Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-1399-2020
© Author(s) 2020. 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-13-1399-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
23 Mar 2020
Development and technical paper |
| 23 Mar 2020
| 23 Mar 2020
Dynamic upscaling of decomposition kinetics for carbon cycling models
Arjun Chakrawal
CORRESPONDING AUTHOR
Department of Physical Geography, Stockholm University, Svante Arrhenius väg 8C, Frescati, 106 91 Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Anke M. Herrmann
Department of Soil & Environment, Swedish University of Agricultural Sciences, P.O. Box 7014, 75007 Uppsala, Sweden
John Koestel
Department of Soil & Environment, Swedish University of Agricultural Sciences, P.O. Box 7014, 75007 Uppsala, Sweden
Jerker Jarsjö
Department of Physical Geography, Stockholm University, Svante Arrhenius väg 8C, Frescati, 106 91 Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Naoise Nunan
Institute of Ecology and Environmental Sciences – Paris, Sorbonne Université-CNRS-IRD-INRA-P7-UPEC, 4 place Jussieu, 75005 Paris, France
Thomas Kätterer
Department of Ecology, Swedish University of Agricultural Sciences, P.O. Box 7044, 75007 Uppsala, Sweden
Stefano Manzoni
Department of Physical Geography, Stockholm University, Svante Arrhenius väg 8C, Frescati, 106 91 Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
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We collated the Open Tension-disk Infiltrometer Meta-database (OTIM). We analysed topsoil hydraulic conductivities at supply tensions between 0 and 100 mm of 466 data entries. We found indications of different flow mechanisms at saturation and at tensions >20 mm. Climate factors were better correlated with near-saturated hydraulic conductivities than soil properties. Land use, tillage system, soil compaction and experimenter bias significantly influenced K to a similar degree to soil properties.
Guillaume Blanchy, Lukas Albrecht, John Koestel, and Sarah Garré
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Adapting agricultural practices to future climatic conditions requires us to synthesize the effects of management practices on soil properties with respect to local soil and climate. We showcase different automated text-processing methods to identify topics, extract metadata for building a database and summarize findings from publication abstracts. While human intervention remains essential, these methods show great potential to support evidence synthesis from large numbers of publications.
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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
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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
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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.
Lauric Cécillon, François Baudin, Claire Chenu, Bent T. Christensen, Uwe Franko, Sabine Houot, Eva Kanari, Thomas Kätterer, Ines Merbach, Folkert van Oort, Christopher Poeplau, Juan Carlos Quezada, Florence Savignac, Laure N. Soucémarianadin, and Pierre Barré
Geosci. Model Dev., 14, 3879–3898, https://doi.org/10.5194/gmd-14-3879-2021, https://doi.org/10.5194/gmd-14-3879-2021, 2021
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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.
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
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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.
Benjamin M. C. Fischer, Laura Morillas, Johanna Rojas Conejo, Ricardo Sánchez-Murillo, Andrea Suárez Serrano, Jay Frentress, Chih-Hsin Cheng, Monica Garcia, Stefano Manzoni, Mark S. Johnson, and Steve W. Lyon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-404, https://doi.org/10.5194/hess-2020-404, 2020
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We investigated in an upland rice experiment in Costa Rica whether mixing biochar (a charcoal) in soils could increase the resilience of rainfed agriculture to climate variability. We found that rice plants with biochar had access to larger stores of water more consistently and thus could withstand seven extra dry days relative to rice grown in non-treated soils. However, biochar can complement, but not necessarily replace, other water management strategies.
Stefano Manzoni, Arjun Chakrawal, Thomas Fischer, Joshua P. Schimel, Amilcare Porporato, and Giulia Vico
Biogeosciences, 17, 4007–4023, https://doi.org/10.5194/bg-17-4007-2020, https://doi.org/10.5194/bg-17-4007-2020, 2020
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Carbon dioxide is produced by soil microbes through respiration, which is particularly fast when soils are moistened by rain. Will respiration increase with future more intense rains and longer dry spells? With a mathematical model, we show that wetter conditions increase respiration. In contrast, if rainfall totals stay the same, but rain comes all at once after long dry spells, the average respiration will not change, but the contribution of the respiration bursts after rain will increase.
Stefano Manzoni, Giorgos Maneas, Anna Scaini, Basil E. Psiloglou, Georgia Destouni, and Steve W. Lyon
Hydrol. Earth Syst. Sci., 24, 3557–3571, https://doi.org/10.5194/hess-24-3557-2020, https://doi.org/10.5194/hess-24-3557-2020, 2020
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A modeling tool is developed to assess the vulnerability of coastal wetlands to climatic and water management changes. Applied to the case study of the Gialova lagoon (Greece), this tool highlights the reliance of the lagoon functionality on scarce freshwater sources already under high demand from agriculture. Climatic changes will likely increase lagoon salinity, despite efforts to improve water management.
