Articles | Volume 17, issue 10
https://doi.org/10.5194/gmd-17-4515-2024
© Author(s) 2024. 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-17-4515-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
31 May 2024
Model description paper |
| 31 May 2024
| 31 May 2024
In silico calculation of soil pH by SCEPTER v1.0
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
Isabella Chiaravalloti
Department of Earth and Planetary Sciences, Yale University, New Haven, CT 06511, USA
Yale Center for Natural Carbon Capture (YCNCC), Yale University, New Haven, CT 06511, USA
Shuang Zhang
Department of Oceanography, Texas A&M University, College Station, TX 77843, USA
Noah J. Planavsky
Department of Earth and Planetary Sciences, Yale University, New Haven, CT 06511, USA
Yale Center for Natural Carbon Capture (YCNCC), Yale University, New Haven, CT 06511, USA
Christopher T. Reinhard
CORRESPONDING AUTHOR
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
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Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
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Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
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Geosci. Model Dev., 14, 5999–6023, https://doi.org/10.5194/gmd-14-5999-2021, https://doi.org/10.5194/gmd-14-5999-2021, 2021
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Biogeochemical interactions between iron and sulfur are central to the long-term biogeochemical evolution of Earth’s oceans. Here, we introduce an iron–sulphur cycle in a model of Earth's oceans. Our analyses show that the results of the model are robust towards parameter choices and that simulated concentrations and reactions are comparable to those observed in ancient ocean analogues (anoxic lakes). Our model represents an important step forward in the study of iron–sulfur cycling.
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Yoshiki Kanzaki
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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.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošeľa, Doroteja Bitunjac, Masa Zorana Ostrogovic Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-45, https://doi.org/10.5194/gmd-2024-45, 2024
Revised manuscript accepted for GMD
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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 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.
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
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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
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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
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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
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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
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-42, https://doi.org/10.5194/gmd-2024-42, 2024
Revised manuscript accepted for GMD
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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.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2024-464, https://doi.org/10.5194/egusphere-2024-464, 2024
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Our study employs Long Short-Term Memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. 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 unlocking the secrets of vegetation phenology responses to climate change with deep learning techniques.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, and Christoph Müller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2946, https://doi.org/10.5194/egusphere-2023-2946, 2024
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We present a new approach to model 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, the nitrogen (N) deficit and carbon (C) costs. The new approach improved global sums and spatial patterns of BNF compared to the scientific literature and the models’ ability to project future C and N cycle dynamics.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
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Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Cited articles
Alva, A. K., Sumner, M. E., and Miller, W. P.: Relationship between ionic strength and electrical conductivity for soil solutions, Soil Sci., 152, 239–242, https://doi.org/10.1097/00010694-199110000-00001, 1991.
Appelo, C. A. J.: Cation and proton exchange, pH variations, and carbonate reactions in a freshening aquifer, Water Resour. Res., 30, 2793–2805, https://doi.org/10.1029/94WR01048, 1994.
Aradóttir, E. S. P., Sonnenthal, E. L., and Jónsson, H.: Development and evaluation of a thermodynamic dataset for phases of interest in CO2 mineral sequestration in basaltic rocks, Chem. Geol., 304, 26–38, https://doi.org/10.1016/j.chemgeo.2012.01.031, 2012.
Beerling, D. J., Kantzas, E. P., Lomas, M. R., Wade, P., Eufrasio, R. M., Renforth, P., Sarkar, B., Andrews, M. G., James, R. H., Pearce, C. R., Mercure, J.-F., Pollitt, H., Holden, P. B., Edwards, N. R., Khanna, M., Koh, L., Quegan, S., Pidgeon, N. F., Janssens, I. A., Hansen, J., and Banwart, S. A.: Potential for large-scale CO2 removal via enhanced rock weathering with croplands, Nature, 583, 242–248, https://doi.org/10.1038/s41586-020-2448-9, 2020.
Brantley, S. L., Kubicki, J. D., and White, A. F.: Kinetics of Water-Rock Interaction, Springer, ISBN 978-0-387-73562-7, 2008.
Chiaravalloti, I., Theunissen, N., Zhang, S., Wang, J., Sun, F., Ahmed, A. A., Pihlap, E., Reinhard, C. T., and Planavsky, N. J.: Mitigation of soil nitrous oxide emissions during maize production with basalt amendments, Front. Clim., 5, 1203043, https://doi.org/10.3389/fclim.2023.1203043, 2023.
Dietzen, C. and Rosing, M. T.: Quantification of CO2 uptake by enhanced weathering of silicate minerals applied to acidic soils, Int. J. Greenhouse Gas Contr., 125, 103872, https://doi.org/10.1016/j.ijggc.2023.103872, 2023.
