hence, only keeping peatlands in their natural state prevents them from becoming strong CO2 sources.
Lorenzo Menichetti, Thomas Kätterer, and Jens Leifeld
Biogeosciences, 13, 3003–3019, https://doi.org/10.5194/bg-13-3003-2016, https://doi.org/10.5194/bg-13-3003-2016, 2016
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Soil organic carbon dynamics are crucial for the global greenhouse gas balance, but their complexity is difficult to model and understand. We therefore often rely on radiocarbon measurements for calibrating models, but their effect on our understanding of the processes is still unclear. We calibrated five model structures on data from a long-term Swiss field experiment in a Bayesian framework to assess the effect of radiocarbon on the parameter and structural uncertainty of a soil carbon model.
R. Hüppi, R. Felber, A. Neftel, J. Six, and J. Leifeld
SOIL, 1, 707–717, https://doi.org/10.5194/soil-1-707-2015, https://doi.org/10.5194/soil-1-707-2015, 2015
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Biochar is considered an opportunity to tackle major environmental issues in agriculture. Adding pyrolised organic residues to soil may sequester carbon, increase yields and reduce nitrous oxide emissions from soil. It is unknown, whether the latter is induced by changes in soil pH. We show that biochar application substantially reduces nitrous oxide emissions from a temperate maize cropping system. However, the reduction was only achieved with biochar but not with liming.
J. Leifeld and J. Mayer
SOIL, 1, 537–542, https://doi.org/10.5194/soil-1-537-2015, https://doi.org/10.5194/soil-1-537-2015, 2015
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We present 14C data for field replicates of a controlled agricultural long-term experiment. We show that 14C variability is, on average, 12 times that of the analytical precision of the 14C measurement. Experimental 14C variability is related to neither management nor soil depth. Application of a simple carbon turnover model reveals that experimental variability of radiocarbon results in higher absolute uncertainties of estimated carbon turnover time for deeper soil layers.
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.
J. Leifeld, C. Bader, E. Borraz, M. Hoffmann, M. Giebels, M. Sommer, and J. Augustin
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-12341-2014, https://doi.org/10.5194/bgd-11-12341-2014, 2014
Revised manuscript not accepted
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
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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.
Elad Levintal, Yonatan Ganot, Gail Taylor, Peter Freer-Smith, Kosana Suvocarev, and Helen E. Dahlke
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Laura Summerauer, Philipp Baumann, Leonardo Ramirez-Lopez, Matti Barthel, Marijn Bauters, Benjamin Bukombe, Mario Reichenbach, Pascal Boeckx, Elizabeth Kearsley, Kristof Van Oost, Bernard Vanlauwe, Dieudonné Chiragaga, Aimé Bisimwa Heri-Kazi, Pieter Moonen, Andrew Sila, Keith Shepherd, Basile Bazirake Mujinya, Eric Van Ranst, Geert Baert, Sebastian Doetterl, and Johan Six
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Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
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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.
Laura Arata, Katrin Meusburger, Alexandra Bürge, Markus Zehringer, Michael E. Ketterer, Lionel Mabit, and Christine Alewell
SOIL, 3, 113–122, https://doi.org/10.5194/soil-3-113-2017, https://doi.org/10.5194/soil-3-113-2017, 2017
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.
Cited articles
Antal, M. J. and Grønli, M.: The Art, Science, and Technology of Charcoal
Production, Ind. Eng. Chem. Res., 42, 1619–1640,
https://doi.org/10.1021/ie0207919, 2003.
Ascough, P. L., Bird, M. I., Francis, S. M., Thornton, B., Midwood, A. J.,
Scott, A. C., and Apperley, D.: Variability in oxidative degradation of
charcoal: Influence of production conditions and environmental exposure,
Geochim. Cosmochim. Ac., 75, 2361–2378, https://doi.org/10.1016/j.gca.2011.02.002,
2011.
Bird, M. I., Wynn, J. G., Saiz, G., Wurster, C. M., and McBeath, A.: The
Pyrogenic Carbon Cycle, Annu. Rev. Earth Planet. Sci., 43,
273–298, https://doi.org/10.1146/annurev-earth-060614-105038, 2015.