Navid Ghajarnia, Georgia Destouni, Josefin Thorslund, Zahra Kalantari, Imenne Åhlén, Jesús A. Anaya-Acevedo, Juan F. Blanco-Libreros, Sonia Borja, Sergey Chalov, Aleksandra Chalova, Kwok P. Chun, Nicola Clerici, Amanda Desormeaux, Bethany B. Garfield, Pierre Girard, Olga Gorelits, Amy Hansen, Fernando Jaramillo, Jerker Jarsjö, Adnane Labbaci, John Livsey, Giorgos Maneas, Kathryn McCurley Pisarello, Sebastián Palomino-Ángel, Jan Pietroń, René M. Price, Victor H. Rivera-Monroy, Jorge Salgado, A. Britta K. Sannel, Samaneh Seifollahi-Aghmiuni, Ylva Sjöberg, Pavel Terskii, Guillaume Vigouroux, Lucia Licero-Villanueva, and David Zamora
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Hydroclimate and land-use conditions determine the dynamics of wetlands and their ecosystem services. However, knowledge and data for conditions and changes over entire wetlandscapes are scarce. This paper presents a novel database for 27 wetlandscapes around the world, combining survey-based local information and hydroclimatic and land-use datasets. The developed database can enhance our capacity to understand and manage critical wetland ecosystems and their services under global change.
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
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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.
Haicheng Zhang, Daniel S. Goll, Stefano Manzoni, Philippe Ciais, Bertrand Guenet, and Yuanyuan Huang
Geosci. Model Dev., 11, 4779–4796, https://doi.org/10.5194/gmd-11-4779-2018, https://doi.org/10.5194/gmd-11-4779-2018, 2018
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Carbon use efficiency (CUE) of decomposers depends strongly on the organic matter quality (C : N ratio) and soil nutrient availability rather than a fixed value. A soil biogeochemical model with flexible CUE can better capture the differences in respiration rate of litter with contrasting C : N ratios and under different levels of mineral N availability than the model with fixed CUE, and well represent the effect of varying litter quality (N content) on SOM formation across temporal scales.
Stefano Manzoni, Petr Čapek, Philipp Porada, Martin Thurner, Mattias Winterdahl, Christian Beer, Volker Brüchert, Jan Frouz, Anke M. Herrmann, Björn D. Lindahl, Steve W. Lyon, Hana Šantrůčková, Giulia Vico, and Danielle Way
Biogeosciences, 15, 5929–5949, https://doi.org/10.5194/bg-15-5929-2018, https://doi.org/10.5194/bg-15-5929-2018, 2018
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Carbon fixed by plants and phytoplankton through photosynthesis is ultimately stored in soils and sediments or released to the atmosphere during decomposition of dead biomass. Carbon-use efficiency is a useful metric to quantify the fate of carbon – higher efficiency means higher storage and lower release to the atmosphere. Here we summarize many definitions of carbon-use efficiency and study how this metric changes from organisms to ecosystems and from terrestrial to aquatic environments.
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
Corina Buendía, Axel Kleidon, Stefano Manzoni, Björn Reu, and Amilcare Porporato
Biogeosciences, 15, 279–295, https://doi.org/10.5194/bg-15-279-2018, https://doi.org/10.5194/bg-15-279-2018, 2018
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Amazonia is highly biodiverse and of global importance for regulating the climate system. Because soils are highly weathered, phosphorus (P) is suggested to limit ecosystem productivity. Here, we evaluate the importance of P redistribution by animals using a simple mathematical model synthesizing the major processes of the Amazon P cycle. Our findings suggest that food web complexity plays an important role for sustaining the productivity of terra firme forests.
Hannes Keck, Bjarne W. Strobel, Jon Petter Gustafsson, and John Koestel
SOIL, 3, 177–189, https://doi.org/10.5194/soil-3-177-2017, https://doi.org/10.5194/soil-3-177-2017, 2017
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Several studies have shown that the cation adsorption sites in soils are heterogeneously distributed in space. In many soil system models this knowledge is not included yet. In our study we proposed a new method to map the 3-D distribution of cation adsorption sites in undisturbed soils. The method is based on three-dimensional X-ray scanning with a contrast agent and image analysis. We are convinced that this approach will strongly aid the development of more realistic soil system models.
Cédric Doupoux, Patricia Merdy, Célia Régina Montes, Naoise Nunan, Adolpho José Melfi, Osvaldo José Ribeiro Pereira, and Yves Lucas
Biogeosciences, 14, 2429–2440, https://doi.org/10.5194/bg-14-2429-2017, https://doi.org/10.5194/bg-14-2429-2017, 2017
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Amazonian podzol soils store huge amounts of carbon and play a key role in transferring organic matter to the Amazon River. We modelled their formation by constraining both total carbon and radiocarbon. We found that the most waterlogged zones of the podzolized areas are the main source of dissolved organic matter found in the river network. The genesis time calculated considering the more likely settings runs to around 15–25 and 150–250 kyr for young and old podzols, respectively.
Karin Ebert, Karin Ekstedt, and Jerker Jarsjö
Nat. Hazards Earth Syst. Sci., 16, 1571–1582, https://doi.org/10.5194/nhess-16-1571-2016, https://doi.org/10.5194/nhess-16-1571-2016, 2016
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Future sea level rise is inevitable. We investigate the effects of 2 m sea level rise on the island of Gotland, Sweden. In a multi-criteria analysis we analyze the quantity of infrastructure that will be inundated, and the effect of saltwater intrusion in wells. Almost 100 km2 (3 %) of Gotland's land area will be inundated. Important touristic and nature values will be strongest affected. Well salinization will greatly increase. Administrative planning is needed to prepare for changes.
