Articles | Volume 11, issue 6
https://doi.org/10.5194/gmd-11-2009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-2009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
04 Jun 2018
Model description paper |
| 04 Jun 2018
Soil Methanotrophy Model (MeMo v1.0): a process-based model to quantify global uptake of atmospheric methane by soil
Fabiola Murguia-Flores
CORRESPONDING AUTHOR
School of Geographical Sciences, University of Bristol, Bristol, BS8
1SS, UK
Sandra Arndt
School of Geographical Sciences, University of Bristol, Bristol, BS8
1SS, UK
current address: Department of Geosciences, Environment and Society, Université
Libre de Bruxelles, Brussels, Belgium
Anita L. Ganesan
School of Geographical Sciences, University of Bristol, Bristol, BS8
1SS, UK
Guillermo Murray-Tortarolo
Catedra CONACyT comisionado al Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autonoma de Mexico, Morelia, Mexico
Edward R. C. Hornibrook
School of Earth Sciences, University of Bristol, Bristol, BS8 1RJ,
UK
current address: Earth, Environmental and Geographic Sciences, The University of
British Columbia, Okanagan Campus, Kelowna, BC, V1V 1V7, Canada
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Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
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Daniel Say, Anita L. Ganesan, Mark F. Lunt, Matthew Rigby, Simon O'Doherty, Chris Harth, Alistair J. Manning, Paul B. Krummel, and Stephane Bauguitte
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1287, https://doi.org/10.5194/acp-2018-1287, 2019
Publication in ACP not foreseen
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Sarah Connors, Alistair J. Manning, Andrew D. Robinson, Stuart N. Riddick, Grant L. Forster, Anita Ganesan, Aoife Grant, Stephen Humphrey, Simon O'Doherty, Dave E. Oram, Paul I. Palmer, Robert L. Skelton, Kieran Stanley, Ann Stavert, Dickon Young, and Neil R. P. Harris
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1187, https://doi.org/10.5194/acp-2018-1187, 2018
Preprint withdrawn
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Ronald G. Prinn, Ray F. Weiss, Jgor Arduini, Tim Arnold, H. Langley DeWitt, Paul J. Fraser, Anita L. Ganesan, Jimmy Gasore, Christina M. Harth, Ove Hermansen, Jooil Kim, Paul B. Krummel, Shanlan Li, Zoë M. Loh, Chris R. Lunder, Michela Maione, Alistair J. Manning, Ben R. Miller, Blagoj Mitrevski, Jens Mühle, Simon O'Doherty, Sunyoung Park, Stefan Reimann, Matt Rigby, Takuya Saito, Peter K. Salameh, Roland Schmidt, Peter G. Simmonds, L. Paul Steele, Martin K. Vollmer, Ray H. Wang, Bo Yao, Yoko Yokouchi, Dickon Young, and Lingxi Zhou
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Goulven Gildas Laruelle, Nicolas Goossens, Sandra Arndt, Wei-Jun Cai, and Pierre Regnier
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Mark F. Lunt, Matt Rigby, Anita L. Ganesan, and Alistair J. Manning
Geosci. Model Dev., 9, 3213–3229, https://doi.org/10.5194/gmd-9-3213-2016, https://doi.org/10.5194/gmd-9-3213-2016, 2016
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Chiara Volta, Goulven Gildas Laruelle, Sandra Arndt, and Pierre Regnier
Hydrol. Earth Syst. Sci., 20, 991–1030, https://doi.org/10.5194/hess-20-991-2016, https://doi.org/10.5194/hess-20-991-2016, 2016
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A generic estuarine model is applied to three idealized tidal estuaries representing the main hydro-geometrical estuarine classes. The study provides insight into the estuarine biogeochemical dynamics, in particular the air-water CO2/sub> flux, as well as the potential response to future environmental changes and to uncertainties in model parameter values. We believe that our approach could help improving upscaling strategies to better integrate estuaries in regional/global biogeochemical studies.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
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We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
J. A. Bradley, A. M. Anesio, J. S. Singarayer, M. R. Heath, and S. Arndt
Geosci. Model Dev., 8, 3441–3470, https://doi.org/10.5194/gmd-8-3441-2015, https://doi.org/10.5194/gmd-8-3441-2015, 2015
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Recent climate warming causing ice retreat exposes new terrestrial ecosystems that have potentially significant yet largely unexplored roles on large-scale biogeochemical cycling and climate. SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical model designed to simulate microbial community establishment and elemental cycling (C, N and P) during initial soil formation in exposed glacier forefields. It is also transferable to other extreme ecosystem types.
