Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3879-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3879-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 Jun 2021
Model description paper |
| 24 Jun 2021
| 24 Jun 2021
Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval® thermal analysis (PARTYSOCv2.0 and PARTYSOCv2.0EU)
Normandie Univ., UNIROUEN, INRAE, ECODIV, Rouen, France
Laboratoire de Géologie, École normale supérieure, CNRS,
PSL Univ., IPSL, Paris, France
François Baudin
Institut des Sciences de la Terre de Paris, Sorbonne Université,
CNRS, 75005 Paris, France
Claire Chenu
UMR 1402 ECOSYS, INRAE, AgroParisTech, Univ. Paris Saclay,
78850 Thiverval-Grignon, France
Bent T. Christensen
Department of Agroecology, Aarhus University, AU Foulum, 8830 Tjele,
Denmark
Uwe Franko
Department of soil system science, Helmholtz Centre for Environmental
Research, UFZ, 06120 Halle, Germany
Sabine Houot
UMR 1402 ECOSYS, INRAE, AgroParisTech, Univ. Paris Saclay,
78850 Thiverval-Grignon, France
Eva Kanari
Laboratoire de Géologie, École normale supérieure, CNRS,
PSL Univ., IPSL, Paris, France
Institut des Sciences de la Terre de Paris, Sorbonne Université,
CNRS, 75005 Paris, France
Thomas Kätterer
Department of Ecology, Swedish University of Agricultural Sciences,
75007 Uppsala, Sweden
Ines Merbach
Department Community Ecology, Helmholtz Centre for Environmental
Research, UFZ, 06246 Bad Lauchstädt, Germany
Folkert van Oort
UMR 1402 ECOSYS, INRAE, AgroParisTech, Univ. Paris Saclay,
78850 Thiverval-Grignon, France
Christopher Poeplau
Thünen Institute of Climate-Smart Agriculture, 38116 Braunschweig,
Germany
Juan Carlos Quezada
Laboratory of Ecological Systems ECOS and Laboratory of Plant Ecology
Research PERL, School of Architecture, Civil and Environmental Engineering
ENAC, École Polytechnique Fédérale de Lausanne EPFL, 1015
Lausanne, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
1015 Lausanne, Switzerland
Ecosystem Management, Institute of Terrestrial Ecosystems, Department
of Environmental Systems Science, ETHZ, 8092 Zürich, Switzerland
Florence Savignac
Institut des Sciences de la Terre de Paris, Sorbonne Université,
CNRS, 75005 Paris, France
Laure N. Soucémarianadin
ACTA – les instituts techniques agricoles, 75595 Paris, France
Pierre Barré
Laboratoire de Géologie, École normale supérieure, CNRS,
PSL Univ., IPSL, Paris, France
Related authors
Eva Kanari, Lauric Cécillon, François Baudin, Hugues Clivot, Fabien Ferchaud, Sabine Houot, Florent Levavasseur, Bruno Mary, Laure Soucémarianadin, Claire Chenu, and Pierre Barré
Biogeosciences, 19, 375–387, https://doi.org/10.5194/bg-19-375-2022, https://doi.org/10.5194/bg-19-375-2022, 2022
Short summary
Short summary
Soil organic carbon (SOC) is crucial for climate regulation, soil quality, and food security. Predicting its evolution over the next decades is key for appropriate land management policies. However, SOC projections lack accuracy. Here we show for the first time that PARTYSOC, an approach combining thermal analysis and machine learning optimizes the accuracy of SOC model simulations at independent sites. This method can be applied at large scales, improving SOC projections on a continental scale.
Mathieu Chassé, Suzanne Lutfalla, Lauric Cécillon, François Baudin, Samuel Abiven, Claire Chenu, and Pierre Barré
Biogeosciences, 18, 1703–1718, https://doi.org/10.5194/bg-18-1703-2021, https://doi.org/10.5194/bg-18-1703-2021, 2021
Short summary
Short summary
Evolution of organic carbon content in soils could be a major driver of atmospheric greenhouse gas concentrations over the next century. Understanding factors controlling carbon persistence in soil is a challenge. Our study of unique long-term bare-fallow samples, depleted in labile organic carbon, helps improve the separation, evaluation and characterization of carbon pools with distinct residence time in soils and gives insight into the mechanisms explaining soil organic carbon persistence.
Lauric Cécillon, François Baudin, Claire Chenu, Sabine Houot, Romain Jolivet, Thomas Kätterer, Suzanne Lutfalla, Andy Macdonald, Folkert van Oort, Alain F. Plante, Florence Savignac, Laure N. Soucémarianadin, and Pierre Barré
Biogeosciences, 15, 2835–2849, https://doi.org/10.5194/bg-15-2835-2018, https://doi.org/10.5194/bg-15-2835-2018, 2018
Pierre Barré, Denis A. Angers, Isabelle Basile-Doelsch, Antonio Bispo, Lauric Cécillon, Claire Chenu, Tiphaine Chevallier, Delphine Derrien, Thomas K. Eglin, and Sylvain Pellerin
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-395, https://doi.org/10.5194/bg-2017-395, 2017
Manuscript not accepted for further review
Short summary
Short summary
Soil C storage is currently discussed at a high political level. This paper discusses whether the concept of soil C saturation deficit can be appropriate to determine quantitatively the soil C storage potential and contribute to answer operational questions raised by policy makers. After a review of the literature, we conclude that for practical and conceptual reasons, the C saturation deficit is not appropriate for assessing quantitatively the soil total OC storage potential.
Sophie Hage, Megan L. Baker, Nathalie Babonneau, Guillaume Soulet, Bernard Dennielou, Ricardo Silva Jacinto, Robert G. Hilton, Valier Galy, François Baudin, Christophe Rabouille, Clément Vic, Sefa Sahin, Sanem Açikalin, and Peter J. Talling
EGUsphere, https://doi.org/10.5194/egusphere-2024-900, https://doi.org/10.5194/egusphere-2024-900, 2024
Short summary
Short summary
Climate projections require to quantify the exchange of carbon between the atmosphere, land and oceans, yet the land-to-ocean flux of carbon is difficult to measure. Here, we quantify the carbon flux between the second largest river on Earth and the ocean. Carbon in the form of vegetation and soil is transported by episodic submarine avalanches in a 1000 km-long canyon at up to 5 km of water depth. The carbon flux induced by avalanches is at least ten times greater than that induced by tides.
Marija Stojanova, Pierre Arbelet, François Baudin, Nicolas Bouton, Giovanni Caria, Lorenza Pacini, Nicolas Proix, Edouard Quibel, Achille Thin, and Pierre Barré
EGUsphere, https://doi.org/10.5194/egusphere-2024-578, https://doi.org/10.5194/egusphere-2024-578, 2024
Short summary
Short summary
Because of its importance for climate regulation and soil health, many studies are focusing on carbon dynamics in soils. However, quantifying organic and inorganic carbon remains an issue in carbonated soils. In this technical note, we propose a validated correction method to quantify organic and inorganic carbon in soils using Rock-Eval® thermal analysis. With this correction, Rock-Eval® method has the potential to become the standard method for quantifying carbon in carbonate soils.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
Short summary
Short summary
Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Amicie A. Delahaie, Lauric Cécillon, Marija Stojanova, Samuel Abiven, Pierre Arbelet, Dominique Arrouays, François Baudin, Antonio Bispo, Line Boulonne, Claire Chenu, Jussi Heinonsalo, Claudy Jolivet, Kristiina Karhu, Manuel P. Martin, Lorenza Pacini, Christopher Poeplau, Céline Ratié, Pierre Roudier, Nicolas P. A. Saby, Florence Savignac, and Pierre Barré
EGUsphere, https://doi.org/10.5194/egusphere-2024-197, https://doi.org/10.5194/egusphere-2024-197, 2024
Short summary
Short summary
This manuscript compares the soil organic carbon fractions obtained from a new thermal fractionation scheme and a well-known physical fractionation scheme on an unprecedented dataset of French topsoil samples. For each fraction, we use a machine learning model to determine its environmental drivers (pedology, climate, and land cover). Our results suggest that these two fractionation schemes provide different fractions, which means they provide complementary information.