Borchard, N., Ladd, B., Eschemann, S., Hegenberg, D., Möseler, B. M., and
Amelung, W.: Black carbon and soil properties at historical charcoal
production sites in Germany, Geoderma, 232, 236–242,
https://doi.org/10.1016/j.geoderma.2014.05.007, 2014.
Brodowski, S., Rodionov, A., Haumaier, L., Glaser, B., and Amelung, W.:
Revised black carbon assessment using benzene polycarboxylic acids, Org.
Geochem., 36, 1299–1310, 2005.
Burgeon, V., Fouché, J., Leifeld, J., Chenu, C., and Cornélis, J. T.:
Organo-mineral associations largely contribute to the stabilization of
century-old pyrogenic organic matter in cropland soils, Geoderma, 388, 114841, https://doi.org/10.1016/j.geoderma.2020.114841, 2021.
Cheng, C.-H., Lehmann, J., and Engelhard, M. H.: Natural oxidation of black
carbon in soils: Changes in molecular form and surface charge along a
climosequence, Geochim. Cosmochim. Ac., 72, 1598–1610,
https://doi.org/10.1016/j.gca.2008.01.010, 2008.
Cohen-Ofri, I., Weiner, L., Boaretto, E., Mintz, G., and Weiner, S.: Modern
and fossil charcoal: aspects of structure and diagenesis, J. Archaeol. Sci.,
33, 428–439, https://doi.org/10.1016/j.jas.2005.08.008, 2006.
Czimczik, C. I. and Masiello, C. A.: Controls on black carbon storage in
soils, Global Biogeochem. Cy., 21, GB3005, https://doi.org/10.1029/2006GB002798,
2007.
De la Rosa, J. M., Knicker, H., López-Capel, E., Manning, D. A. C.,
González-Perez, J. A., and González-Vila, F. J.: Direct Detection of
Black Carbon in Soils by Py-GC/MS, Carbon-13 NMR Spectroscopy and
Thermogravimetric Techniques, Soil Sci. Soc. Am. J., 72, 258,
https://doi.org/10.2136/sssaj2007.0031, 2008.
Dehkordi, R. H., Burgeon, V., Fouche, J., Gomez, E. P., Cornelis, J. T.,
Nguyen, F., Denis, A., and Meersmans, J.: Using UAV collected RGB and
multispectral images to evaluate winter wheat performance across a site
characterized by century-old biochar patches in Belgium, Remote Sens.,
12, 2504, https://doi.org/10.3390/RS12152504, 2020.
Dell'Abate, M. T., Benedetti, A., Trinchera, A., and Dazzi, C.: Humic
substances along the profile of two Typic Haploxerert, Geoderma, 107,
281–296, https://doi.org/10.1016/S0016-7061(01)00153-7, 2002.
Elmquist, M., Gustafsson, O., and Andersson, P.: Quantification of
sedimentary black carbon using the chemothermal oxidation method: an
evaluation of ex situ pretreatments and standard additions approaches,
Limnol. Oceanogr.-Meth., 2, 417–427, 2004.
Emrich, W.: Handbook of Charcoal Making, D. Reidel Publishing Company,
Dordrecht, The Netherlands, ISBN 978-90-481-8411-8,
https://doi.org/10.1007/978-94-017-0450-2, 1985.
Evrard, R.: Forges anciennes, Editions Solédi, Liège, Belgium,
1956.
Fabbri, D., Torri, C., and Spokas, K. A.: Analytical pyrolysis of synthetic
chars derived from biomass with potential agronomic application (biochar).
Relationships with impacts on microbial carbon dioxide production, J. Anal.
Appl. Pyrolysis, 93, 77–84, https://doi.org/10.1016/j.jaap.2011.09.012, 2012.
Fernández, J. M., Plante, A. F., Leifeld, J., and Rasmussen, C.:
Methodological considerations for using thermal analysis in the
characterization of soil organic matter, J. Therm. Anal. Calorim., 104,
389–398, https://doi.org/10.1007/s10973-010-1145-6, 2010.
Forbes, M. S., Raison, R. J., and Skjemstad, J. O.: Formation, transformation
and transport of black carbon (charcoal) in terrestrial and aquatic
ecosystems, Sci. Total Environ., 370, 190–206,
https://doi.org/10.1016/j.scitotenv.2006.06.007, 2006.