A. L. Ganesan, A. J. Manning, A. Grant, D. Young, D .E. Oram, W. T. Sturges, J. B. Moncrieff, and S. O'Doherty
Atmos. Chem. Phys., 15, 6393–6406, https://doi.org/10.5194/acp-15-6393-2015, https://doi.org/10.5194/acp-15-6393-2015, 2015
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The UK is one of several countries to enact legislation to reduce its greenhouse gas emissions. We present top-down emissions of methane and nitrous oxide for the UK and Ireland over 2012-2014. We inferred average UK emissions of 2.09Tg/yr CH4 and 0.101Tg/yr N2O and used sectoral distributions to determine whether these discrepancies can be attributed to specific source sectors. We found the agricultural sector likely to be overestimated in the bottom-up emissions inventories of both gases.
C. Volta, S. Arndt, H. H. G. Savenije, G. G. Laruelle, and P. Regnier
Geosci. Model Dev., 7, 1271–1295, https://doi.org/10.5194/gmd-7-1271-2014, https://doi.org/10.5194/gmd-7-1271-2014, 2014
A. L. Ganesan, M. Rigby, A. Zammit-Mangion, A. J. Manning, R. G. Prinn, P. J. Fraser, C. M. Harth, K.-R. Kim, P. B. Krummel, S. Li, J. Mühle, S. J. O'Doherty, S. Park, P. K. Salameh, L. P. Steele, and R. F. Weiss
Atmos. Chem. Phys., 14, 3855–3864, https://doi.org/10.5194/acp-14-3855-2014, https://doi.org/10.5194/acp-14-3855-2014, 2014
A. L. Ganesan, A. Chatterjee, R. G. Prinn, C. M. Harth, P. K. Salameh, A. J. Manning, B. D. Hall, J. Mühle, L. K. Meredith, R. F. Weiss, S. O'Doherty, and D. Young
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V. Krumins, M. Gehlen, S. Arndt, P. Van Cappellen, and P. Regnier
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Biogeosciences
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Sources of Uncertainty in the Global Fire Model SPITFIRE: Development of LPJmL-SPITFIRE1.9 and Directions for Future Improvements
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
FESOM2.1-REcoM3-MEDUSA2: an ocean-sea ice-biogeochemistry model coupled to a sediment model
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
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.
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.
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.
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.
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.
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.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
EGUsphere, https://doi.org/10.5194/egusphere-2024-1914, https://doi.org/10.5194/egusphere-2024-1914, 2024
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Under climate change, the conditions for wildfires to form are becoming more frequent 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 crucial platform for future developments.
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
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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.
Juliette Bernard, Marielle Saunois, Elodie Salmon, Philippe Ciais, Shushi Peng, Antoine Berchet, Penélope Serrano-Ortiz, Palingamoorthy Gnanamoorthy, and Joachim Jansen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1331, https://doi.org/10.5194/egusphere-2024-1331, 2024
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Despite their importance, uncertainties remain in estimating methane emissions from wetlands. Here, a simplified model that operates at a global scale is developed. Taking advantage of advances in remote sensing data and in situ observations, the model effectively reproduces the spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights for sensitivity analyses.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie Fisher, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2024-978, https://doi.org/10.5194/egusphere-2024-978, 2024
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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 and variability of carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research on these processes.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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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.
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
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.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-181, https://doi.org/10.5194/gmd-2023-181, 2023
Revised manuscript accepted for GMD
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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 storage of carbon in sediments slows down carbon cycling and influences feedbacks in the atmosphere-ocean-sediment system. Here we coupled a sediment model to an ocean biogeochemistry model and found a shift of carbon storage from the atmosphere to the ocean-sediment system.