Victor Moinard, Antoine Savoie, Catherine Pasquier, Adeline Besnault, Yolaine Goubard-Delaunay, Baptiste Esnault, Marco Carozzi, Polina Voylokov, Sophie Génermont, Benjamin Loubet, Catherine Hénault, Florent Levavasseur, Jean-Marie Paillat, and Sabine Houot
EGUsphere, https://doi.org/10.5194/egusphere-2024-161, https://doi.org/10.5194/egusphere-2024-161, 2024
Short summary
Short summary
Anaerobic digestion is used for biogas production. The resulting digestates may be associated with different crop performances and N losses compared to undigested animal effluents. We monitored N flows during a three-year field experiment with different fertilizations based on cattle effluents, digestates, or mineral fertilizers. Digestates were effective N fertilizer but required attention to NH3 volatilization. We identified no additional risks of N2O emissions with digestates.
Tchodjowiè P. I. Kpemoua, Pierre Barré, Sabine Houot, François Baudin, Cédric Plessis, and Claire Chenu
EGUsphere, https://doi.org/10.5194/egusphere-2023-2955, https://doi.org/10.5194/egusphere-2023-2955, 2023
Short summary
Short summary
Several agroecological management options foster soil organic C stocks accrual. What is the persistence of this « additional » C? We used three different methodological approaches and >20 years field experiments under temperate conditions. We found that the additional C is less stable at the pluri-decadal scale than the baseline C. This highlights the need to maintain agroecological practices to keep these carbon stocks at a high level over time.
Maria Regina Gmach, Martin A. Bolinder, Lorenzo Menichetti, Thomas Kätterer, Heide Spiegel, Olle Åkesson, Jürgen Kurt Friedel, Andreas Surböck, Agnes Schweinzer, and Taru Sandén
EGUsphere, https://doi.org/10.5194/egusphere-2023-1229, https://doi.org/10.5194/egusphere-2023-1229, 2023
Short summary
Short summary
We evaluated the effect of soil management practices on decomposition at 29 sites (13 in Sweden and 16 in Austria ) with long-term field experiments using the Tea Bag Index (TBI) approach. In Austria, decomposition differed more between sites, and in Sweden differed more between soil management. We found that k and S were mainly governed by climatic conditions. In general, organic and mineral fertilization increased k and S, and reduced tillage increased S. Edaphic factors also affected k and S.
Amicie A. Delahaie, Pierre Barré, François Baudin, Dominique Arrouays, Antonio Bispo, Line Boulonne, Claire Chenu, Claudy Jolivet, Manuel P. Martin, Céline Ratié, Nicolas P. A. Saby, Florence Savignac, and Lauric Cécillon
SOIL, 9, 209–229, https://doi.org/10.5194/soil-9-209-2023, https://doi.org/10.5194/soil-9-209-2023, 2023
Short summary
Short summary
We characterized organic matter in French soils by analysing samples from the French RMQS network using Rock-Eval thermal analysis. We found that thermal analysis is appropriate to characterize large set of samples (ca. 2000) and provides interpretation references for Rock-Eval parameter values. This shows that organic matter in managed soils is on average more oxidized and more thermally stable and that some Rock-Eval parameters are good proxies for organic matter biogeochemical stability.
Tino Peplau, Christopher Poeplau, Edward Gregorich, and Julia Schroeder
Biogeosciences, 20, 1063–1074, https://doi.org/10.5194/bg-20-1063-2023, https://doi.org/10.5194/bg-20-1063-2023, 2023
Short summary
Short summary
We buried tea bags and temperature loggers in a paired-plot design in soils under forest and agricultural land and retrieved them after 2 years to quantify the effect of land-use change on soil temperature and litter decomposition in subarctic agricultural systems. We could show that agricultural soils were on average 2 °C warmer than forests and that litter decomposition was enhanced. The results imply that deforestation amplifies effects of climate change on soil organic matter dynamics.
Niel Verbrigghe, Niki I. W. Leblans, Bjarni D. Sigurdsson, Sara Vicca, Chao Fang, Lucia Fuchslueger, Jennifer L. Soong, James T. Weedon, Christopher Poeplau, Cristina Ariza-Carricondo, Michael Bahn, Bertrand Guenet, Per Gundersen, Gunnhildur E. Gunnarsdóttir, Thomas Kätterer, Zhanfeng Liu, Marja Maljanen, Sara Marañón-Jiménez, Kathiravan Meeran, Edda S. Oddsdóttir, Ivika Ostonen, Josep Peñuelas, Andreas Richter, Jordi Sardans, Páll Sigurðsson, Margaret S. Torn, Peter M. Van Bodegom, Erik Verbruggen, Tom W. N. Walker, Håkan Wallander, and Ivan A. Janssens
Biogeosciences, 19, 3381–3393, https://doi.org/10.5194/bg-19-3381-2022, https://doi.org/10.5194/bg-19-3381-2022, 2022
Short summary
Short summary
In subarctic grassland on a geothermal warming gradient, we found large reductions in topsoil carbon stocks, with carbon stocks linearly declining with warming intensity. Most importantly, however, we observed that soil carbon stocks stabilised within 5 years of warming and remained unaffected by warming thereafter, even after > 50 years of warming. Moreover, in contrast to the large topsoil carbon losses, subsoil carbon stocks remained unaffected after > 50 years of soil warming.
Eva Kanari, Lauric Cécillon, François Baudin, Hugues Clivot, Fabien Ferchaud, Sabine Houot, Florent Levavasseur, Bruno Mary, Laure Soucémarianadin, Claire Chenu, and Pierre Barré
Biogeosciences, 19, 375–387, https://doi.org/10.5194/bg-19-375-2022, https://doi.org/10.5194/bg-19-375-2022, 2022
Short summary
Short summary
Soil organic carbon (SOC) is crucial for climate regulation, soil quality, and food security. Predicting its evolution over the next decades is key for appropriate land management policies. However, SOC projections lack accuracy. Here we show for the first time that PARTYSOC, an approach combining thermal analysis and machine learning optimizes the accuracy of SOC model simulations at independent sites. This method can be applied at large scales, improving SOC projections on a continental scale.
Elisa Bruni, Bertrand Guenet, Yuanyuan Huang, Hugues Clivot, Iñigo Virto, Roberta Farina, Thomas Kätterer, Philippe Ciais, Manuel Martin, and Claire Chenu
Biogeosciences, 18, 3981–4004, https://doi.org/10.5194/bg-18-3981-2021, https://doi.org/10.5194/bg-18-3981-2021, 2021
Short summary
Short summary
Increasing soil organic carbon (SOC) stocks is beneficial for climate change mitigation and food security. One way to enhance SOC stocks is to increase carbon input to the soil. We estimate the amount of carbon input required to reach a 4 % annual increase in SOC stocks in 14 long-term agricultural experiments around Europe. We found that annual carbon input should increase by 43 % under current temperature conditions, by 54 % for a 1 °C warming scenario and by 120 % for a 5 °C warming scenario.