Lorenzo Menichetti, Thomas Kätterer, and Jens Leifeld
Biogeosciences, 13, 3003–3019, https://doi.org/10.5194/bg-13-3003-2016, https://doi.org/10.5194/bg-13-3003-2016, 2016
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Soil organic carbon dynamics are crucial for the global greenhouse gas balance, but their complexity is difficult to model and understand. We therefore often rely on radiocarbon measurements for calibrating models, but their effect on our understanding of the processes is still unclear. We calibrated five model structures on data from a long-term Swiss field experiment in a Bayesian framework to assess the effect of radiocarbon on the parameter and structural uncertainty of a soil carbon model.
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
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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
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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. C. Clason, C. Coch, J. Jarsjö, K. Brugger, P. Jansson, and G. Rosqvist
Hydrol. Earth Syst. Sci., 19, 2701–2715, https://doi.org/10.5194/hess-19-2701-2015, https://doi.org/10.5194/hess-19-2701-2015, 2015
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
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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.
M. Larsbo, J. Koestel, and N. Jarvis
Hydrol. Earth Syst. Sci., 18, 5255–5269, https://doi.org/10.5194/hess-18-5255-2014, https://doi.org/10.5194/hess-18-5255-2014, 2014
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The characteristics of the macropore network determine the potential for fast transport of solutes through soil. Such characteristics computed from 3-dimensional X-ray tomography images were combined with measured solute breakthrough curves and near-saturated hydraulic conductivities. At a given flow rate, smaller macroporosities, poorer local connectivity of the macropore network and smaller near-saturated hydraulic conductivities resulted in a greater degree of preferential transport.
J. Thorslund, J. Jarsjö, T. Wällstedt, C. M. Mörth, M. Y. Lychagin, and S. R. Chalov
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-9715-2014, https://doi.org/10.5194/hessd-11-9715-2014, 2014
Preprint withdrawn
O. Monga, P. Garnier, V. Pot, E. Coucheney, N. Nunan, W. Otten, and C. Chenu
Biogeosciences, 11, 2201–2209, https://doi.org/10.5194/bg-11-2201-2014, https://doi.org/10.5194/bg-11-2201-2014, 2014
Related subject area
Biogeosciences
Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849
Simulating the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5)
pyVPRM: a next-generation vegetation photosynthesis and respiration model for the post-MODIS era
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Development and assessment of the physical–biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Implementing a process-based representation of soil water movement in a second-generation dynamic vegetation model: application to dryland ecosystems (LPJ-GUESS-RE v1.0)
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
CROMES v1.0: A flexible CROp Model Emulator Suite for climate impact assessment
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Simple Eulerian-Lagrangian approach to solve equations for sinking particulate organic matter in the ocean
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Evaluating the performance of CE-QUAL-W2 version 4.5 sediment diagenesis model
Representing high-latitude deep carbon in the pre-industrial state of the ORCHIDEE-MICT land surface model (r8704)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
A trait-based model to describe plant community dynamics in managed grasslands (GrasslandTraitSim.jl v1.0.0)
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Data-Informed Inversion Model (DIIM): a framework to retrieve marine optical constituents in the BOUSSOLE site using a three-stream irradiance model
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Sunburned plankton: Ultraviolet radiation inhibition of phytoplankton photosynthesis in the Community Earth System Model version 2
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
Geosci. Model Dev., 18, 4915–4933, https://doi.org/10.5194/gmd-18-4915-2025, https://doi.org/10.5194/gmd-18-4915-2025, 2025
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This study enhances the accuracy of modeling the carbon dynamics of the Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to use in refining global carbon cycle models.
Benjamin F. Meyer, João P. Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
Geosci. Model Dev., 18, 4643–4666, https://doi.org/10.5194/gmd-18-4643-2025, https://doi.org/10.5194/gmd-18-4643-2025, 2025
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Climate change has increased the likelihood of drought events across Europe, potentially threatening the European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show its ability to capture species-specific evapotranspiration responses to drought and to reproduce flux observations of both gross primary production and evapotranspiration.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Carolina Natel, David Martín Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
Geosci. Model Dev., 18, 4317–4333, https://doi.org/10.5194/gmd-18-4317-2025, https://doi.org/10.5194/gmd-18-4317-2025, 2025
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We developed fast machine learning models to predict forest regrowth and carbon dynamics under climate change. These models mimic the outputs of a complex vegetation model but run 95 % faster, enabling global analyses and supporting climate solutions in large modeling frameworks such as LandSyMM.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025, https://doi.org/10.5194/gmd-18-4103-2025, 2025
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This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
Geosci. Model Dev., 18, 3941–3964, https://doi.org/10.5194/gmd-18-3941-2025, https://doi.org/10.5194/gmd-18-3941-2025, 2025
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Physical–biogeochemical ocean global models are required to analyze difficult oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The developed model is an important tool for studying physical–biogeochemical processes.