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.
Cited articles
Adamsen, A. P. S. and King, G. M.: Methane Consumption in Temperate and
Subarctic Forest Soils: Rates, Vertical Zonation, and Responses to Water and
Nitrogen, Appl. Environ, Microbiol., 59, 485–490, 1993.
Allan, W., Struthers, H., and Lowe, D. C.: Methane carbon isotope effects
caused by atomic chlorine in the marine boundary layer: Global model results
compared with Southern Hemisphere measurements, J. Geophys. Res.-Atmos., 112,
D04306, https://doi.org/10.1029/2006JD007369, 2007.
Arndt, S., Jørgensen, B. B., LaRowe, D. E., Middelburg, J. J., Pancost, R.
D., and Regnier, P.: Quantifying the degradation of organic matter in marine
sediments: A review and synthesis, Earth-Sci. Rev., 123, 53–86,
https://doi.org/10.1016/j.earscirev.2013.02.008, 2013.
Aronson, E. L. and Helliker, B. R.: Methane flux in non-wetland soils in
response to nitrogen addition: a meta-analysis, Ecology, 91, 3242–3251,
https://doi.org/10.1890/09-2185.1, 2010.
Bodelier, P. L. E. and Laanbroek, H. J.: Nitrogen as a regulatory factor of
methane oxidation in soils and sediments, FEMS Microbiol. Ecol., 47,
265–277, https://doi.org/10.1016/S0168-6496(03)00304-0, 2004.
Boeckx, P. and Van Cleemput, O.: Methane Oxidation in a Neutral Landfill
Cover Soil: Influence of Moisture Content, Temperature, and
Nitrogen-Turnover, J. Environ. Qual., 25, 178,
https://doi.org/10.2134/jeq1996.00472425002500010023x, 1996.
Borken, W., Davidson, E. A., Savage, K., Sundquist, E. T., and Steudler, P.:
Effect of summer throughfall exclusion, summer drought, and winter snow cover
on methane fluxes in a temperate forest soil, Soil Biol. Biochem., 38,
1388–1395, https://doi.org/10.1016/j.soilbio.2005.10.011, 2006.
Born, M., Dörr, H., and Levin, I.: Methane consumption in aerated soils
of the temperate zone, Tellus B, 42, 2–8,
https://doi.org/10.1034/j.1600-0889.1990.00002.x, 1990.
Bradford, M. A., Ineson, P., Wookey, P. A., and Lappin-Scott, H. M.: The
effects of acid nitrogen and acid sulphur deposition on CH4 oxidation in a
forest soil: a laboratory study, Soil Biol. Biochem., 33, 1695–1702,
https://doi.org/10.1016/S0038-0717(01)00091-8, 2001.
Bradley, J. A., Anesio, A. M., and Arndt, S.: Bridging the divide: a
model-data approach to Polar and Alpine microbiology, FEMS Microbiol. Ecol.,
92, fiw015, https://doi.org/10.1093/femsec/fiw015, 2016.
Brady, N. C., Weil, R. R., and Weil, R.: The Nature and Properties of Soils,
Prentice-Hall, Upper Sadler River, 881 pp., 1999.
Bronson, K. F. and Mosier, A. R.: Suppression of methane oxidation in aerobic
soil by nitrogen fertilizers, nitrification inhibitors, and urease
inhibitors, Biol. Fertil. Soils, 17, 263–268, https://doi.org/10.1007/BF00383979, 1994.
Burke, R. A., Meyer, J. L., Cruse, J. M., Birkhead, K. M., and Paul, M. J.:
Soil-atmosphere exchange of methane in adjacent cultivated and floodplain
forest soils, J. Geophys. Res.-Atmos., 104, 8161–8171,
https://doi.org/10.1029/1999JD900015, 1999.