Fernández, F. G. and Hoeft, R. G.: Managing soil pH and crop nutrients, in: Illinois Agronomy Handbook, 24, 91–112, 2009.
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1km spatial resolution climate surfaces for global land areas, Int. J. Climatol., 37, 4302–4315, 2017.
Geibe, C. E., Danielsson, R., van Hees, P. A., and Lundström, U. S.: Comparison of soil solution chemistry sampled by centrifugation, two types of suction lysimeters and zero-tension lysimeters, Appl. Geochem., 21, 2096–2111, https://doi.org/10.1016/j.apgeochem.2006.07.010, 2006.
Goldberg, R. N., Kishore, N., and Lennen, R. M.: Thermodynamic quantities for the ionization reactions of buffers, J. Phys. Chem. Ref. Data, 31, 231–370, https://doi.org/10.1063/1.1416902, 2002.
Goll, D. S., Ciais, P., Amann, T., Buermann, W., Chang, J., Eker, S., Hartmann, J., Janssens, I., Li, W., Obersteiner, M., Penuelas, J., Tanaka, K., and Vicca, S: Potential CO2 removal from enhanced weathering by ecosystem responses to powdered rock, Nat. Geosci., 14, 545–549, https://doi.org/10.1038/s41561-021-00798-x, 2021.
Goulding, K. W. T.: Soil acidification and the importance of liming agricultural soils with particular reference to the United Kingdom, Soil Use Manage., 32, 390–399, https://doi.org/10.1111/sum.12270, 2016.
Grybos, M., Davranche, M., Gruau, G., Petitjean, P., and Pédrot, M.: Increasing pH drives organic matter solubilization from wetland soils under reducing conditions, Geoderma, 154, 13–19, https://doi.org/10.1016/j.geoderma.2009.09.001, 2009.
Hamilton, S. K., Kurzman, A. L., Arango, C., Jin, L., and Robertson, G. P.: Evidence for carbon sequestration by agricultural liming, Global Biogeochem. Cycles, 21, GB2021, https://doi.org/10.1029/2006GB002738, 2007.
IPCC: 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC, ISBN 4-88788-032-4, 2006.
IPCC: Global Warming of 1.5 °C, IPCC, https://doi.org/10.1017/9781009157940, 2018.
ISRIC: WISE Soil Property Databases, https://www.isric.org/explore/wise-databases, last access: 19 January 2023, 2022.
Jones Jr, J. B. (Ed.): Soil Analysis Handbook of Reference Methods, CRC press, https://doi.org/10.1201/9780203739433, 1999.
Kantzas, E. P., Val Martin, M., Lomas, M. R., Eufrasio, R. M., Renforth, P., Lewis, A. L., Taylor, L. L., Mecure, J. F., Pollitt, H., Vercoulen, P. V., and Vakilifard, N.: Substantial carbon drawdown potential from enhanced rock weathering in the United Kingdom. Nat. Geosci., 15, 382–389, https://doi.org/10.1038/s41561-022-00925-2, 2022.
Kanzaki, Y.: cdr-laboratory/SCEPTER: v1.0.1 (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.10805268, 2024.
Kanzaki, Y., Zhang, S., Planavsky, N. J., and Reinhard, C. T.: Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9, Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, 2022.
Kanzaki, Y., Planavsky, N. J., and Reinhard, C. T.: New estimates of the storage permanence and ocean co-benefits of enhanced rock weathering, PNAS Nexus, 2, pgad059, https://doi.org/10.1093/pnasnexus/pgad059, 2023.
Kelland, M. E., Wade, P. W., Lewis, A. L., Taylor, L. L., Sarkar, B., Andrews, M. G., Lomas, M. R., Cotton, T. A., Kemp, S. J., James, R. H., and Pearce, C. R.: Increased yield and CO2 sequestration potential with the C4 cereal Sorghum bicolor cultivated in basaltic rock dust-amended agricultural soil, Global Change Biol., 26, 3658–3676, https://doi.org/10.1111/gcb.15089, 2020.
Kissel, D. E. and Sonon, L. S.: Soil Test Handbook for Georgia, University of Georgia College of Agricultural and Environmental Sciences, Athens, GA, 2008.
Kopittke, P. M., Menzies, N. W., Wang, P., McKenna, B. A., and Lombi, E.: Soil and the intensification of agriculture for global food security, Environ. Int., 132, 105078, https://doi.org/10.1016/j.envint.2019.105078, 2019.