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025, https://doi.org/10.5194/gmd-18-3857-2025, 2025
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This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025, https://doi.org/10.5194/gmd-18-3241-2025, 2025
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Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
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Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
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We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
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Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
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The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
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Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Wim Verbruggen, David Wårlind, Stéphanie Horion, Félicien Meunier, Hans Verbeeck, and Guy Schurgers
EGUsphere, https://doi.org/10.5194/egusphere-2025-1259, https://doi.org/10.5194/egusphere-2025-1259, 2025
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We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
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Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
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Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Christian Folberth, Artem Baklanov, Nikolay Khabarov, Thomas Oberleitner, Juraj Balkovič, and Rastislav Skalský
EGUsphere, https://doi.org/10.5194/egusphere-2025-862, https://doi.org/10.5194/egusphere-2025-862, 2025
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Global gridded crop models (GGCMs) are important tools in agricultural climate impact assessments but computationally costly. An emergent approach to derive crop productivity estimates similar to those from GGCMs are emulators that mimic the original model, but typically with considerable bias. Here we present a modelling package that trains emulators with very high accuracy and high computational gain, providing a basis for more comprehensive scenario assessments.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
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We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Vladimir Maderich, Igor Brovchenko, Kateryna Kovalets, Seongbong Seo, and Kyeong Ok Kim
EGUsphere, https://doi.org/10.5194/egusphere-2025-491, https://doi.org/10.5194/egusphere-2025-491, 2025
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We have developed a new simple Eulerian-Lagrangian approach to solve equations for sinking particulate organic matter in the ocean. We rely on the known parameterizations, but our approach to solving the problem differs, allowing the algorithm to be incorporated into biogeochemical global ocean models with relative ease. New analytical and numerical solutions confirmed that feedback between degradation rate and sinking velocity significantly changes particulate matter fluxes.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Manuel Almeida and Pedro Coelho
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-202, https://doi.org/10.5194/gmd-2024-202, 2025
Revised manuscript accepted for GMD
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This study aims to assess the capabilities of the advanced CE-QUAL-W2 v4.5 sediment diagenesis model, focusing on its application to a reservoir in Portugal over a six-year period (2016–2021). Our findings indicate that the model performs very well in simulating dissolved oxygen profiles, nutrient concentrations, and organic matter levels.
Yi Xi, Philippe Ciais, Dan Zhu, Chunjing Qiu, Yuan Zhang, Shushi Peng, Gustaf Hugelius, Simon P. K. Bowring, Daniel S. Goll, and Ying-Ping Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-206, https://doi.org/10.5194/gmd-2024-206, 2025
Revised manuscript accepted for GMD
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Including high-latitude deep carbon is critical for projecting future soil carbon emissions, yet it’s absent in most land surface models. Here we propose a new carbon accumulation protocol by integrating deep carbon from Yedoma deposits and representing the observed history of peat carbon formation in ORCHIDEE-MICT. Our results show an additional 157 PgC in present-day Yedoma deposits and a 1–5 m shallower peat depth, 43 % less passive soil carbon in peatlands against the convention protocol.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
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The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Felix Nößler, Thibault Moulin, Oksana Buzhdygan, Britta Tietjen, and Felix May
EGUsphere, https://doi.org/10.5194/egusphere-2024-3798, https://doi.org/10.5194/egusphere-2024-3798, 2024
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To predict the response of grassland plant communities to management and climate change, we developed the computer model GrasslandTraitSim.jl. Unlike other models, it uses measurable plant traits such as height, leaf thinness, and root structure as inputs, rather than hard-to-measure species data. This allows realistic simulation of many species. The model tracks daily changes in above- and below-ground biomass, plant height, and soil water, linking plant community composition to biomass supply.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
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In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
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The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Carlos Enmanuel Soto López, Fabio Anselmi, Mirna Gharbi Dit Kacem, and Paolo Lazzari
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-174, https://doi.org/10.5194/gmd-2024-174, 2024
Revised manuscript accepted for GMD
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Our goal was to use an analytical expression to estimate the density of optical constituents, allowing us to have an interpretable formulation consistent with the laws of physics. We focused on a probabilistic approach, optimizing the model and retrieving quantities with their respective uncertainty. Considering future application to Big Data, we also explored a Neural Network based method, retrieving computationally efficient estimates, maintaining consistency with the analytical expression.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, Tumelo C. Moalusi, N. Precious Mongwe, and Pedro M. S. Monteiro