Butterbach-Bahl, K. and Papen, H.: Four years continuous record of
CH4-exchange between the atmosphere and untreated and limed soil of a
N-saturated spruce and beech forest ecosystem in Germany, Plant Soil, 240,
77–90, https://doi.org/10.1023/A:1015856617553, 2002.
Cai, Z. C. and Mosier, A. R.: Effect of NH4Cl addition on methane
oxidation by paddy soils, Soil Biol. Biochem., 32, 1537–1545,
https://doi.org/10.1016/S0038-0717(00)00065-1, 2000.
Castro, M. S., Steudler, P. A., Melillo, J. M., Aber, J. D., and Bowden, R.
D.: Factors controlling atmospheric methane consumption by temperate forest
soils, Global Biogeochem. Cy., 9, 1–10, https://doi.org/10.1029/94GB02651, 1995.
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J.,
Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le
Quéré, C., Myneni, R. B., Piao, S., and Thornton, P.: Carbon and
Other Biogeochemical Cycles, in: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia,
Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK,
New York, NY, USA, 2013.
Clapp, R. B. and Hornberger, G. M.: Empirical equations for some soil
hydraulic properties, Water Resour. Res., 14, 601–604,
https://doi.org/10.1029/WR014i004p00601, 1978.
Curry, C. L.: Modeling the soil consumption of atmospheric methane at the
global scale, Global Biogeochem. Cy., 21, GB4012, https://doi.org/10.1029/2006GB002818,
2007.
Czepiel, P. M., Crill, P. M., and Harriss, R. C.: Environmental factors
influencing the variability of methane oxidation in temperate zone soils, J.
Geophys. Res.-Atmos., 100, 9359–9364, https://doi.org/10.1029/95JD00542, 1995.
Del Grosso, S. J., Parton, W. J., Mosier, A. R., Ojima, D. S., Potter, C. S.,
Borken, W., Brumme, R., Butterbach-Bahl, K., Crill, P. M., Dobbie, K., and
Smith, K. A.: General CH4 oxidation model and comparisons of CH4
Oxidation in natural and managed systems, Global Biogeochem. Cy., 14,
999–1019, https://doi.org/10.1029/1999GB001226, 2000.
De Visscher, A. and Cleemput, O. V.: Induction of enhanced CH4 oxidation
in soils: NH
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A.,
Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and
Jackson, T.: The International Soil Moisture Network: a data hosting facility
for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15,
1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011.
Dörr, H., Katruff, L., and Levin, I.: Proceedings of the NATO advanced
research workshop Soil texture parameterization of the methane uptake in
aerated soils, Chemosphere, 26, 697–713, https://doi.org/10.1016/0045-6535(93)90454-D,
1993.
Dutaur, L. and Verchot, L. V.: A global inventory of the soil CH4 sink,
Global Biogeochem. Cy., 21, GB4013, https://doi.org/10.1029/2006GB002734, 2007.
Epstein, H. E., Burke, I. C., Mosier, A. R., Hutchinson, G. L.: Plant
functional type effects on trace gas fluxes in the shortgrass steppe, in:
Plant-Induced Soil Changes: Processes and Feedbacks, Developments in
Biogeochemistry, edited by: Breemen, N. V., Springer Netherlands, 145–168,
1998.
Etheridge, D. M., Steele, L. P., Francey, R. J., and Langenfelds, R. L.:
Atmospheric methane between 1000 A.D. and present: Evidence of anthropogenic
emissions and climatic variability, J. Geophys. Res.-Atmos., 103,
15979–15993, https://doi.org/10.1029/98JD00923, 1998.
Fang, H., Cheng, S., Yu, G., Cooch, J., Wang, Y., Xu, M., Li, L., Dang, X.,
and Li, Y.: Low-level nitrogen deposition significantly inhibits methane
uptake from an alpine meadow soil on the Qinghai–Tibetan Plateau, Geoderma,
213, 444–452, https://doi.org/10.1016/j.geoderma.2013.08.006, 2014.