Glaser, B. and Birk, J. J.: State of the scientific knowledge on properties
and genesis of Anthropogenic Dark Earths in Central Amazonia (terra preta de
Índio), Geochim. Cosmochim. Ac., 82, 39–51,
https://doi.org/10.1016/j.gca.2010.11.029, 2012.
Glaser, B., Haumaier, L., Guggenberger, G., and Zech, W.: Black carbon in
soils: the use of benzenecarboxylic acids as specific markers, Org.
Geochem., 29, 811–819, 1998.
Glaser, B., Haumaier, L., Guggenberger, G., and Zech, W.: The “Terra Preta”
phenomenon: a model for sustainable agriculture in the humid tropics,
Naturwissenschaften, 88, 37–41, https://doi.org/10.1007/s001140000193, 2001.
Glaser, B., Lehmann, J., and Zech, W.: Ameliorating physical and chemical
properties of highly weathered soils in the tropics with charcoal – a
review, Biol. Fertil. Soils, 35, 219–230, https://doi.org/10.1007/s00374-002-0466-4,
2002.
Goldberg, E. D.: Black carbon in the environment, John Wiley & Sons, New
York, ISBN 0471819794, 1985.
Gustafsson, Ö., Bucheli, T. D., Kukulska, Z., Andersson, M., Largeau,
C., Rouzaud, J. N., Reddy, C. M., and Eglinton, T. I.: Evaluation of a
protocol for the quantification of black carbon in sediments., Global
Biogeochem. Cy., 15, 881–890, 2001.
Hammes, K., Schmidt, M. W. I., Smernik, R. J., Currie, L. A., Ball, W. P.,
Nguyen, T. H., Louchouarn, P., Houel, S., Gustafsson, Ö., Elmquist, M.,
Cornelissen, G., Skjemstad, J. O., Masiello, C. a., Song, J., Peng, P.,
Mitra, S., Dunn, J. C., Hatcher, P. G., Hockaday, W. C., Smith, D. M.,
Hartkopf-Fröder, C., Böhmer, A., Lüer, B., Huebert, B. J.,
Amelung, W., Brodowski, S., Huang, L., Zhang, W., Gschwend, P. M.,
Flores-Cervantes, D. X., Largeau, C., Rouzaud, J.-N., Rumpel, C.,
Guggenberger, G., Kaiser, K., Rodionov, A., Gonzalez-Vila, F. J.,
Gonzalez-Perez, J. A., De la Rosa, J. M., Manning, D. A. C.,
López-Capél, E., and Ding, L.: Comparison of quantification methods
to measure fire-derived (black/elemental) carbon in soils and sediments
using reference materials from soil, water, sediment and the atmosphere,
Global Biogeochem. Cy., 21, GB3016, https://doi.org/10.1029/2006GB002914, 2007.
Hardy, B., Cornelis, J.-T., Houben, D., Lambert, R., and Dufey, J. E.: The
effect of pre-industrial charcoal kilns on chemical properties of forest
soil of Wallonia, Belgium, [data set], Eur. J. Soil Sci., 67, 206–216,
https://doi.org/10.1111/ejss.12324, 2016.
Hardy, B., Cornelis, J.-T., Houben, D., Leifeld, J., Lambert, R., and Dufey,
J.: Evaluation of the long-term effect of biochar on properties of temperate
agricultural soil at pre-industrial charcoal kiln sites in Wallonia,
Belgium, Eur. J. Soil Sci., 68, 80–89, https://doi.org/10.1111/ejss.12395, 2017a.
Hardy, B., Leifeld, J., Knicker, H., Dufey, J. E., Deforce, K., and
Cornélis, J. T.: Long term change in chemical properties of
preindustrial charcoal particles aged in forest and agricultural temperate
soil, [data set], Org. Geochem., 107, 33–45, https://doi.org/10.1016/j.orggeochem.2017.02.008,
2017b.
Harvey, O. R., Kuo, L.-J., Zimmerman, A. R., Louchouarn, P., Amonette, J. E.,
and Herbert, B. E.: An index-based approach to assessing recalcitrance and
soil carbon sequestration potential of engineered black carbons (biochars),
Environ. Sci. Technol., 46, 1415–21, https://doi.org/10.1021/es2040398, 2012.
Hernandez-Soriano, M. C., Kerré, B., Goos, P., Hardy, B., Dufey, J., and
Smolders, E.: Long-term effect of biochar on the stabilization of recent
carbon: soils with historical inputs of charcoal, GCB Bioenergy, 8, 371–381,
https://doi.org/10.1111/gcbb.12250, 2015.