Mathieu Chassé, Suzanne Lutfalla, Lauric Cécillon, François Baudin, Samuel Abiven, Claire Chenu, and Pierre Barré
Biogeosciences, 18, 1703–1718, https://doi.org/10.5194/bg-18-1703-2021, https://doi.org/10.5194/bg-18-1703-2021, 2021
Short summary
Short summary
Evolution of organic carbon content in soils could be a major driver of atmospheric greenhouse gas concentrations over the next century. Understanding factors controlling carbon persistence in soil is a challenge. Our study of unique long-term bare-fallow samples, depleted in labile organic carbon, helps improve the separation, evaluation and characterization of carbon pools with distinct residence time in soils and gives insight into the mechanisms explaining soil organic carbon persistence.
Katharina Hildegard Elisabeth Meurer, Claire Chenu, Elsa Coucheney, Anke Marianne Herrmann, Thomas Keller, Thomas Kätterer, David Nimblad Svensson, and Nicholas Jarvis
Biogeosciences, 17, 5025–5042, https://doi.org/10.5194/bg-17-5025-2020, https://doi.org/10.5194/bg-17-5025-2020, 2020
Short summary
Short summary
We present a simple model that describes, for the first time, the dynamic two-way interactions between soil organic matter and soil physical properties (porosity, pore size distribution, bulk density and layer thickness). The model was able to accurately reproduce the changes in soil organic carbon, soil bulk density and surface elevation observed during 63 years in a field trial, as well as soil water retention curves measured at the end of the experimental period.
Arjun Chakrawal, Anke M. Herrmann, John Koestel, Jerker Jarsjö, Naoise Nunan, Thomas Kätterer, and Stefano Manzoni
Geosci. Model Dev., 13, 1399–1429, https://doi.org/10.5194/gmd-13-1399-2020, https://doi.org/10.5194/gmd-13-1399-2020, 2020
Short summary
Short summary
Soils are heterogeneous, which results in a nonuniform spatial distribution of substrates and the microorganisms feeding on them. Our results show that the variability in the spatial distribution of substrates and microorganisms at the pore scale is crucial because it affects how fast substrates are used by microorganisms and thus the decomposition rate observed at the soil core scale. This work provides a methodology to include microscale heterogeneity in soil carbon cycling models.
Christopher Poeplau, Páll Sigurðsson, and Bjarni D. Sigurdsson
SOIL, 6, 115–129, https://doi.org/10.5194/soil-6-115-2020, https://doi.org/10.5194/soil-6-115-2020, 2020
Short summary
Short summary
Global warming leads to increased mineralisation of soil organic matter, inducing a positive climate–carbon cycle feedback loop. Loss of organic matter can be associated with loss of soil structure. Here we use a strong geothermal gradient to investigate soil warming effects on soil organic matter and structural parameters in subarctic forest and grassland soils. Strong depletion of organic matter caused a collapse of aggregates, highlighting the potential impact of warming on soil function.
Moritz Laub, Michael Scott Demyan, Yvonne Funkuin Nkwain, Sergey Blagodatsky, Thomas Kätterer, Hans-Peter Piepho, and Georg Cadisch
Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, https://doi.org/10.5194/bg-17-1393-2020, 2020
Short summary
Short summary
Loss of soil carbon to the atmosphere represents a global challenge. We tested an innovative way to reduce the high uncertainty related to turnover of carbon stored in soils. With the use of infrared spectra of soils from model bare fallow systems, we were able to better assess the current state of soil carbon and predict its behavior in overdecadal time spans. In agreement with recent studies, carbon turnover seems faster than earlier assumed, with potential for high loss under mismanagement.
Suzanne Lutfalla, Pierre Barré, Sylvain Bernard, Corentin Le Guillou, Julien Alléon, and Claire Chenu
Biogeosciences, 16, 1401–1410, https://doi.org/10.5194/bg-16-1401-2019, https://doi.org/10.5194/bg-16-1401-2019, 2019
Short summary
Short summary
Soils store large amounts of carbon in soil organic matter, which comes from plant debris and roots. The mechanisms protecting it from biodegradation are not fully understood. Here, we carry out a size-fractionation of soil sampled on different dates in a field experiment. Using carbon and nitrogen content and spectroscopy and microscopy we conclude that organic matter enriched in nitrogen is preferentially protected from biodegradation and that clay minerals have differing protective abilities.
Lauric Cécillon, François Baudin, Claire Chenu, Sabine Houot, Romain Jolivet, Thomas Kätterer, Suzanne Lutfalla, Andy Macdonald, Folkert van Oort, Alain F. Plante, Florence Savignac, Laure N. Soucémarianadin, and Pierre Barré
Biogeosciences, 15, 2835–2849, https://doi.org/10.5194/bg-15-2835-2018, https://doi.org/10.5194/bg-15-2835-2018, 2018
Pierre Barré, Denis A. Angers, Isabelle Basile-Doelsch, Antonio Bispo, Lauric Cécillon, Claire Chenu, Tiphaine Chevallier, Delphine Derrien, Thomas K. Eglin, and Sylvain Pellerin
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-395, https://doi.org/10.5194/bg-2017-395, 2017
Manuscript not accepted for further review
Short summary
Short summary
Soil C storage is currently discussed at a high political level. This paper discusses whether the concept of soil C saturation deficit can be appropriate to determine quantitatively the soil C storage potential and contribute to answer operational questions raised by policy makers. After a review of the literature, we conclude that for practical and conceptual reasons, the C saturation deficit is not appropriate for assessing quantitatively the soil total OC storage potential.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
C. Poeplau, H. Marstorp, K. Thored, and T. Kätterer
SOIL, 2, 175–184, https://doi.org/10.5194/soil-2-175-2016, https://doi.org/10.5194/soil-2-175-2016, 2016
Short summary
Short summary
We compared two long-term contrasting systems of urban lawn management (frequently cut utility lawn vs. seldomly cut meadow-like lawn) regarding their effect on soil carbon in three Swedish cities. Biomass production was also measured during 1 year. The utility lawns had a significantly higher biomass production, which resulted in a higher soil carbon storage, since clippings were not removed. Soil carbon sequestration outweighed the higher management-related CO2 emissions of the utility lawns.
Christopher Poeplau, Martin A. Bolinder, Holger Kirchmann, and Thomas Kätterer
Biogeosciences, 13, 1119–1127, https://doi.org/10.5194/bg-13-1119-2016, https://doi.org/10.5194/bg-13-1119-2016, 2016
Short summary
Short summary
Nutrients determine the balance between inputs and outputs to and from the soil and thus exert a strong impact on the total soil organic carbon stock. However, for phosphorus, this impact has not been comprehensively addressed. Here we show in 10 different long-term experiments that phosphorus fertilisation can significantly deplete soil carbon stocks, despite a positive impact on plant growth and thus carbon inputs. Thus, soil carbon decay is most likely stimulated even more strongly.
