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.
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
Related authors
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
Short summary
Short summary
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.
Xiankun Li, Marleen Pallandt, Dilip Naidu, Johannes Rousk, Gustaf Hugelius, and Stefano Manzoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3324, https://doi.org/10.5194/egusphere-2024-3324, 2024
Short summary
Short summary
While laboratory studies have identified many drivers and their effects on the carbon emission pulse after rewetting of dry soils, a validation with field data is still missing. Here, we show that the carbon emission pulse in the laboratory and in the field increases with soil organic carbon and temperature, but their trends with pre-rewetting dryness and moisture increment at rewetting differ. We conclude that the laboratory findings can be partially validated.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, Qinuo Zhang, Xuejun Yi, Haijun Wang, Wei Liu, Wei Gao, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-324, https://doi.org/10.5194/hess-2024-324, 2024
Preprint under review for HESS
Short summary
Short summary
The hydrology of cold regions in the human population is poorly understood due to complex motion and limited data, hindering streamflow analysis. Using existing models, we compared runoff from an extended model with snowmelt and frozen ground, validating its reliability and integration. This study focuses on the effects of snowmelt and frozen ground on runoff, affecting precipitation type, surface-groundwater partitioning, and evapotranspiration.
Daniel Escobar, Stefano Manzoni, Jeimar Tapasco, and Salim Belyazid
EGUsphere, https://doi.org/10.5194/egusphere-2024-2754, https://doi.org/10.5194/egusphere-2024-2754, 2024
Short summary
Short summary
We studied carbon dynamics in afforested, drained peatlands using the ForSAFE-Peat model over two forest rotations. Our simulations showed that while trees store carbon, significant soil carbon losses occur, particularly early on, indicating that forest growth may not fully offset these losses once carbon time dynamics are considered. This emphasizes the need to consider both soil and harvested wood products when evaluating the climate impact of such systems.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
Short summary
Short summary
Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
Short summary
Short summary
The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Martin Thurner, Kailiang Yu, Stefano Manzoni, Anatoly Prokushkin, Melanie A. Thurner, Zhiqiang Wang, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1794, https://doi.org/10.5194/egusphere-2024-1794, 2024
Short summary
Short summary
Nitrogen concentrations in tree tissues (leaves, branches, stems, and roots) control photosynthesis, growth and respiration, and thus influence vegetation carbon uptake. Our novel database allows us to identify the controls of tree tissue nitrogen concentrations in boreal and temperate forests, such as tree age/size, species and climate. Changes therein will affect tissue N concentrations and thus also vegetation carbon uptake.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
Short summary
Short summary
Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
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
Short summary
Short summary
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.
Maria Regina Gmach, Martin Anders Bolinder, Lorenzo Menichetti, Thomas Kätterer, Heide Spiegel, Olle Åkesson, Jürgen Kurt Friedel, Andreas Surböck, Agnes Schweinzer, and Taru Sandén
SOIL, 10, 407–423, https://doi.org/10.5194/soil-10-407-2024, https://doi.org/10.5194/soil-10-407-2024, 2024
Short summary
Short summary
We evaluated the effect of soil management practices on decomposition at 29 sites (13 in Sweden and 16 in Austria) using long-term field experiments with the Tea Bag Index (TBI) approach. We found that the decomposition rate (k) and stabilization factor (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.
Gina Garland, John Koestel, Alice Johannes, Olivier Heller, Sebastian Doetterl, Dani Or, and Thomas Keller
SOIL, 10, 23–31, https://doi.org/10.5194/soil-10-23-2024, https://doi.org/10.5194/soil-10-23-2024, 2024
Short summary
Short summary
The concept of soil aggregates is hotly debated, leading to confusion about their function or relevancy to soil processes. We propose that the use of conceptual figures showing detached and isolated aggregates can be misleading and has contributed to this skepticism. Here, we conceptually illustrate how aggregates can form and dissipate within the context of undisturbed soils, highlighting the fact that aggregates do not necessarily need to have distinct physical boundaries.
Daniela Guasconi, Sara Cousins, Stefano Manzoni, Nina Roth, and Gustaf Hugelius
EGUsphere, https://doi.org/10.5194/egusphere-2023-2673, https://doi.org/10.5194/egusphere-2023-2673, 2023
Short summary
Short summary
This study assesses the effects of experimental drought and of a soil amendment on soil and vegetation carbon pools, at different soil depths. Drought consistently reduced soil moisture and aboveground biomass, while compost increased total soil carbon content and aboveground biomass, and effects were more pronounced in the topsoil. Root biomass was not significantly affected by the treatments. The contrasting response of roots and shoots improves our understanding of ecosystem carbon dynamics.
Guillaume Blanchy, Lukas Albrecht, Gilberto Bragato, Sarah Garré, Nicholas Jarvis, and John Koestel
Hydrol. Earth Syst. Sci., 27, 2703–2724, https://doi.org/10.5194/hess-27-2703-2023, https://doi.org/10.5194/hess-27-2703-2023, 2023
Short summary
Short summary
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
SOIL, 9, 155–168, https://doi.org/10.5194/soil-9-155-2023, https://doi.org/10.5194/soil-9-155-2023, 2023
Short summary
Short summary
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.
Stefano Manzoni, Simone Fatichi, Xue Feng, Gabriel G. Katul, Danielle Way, and Giulia Vico
Biogeosciences, 19, 4387–4414, https://doi.org/10.5194/bg-19-4387-2022, https://doi.org/10.5194/bg-19-4387-2022, 2022
Short summary
Short summary
Increasing atmospheric carbon dioxide (CO2) causes leaves to close their stomata (through which water evaporates) but also promotes leaf growth. Even if individual leaves save water, how much will be consumed by a whole plant with possibly more leaves? Using different mathematical models, we show that plant stands that are not very dense and can grow more leaves will benefit from higher CO2 by photosynthesizing more while adjusting their stomata to consume similar amounts of water.
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.
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.
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
Short summary
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.
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.
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
Preprint withdrawn
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Earth Syst. Sci. Data, 12, 1083–1100, https://doi.org/10.5194/essd-12-1083-2020, https://doi.org/10.5194/essd-12-1083-2020, 2020
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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. 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
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.
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
Short summary
Short summary
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
Related subject area
Biogeosciences
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
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
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
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
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Lambda-PFLOTRAN 1.0: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
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
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
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)
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
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)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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 and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie Fisher, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2024-978, https://doi.org/10.5194/egusphere-2024-978, 2024
Short summary
Short summary
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 and variability of carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research on 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. Discuss., https://doi.org/10.5194/gmd-2024-34, https://doi.org/10.5194/gmd-2024-34, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The newly developed Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate respiration and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow via a Jupyter Notebook interface, that digests raw organic matter chemistry data via FTICR-MS, develops the representative reaction network, and completes a biogeochemical simulation with the open source, parallel reactive flow and transport code PFLOTRAN.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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 > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
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.
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.
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.
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.
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.
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.
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...