Gulledge, J. and Schimel, J. P.: Low-Concentration Kinetics of Atmospheric
CH4 Oxidation in Soil and Mechanism of NH
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated
high-resolution grids of monthly climatic observations – the CRU TS3.10
Dataset, Int., J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hein, R., Crutzen, P. J., and Heimann, M.: An inverse modelling approach to
investigate the global atmospheric methane cycle, Global Biogeochem. Cy., 11,
43–76, https://doi.org/10.1029/96GB03043, 1997.
Ho, A., Kerckhof, F.-M., Luke, C., Reim, A., Krause, S., Boon, N., and
Bodelier, P. L. E.: Conceptualizing functional traits and ecological
characteristics of methane-oxidizing bacteria as life strategies, Environ.
Microbiol. Rep., 5, 335–345, https://doi.org/10.1111/j.1758-2229.2012.00370.x, 2013.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer,
G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones, C. D.,
Kindermann, G., Kinoshita, T., Goldewijk, K. K., Riahi, K., Shevliakova, E.,
Smith, S., Stehfest, E., Thomson, A., Thornton, P., Vuuren, D. P., and van
Wang, Y. P.: Harmonization of land-use scenarios for the period 1500–2100:
600 years of global gridded annual land-use transitions, wood harvest, and
resulting secondary lands, Clim. Change, 109, 117–161,
https://doi.org/10.1007/s10584-011-0153-2, 2011.
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G.,
Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler,
L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A.,
Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J., Krummel,
P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quéré, C., Naik, V.,
O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn, R.
G., Rigby, M., Ringeval, B., Santini, M., Schmidt, M., Shindell, D. T.,
Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K., Szopa,
S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F.,
Williams, J. E., and Zeng, G.: Three decades of global methane sources and
sinks, Nat. Geosci., 6, 813–823, https://doi.org/10.1038/ngeo1955, 2013.
Klemedtsson, Å. K. and Klemedtsson, L.: Methane uptake in Swedish forest
soil in relation to liming and extra N-deposition, Biol. Fertil. Soils., 25,
296–301, https://doi.org/10.1007/s003740050318, 1997.
Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R.,
Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G.,
Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell,
D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M.,
Dahl-Jensen, D., Das, S., Fritzsche, D., and Nolan, M.: Multi-model mean
nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate
Model Intercomparison Project (ACCMIP): evaluation of historical and
projected future changes, Atmos. Chem. Phys., 13, 7997–8018,
https://doi.org/10.5194/acp-13-7997-2013, 2013.
Le Mer, J. and Roger, P.: Production, oxidation, emission and consumption of
methane by soils: A review, Eur. J. Soil Biol., 37, 25–50,
https://doi.org/10.1016/S1164-5563(01)01067-6, 2001.
Li, C., Aber, J., Stange, F., Butterbach-Bahl, K., and Papen, H.: A
process-oriented model of N2O and NO emissions from forest soils: 1. Model
development, J. Geophys. Res.-Atmos., 105, 4369–4384,
https://doi.org/10.1029/1999JD900949, 2000.
Low, P. F., Hoekstra, P., and Anderson, D. M.: Some Thermodynamic
Relationships for Soils at or Below the Freezing Point: 2. Effects of
Temperature and Pressure on Unfrozen Soil Water, Water Resour. Res., 4,
541–544, https://doi.org/10.1029/WR004i003p00541, 1968.
Luo, G. J., Kiese, R., Wolf, B., and Butterbach-Bahl, K.: Effects of soil
temperature and moisture on methane uptake and nitrous oxide emissions across
three different ecosystem types, Biogeosciences, 10, 3205–3219,
https://doi.org/10.5194/bg-10-3205-2013, 2013.
MacDonald, J. A., Skiba, U., Sheppard, L. J., Hargreaves, K. J., Smith, K.
A., and Fowler, D.: Soil environmental variables affecting the flux of
methane from a range of forest, moorland and agricultural soils,
Biogeochemistry, 34, 113–132, https://doi.org/10.1007/BF00000898, 1996.
McLain, J. E. T. and Ahmann, D. M.: Increased moisture and methanogenesis
contribute to reduced methane oxidation in elevated CO2 soils, Biol.
Fertil. Soils, 44, 623–631, https://doi.org/10.1007/s00374-007-0246-2, 2007.