C. Poeplau, M. A. Bolinder, J. Eriksson, M. Lundblad, and T. Kätterer
Biogeosciences, 12, 3241–3251, https://doi.org/10.5194/bg-12-3241-2015, https://doi.org/10.5194/bg-12-3241-2015, 2015
Short summary
Short summary
Soil carbon dynamics of the past 2 decades in Swedish agricultural soils were assessed using three consecutive soil inventories. We found a significant increase in country-wide soil carbon concentrations, which is in contrast to trends reported in neighbouring countries. We explained this by a significant rise of the proportion of leys in Swedish agriculture, which was found to be strongly related to the increase in horse population. Human lifestyle can affect soil carbon.
Related subject area
Biogeosciences
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
A global behavioural model of human fire use and management: WHAM! v1.0
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): calibration-free calculations of water and energy fluxes
biospheremetrics v1.0.1: An R package to calculate two complementary terrestrial biosphere integrity indicators: human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
In-silico calculation of soil pH by SCEPTER v1.0
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: Simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling
Impact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles D. Koven, Ryan G. Knox, Lara M. Kueppers, and Chonggang Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-191, https://doi.org/10.5194/gmd-2023-191, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We adapt a fire-behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James Millington
EGUsphere, https://doi.org/10.5194/egusphere-2023-2162, https://doi.org/10.5194/egusphere-2023-2162, 2023
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
EGUsphere, https://doi.org/10.5194/egusphere-2023-1626, https://doi.org/10.5194/egusphere-2023-1626, 2023
Short summary
Short summary
Numerous estimations of water and energy balances heavily depend on empirical equations that necessitate site-specific calibration. This equifinality poses the risk of obtaining 'right answers for wrong reasons.' In this paper, we introduce novel formulations based on first-principles to calculate calibration-free quantities, such as net radiation, evapotranspiration, condensation, soil water content, surface runoff, subsurface lateral flow, and snow-water equivalent.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
EGUsphere, https://doi.org/10.5194/egusphere-2023-2503, https://doi.org/10.5194/egusphere-2023-2503, 2023
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract >25 % of the potential pre-industrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of land, water, and fertilizer use, as well as climate change.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-137, https://doi.org/10.5194/gmd-2023-137, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater pH and bulk soil pH is thus crucial to accurate evaluation of alkalinity required to counteract soil acidification and resulting capture of anthropogenic carbon dioxide through the Enhanced Rock Weathering technique. This has been enabled by the updated reactive-transport SCEPTER code and newly developed framework to simulate soil pH.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
EGUsphere, https://doi.org/10.5194/egusphere-2023-1287, https://doi.org/10.5194/egusphere-2023-1287, 2023
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predict their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that important questions related to plant-atmosphere interactions can be addressed, such as the effects of rising CO2 and ozone pollution on carbon uptake of the biosphere. The model has been well validated with both ground and satellite observations.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
Short summary
Short summary
We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
Short summary
Short summary
To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
Short summary
Short summary
Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
Short summary
Short summary
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
Short summary
Short summary
The coastal marine environment serves as a transition zone in the land–ocean continuum and is susceptible to episodic phenomena such as flash floods, which cause massive organic matter deposition. Here, we present a model of sediment early diagenesis that explicitly describes this type of deposition while also incorporating unique flood deposit characteristics. This model can be used to investigate the temporal evolution of marine sediments following abrupt changes in environmental conditions.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Cited articles
Abiven, S., Menasseri, S., and Chenu, C.: The effects of organic inputs over
time on soil aggregate stability – A literature analysis, Soil Biol.
Biochem., 41, 1–12, https://doi.org/10.1016/j.soilbio.2008.09.015,
2009.
Amundson, R., Berhe, A. A., Hopmans, J. W., Olson, C., Sztein, A. E., and
Sparks, D. L.: Soil and human security in the 21st century, Science, 348,
1261071–1261071, https://doi.org/10.1126/science.1261071, 2015.
Ansorge, H.: Die Wirkung des Stallmistes im “Statischen
Düngungsversuch” Lauchstädt, 2. Mitteilung: Veränderung des
Humusgehaltes im Boden, 10, 401–412, 1966.
Avery, B. W. and Catt, J. A.: The soil at Rothamsted, Lawes Agricultural
Trust, Harpenden, 1995.
Baldock, J. A., Hawke, B., Sanderman, J., and Macdonald, L. M.: Predicting
contents of carbon and its component fractions in Australian soils from
diffuse reflectance mid-infrared spectra, Soil Res., 51, 577,
https://doi.org/10.1071/SR13077, 2013.
Balesdent, J.: The significance of organic separates to carbon dynamics and
its modelling in some cultivated soils, Eur. J. Soil Sci., 47, 485–493,
https://doi.org/10.1111/j.1365-2389.1996.tb01848.x, 1996.
Balesdent, J. and Guillet, B.: Les datations par le 14C des matières
organiques des sols. Contribution à l'étude de l'humification et du
renouvellement des substances humiques, Science du sol, 2, 93–112, 1982.
Balesdent, J. and Mariotti, A.: Measurement of soil organic matter turnover
using 13C natural abundance, in: Mass spectrometry of soils, edited by:
Boutton, T. W. and Yamasaki, S. I., 83–111, 1996.
Balesdent, J., Mariotti, A., and Guillet, B.: Natural 13C abundance as a
tracer for studies of soil organic matter dynamics, Soil Biol.
Biochem., 19, 25–30, https://doi.org/10.1016/0038-0717(87)90120-9,
1987.
Balesdent, J., Wagner, G. H., and Mariotti, A.: Soil organic matter turnover
in long-term field experiments as revealed by carbon-13 natural abundance,
Soil Science Society of America Journal, 52, 118–124,
https://doi.org/10.2136/sssaj1988.03615995005200010021x, 1988.
Balesdent, J., Basile-Doelsch, I., Chadoeuf, J., Cornu, S., Derrien, D.,
Fekiacova, Z., and Hatté, C.: Atmosphere–soil carbon transfer as a
function of soil depth, Nature, 559, 599–602,
https://doi.org/10.1038/s41586-018-0328-3, 2018.
Barré, P., Eglin, T., Christensen, B. T., Ciais, P., Houot, S., Kätterer, T., van Oort, F., Peylin, P., Poulton, P. R., Romanenkov, V., and Chenu, C.: Quantifying and isolating stable soil organic carbon using long-term bare fallow experiments, Biogeosciences, 7, 3839–3850, https://doi.org/10.5194/bg-7-3839-2010, 2010.
Barré, P., Plante, A. F., Cécillon, L., Lutfalla, S., Baudin, F.,
Bernard, S., Christensen, B. T., Eglin, T., Fernandez, J. M., Houot, S.,
Kätterer, T., Le Guillou, C., Macdonald, A., van Oort, F., and Chenu,
C.: The energetic and chemical signatures of persistent soil organic matter,
Biogeochemistry, 130, 1–12, https://doi.org/10.1007/s10533-016-0246-0,
2016.
Behar, F., Beaumont, V., and De B. Penteado, H. L.: Rock-Eval 6 technology:
performances and developments, Oil Gas Sci. Technol., 56, 111–134, https://doi.org/10.2516/ogst:2001013, 2001.
Beleites, C. and Sergo, V.: hyperSpec: a package to handle hyperspectral
data sets in R, R package version 0.99-20201127, available at: https://github.com/cbeleites/hyperSpecm (last access: 15 June 2021), 2020.