Hirsch, F., Schneider, A., Bauriegel, A., Raab, A., and Raab, T.: Formation,
classification, and properties of soils at two relict charcoal hearth sites
in Brandenburg, Germany, Front. Environ. Sci., 6,
https://doi.org/10.3389/fenvs.2018.00094, 2018.
Hoyois, G.: L'Ardenne et l'Ardennais, L'Evolution Economique et Sociale
d'une région, Tome 2, Bruxelles-Paris: Éditions universitaires;
Gembloux: J. Duculot, imprimeur-éditeur, 1953.
Hu, Y., Wang, Z., Cheng, X., Liu, M., and Ma, C.: Effects of catalysts on
combustion characteristics and kinetics of coal-char blends, IOP Conf. Ser.
Earth Environ. Sci., 133, 012023, https://doi.org/10.1088/1755-1315/133/1/012023, 2018.
IUSS Working Group WRB: World reference base for soil resources 2014,
International soil classification system for naming soils and creating
legends for soil maps, World Soil Resources Reports No 106, Food
and Agriculture Organization of the United Nations, Rome, Italy, ISBN 978-92-5-108369-7, 2014.
Kalinichev, A. G. and Kirkpatrick, R. J.: Molecular dynamics simulation of
cationic complexation with natural organic matter, Eur. J. Soil Sci., 58,
909–917, https://doi.org/10.1111/j.1365-2389.2007.00929.x, 2007.
Kappenberg, A., Bläsing, M., Lehndorff, E., and Amelung, W.: Black carbon
assessment using benzene polycarboxylic acids: Limitations for organic-rich
matrices, Org. Geochem., 94, 47–51,
doi:doi:https://doi.org/10.1016/j.orggeochem, 2016.
Keiluweit, M., Nico, P. S., Johnson, M. G., and Kleber, M.: Dynamic molecular
structure of plant biomass-derived black carbon (biochar), Environ. Sci.
Technol., 44, 1247–53, https://doi.org/10.1021/es9031419, 2010.
Kerré, B., Bravo, C. T., Leifeld, J., Cornelissen, G., and Smolders, E.:
Historical soil amendment with charcoal increases sequestration of
non-charcoal carbon: a comparison among methods of black carbon
quantification, Eur. J. Soil Sci., 67, 324–331, https://doi.org/10.1111/ejss.12338,
2016.
Kerré, B., Willaert, B., and Smolders, E.: Lower residue decomposition in
historically charcoal-enriched soils is related to increased adsorption of
organic matter, Soil Biol. Biochem., 104, 1–7,
https://doi.org/10.1016/j.soilbio.2016.10.007, 2017.
Knicker, H.: Pyrogenic organic matter in soil: Its origin and occurrence,
its chemistry and survival in soil environments, Quat. Int., 243,
251–263, https://doi.org/10.1016/j.quaint.2011.02.037, 2011.
Kucerík, J., Kovár, J., and Pekar, M.: Thermoanalytical
investigation of lignite humic acids fractions, J. Therm. Anal. Calorim.,
76, 55–65, https://doi.org/10.1023/B:JTAN.0000027803.24266.48, 2004.
Laird, D. A.: The charcoal vision: a win-win-win scenario for simultaneously
producing bioenergy, permanently sequestering carbon, while improving soil
and water quality, Agron. J., 100, 178–181, https://doi.org/10.2134/agronj2007.0161,
2008.
Lasota, J., Błońska, E., Babiak, T., Piaszczyk, W., Stępniewska,
H., Jankowiak, R., Boroń, P., and Lenart-Boroń, A.: Effect of
Charcoal on the Properties, Enzyme Activities and Microbial Diversity of
Temperate Pine Forest Soils, Forests, 12, 1488, https://doi.org/10.3390/f12111488,
2021.
Lehmann, J.: Bio-energy in the black, Front. Ecol. Environ., 5, 381–387,
2007.
Lehmann, J., Liang, B., Solomon, D., Lerotic, M., Luizão, F., Kinyangi,
J., Schäfer, T., Wirick, S., and Jacobsen, C.: Near-edge X-ray absorption
fine structure (NEXAFS) spectroscopy for mapping nano-scale distribution of
organic carbon forms in soil: Application to black carbon particles, Global
Biogeochem. Cy., 19, GB1013, https://doi.org/10.1029/2004GB002435, 2005.