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-182, https://doi.org/10.5194/gmd-2024-182, 2024
Revised manuscript accepted for GMD
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Mesoscale features (10's to 100's of km) in the Southern Ocean (SO) are crucial for global heat and carbon transport, but often unresolved in models due to high computational costs. To address this source of uncertainty, we use a regional, NEMO model of the SO at 8 km resolution with coupled ocean, ice, and biogeochemistry, BIOPERIANT12. This serves as an experimental platform to explore physical-biogeochemical interactions, model parameters/formulations, and configuring future models.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
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Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
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We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-94, https://doi.org/10.5194/gmd-2024-94, 2024
Revised manuscript accepted for GMD
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We develop a new feature in the atmosphere and ocean components of the Community Earth System Model version 2. We have implemented ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation. The new feature will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
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The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
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This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Cited articles
Abramoff, R., Xu, X., Hartman, M., O’Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., and Mayes, M. A.: The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century, Biogeochemistry, 137, 51–71, https://doi.org/10.1007/s10533-017-0409-7, 2018. a
Albertson, J. D. and Montaldo, N.: Temporal dynamics of soil moisture
variability: 1. Theoretical basis, Water Resour. Res., 39, 1–14,
https://doi.org/10.1029/2002WR001616, 2003. a
Aleklett, K., Kiers, E. T., Ohlsson, P., Shimizu, T. S., Caldas, V. E., and
Hammer, E. C.: Build Your Own Soil: Exploring Microfluidics to Create
Microbial Habitat Structures, ISME J., 12, 312–319,
https://doi.org/10.1038/ismej.2017.184, 2018. a
Allison, S. D.: Cheaters, diffusion and nutrients constrain decomposition by
microbial enzymes in spatially structured environments, Ecol. Lett., 8,
626–635, https://doi.org/10.1111/j.1461-0248.2005.00756.x, 2005. a
Allison, S. D.: A trait-based approach for modelling microbial litter
decomposition, Ecol. Lett., 15, 1058–1070, https://doi.org/10.1111/j.1461-0248.2012.01807.x, 2012. a
Barraquand, F. and Murrell, D. J.: Scaling up predator-prey dynamics using
spatial moment equations, Meth. Ecol. Evol., 4, 276–289,
https://doi.org/10.1111/2041-210X.12014, 2013. a, b
Bergström, U., Englund, G., and Leonardsson, K.: Plugging space into
predator-prey models: an empirical approach., Am. Nat., 167,
246–259, https://doi.org/10.1086/499372, 2006. a, b, c
Bouckaert, L., Sleutel, S., Van Loo, D., Brabant, L., Cnudde, V.,
Van Hoorebeke, L., and De Neve, S.: Carbon mineralisation and pore size
classes in undisturbed soil cores, Soil Res., 51, 14–22,
https://doi.org/10.1071/SR12116, 2013. a
Chakrawal, A.: Dynamic upscaling of decomposition kinetics for carbon cycling
models: Heterogeneous_SOMDynamics-v2.0, https://doi.org/10.5281/zenodo.3576613, 2019. a
Chesson, P.: Making sense of spatial models in ecology, Modeling
spatiotemporal dynamics in ecology, Landes Bioscience Austin, Texas, USA, 151–166, 1998. a
Dagan, G.: Theory of solute transport by groundwater, Annu. Rev. Fluid Mech., 19, 183–213,
https://doi.org/10.1146/annurev.fl.19.010187.001151, 1987. a
Dentz, M., Le Borgne, T., Englert, A., and Bijeljic, B.: Mixing, spreading and
reaction in heterogeneous media: A brief review, J. Contam.
Hydrol., 120–121, 1–17, https://doi.org/10.1016/j.jconhyd.2010.05.002, 2011. a, b
Dungait, J. A., Hopkins, D. W., Gregory, A. S., and Whitmore, A. P.: Soil
organic matter turnover is governed by accessibility not recalcitrance,
Glob. Change Biol., 18, 1781–1796,
https://doi.org/10.1111/j.1365-2486.2012.02665.x, 2012. a
Ebrahimi, A. and Or, D.: Microbial community dynamics in soil aggregates shape biogeochemical gas fluxes from soil profiles – upscaling an aggregate
biophysical model, Glob. Change Biol., 22, 3141–3156,
https://doi.org/10.1111/gcb.13345, 2016. a
Ebrahimi, A. and Or, D.: On Upscaling of Soil Microbial Processes and Biogeochemical Fluxes From Aggregates to Landscapes, J. Geophys. Res.-Biogeo., 123, 1526–1547, https://doi.org/10.1029/2017JG004347, 2018. a
Ekschmitt, K., Kandeler, E., Poll, C., Brune, A., Buscot, F., Friedrich, M.,
Gleixner, G., Hartmann, A., Kästner, M., Marhan, S., Miltner, A.,
Scheu, S., and Wolters, V.: Soil-carbon preservation through habitat
constraints and biological limitations on decomposer activity, J. Plant Nutr. Soil Sc., 171, 27–35, https://doi.org/10.1002/jpln.200700051, 2008. a
Englund, G. and Leonardsson, K.: Scaling up the functional response for
spatially heterogeneous systems, Ecol. Lett., 11, 440–449,
https://doi.org/10.1111/j.1461-0248.2008.01159.x, 2008. a
Falconer, R. E., Battaia, G., Schmidt, S., Baveye, P., Chenu, C., and Otten,
W.: Microscale Heterogeneity Explains Experimental Variability and
Non-Linearity in Soil Organic Matter Mineralisation, PLOS ONE, 10,
e0123774, https://doi.org/10.1371/journal.pone.0123774, 2015. a, b
Fatichi, S., Katul, G. G., Ivanov, V. Y., Pappas, C., Paschalis, A., Consolo,
A., Kim, J., and Burlando, P.: Abiotic and biotic controls of soil moisture
spatiotemporal variability and the occurrence of hysteresis, Water Resour.
Res., 51, 3505–3524, https://doi.org/10.1002/2014WR016102, 2015. a
Forney, D. C. and Rothman, D. H.: Common structure in the heterogeneity of
plant-matter decay, J. R. Soc. Interface, 9, 2255–2267,
https://doi.org/10.1098/rsif.2012.0122, 2012. a, b
Fraser, F. C., Todman, L. C., Corstanje, R., Deeks, L. K., Harris, J. A.,
Pawlett, M., Whitmore, A. P., and Ritz, K.: Distinct respiratory responses
of soils to complex organic substrate are governed predominantly by soil
architecture and its microbial community, Soil Biol. Biochem.