Bellon-Maurel, V., Fernandez-Ahumada, E., Palagos, B., Roger, J.-M., and
McBratney, A.: Critical review of chemometric indicators commonly used for
assessing the quality of the prediction of soil attributes by NIR
spectroscopy, TrAC-Trend Anal. Chem., 29, 1073–1081,
https://doi.org/10.1016/j.trac.2010.05.006, 2010.
Borchers, H. W.: racma: Practical Numerical Math Functions. R package version 2.2.9, available at: https://CRAN.R-project.org/package=pracma (last access: 22 June 2021), 2019.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001.
Buyanovsky, G. A. and Wagner, G. H.: Carbon cycling in cultivated land and
its global significance, Glob. Change Biol., 4, 131–141,
https://doi.org/10.1046/j.1365-2486.1998.00130.x, 1998a.
Buyanovsky, G. A. and Wagner, G. H.: Changing role of cultivated land in the
global carbon cycle, Biol. Fert Soils, 27, 242–245,
https://doi.org/10.1007/s003740050427, 1998b.
Canty, A. and Ripley, B.: boot: Bootstrap R (S-Plus) Functions, R package version 1.3-28, 2020.
Cardinael, R., Eglin, T., Guenet, B., Neill, C., Houot, S., and Chenu, C.:
Is priming effect a significant process for long-term SOC dynamics? Analysis
of a 52-years old experiment, Biogeochemistry, 123, 203–219,
https://doi.org/10.1007/s10533-014-0063-2, 2015.
Cécillon, L.: lauric-cecillon/PARTYsoc: Second version of the PARTYsoc statistical model (Version v2.0), Zenodo, https://doi.org/10.5281/zenodo.4446138, 2021.
Cécillon, L., Cassagne, N., Czarnes, S., Gros, R., and Brun, J.-J.:
Variable selection in near infrared spectra for the biological
characterization of soil and earthworm casts, Soil Biol. Biochem.,
40, 1975–1979, https://doi.org/10.1016/j.soilbio.2008.03.016, 2008.
Cécillon, L., Baudin, F., Chenu, C., Houot, S., Jolivet, R., Kätterer, T., Lutfalla, S., Macdonald, A., van Oort, F., Plante, A. F., Savignac, F., Soucémarianadin, L. N., and Barré, P.: A model based on Rock-Eval thermal analysis to quantify the size of the centennially persistent organic carbon pool in temperate soils, Biogeosciences, 15, 2835–2849, https://doi.org/10.5194/bg-15-2835-2018, 2018.
Cerri, C., Feller, C., Balesdent, J., Victoria, R., and Plenccassagne, A.:
Application du traçage isotopique naturel en 13C, à l'étude de
la dynamique de la matière organique dans les sols, Cr.
Acad. Sci., 300,
423–428, 1985.
Christensen, B. T. and Johnston, A. E.: Soil organic matter and soil
quality – Lessons learned from long-term experiments at Askov and
Rothamsted, Dev. Soil Sci., 25, 399–430,
https://doi.org/10.1016/S0166-2481(97)80045-1, 1997.
Christensen, B. T., Thomsen, I. K., and Eriksen, J.: The Askov long-term
experiments: 1894–2019: a unique research platform turns 125 years, DCA –
Nationalt Center for Fødevarer og Jordbrug, Tjele, 2019.
Clivot, H., Mouny, J.-C., Duparque, A., Dinh, J.-L., Denoroy, P., Houot, S.,
Vertès, F., Trochard, R., Bouthier, A., Sagot, S., and Mary, B.:
Modeling soil organic carbon evolution in long-term arable experiments with
AMG model, Environ. Modell. Softw., 118, 99–113,
https://doi.org/10.1016/j.envsoft.2019.04.004, 2019.
Cotrufo, M. F., Ranalli, M. G., Haddix, M. L., Six, J., and Lugato, E.: Soil
carbon storage informed by particulate and mineral-associated organic
matter, Nat. Geosci., 12, 989–994,
https://doi.org/10.1038/s41561-019-0484-6, 2019.
Coulston, J. W., Blinn, C. E., Thomas, V. A., and Wynne, R. H.:
Approximating prediction uncertainty for random forest regression models,
Photogramm. Eng. Rem. S., 82, 189–197,
https://doi.org/10.14358/PERS.82.3.189, 2016.
Dangal, S., Sanderman, J., Wills, S., and Ramirez-Lopez, L.: Accurate and
precise prediction of soil properties from a large mid-infrared spectral
library, Soil Syst., 3, 11, https://doi.org/10.3390/soilsystems3010011,
2019.
Davison, A. C. and Hinkley, D. V.: Bootstrap methods and their application,
Cambridge University Press, Cambridge, New York, NY, USA, 582 pp., 1997.
Disnar, J. R., Guillet, B., Keravis, D., Di-Giovanni, C., and Sebag, D.:
Soil organic matter (SOM) characterization by Rock-Eval pyrolysis: scope and
limitations, Org. Geochem., 34, 327–343,
https://doi.org/10.1016/S0146-6380(02)00239-5, 2003.
European Commission: Soils of the European Union, Joint Research Centre,
Institute for Environment and Sustainability, Publications Office, LU,
2008.
Falloon, P., Smith, P., Coleman, K., and Marshall, S.: Estimating the size
of the inert organic matter pool from total soil organic carbon content for
use in the Rothamsted carbon model, Soil Biol. Biochem., 30,
1207–1211, https://doi.org/10.1016/S0038-0717(97)00256-3, 1998.
Falloon, P. D. and Smith, P.: Modelling refractory soil organic matter,
Biol. Fert. Soils, 30, 388–398,
https://doi.org/10.1007/s003740050019, 2000.
FAO: World reference base for soil resources 2014: international soil
classification system for naming soils and creating legends for soil maps, FAO, Rome, 2014.
Franko, U. and Merbach, I.: Modelling soil organic matter dynamics on a bare
fallow Chernozem soil in Central Germany, Geoderma, 303, 93–98,
https://doi.org/10.1016/j.geoderma.2017.05.013, 2017.
Genuer, R. and Poggi, J.-M.: Random Forests with R, Springer International
Publishing, Cham, https://doi.org/10.1007/978-3-030-56485-8, 2020.
Gogé, F., Joffre, R., Jolivet, C., Ross, I., and Ranjard, L.:
Optimization criteria in sample selection step of local regression for
quantitative analysis of large soil NIRS database, Chemometr.
Intell. Lab., 110, 168–176,
https://doi.org/10.1016/j.chemolab.2011.11.003, 2012.
Gray, J., Karunaratne, S., Bishop, T., Wilson, B., and Veeragathipillai, M.:
Driving factors of soil organic carbon fractions over New South Wales,
Australia, Geoderma, 353, 213–226,
https://doi.org/10.1016/j.geoderma.2019.06.032, 2019.
Gregorich, E. G., Gillespie, A. W., Beare, M. H., Curtin, D., Sanei, H., and
Yanni, S. F.: Evaluating biodegradability of soil organic matter by its
thermal stability and chemical composition, Soil Biol. Biochem.,
91, 182–191, https://doi.org/10.1016/j.soilbio.2015.08.032, 2015.
He, Y., Trumbore, S. E., Torn, M. S., Harden, J. W., Vaughn, L. J. S.,
Allison, S. D., and Randerson, J. T.: Radiocarbon constraints imply reduced
carbon uptake by soils during the 21st century, Science, 353, 1419–1424,
https://doi.org/10.1126/science.aad4273, 2016.