Leifeld, J.: Thermal stability of black carbon characterised by oxidative
differential scanning calorimetry, Org. Geochem., 38, 112–127,
https://doi.org/10.1016/j.orggeochem.2006.08.004, 2007.
Leifeld, J., Heiling, M., and Hajdas, I.: Age and thermal stability of
particulate organic matter fractions indicate the presence of black carbon
in soil, Radiocarbon, 57, 99–107, https://doi.org/10.2458/azu, 2015.
Leifeld, J., Alewell, C., Bader, C., Krüger, J. P., Mueller, C. W.,
Sommer, M., Steffens, M., and Szidat, S.: Pyrogenic Carbon Contributes
Substantially to Carbon Storage in Intact and Degraded Northern Peatlands,
L. Degrad. Dev., 29, 2082–2091, https://doi.org/10.1002/ldr.2812, 2018.
Li, J., Li, B., and Zhang, X. C.: Comparative studies of thermal degradation
between Larch lignin and Manchurian Ash lignin, Polym. Degrad. Stab., 78,
279–285, 2002.
Liang, B., Lehmann, J., Sohi, S. P., Thies, J. E., O'Neill, B., Trujillo,
L., Gaunt, J., Solomon, D., Grossman, J., Neves, E. G., and Luizão, F.
J.: Black carbon affects the cycling of non-black carbon in soil, Org.
Geochem., 41, 206–213, https://doi.org/10.1016/j.orggeochem.2009.09.007, 2010.
Mao, J.-D., Johnson, R. L., Lehmann, J., Olk, D. C., Neves, E. G., Thompson,
M. L., and Schmidt-Rohr, K.: Abundant and stable char residues in soils:
implications for soil fertility and carbon sequestration, Environ. Sci.
Technol., 46, 9571–9576, https://doi.org/10.1021/es301107c, 2012.
Masiello, C. A.: New directions in black carbon organic geochemistry, Mar.
Chem., 92, 201–213, https://doi.org/10.1016/j.marchem.2004.06.043, 2004.
Mastrolonardo, G., Calderaro, C., Cocozza, C., Hardy, B., Dufey, J., and
Cornelis, J. T.: Long-term effect of charcoal accumulation in hearth soils
on tree growth and nutrient cycling, Front. Environ. Sci., 7, 1–15,
https://doi.org/10.3389/fenvs.2019.00051, 2019.
McBeath, A. V. and Smernik, R. J.: Variation in the degree of aromatic
condensation of chars, Org. Geochem., 40, 1161–1168,
https://doi.org/10.1016/j.orggeochem.2009.09.006, 2009.
McBeath, A. V., Wurster, C. M., and Bird, M. I.: Influence of feedstock
properties and pyrolysis conditions on biochar carbon stability as
determined by hydrogen pyrolysis, Biomass Bioener., 73, 155–173,
https://doi.org/10.1016/j.biombioe.2014.12.022, 2015.
Mukherjee, S. and Kumar, M.: Cycling of black carbon and black nitrogen in
the hydro-geosphere: Insights on the paradigm, pathway, and processes, Sci.
Total Environ., 770, 144711,
https://doi.org/10.1016/j.scitotenv.2020.144711., 2021.
Nguyen, T. H., Brown, R., and Ball, W. P.: An evaluation of thermal
resistance as a measure of black carbon content in diesel soot, wood char,
and sediment, Org. Geochem., 35, 217–234,
https://doi.org/10.1016/j.orggeochem.2003.09.005, 2004.
Peltre, C., Fernández, J. M., Craine, J. M., and Plante, A. F.:
Relationships between Biological and Thermal Indices of Soil Organic Matter
Stability Differ with Soil Organic Carbon Level, Soil Sci. Soc. Am. J.,
77, 2020, https://doi.org/10.2136/sssaj2013.02.0081, 2013.
Plante, a. F., Pernes, M., and Chenu, C.: Changes in clay-associated organic
matter quality in a C depletion sequence as measured by differential thermal
analyses, Geoderma, 129, 186–199, https://doi.org/10.1016/j.geoderma.2004.12.043,
2005.