Köhler, P., Hartmann, J., and Wolf-Gladrow, D. A.: Geoengineering potential of artificially enhanced silicate weathering of olivine, P. Natl. Acad. Sci. USA, 107, 20228–20233, https://doi.org/10.1073/pnas.1000545107, 2010.
La-Scalea, M. A., Menezes, C. M. S., and Ferreira, E. I.: Molecular volume calculation using AM1 semi-empirical method toward diffusion coefficients and electrophoretic mobility estimates in aqueous solution, J. Mol. Struct.-THEOCHEM, 730, 111–120, https://doi.org/10.1016/j.theochem.2005.05.030, 2005.
Li, Y.-H. and Gregory, S.: Diffusion of ions in sea water and in deep-sea sediments, Geochim. Cosmochim. Ac., 38, 703–714, https://doi.org/10.1016/0016-7037(74)90145-8, 1974.
Likhachev, E. R.: Dependence of water viscosity on temperature and pressure, Tech. Phys., 48, 514–515, https://doi.org/10.1134/1.1568496, 2003.
McGechan, M. B. and Lewis, D. R.: SW – soil and water: sorption of phosphorus by soil, part 1: principles, equations and models, Biosyst. Eng., 82, 1–24, https://doi.org/10.1006/bioe.2002.0054, 2002.
McLean, E. O.: Soil pH and lime requirement, In: Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties, 9, edited by: Page, A. L., 199–224, https://doi.org/10.2134/agronmonogr9.2.2ed.c12, 1983.
Miller, R. O. and Kissel, D. E.: Comparison of soil pH methods on soils of North America, Soil Sci. Soc. Am. J., 74, 310–316, https://doi.org/10.2136/sssaj2008.0047, 2010.
Nambu, K. and Yonebayashi, K.: Acidic properties of dissolved organic matter leached from organic layers in temperate forests, Soil Sci. Plant Nutr., 45, 65–77, https://doi.org/10.1080/00380768.1999.10409324, 1999.
Nielsen, K. E., Irizar, A., Nielsen, L. P., Kristiansen, S. M., Damgaard, C., Holmstrup, M., Petersen, A. R., and Strandberg, M.: In situ measurements reveal extremely low pH in soil, Soil Biol. Biochem., 115, 63–65, https://doi.org/10.1016/j.soilbio.2017.08.003, 2017.
Othmer, D. F. and Thakar, M. S.: Correlating diffusion coefficient in liquids, Ind. Eng. Chem., 45, 589–593, https://doi.org/10.1021/ie50519a036, 1953.
Pan, B., Lam, S. K., Wang, E., Mosier, A., and Chen, D.: New approach for predicting nitrification and its fraction of N2O emissions in global terrestrial ecosystems, Environ. Res. Lett., 16, 034053, https://doi.org/10.1088/1748-9326/abe4f5, 2021.
Parfitt, R. L., Giltrap, D. J., and Whitton, J. S.: Contribution of organic matter and clay minerals to the cation exchange capacity of soils, Commun. Soil Sci. Plant Anal., 26, 1343–1355, https://doi.org/10.1080/00103629509369376, 1995.
Parkhurst, D. L. and Appelo, C. A. J.: Description of input and examples for PHREEQC version 3: a computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations, U. S. Geological Survey, https://doi.org/10.3133/tm6A43, 2013.
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, https://doi.org/10.5194/soil-7-217-2021, 2021.
Pollyea, R. M. and Rimstidt, J. D.: Rate equations for modeling carbon dioxide sequestration in basalt, Appl. Geochem., 81, 53–62, https://doi.org/10.1016/j.apgeochem.2017.03.020, 2017.
Ponnamperuma, F. N., Tianco, E. M., and Loy, T. A.: Ionic strengths of the solutions of flooded soils and other natural aqueous solutions from specific conductance, Soil Sci., 102, 408–413, https://doi.org/10.1097/00010694-196612000-00009, 1966.
Rau, G. H., Knauss, K. G., Langer, W. H., and Caldeira, K.: Reducing energy-related CO2 emissions using accelerated weathering of limestone, Energy, 32, 1471–1477, https://doi.org/10.1016/j.energy.2006.10.011, 2007.
Reitz, M., Sanford, W. E., Senay, G. B., and Cazenas, J.: Annual estimates of recharge, quick-flow runoff, and evapotranspiration for the contiguous US using empirical regression equations. J. Am. Water Resour. Assoc., 53, 961–983, https://doi.org/10.1111/1752-1688.12546, 2017.
Rengel, Z. (Ed.): Handbook of Soil Acidity, CRC Press, https://doi.org/10.1201/9780203912317, 2003.