Hénin, S. and Dupuis, M.: Bilan de la matière organique des sols, Annales Agronomiques, 1,
17–29, 1945.
Hénin, S. and Turc, L.: Essai de fractionnement des matières
organiques du sol, Comptes rendus de l'Académie d'agriculture de Francem 35, 41–43, 1949.
Houot, S., Molina, J. A. E., Chaussod, R., and Clapp, C. E.: Simulation by
NCSOIL of net mineralization in soils from the Deherain and 36 parcelles
fields at Grignon, Soil Sci. Soc. Am. J., 53, 451–455,
https://doi.org/10.2136/sssaj1989.03615995005300020023x, 1989.
Hsieh, Y.-P.: Pool size and mean age of stable soil organic carbon in
croplands, Soil Sci. Soc. Am. J., 56, 460–464,
https://doi.org/10.2136/sssaj1992.03615995005600020049x, 1992.
Huggins, D. R., Buyanovsky, G. A., Wagner, G. H., Brown, J. R., Darmody, R.
G., Peck, T. R., Lesoing, G. W., Vanotti, M. B., and Bundy, L. G.: Soil
organic C in the tallgrass prairie-derived region of the corn belt: effects
of long-term crop management, Soil Till. Res., 47, 219–234,
https://doi.org/10.1016/S0167-1987(98)00108-1, 1998.
IPBES: Summary for policymakers of the assessment report on land degradation
and restoration of the Intergovernmental Science-Policy Platform on
Biodiversity and Ecosystem Services, edited by: Scholes, R. J.,
Montanarella, L., Brainich, E., Brainich, E., Barger, N., ten Brink, B.,
Cantele, M., Erasmus, B., Fisher, J., Gardner, T., Holland, T. G., Kohler,
F., Kotiaho, S., von Maltitz, G., Nangendo, G., Pandit, R., Parrotta, J.,
Potts, M. D., Prince, S., Sankaran, M., and Willemen, L., Intergovernmental
Science-Policy Platform on Biodiversity and Ecosystem Services, 2018.
IPCC: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, edited by: Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J., Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M., and Malley, J., available at: https://www.ipcc.ch/srccl/ (last access: 22 June 2021), 2019.
ISO 10694: Soil quality – Determination of organic and total carbon after dry combustion (elementary analysis), available at: https://www.iso.org/standard/18782.html (last access: 22 June 2021), 1995.
Jaconi, A., Poeplau, C., Ramirez-Lopez, L., Van Wesemael, B., and Don, A.:
Log-ratio transformation is the key to determining soil organic carbon
fractions with near-infrared spectroscopy, Eur. J. Soil. Sci., 70, 127–139,
https://doi.org/10.1111/ejss.12761, 2019.
Janzen, H. H.: The soil carbon dilemma: shall we hoard it or use it?, Soil
Biol. Biochem., 38, 419–424,
https://doi.org/10.1016/j.soilbio.2005.10.008, 2006.
Jenkinson, D. S.: The turnover of organic carbon and nitrogen in soil, Philos.
T. R. Soc. Lond. B, 329, 361–368,
https://doi.org/10.1098/rstb.1990.0177, 1990.
Jenkinson, D. S. and Coleman, K.: Calculating the annual input of organic
matter to soil from measurements of total organic carbon and radiocarbon,
Eur. J. Soil Sci., 45, 167–174,
https://doi.org/10.1111/j.1365-2389.1994.tb00498.x, 1994.
Jenkinson, D. S., Adams, D. E., and Wild, A.: Model estimates of CO2
emissions from soil in response to global warming, Nature, 351, 304–306,
https://doi.org/10.1038/351304a0, 1991.
Johnston, A. E., Poulton, P. R., and Coleman, K.: Soil organic matter: its
importance in sustainable agriculture and carbon dioxide fluxes, in:
Adv. Agronom., 101, 1–57,
https://doi.org/10.1016/S0065-2113(08)00801-8, 2009.
Jolivet, C., Almeida-Falcon, J. L., Berché, P., Boulonne, L., Fontaine,
M., Gouny, L., Lehmann, S., Maître, B., Ratié, C., Schellenberger,
E., and Soler-Dominguez, N.: Manuel du Réseau de mesures de la
qualité des sols, RMQS2: deuxième campagne métropolitaine, 2016
– 2027, Version 3, INRA, US 1106 InfoSol, Orléans, France, 2018.
Kätterer, T., Bolinder, M. A., Andrén, O., Kirchmann, H., and
Menichetti, L.: Roots contribute more to refractory soil organic matter than
above-ground crop residues, as revealed by a long-term field experiment,
Agriculture, Ecosyst. Environ., 141, 184–192,
https://doi.org/10.1016/j.agee.2011.02.029, 2011.
Keesstra, S. D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerdà, A., Montanarella, L., Quinton, J. N., Pachepsky, Y., van der Putten, W. H., Bardgett, R. D., Moolenaar, S., Mol, G., Jansen, B., and Fresco, L. O.: The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals, SOIL, 2, 111–128, https://doi.org/10.5194/soil-2-111-2016, 2016.
Khedim, N., Cécillon, L., Poulenard, J., Barré, P., Baudin, F.,
Marta, S., Rabatel, A., Dentant, C., Cauvy-Fraunié, S., Anthelme, F.,
Gielly, L., Ambrosini, R., Franzetti, A., Azzoni, R. S., Caccianiga, M. S.,
Compostella, C., Clague, J., Tielidze, L., Messager, E., Choler, P., and
Ficetola, G. F.: Topsoil organic matter build-up in glacier forelands around
the world, Glob. Change Biol., 27, 1662–1677,
https://doi.org/10.1111/gcb.15496,
2021.
Koch, A., McBratney, A., Adams, M., Field, D., Hill, R., Crawford, J.,
Minasny, B., Lal, R., Abbott, L., O'Donnell, A., Angers, D., Baldock, J.,
Barbier, E., Binkley, D., Parton, W., Wall, D. H., Bird, M., Bouma, J.,
Chenu, C., Flora, C. B., Goulding, K., Grunwald, S., Hempel, J., Jastrow,
J., Lehmann, J., Lorenz, K., Morgan, C. L., Rice, C. W., Whitehead, D.,
Young, I., and Zimmermann, M.: Soil security: solving the global soil
crisis, Glob. Policy, 4, 434–441, https://doi.org/10.1111/1758-5899.12096,
2013.
Körschens, M., Weigel, A., and Schulz, E.: Turnover of soil organic
matter (SOM) and long-term balances – tools for evaluating sustainable
productivity of soils, Z. Pflanzenernaehr. Bodenk., 161, 409–424,
https://doi.org/10.1002/jpln.1998.3581610409, 1998.
Lal, R.: Soil carbon sequestration impacts on global climate change and food
security, Science, 304, 1623–1627, https://doi.org/10.1126/science.1097396,
2004.
Lavallee, J. M., Soong, J. L., and Cotrufo, M. F.: Conceptualizing soil
organic matter into particulate and mineral-associated forms to address
global change in the 21st century, Glob. Change Biol., 26, 261–273,
https://doi.org/10.1111/gcb.14859, 2020.
Liaw, A. and Wiener, M.: Classification and regression by randomForest, R News, 2,
18–22, 2002.