Plante, A. F., Fernández, J. M., and Leifeld, J.: Application of thermal
analysis techniques in soil science, Geoderma, 153, 1–10,
https://doi.org/10.1016/j.geoderma.2009.08.016, 2009.
Plante, A. F., Fernández, J. M., Haddix, M. L., Steinweg, J. M., and
Conant, R. T.: Biological, chemical and thermal indices of soil organic
matter stability in four grassland soils, Soil Biol. Biochem., 43,
1051–1058, https://doi.org/10.1016/j.soilbio.2011.01.024, 2011.
Plante, A. F., Beaupré, S. R., Roberts, M. L., and Baisden, T.:
Distribution of Radiocarbon Ages in Soil Organic Matter by Thermal
Fractionation, Radiocarbon, 55, 1077–1083,
https://doi.org/10.1017/s0033822200058215, 2013.
Pollet, S., Chabert, A., Burgeon, V., Cornélis, J.-T., Fouché, J.,
Gers, C., Hardy, B., and Pey, B.: Limited effects of century-old biochar on
taxonomic and functional diversities of collembolan communities across
land-uses, Soil Biol. Biochem., 164, 108484,
https://doi.org/10.1016/j.soilbio.2021.108484, 2022.
Preston, C. M. and Schmidt, M. W. I.: Black (pyrogenic) carbon: a synthesis of current knowledge and uncertainties with special consideration of boreal regions, Biogeosciences, 3, 397–420, https://doi.org/10.5194/bg-3-397-2006, 2006.
Reisser, M., Purves, R. S., Schmidt, M. W. I., and Abiven, S.: Pyrogenic
Carbon in Soils: A Literature-Based Inventory and a Global Estimation of Its
Content in Soil Organic Carbon and Stocks, Front. Earth Sci., 4,
1–14, https://doi.org/10.3389/feart.2016.00080, 2016.
Roth, P. J., Lehndorff, E., Brodowski, S., Bornemann, L.,
Sanchez-García, L., Gustafsson, Ö., and Amelung, W.: Differentiation
of charcoal, soot and diagenetic carbon in soil: Method comparison and
perspectives, Org. Geochem., 46, 66–75,
https://doi.org/10.1016/j.orggeochem.2012.01.012, 2012.
Sagrilo, E., Jeffery, S., Hoffland, E., and Kuyper, T. W.: Emission of CO2
from biochar-amended soils and implications for soil organic carbon, GCB
Bioener., 7, 1294–1304, https://doi.org/10.1111/gcbb.12234, 2014.
Samojlik, T., Jȩdrzejewska, B., Michniewicz, M., Krasnodȩbski, D., Dulinicz,
M., Olczak, H., Karczewski, A., and Rotherham, I. D.: Tree species used for
low-intensity production of charcoal and wood-tar in the 18th-century Białowieza Primeval Forest, Poland, Phytocoenologia, 43, 1–12,
https://doi.org/10.1127/0340-269X/2013/0043-0511, 2013.
Sanderman, J. and Grandy, A. S.: Ramped thermal analysis for isolating biologically meaningful soil organic matter fractions with distinct residence times, SOIL, 6, 131–144, https://doi.org/10.5194/soil-6-131-2020, 2020.
Santín, C., Doerr, S. H., Kane, E. S., Masiello, C. A., Ohlson, M., de
la Rosa, J. M., Preston, C. M., and Dittmar, T.: Towards a global assessment
of pyrogenic carbon from vegetation fires, Glob. Chang. Biol., 22,
76–91, https://doi.org/10.1111/gcb.12985, 2016.
Schenkel, Y., Bertaux, P., Vanwijnsberghe, S., and Carre, J.: An evaluation
of the mound kiln carbonization technique, Biomass Bioenerg., 14,
505–516, 1998.
Schmidt, H. P., Kammann, C., Hagemann, N., Leifeld, J., Bucheli, T. D.,
Sánchez Monedero, M. A., and Cayuela, M. L.: Biochar in agriculture – A
systematic review of 26 global meta-analyses, GCB Bioenerg., 13,
1708–1730, https://doi.org/10.1111/gcbb.12889, 2021.
Schmidt, M. W. I. and Noack, A. G.: Black carbon in soils and sediments:
Analysis, distribution, implications, and current challenges, Global
Biogeochem. Cy., 14, 777–793, https://doi.org/10.1029/1999GB001208, 2000.