103, 493–501, https://doi.org/10.1016/j.soilbio.2016.09.015, 2016. a
Georgiou, K., Abramoff, R. Z., Harte, J., Riley, W. J., and Torn, M. S.:
Microbial community-level regulation explains soil carbon responses to
long-term litter manipulations, Nat. Commun., 8, 1–10,
https://doi.org/10.1038/s41467-017-01116-z, 2017. a
German, D. P., Marcelo, K. R. B., Stone, M. M., and Allison, S. D.: The
Michaelis-Menten kinetics of soil extracellular enzymes in response to
temperature: A cross-latitudinal study, Glob. Change Biol., 18,
1468–1479, https://doi.org/10.1111/j.1365-2486.2011.02615.x, 2012. a
Ginovart, M. and Valls, J.: Individual Based Modelling of Microbial Activity
to Study Mineralization and Nitrification Process in Soil, AICME II
abstracts, 6, 773–795, https://doi.org/10.1016/j.nonrwa.2004.12.005, 1996. a
Herbst, M., Tappe, W., Kummer, S., and Vereecken, H.: The impact of sieving on heterotrophic respiration response to water content in loamy and sandy
topsoils, Geoderma, 272, 73–82, https://doi.org/10.1016/j.geoderma.2016.03.002, 2016. a, b
Hunt, A. G. and Manzoni, S.: Networks on Networks, 2053–2571, Morgan & Claypool Publishers, 175 pp., https://doi.org/10.1088/978-1-6817-4159-8, 2015. a
Jenkinson, D. and Rayner, J.: The turnover of soil organic matter in some of
the Rothamsted classical experiments, Soil Sci., 123, 298–305, 1977. a
Jenny, H., Gessel, S., and Bingham, F.: Comparative study of decomposition
rates of organic matter in temperate and tropical regions, Soil Sci., 68,
419–432, 1949. a
Juarez, S., Nunan, N., Duday, A. C., Pouteau, V., Schmidt, S., Hapca, S.,
Falconer, R., Otten, W., and Chenu, C.: Effects of different soil structures
on the decomposition of native andadded organic carbon, Eur. J.
Soil Biol., 58, 81–90, https://doi.org/10.1016/j.ejsobi.2013.06.005, 2013. a, b
Kaiser, C., Franklin, O., Dieckmann, U., and Richter, A.: Microbial community
dynamics alleviate stoichiometric constraints during litter decay, Ecol.
Lett., 17, 680–690, https://doi.org/10.1111/ele.12269, 2014. a, b
Keeling, M. J. J., Wilson, H. B. B., and Pacala, S. W. W.: Deterministic
Limits to Stochastic Spatial Models of Natural Enemies, Am.
Nat., 159, 57–80, https://doi.org/10.1086/324119, 2002. a
Keiluweit, M., Wanzek, T., Kleber, M., Nico, P., and Fendorf, S.: Anaerobic microsites have an unaccounted role in soil carbon stabilization, Nat. Commun., 8, 1771, https://doi.org/10.1038/s41467-017-01406-6, 2017. a
Killham, K., Amato, M., and Ladd, J. N.: Effect of substrate location in soil and soil pore-water regime on carbon turnover, Soil Biol.
Biochem., 25, 57–62, https://doi.org/10.1016/0038-0717(93)90241-3, 1993. a, b
Koestel, J. and Schlüter, S.: Quantification of the structure evolution in a
garden soil over the course of two years, Geoderma, 338, 597–609,
https://doi.org/10.1016/j.geoderma.2018.12.030, 2019. a
Kravchenko, A. N. and Guber, A. K.: Soil pores and their contributions to soil carbon processes, Geoderma, 287, 31–39,
https://doi.org/10.1016/j.geoderma.2016.06.027, 2017. a, b
Kuzyakov, Y. and Blagodatskaya, E.: Microbial hotspots and hot moments in soil: concept & review, Soil Biol. Biochem., 83, 184–199,
https://doi.org/10.1016/j.soilbio.2015.01.025, 2015. a
Lennon, J. J.: Red-shifts and red herrings in geographical ecology, Ecography, 23, 101–113, https://doi.org/10.1111/j.1600-0587.2000.tb00265.x, 2000. a
Lugo-Méndez, H. D., Valdés-Parada, F. J., Porter, M. L., Wood,
B. D., and Ochoa-Tapia, J. A.: Upscaling Diffusion and Nonlinear Reactive
Mass Transport in Homogeneous Porous Media, Transport Porous Med., 107,
683–716, https://doi.org/10.1007/s11242-015-0462-4, 2015. a
Manzoni, S. and Katul, G.: Invariant soil water potential at zero microbial
respiration explained by hydrological discontinuity in dry soils,
Geophys. Res. Lett., 41, 7151–7158, https://doi.org/10.1002/2014GL061467,
2014. a
Manzoni, S. and Porporato, A.: A theoretical analysis of nonlinearities and
feedbacks in soil carbon and nitrogen cycles, Soil Biol. Biochem.,
39, 1542–1556, https://doi.org/10.1016/j.soilbio.2007.01.006, 2007. a, b, c
Manzoni, S. and Porporato, A.: Soil carbon and nitrogen mineralization: Theory
and models across scales, Soil Biol. Biochem., 41, 1355–1379,
https://doi.org/10.1016/j.soilbio.2009.02.031, 2009. a, b, c, d
Manzoni, S., Porporato, A., and Schimel, J. P.: Soil heterogeneity in lumped
mineralization–immobilization models, Soil Biol. Biochem., 40,
1137–1148, https://doi.org/10.1016/j.soilbio.2007.12.006, 2008. a, b
Manzoni, S., Piñeiro, G., Jackson, R. B., Jobbágy, E. G., Kim,
J. H., and Porporato, A.: Analytical models of soil and litter
decomposition: Solutions for mass loss and time-dependent decay rates, Soil Biol. Biochem., 50, 66–76, https://doi.org/10.1016/j.soilbio.2012.02.029,
2012. a
Melbourne, B. A. and Chesson, P.: The scale transition: Scaling up population dynamics with field data, Ecology, 87, 1478–1488,
https://doi.org/10.1890/0012-9658(2006)87[1478:TSTSUP]2.0.CO;2, 2006. a
Monga, O., Bousso, M., Garnier, P., and Pot, V.: 3D geometric structures and
biological activity: Application to microbial soil organic matter
decomposition in pore space, Ecol. Model., 216, 291–302,
https://doi.org/10.1016/j.ecolmodel.2008.04.015, 2008. a
Monga, O., Garnier, P., Pot, V., Coucheney, E., Nunan, N., Otten, W., and Chenu, C.: Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion-based model MOSAIC, Biogeosciences, 11, 2201–2209, https://doi.org/10.5194/bg-11-2201-2014, 2014. a
Morozov, A. and Poggiale, J. C.: From spatially explicit ecological models to mean-field dynamics: The state of the art and perspectives, Ecol.