Ludwig, B., Schulz, E., Rethemeyer, J., Merbach, I., and Flessa, H.:
Predictive modelling of C dynamics in the long-term fertilization experiment
at Bad Lauchstädt with the Rothamsted Carbon Model, Eur. J. Soil Sci., 58, 1155–1163,
https://doi.org/10.1111/j.1365-2389.2007.00907.x, 2007.
Luo, Y., Ahlström, A., Allison, S. D., Batjes, N. H., Brovkin, V.,
Carvalhais, N., Chappell, A., Ciais, P., Davidson, E. A., Finzi, A.,
Georgiou, K., Guenet, B., Hararuk, O., Harden, J. W., He, Y., Hopkins, F.,
Jiang, L., Koven, C., Jackson, R. B., Jones, C. D., Lara, M. J., Liang, J.,
McGuire, A. D., Parton, W., Peng, C., Randerson, J. T., Salazar, A., Sierra,
C. A., Smith, M. J., Tian, H., Todd-Brown, K. E. O., Torn, M., van
Groenigen, K. J., Wang, Y. P., West, T. O., Wei, Y., Wieder, W. R., Xia, J.,
Xu, X., Xu, X., and Zhou, T.: Toward more realistic projections of soil
carbon dynamics by Earth system models, Global Biogeochem. Cy., 30,
40–56, https://doi.org/10.1002/2015GB005239, 2016.
Monnier, G., Turc, C., and Jeanson Luusinang, C.: Une methode de fractionnement densimétrique par centrifugation des matières organiques du sol, Annales Agronomiques,
13, 55–63, 1962.
Nikiforoff, C. C.: Some General Aspects of the Chernozem Formation, Soil
Sci. Soc. Am. J., 1, 333–342,
https://doi.org/10.2136/sssaj1937.03615995000100000060x, 1936.
Patil, A., Huard, D., and Fonnesbeck, C.: PyMC: Bayesian stochastic
modelling in Python, J. Stat. Softw., 35,
https://doi.org/10.18637/jss.v035.i04, 2010.
Pellerin, S., Bamière, L., Launay, C., Martin, R., Schiavo, M., Angers,
D., Augusto, L., Balesdent, J., Basile-Doelsch, I., Bellassen, V.,
Cardinael, R., Cécillon, L., Ceschia, E., Chenu, C., Constantin, J.,
Darroussin, J., Delacote, P., Delame, N., Gastal, F., Gilbert, D., Graux,
A.-I., Guenet, B., Houot, S., Klumpp, K., Letort, E., Litrico, I., Martin,
M., Menasseri-Aubry, S., Meziere, D., Morvan, T., Mosnier, C.,
Roger-Estrade, J., Saint-André, L., Sierra, J., Therond, O., Viaud, V.,
Grateau, R., Le Perchec, S., Savini, I., and Rechauchère, O.: Stocker du carbone dans les sols français, Quel potentiel au regard de l’objectif 4 pour 1000 et à quel coût? Rapport scientifique de l'étude, INRA (France), 540 pp., available at: https://www.inrae.fr/sites/default/files/pdf/Rapport Etude 4p1000.pdf (last access: 22 June 2021), 2020.
Petersen, B. M., Berntsen, J., Hansen, S., and Jensen, L. S.: CN-SIM – a
model for the turnover of soil organic matter. I. Long-term carbon and
radiocarbon development, Soil Biol. Biochem., 37, 359–374,
https://doi.org/10.1016/j.soilbio.2004.08.006, 2005.
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.
Poeplau, C., Don, A., Dondini, M., Leifeld, J., Nemo, R., Schumacher, J.,
Senapati, N., and Wiesmeier, M.: Reproducibility of a soil organic carbon
fractionation method to derive RothC carbon pools: Soil carbon fractionation
ring trial, Eur. J. Soil Sci., 64, 735–746,
https://doi.org/10.1111/ejss.12088, 2013.
Poeplau, C., Don, A., Six, J., Kaiser, M., Benbi, D., Chenu, C., Cotrufo, M.
F., Derrien, D., Gioacchini, P., Grand, S., Gregorich, E., Griepentrog, M.,
Gunina, A., Haddix, M., Kuzyakov, Y., Kühnel, A., Macdonald, L. M.,
Soong, J., Trigalet, S., Vermeire, M.-L., Rovira, P., van Wesemael, B.,
Wiesmeier, M., Yeasmin, S., Yevdokimov, I., and Nieder, R.: Isolating
organic carbon fractions with varying turnover rates in temperate
agricultural soils – A comprehensive method comparison, Soil Biol.
Biochem., 125, 10–26, https://doi.org/10.1016/j.soilbio.2018.06.025,
2018.
Poeplau, C., Barré, P., Cécillon, L., Baudin, F., and Sigurdsson, B.
D.: Changes in the Rock-Eval signature of soil organic carbon upon extreme
soil warming and chemical oxidation - A comparison, Geoderma, 337, 181–190,
https://doi.org/10.1016/j.geoderma.2018.09.025, 2019.
Quezada, J. C., Etter, A., Ghazoul, J., Buttler, A., and Guillaume, T.:
Carbon neutral expansion of oil palm plantations in the Neotropics, Sci.
Adv., 5, eaaw4418, https://doi.org/10.1126/sciadv.aaw4418, 2019.
Ramirez-Lopez, L., Behrens, T., Schmidt, K., Rossel, R. A. V., Demattê,
J. A. M., and Scholten, T.: Distance and similarity-search metrics for use
with soil vis–NIR spectra, Geoderma, 199, 43–53,
https://doi.org/10.1016/j.geoderma.2012.08.035, 2013a.
Ramirez-Lopez, L., Behrens, T., Schmidt, K., Stevens, A., Demattê, J. A.
M., and Scholten, T.: The spectrum-based learner: A new local approach for
modeling soil vis–NIR spectra of complex datasets, Geoderma, 195–196,
268–279, https://doi.org/10.1016/j.geoderma.2012.12.014, 2013b.
R Core Team: R: a language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria, 2020.
RStudio Team: RStudio: integrated development for R, RStudio, Inc., Boston,
MA, 2020.
Rühlmann, J.: A new approach to estimating the pool of stable organic
matter in soil using data from long-term field experiments, Plant Soil, 213, 149–160,
https://doi.org/10.1023/A:1004552016182, 1999.
Saenger, A., Cécillon, L., Sebag, D., and Brun, J.-J.: Soil organic
carbon quantity, chemistry and thermal stability in a mountainous landscape:
A Rock–Eval pyrolysis survey, Org. Geochem., 54, 101–114,
https://doi.org/10.1016/j.orggeochem.2012.10.008, 2013.
Saenger, A., Cécillon, L., Poulenard, J., Bureau, F., De Daniéli,
S., Gonzalez, J.-M., and Brun, J.-J.: Surveying the carbon pools of mountain
soils: A comparison of physical fractionation and Rock-Eval pyrolysis,
Geoderma, 241–242, 279–288,
https://doi.org/10.1016/j.geoderma.2014.12.001, 2015.
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.
Sanderman, J., Hengl, T., and Fiske, G. J.: Soil carbon debt of 12,000 years
of human land use, P. Natl. Acad. Sci. USA, 114, 9575–9580,
https://doi.org/10.1073/pnas.1706103114, 2017.