Robie, R. A. Hemingway, B. S., and Fisher, J. R.: Thermodynamic properties of minerals and related substances at 298.15 K and 1 bar (105 pascals) pressure and at higher temperatures, U. S. Geological Survey, https://doi.org/10.3133/b1452, 1978.
Schulz, H. D. and Zabel, M.: Marine Geochemistry, Springer, https://doi.org/10.1007/3-540-32144-6, 2006.
Sikora, F. J.: A buffer that mimics the SMP buffer for determining lime requirement of soil, Soil Sci. Soc. Am. J., 70, 474–486, https://doi.org/10.2136/sssaj2005.0164, 2006.
Steefel, C. I.: CrunchFlow Software for Modeling Multicomponent Reactive Flow and Transport USER'S MANUAL, 2009.
Steefel, C. I., Carroll, S., Zhao, P., and Roberts, S.: Cesium migration in Hanford sediment: a multisite cation exchange model based on laboratory transport experiments, J. Contam. Hydrol., 67, 219–246, https://doi.org/10.1016/S0169-7722(03)00033-0, 2003.
Steiner, Z., Lazar, B., Erez, J., and Turchyn, A. V.: Comparing Rhizon samplers and centrifugation for pore-water separation in studies of the marine carbonate system in sediments, Limnol. Oceanogr.-Meth., 16, 828–839, https://doi.org/10.1002/lom3.10286, 2018.
Strefler, J., Amann, T., Bauer, N., Kriegler, E., and Hartmann, J.: Potential and costs of carbon dioxide removal by enhanced weathering of rocks, Environ. Res. Lett., 13, 034010, https://doi.org/10.1088/1748-9326/aaa9c4, 2018.
Swoboda, P., Döring, T. F., and Hamer, M.: Remineralizing soils? The agricultural usage of silicate rock powders: A review, Sci. Total Environ., 807, 150976, https://doi.org/10.1016/j.scitotenv.2021.150976, 2022.
Taylor, L. L., Quirk, J., Thorley, R. M. S., Kharecha, P. A., Hansen, J., Ridgwell, A., Lomas, M. R., Banwart, S. A., and Beerling, D. J.: Enhanced weathering strategies for stabilizing climate and averting ocean acidification, Nat. Clim. Change, 6, 402–406, https://doi.org/10.1038/NCLIMATE2882, 2016.
Thomas, G. W.: Soil pH and soil acidity, in: Methods of Soil Analysis: Part 3 Chemical Methods, 5, edited by: Sparks, D. L., Page, A. L., Helmke, P. A., Loeppert, R. H., Soltanpour, P. N., Tabatabai, M. A., Johnston, C. T., and Sumner, M. E., 475–490, https://doi.org/10.2136/sssabookser5.3.c16, 1996.
Thomas Sims, J.: Lime requirement, in: Methods of Soil Analysis: Part 3 Chemical Methods, 5, edited by: Sparks, D. L., Page, A. L., Helmke, P. A., Loeppert, R. H., Soltanpour, P. N., Tabatabai, M. A., Johnston, C. T., and Sumner, M. E., 491–515, https://doi.org/10.2136/sssabookser5.3.c17, 1996.
Vakilifard, N., Kantzas, E. P., Edwards, N. R., Holden, P. B., and Beerling, D. J.: The role of enhanced rock weathering deployment with agriculture in limiting future warming and protecting coral reefs, Environ. Res. Lett., 16, 094005, https://doi.org/10.1088/1748-9326/ac1818, 2021.
Van der Zee, S. E. and van Riemsdijk, W. H.: Model for long-term phosphate reaction kinetics in soil, J. Environ. Qual., 17, 35–41, https://doi.org/10.2134/jeq1988.00472425001700010005x, 1988.
Walkinshaw, M., O'Geen, A. T., and Beaudette, D. E.: Soil Properties, California Soil Resource Lab, http://casoilresource.lawr.ucdavis.edu/soil-properties/ (last access: 22 May 2023), 2022.
Wang, Y., Mao, J., Jin, M., Hoffman, F. M., Shi, X., Wullschleger, S. D., and Dai, Y.: Development of observation-based global multilayer soil moisture products for 1970 to 2016, Earth Syst. Sci. Data, 13, 4385–4405, https://doi.org/10.5194/essd-13-4385-2021, 2021.
Zhang, S., Planavsky, N. J., Katchinoff, J., Raymond, P. A., Kanzaki, Y., Reershemius, T., and Reinhard, C. T.: River chemistry constraints on the carbon capture potential of surficial enhanced rock weathering, Limnol. Oceanogr., 67. S148–S157, https://doi.org/10.1002/lno.12244, 2022.
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.
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly...
