Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-725-2018
© Author(s) 2018. 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-11-725-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
28 Feb 2018
Model description paper |
| 28 Feb 2018
| 28 Feb 2018
Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)
Hongxing He
CORRESPONDING AUTHOR
Department of Earth Sciences, University of Gothenburg, P.O. Box 460,
Gothenburg 40530, Sweden
Astrid Meyer
Department of Earth Sciences, University of Gothenburg, P.O. Box 460,
Gothenburg 40530, Sweden
now at: Institute of Groundwater Ecology, Helmholtz Zentrum
München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany
Per-Erik Jansson
Department of Sustainable Development, Environmental Science and Engineering,
Royal Institute of Technology (KTH), Teknikringen 10B, SE-100 44 Stockholm, Sweden
Magnus Svensson
Department of Sustainable Development, Environmental Science and Engineering,
Royal Institute of Technology (KTH), Teknikringen 10B, SE-100 44 Stockholm, Sweden
Tobias Rütting
Department of Earth Sciences, University of Gothenburg, P.O. Box 460,
Gothenburg 40530, Sweden
Leif Klemedtsson
Department of Earth Sciences, University of Gothenburg, P.O. Box 460,
Gothenburg 40530, Sweden
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2179, https://doi.org/10.5194/egusphere-2025-2179, 2025
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This study explores how different types of fungi and plant species affect nitrogen cycling in Arctic soils. By removing certain plants, we found that fungi associated with shrubs speed up nitrogen processes more than those with grasses. Dominant plant species enhance nitrogen recycling, while rare species increase nitrogen loss. These findings help predict how Arctic ecosystems respond to climate change, highlighting the importance of fungi and plant diversity in regulating ecosystem processes.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
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In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Janne Rinne, Patryk Łakomiec, Patrik Vestin, Joel D. White, Per Weslien, Julia Kelly, Natascha Kljun, Lena Ström, and Leif Klemedtsson
Biogeosciences, 19, 4331–4349, https://doi.org/10.5194/bg-19-4331-2022, https://doi.org/10.5194/bg-19-4331-2022, 2022
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The study uses the stable isotope 13C of carbon in methane to investigate the origins of spatial and temporal variation in methane emitted by a temperate wetland ecosystem. The results indicate that methane production is more important for spatial variation than methane consumption by micro-organisms. Temporal variation on a seasonal timescale is most likely affected by more than one driver simultaneously.
Anders Lindroth, Norbert Pirk, Ingibjörg S. Jónsdóttir, Christian Stiegler, Leif Klemedtsson, and Mats B. Nilsson
Biogeosciences, 19, 3921–3934, https://doi.org/10.5194/bg-19-3921-2022, https://doi.org/10.5194/bg-19-3921-2022, 2022
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We measured the fluxes of carbon dioxide and methane between a moist moss tundra and the atmosphere on Svalbard in order to better understand how such ecosystems are affecting the climate and vice versa. We found that the system was a small sink of carbon dioxide and a small source of methane. These fluxes are small in comparison with other tundra ecosystems in the high Arctic. Analysis of temperature sensitivity showed that respiration was more sensitive than photosynthesis above about 6 ℃.
Jenie Gil, Maija E. Marushchak, Tobias Rütting, Elizabeth M. Baggs, Tibisay Pérez, Alexander Novakovskiy, Tatiana Trubnikova, Dmitry Kaverin, Pertti J. Martikainen, and Christina Biasi
Biogeosciences, 19, 2683–2698, https://doi.org/10.5194/bg-19-2683-2022, https://doi.org/10.5194/bg-19-2683-2022, 2022
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N2O emissions from permafrost soils represent up to 11.6 % of total N2O emissions from natural soils, and their contribution to the global N2O budget will likely increase due to climate change. A better understanding of N2O production from permafrost soil is needed to evaluate the role of arctic ecosystems in the global N2O budget. By studying microbial N2O production processes in N2O hotspots in permafrost peatlands, we identified denitrification as the dominant source of N2O in these surfaces.
Adrian Wicki, Per-Erik Jansson, Peter Lehmann, Christian Hauck, and Manfred Stähli
Hydrol. Earth Syst. Sci., 25, 4585–4610, https://doi.org/10.5194/hess-25-4585-2021, https://doi.org/10.5194/hess-25-4585-2021, 2021
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Soil moisture information was shown to be valuable for landslide prediction. Soil moisture was simulated at 133 sites in Switzerland, and the temporal variability was compared to the regional occurrence of landslides. We found that simulated soil moisture is a good predictor for landslides, and that the forecast goodness is similar to using in situ measurements. This encourages the use of models for complementing existing soil moisture monitoring networks for regional landslide early warning.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Hongxing He, Per-Erik Jansson, and Annemieke I. Gärdenäs
Geosci. Model Dev., 14, 735–761, https://doi.org/10.5194/gmd-14-735-2021, https://doi.org/10.5194/gmd-14-735-2021, 2021
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This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, Coup-CNP). The extended Coup-CNP, which explicitly considers the symbiosis between soil microbes and plant roots, enables simulations of coupled C, N, and P dynamics for terrestrial ecosystems. Simulations from the new Coup-CNP model provide strong evidence that P fluxes need to be further considered in studies of how ecosystems and C turnover react to climate change.