Schmidt, M. W. I., Skjemstad, J. O., Czimczik, C. I., Glaser, B., Prentice,
K. M., Gelinas, Y., and Kuhlbusch, T. A. J.: Comparative analysis of black
carbon in soils, Global Biogeochem. Cy., 15, 163–167, 2001.
Schneider, A., Hirsch, F., Raab, A., and Raab, T.: Dye tracer visualization
of infiltration patterns in soils on relict charcoal hearths, Front.
Environ. Sci., 6, 1–14, https://doi.org/10.3389/fenvs.2018.00143, 2018.
Schneider, M. P. W., Hilf, M., Vogt, U. F., and Schmidt, M. W. I.: The
benzene polycarboxylic acid (BPCA) pattern of wood pyrolyzed between 200 ∘C and 1000 ∘C, Org. Geochem., 41, 1082–1088,
https://doi.org/10.1016/j.orggeochem.2010.07.001, 2010.
Schnitzer, M., Turner, R. C., and Hoffman, I.: A thermo-gravimetric study of
organic matter of representative Canadian podzol soils, Can. J. Soil Sci.,
44, 7–13, 1964.
Sherrod, L. A., Dunn, G., Peterson, G. A., and Kolberg, R. L.: Inorganic
Carbon Analysis by Modified Pressure-Calcimeter Method, Soil Sci. Soc. Am.
J., 66, 299–305, 2002.
Solomon, D., Lehmann, J., Thies, J., Schäfer, T., Liang, B., Kinyangi,
J., Neves, E., Petersen, J., Luizão, F., and Skjemstad, J.: Molecular
signature and sources of biochemical recalcitrance of organic C in Amazonian
Dark Earths, Geochim. Cosmochim. Ac., 71, 2285–2298,
https://doi.org/10.1016/j.gca.2007.02.014, 2007.
Tan, K. H., Hajek, B. F., and Barshad, I.: Thermal analysis techniques., in
Methods of Soil Analysis, Part I. Physical and Mineralogical Methods,
Agronomy Monograph, Vol. 9, edited by: Klute, A., American
Society of Agronomy, Madison, WI Todor., 151–183, 1986.
Uehara, G. and Gillman, P. G.: The Mineralogy, Chemistry, and Physics of
Tropical Soils with Variable Charge Clays, Editor: Boulder, C.,
Westview Press, Ann Arbor, MI, ISBN 0891584846, 1981.
Wang, J., Xiong, Z., and Kuzyakov, Y.: Biochar stability in soil:
Meta-analysis of decomposition and priming effects, GCB Bioenerg., 8,
512–523, https://doi.org/10.1111/gcbb.12266, 2016.
Wiedemeier, D. B., Abiven, S., Hockaday, W. C., Keiluweit, M., Kleber, M.,
Masiello, C. A., McBeath, A. V., Nico, P. S., Pyle, L. A., Schneider, M. P.
W., Smernik, R. J., Wiesenberg, G. L. B., and Schmidt, M. W. I.: Aromaticity
and degree of aromatic condensation of char, Org. Geochem., 78, 135–143,
https://doi.org/10.1016/j.orggeochem.2014.10.002, 2015a.
Wiedemeier, D. B., Brodowski, S., and Wiesenberg, G. L. B.: Pyrogenic
molecular markers: Linking PAH with BPCA analysis, Chemosphere, 119,
432–437, https://doi.org/10.1016/j.chemosphere.2014.06.046, 2015b.
Wolf, M., Lehndorff, E., Wiesenberg, G. L. B., Stockhausen, M., Schwark, L.,
and Amelung, W.: Towards reconstruction of past fire regimes from
geochemical analysis of charcoal, Org. Geochem., 55, 11–21,
https://doi.org/10.1016/j.orggeochem.2012.11.002, 2013.
Zanutel, M., Garré, S., and Bielders, C. L.: Long-term effect of biochar
on physical properties of agricultural soils with different textures at
pre-industrial charcoal kiln sites in Wallonia (Belgium), Eur. J. Soil Sci., 73, 1–17, https://doi.org/10.1111/ejss.13157, 2021.
Short summary
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.
Soil amendment with artificial black carbon (BC; biomass transformed by incomplete combustion) has...