Compl., 10, 1–11, https://doi.org/10.1016/j.ecocom.2012.04.001, 2012. a
Murrell, D. J., Dieckmann, U., and Law, R.: On moment closures for population dynamics in continuous space, J. Theor. Biol. 229, 421–432,
https://doi.org/10.1016/j.jtbi.2004.04.013, 2004. a
Negassa, W. C., Guber, A. K., Kravchenko, A. N., Marsh, T. L., Hildebrandt, B., and Rivers, M. L.: Properties of soil pore space regulate pathways of plant residue decomposition and community structure of associated bacteria, PLoS ONE, 10, 1–22, https://doi.org/10.1371/journal.pone.0123999, 2015. a
Nguyen-Ngoc, D., Leye, B., Monga, O., Garnier, P., and Nunan, N.: Modeling
Microbial Decomposition in Real 3D Soil Structures Using Partial Differential
Equations, Int. J. Geosci., 4, 15–26,
https://doi.org/10.4236/ijg.2013.410A003, 2013. a
Nunan, N., Wu, K., Young, I. M., Crawford, J. W., and Ritz, K.: In situ
spatial patterns of soil bacterial populations, mapped at multiple scales, in
an arable soil, Microb. Ecol. 44, 296–305,
https://doi.org/10.1007/s00248-002-2021-0, 2002. a
Nunan, N., Wu, K., Young, I. M., Crawford, J. W., and Ritz, K.: Spatial
distribution of bacterial communities and their relationships with the
micro-architecture of soil, FEMS Microbiol. Ecol., 44, 203–215,
https://doi.org/10.1016/S0168-6496(03)00027-8, 2003. a
Olson, J. S.: Energy Storage and the Balance of Producers and Decomposers in
Ecological Systems, Ecology, 44, 322–331, https://doi.org/10.2307/1932179, 1963. a
Parton, W., Schimel, D. S., Cole, C., and Ojima, D.: Analysis of factors
controlling soil organic matter levels in Great Plains Grasslands 1, Soil
Sci. Soc. Am. J., 51, 1173–1179, 1987. a
Peth, S., Chenu, C., Leblond, N., Mordhorst, A., Garnier, P., Nunan, N., Pot,
V., Ogurreck, M., and Beckmann, F.: Localization of soil organic matter in
soil aggregates using synchrotron-based X-ray microtomography, Soil Biol. Biochem., 78, 189–194, https://doi.org/10.1016/j.soilbio.2014.07.024, 2014. a
Porter, M. L., Valdés-Parada, F. J., and Wood, B. D.: Multiscale
modeling of chemotaxis in homogeneous porous media, Water Resour.
Res., 47, 1–13, https://doi.org/10.1029/2010WR009646, 2011. a
Rawlins, B. G., Wragg, J., Reinhard, C., Atwood, R. C., Houston, A., Lark, R. M., and Rudolph, S.: Three-dimensional soil organic matter distribution, accessibility and microbial respiration in macroaggregates using osmium staining and synchrotron X-ray computed tomography, SOIL, 2, 659–671, https://doi.org/10.5194/soil-2-659-2016, 2016. a, b
Raynaud, X. and Nunan, N.: Spatial ecology of bacteria at the microscale in
soil, PLoS ONE, 9, e87217, https://doi.org/10.1371/journal.pone.0087217, 2014. a, b
Ruamps, L. S., Nunan, N., and Chenu, C.: Microbial biogeography at the soil
pore scale, Soil Biol. Biochem., 43, 280–286,
https://doi.org/10.1016/J.SOILBIO.2010.10.010, 2011. a, b
Salomé, C., Nunan, N., Pouteau, V., Lerch, T. Z., and Chenu, C.: Carbon dynamics in topsoil and in subsoil may be controlled by different regulatory mechanisms, Glob. Change Biol., 16, 416–426,
https://doi.org/10.1111/j.1365-2486.2009.01884.x, 2010. a
Schimel, J. P. and Weintraub, M. N.: The implications of exoenzyme activity on microbial carbon and nitrogen limitation in soil: A theoretical model, Soil Biol. Biochem., 35, 549–563, https://doi.org/10.1016/S0038-0717(03)00015-4,
2003. a, b, c
Schmidt, M. W., Torn, M. S., Abiven, S., Dittmar, T., Guggenberger, G.,
Janssens, I. A., Kleber, M., Kögel-Knabner, I., Lehmann, J., Manning,
D. A., Nannipieri, P., Rasse, D. P., Weiner, S., and Trumbore, S. E.:
Persistence of soil organic matter as an ecosystem property, Nature, 478, 49–56, https://doi.org/10.1038/nature10386, 2011. a
Schnecker, J., Bowles, T., Hobbie, E. A., Smith, R. G., and Grandy, A. S.:
Substrate quality and concentration control decomposition and microbial
strategies in a model soil system, Biogeochemistry, 144, 47–59, https://doi.org/10.1007/s10533-019-00571-8, 2019. a, b