Schiedung, M., Don, A., Wordell-Dietrich, P., Alcántara, V., Kuner, P.,
and Guggenberger, G.: Thermal oxidation does not fractionate soil organic
carbon with differing biological stabilities, J. Plant Nutr. Soil Sci., 180,
18–26, https://doi.org/10.1002/jpln.201600172, 2017.
Schulte, R. P. O., Creamer, R. E., Donnellan, T., Farrelly, N., Fealy, R.,
O'Donoghue, C., and O'hUallachain, D.: Functional land management: A
framework for managing soil-based ecosystem services for the sustainable
intensification of agriculture, Environ. Sci. Policy, 38,
45–58, https://doi.org/10.1016/j.envsci.2013.10.002, 2014.
Sebag, D., Verrecchia, E. P., Cécillon, L., Adatte, T., Albrecht, R.,
Aubert, M., Bureau, F., Cailleau, G., Copard, Y., Decaens, T., Disnar,
J.-R., Hetényi, M., Nyilas, T., and Trombino, L.: Dynamics of soil
organic matter based on new Rock-Eval indices, Geoderma, 284, 185–203,
https://doi.org/10.1016/j.geoderma.2016.08.025, 2016.
Shi, Z., Allison, S. D., He, Y., Levine, P. A., Hoyt, A. M., Beem-Miller,
J., Zhu, Q., Wieder, W. R., Trumbore, S., and Randerson, J. T.: The age
distribution of global soil carbon inferred from radiocarbon measurements,
Nat. Geosci., 13, 555–559,
https://doi.org/10.1038/s41561-020-0596-z, 2020.
Skjemstad, J. O., Spouncer, L. R., Cowie, B., and Swift, R. S.: Calibration
of the Rothamsted organic carbon turnover model (RothC ver. 26.3), using
measurable soil organic carbon pools, Soil Res., 42, 79–88,
https://doi.org/10.1071/SR03013, 2004.
Soucémarianadin, L., Cécillon, L., Chenu, C., Baudin, F., Nicolas,
M., Girardin, C., and Barré, P.: Is Rock-Eval 6 thermal analysis a good
indicator of soil organic carbon lability? – A method-comparison study in
forest soils, Soil Biol. Biochem., 117, 108–116,
https://doi.org/10.1016/j.soilbio.2017.10.025, 2018a.
Soucémarianadin, L. N., Cécillon, L., Guenet, B., Chenu, C., Baudin,
F., Nicolas, M., Girardin, C., and Barré, P.: Environmental factors
controlling soil organic carbon stability in French forest soils, Plant
Soil, 426, 267–286, https://doi.org/10.1007/s11104-018-3613-x, 2018b.
Stoorvogel, J. J., Bakkenes, M., Brink, B. J. E., and Temme, A. J. A. M.: To
what extent did we change our soils? A global comparison of natural and
current conditions, Land Degrad. Develop., 28, 1982–1991,
https://doi.org/10.1002/ldr.2721, 2017.
Strobl, C., Malley, J., and Tutz, G.: An introduction to recursive
partitioning: Rationale, application, and characteristics of classification
and regression trees, bagging, and random forests, Psychol. Meth.,
14, 323–348, https://doi.org/10.1037/a0016973, 2009.
Taghizadeh-Toosi, A., Cong, W.-F., Eriksen, J., Mayer, J., Olesen, J. E.,
Keel, S. G., Glendining, M., Kätterer, T., and Christensen, B. T.:
Visiting dark sides of model simulation of carbon stocks in European
temperate agricultural soils: allometric function and model initialization,
Plant Soil, 450, 255–272, https://doi.org/10.1007/s11104-020-04500-9, 2020.
Trumbore, S. E., Vogel, J. S., and Southon, J. R.: AMS 14C measurements of
fractionated soil organic matter: an approach to deciphering the soil carbon
cycle, Radiocarbon, 31, 644–654, https://doi.org/10.1017/S0033822200012248,
1989.
van Oort, F., Paradelo, R., Proix, N., Delarue, G., Baize, D., and Monna,
F.: Centennial fertilization-induced soil processes control trace metal
dynamics. Lessons from a long-term bare fallow experiment, Soil Syst., 2, 23,
https://doi.org/10.3390/soilsystems2020023, 2018.
Viscarra Rossel, R. A. and Hicks, W. S.: Soil organic carbon and its
fractions estimated by visible-near infrared transfer functions: Vis-NIR
estimates of organic carbon and its fractions, Eur. J. Soil Sci., 66, 438–450,
https://doi.org/10.1111/ejss.12237, 2015.
Viscarra Rossel, R. A., Lee, J., Behrens, T., Luo, Z., Baldock, J., and
Richards, A.: Continental-scale soil carbon composition and vulnerability
modulated by regional environmental controls, Nat. Geosci., 12, 547–552,
https://doi.org/10.1038/s41561-019-0373-z, 2019.
von Lützow, M., Kögel-Knabner, I., Ekschmitt, K., Flessa, H.,
Guggenberger, G., Matzner, E., and Marschner, B.: SOM fractionation methods:
Relevance to functional pools and to stabilization mechanisms, Soil Biol.
Biochem., 39, 2183–2207,
https://doi.org/10.1016/j.soilbio.2007.03.007, 2007.
Vos, C., Jaconi, A., Jacobs, A., and Don, A.: Hot regions of labile and stable soil organic carbon in Germany – Spatial variability and driving factors, SOIL, 4, 153–167, https://doi.org/10.5194/soil-4-153-2018, 2018.
Wehrens, R.: Chemometrics with R: Multivariate Data Analysis in the Natural
and Life Sciences, Springer Berlin Heidelberg, Berlin, Heidelberg,
https://doi.org/10.1007/978-3-662-62027-4, 2020.
Wickham, H.: tringr: Simple, consistent wrappers for common string operations, R package version 1.4.0, available at: https://CRAN.R-project.org/package=stringr (last access: 22 June 2021), 2019.
Wiesmeier, M., Urbanski, L., Hobley, E., Lang, B., von Lützow, M.,
Marin-Spiotta, E., van Wesemael, B., Rabot, E., Ließ, M., Garcia-Franco,
N., Wollschläger, U., Vogel, H.-J., and Kögel-Knabner, I.: Soil
organic carbon storage as a key function of soils – A review of drivers and
indicators at various scales, Geoderma, 333, 149–162,
https://doi.org/10.1016/j.geoderma.2018.07.026, 2019.
Zimmermann, M., Leifeld, J., Schmidt, M. W. I., Smith, P., and Fuhrer, J.:
Measured soil organic matter fractions can be related to pools in the RothC
model, Eur. J. Soil Sci., 58, 658–667,
https://doi.org/10.1111/j.1365-2389.2006.00855.x, 2007a.
Zimmermann, M., Leifeld, J., and Fuhrer, J.: Quantifying soil organic carbon
fractions by infrared-spectroscopy, Soil Biol. Biochem., 39,
224–231, https://doi.org/10.1016/j.soilbio.2006.07.010, 2007b.
Short summary
Partitioning soil organic carbon (SOC) into fractions that are stable or active on a century scale is key for more accurate models of the carbon cycle. Here, we describe the second version of a machine-learning model, named PARTYsoc, which reliably predicts the proportion of the centennially stable SOC fraction at its northwestern European validation sites with Cambisols and Luvisols, the two dominant soil groups in this region, fostering modelling works of SOC dynamics.
Partitioning soil organic carbon (SOC) into fractions that are stable or active on a century...