Mousong Wu, Per-Erik Jansson, Jingwei Wu, Xiao Tan, Kang Wang, Peng Chen, and Jiesheng Huang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-466, https://doi.org/10.5194/hess-2018-466, 2018
Revised manuscript not accepted
Wenxin Zhang, Per-Erik Jansson, and Bo Elberling
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-382, https://doi.org/10.5194/bg-2017-382, 2017
Manuscript not accepted for further review
Christine Metzger, Mats B. Nilsson, Matthias Peichl, and Per-Erik Jansson
Geosci. Model Dev., 9, 4313–4338, https://doi.org/10.5194/gmd-9-4313-2016, https://doi.org/10.5194/gmd-9-4313-2016, 2016
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Many interactions between various abiotic and biotic processes and their parameters were identified by global sensitivity analysis, revealing strong dependence of a certain model output (e.g. CO2 or heat fluxes, leaf area index, radiation, water table, soil temperature or snow depth) to model set-up and parameterization in many different processes, a limited transferability of parameter values between models, and the importance of ancillary measurements for improving models and thus predictions.
Mousong Wu, Per-Erik Jansson, Xiao Tan, Jiesheng Huang, and Jingwei Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-507, https://doi.org/10.5194/hess-2016-507, 2016
Revised manuscript not accepted
Louise C. Andresen, Anna-Karin Björsne, Samuel Bodé, Leif Klemedtsson, Pascal Boeckx, and Tobias Rütting
SOIL, 2, 433–442, https://doi.org/10.5194/soil-2-433-2016, https://doi.org/10.5194/soil-2-433-2016, 2016
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In soil the constant transport of nitrogen (N) containing compounds from soil organic matter and debris out into the soil water, is controlled by soil microbes and enzymes that literally cut down polymers (such as proteins) into single amino acids (AA), hereafter microbes consume AAs and excrete ammonium back to the soil. We developed a method for analysing N turnover and flow of organic N, based on parallel 15N tracing experiments. The numerical model gives robust and simultaneous quantification.
Hongxing He, Per-Erik Jansson, Magnus Svensson, Jesper Björklund, Lasse Tarvainen, Leif Klemedtsson, and Åsa Kasimir
Biogeosciences, 13, 2305–2318, https://doi.org/10.5194/bg-13-2305-2016, https://doi.org/10.5194/bg-13-2305-2016, 2016
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We simulate CO2 and N2O dynamics over a full forest rotation on drained agricultural peatland, using CoupModel. Data used for validation include tree ring-derived biomass data (1966–2011) and measured abiotic and soil emission data (2006–2011). The results show that the C fixed in forest biomass is slightly larger than the soil losses over the full rotation period. However when including N2O and indirect emissions from forest thinning products, the forest system switches to a large GHG source.
C. Metzger, P.-E. Jansson, A. Lohila, M. Aurela, T. Eickenscheidt, L. Belelli-Marchesini, K. J. Dinsmore, J. Drewer, J. van Huissteden, and M. Drösler
Biogeosciences, 12, 125–146, https://doi.org/10.5194/bg-12-125-2015, https://doi.org/10.5194/bg-12-125-2015, 2015
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To identify site specific differences in CO2-related processes in open peatlands, we calibrated a process oriented model to fit to detailed measurements of carbon fluxes and compared the resulting parameter ranges between the sites. For most processes a common configuration could be applied. Site specific differences were identified for soil respiration coefficients, plant radiation-use efficiencies and plant storage fractions for spring regrowth.
A. Meyer, L. Tarvainen, A. Nousratpour, R. G. Björk, M. Ernfors, A. Grelle, Å Kasimir Klemedtsson, A. Lindroth, M. Räntfors, T. Rütting, G. Wallin, P. Weslien, and L. Klemedtsson
Biogeosciences, 10, 7739–7758, https://doi.org/10.5194/bg-10-7739-2013, https://doi.org/10.5194/bg-10-7739-2013, 2013
S. H. Wu and P.-E. Jansson
Hydrol. Earth Syst. Sci., 17, 735–749, https://doi.org/10.5194/hess-17-735-2013, https://doi.org/10.5194/hess-17-735-2013, 2013
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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.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
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This study enhances the accuracy of modeling the carbon dynamics of 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 refine global carbon cycle models.
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.
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.
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.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 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.
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.
Benjamin Franklin Meyer, João Paulo 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-3352, https://doi.org/10.5194/egusphere-2024-3352, 2024
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Climate change has increased the likelihood of drought events across Europe, potentially threatening 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 it's capability at capturing species-specific evapotranspiration responses to drought and reproducing flux observations of both gross primary production and evapotranspiration.
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.
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
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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
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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.
Cited articles
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Short summary
Ectomycorrhizal fungi (ECM) have shown a major impact on forest C and N cycles, but are currently neglected in most ecosystem models. We thus implemented the previously developed ectomycorrhizal fungi model, MYCOFON, into a well-established ecosystem model, CoupModel. This paper describes the key components and features of Coup-MYCOFON. The new version of CoupModel can now simulate C and N fluxes and pools, explicitly accounting for links and feedbacks among plant, soil, and ECM.
Ectomycorrhizal fungi (ECM) have shown a major impact on forest C and N cycles, but are...