Sierra, C. A. and Muller, M.: A general mathematical framework for
representing soil organic matter dynamics, Ecol. Monogr. 85,
505–524, https://doi.org/10.1890/15-0361.1, 2015. a, b
Stanley, C. E., Grossmann, G., i Solvas, X. C., and deMello, A. J.:
Soil-on-a-Chip: Microfluidic Platforms for Environmental Organismal
Studies, Lab Chip, 16, 228–241, https://doi.org/10.1039/C5LC01285F, 2016. a
Stenger, R., Barkle, G. F., and Burgess, C. P.: Mineralisation of organic
matter in intact versus sieved/refilled soil cores, Soil Res., 40,
149–160, https://doi.org/10.1071/SR01003, 2002. a
Valdés-Parada, F. J., Porter, M. L., Narayanaswamy, K., Ford, R. M., and Wood, B. D.: Upscaling microbial chemotaxis in porous media, Adv. Water Resour., 32, 1413–1428, https://doi.org/10.1016/j.advwatres.2009.06.010, 2009. a
Van Oijen, M., Cameron, D., Levy, P. E., and Preston, R.: Correcting errors
from spatial upscaling of nonlinear greenhouse gas flux models,
Environ. Model. Softw., 94, 157–165,
https://doi.org/10.1016/j.envsoft.2017.03.023, 2017. a, b, c
Wang, B. and Allison, S. D.: Emergent properties of organic matter
decomposition by soil enzymes, Soil Biol. Biochemistry, 136, 107522,
https://doi.org/10.1016/j.soilbio.2019.107522, 2019. a
Watt, M., Silk, W. K., and Passioura, J. B.: Rates of root and organism growth, soil conditions, and temporal and spatial development of the rhizosphere, Ann. Bot., 97, 839–855, https://doi.org/10.1093/aob/mcl028, 2006. a, b
Whitaker, S.: The Method of Volume Averaging, vol. 13, Theory and
Applications of Transport in Porous Media, Springer Netherlands,
Dordrecht, https://doi.org/10.1007/978-94-017-3389-2, 1999. a
Wieder, W. R., Bonan, G. B., and Allison, S. D.: Global soil carbon projections are improved by modelling microbial processes, Nat. Clim. Change, 3, 909–912,
https://doi.org/10.1038/nclimate1951, 2013. a
Wieder, W. R., Allison, S. D., Davidson, E. A., Georgiou, K., Hararuk, O., He, Y., Hopkins, F., Luo, Y., Smith, M. J., Sulman, B., Todd-Brown, K., Wang,
Y. P., Xia, J., and Xu, X.: Explicitly representing soil microbial processes
in Earth system models, Global Biogeochem. Cy., 29, 1782–1800,
https://doi.org/10.1002/2015GB005188, 2015. a, b
Wieder, W. R., Hartman, M. D., Sulman, B. N., Wang, Y. P., Koven, C. D., and
Bonan, G. B.: Carbon cycle confidence and uncertainty: Exploring variation
among soil biogeochemical models, Glob. Change Biol., 24, 1563–1579,
https://doi.org/10.1111/gcb.13979, 2018. a, b
Witter, E.: Soil C balance in a long-term field experiment in relation to the
size of the microbial biomass, Biol. Fert. Soils, 23, 33–37,
https://doi.org/10.1007/BF00335815, 1996. a
Wutzler, T. and Reichstein, M.: Colimitation of decomposition by substrate and decomposers – a comparison of model formulations, Biogeosciences, 5, 749–759, https://doi.org/10.5194/bg-5-749-2008, 2008. a
Xie, X. S.: Enzyme Kinetics, Past and Present, Science, 342, 1457–1459,
https://doi.org/10.1126/science.1248859, 2013. a
Xu, X., Thornton, P. E., and Post, W. M.: A global analysis of soil microbial
biomass carbon, nitrogen and phosphorus in terrestrial ecosystems, Global
Ecol. Biogeogr., 22, 737–749, 2013. a
Yan, Z., Liu, C., Todd-Brown, K. E., Liu, Y., Bond-Lamberty, B., and Bailey,
V. L.: Pore-scale investigation on the response of heterotrophic respiration
to moisture conditions in heterogeneous soils, Biogeochemistry, 131,
121–134, https://doi.org/10.1007/s10533-016-0270-0, 2016. a
Zelenev, V., Bruggen, A. V., and Semenov, A.: BACWAVE, a Spatial–Temporal
Model for Traveling Waves of Bacterial Populations in Response to a Moving
Carbon Source in Soil, Microb. ecol., 40, 260–272,
https://doi.org/10.1007/s002480000029, 2000. a, b
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.
Soils are heterogeneous, which results in a nonuniform spatial distribution of substrates and...