Mclain, J. E. T., Kepler, T. B., and Ahmann, D. M.: Belowground factors
mediating changes in methane consumption in a forest soil under elevated
CO2, Global Biogeochem. Cy., 16, 1050, https://doi.org/10.1029/2001GB001439, 2002.
Moldrup, P., Kruse, C. W., Rolston, D. E., and Yamaguchi, T.: Modelling
diffusion and reaction in soils: III. Predicting gas diffusivity from the
Campbell soil-water retention model, Soil Sci., 161, 366–375, 1996.
Moldrup, P., Deepagoda, T. K. K. C., Hamamoto, S., Komatsu, T., Kawamoto, K.,
Rolston, D. E., and de Jonge, L. W.: Structure-Dependent Water-Induced Linear
Reduction Model for Predicting Gas Diffusivity and Tortuosity in Repacked and
Intact Soil, Vadose Zone J., 12, 1–11, https://doi.org/10.2136/vzj2013.01.0026, 2013.
Mosier, A. R., Parton, W. J., Valentine, D. W., Ojima, D. S., Schimel, D. S.,
and Delgado, J. A.: CH4 and N2O fluxes in the Colorado shortgrass
steppe: 1. Impact of landscape and nitrogen addition, Global Biogeochem. Cy.,
10, 387–399, https://doi.org/10.1029/96GB01454, 1996.
Mosier, A. R., Morgan, J. A., King, J. Y., LeCain, D., and Milchunas, D. G.:
Soil-atmosphere exchange of CH4, CO2, NOx, and N2O in the
Colorado shortgrass steppe under elevated CO2, Plant Soil, 240, 201–211,
https://doi.org/10.1023/A:1015783801324, 2002.
Myhre, G., Highwood, E. J., Shine, K. P., and Stordal, F.: New estimates of
radiative forcing due to well mixed greenhouse gases, Geophys. Res. Lett.,
25, 2715–2718, https://doi.org/10.1029/98GL01908, 1998.
Nishina, K., Ito, A., Hanasaki, N., and Hayashi, S.: Reconstruction of
spatially detailed global map of NH
Oh, Y., Stackhouse, B., Lau, M. C. Y., Xu, X., Trugman, A. T., Moch, J.,
Onstott, T. C., Jørgensen, C. J., D'Imperio, L., Elberling, B., Emmerton,
C. A., St. Louis, V. L., and Medvigy, D.: A scalable model for methane
consumption in arctic mineral soils, Geophys. Res. Lett., 43, 5143–5150,
https://doi.org/10.1002/2016GL069049, 2016.
Oremland, R. S. and Culbertson, C. W.: Importance of methane-oxidizing
bacteria in the methane budget as revealed by the use of a specific
inhibitor, Nature, 356, 421–423, https://doi.org/10.1038/356421a0, 1992.
Phillips, R. L., Whalen, S. C., Schlesinger, W. H.: Response of soil
methanotrophic activity to carbon dioxide enrichment in a North Carolina
coniferous forest, Soil Biol. Biochem., 33, 793–800,
https://doi.org/10.1016/S0038-0717(00)00227-3, 2001.
Potter, C. S., Davidson, E. A., and Verchot, L. V.: Estimation of global
biogeochemical controls and seasonality in soil methane consumption,
Chemosphere, 32, 2219–2246, https://doi.org/10.1016/0045-6535(96)00119-1, 1996.
Prather, M. J., Holmes, C. D., and Hsu, J.: Reactive greenhouse gas
scenarios: Systematic exploration of uncertainties and the role of
atmospheric chemistry, Geophys. Res. Lett., 39, L09803,
https://doi.org/10.1029/2012GL051440, 2012.
Priemé, A. and Christensen, S.: Seasonal and spatial variation of methane
oxidation in a Danish spruce forest, Soil Biol. Biochem., 29, 1165–1172,
https://doi.org/10.1016/S0038-0717(97)00038-2, 1997.
Ramankutty, N. and Foley, J. A.: Estimating historical changes in global land
cover: Croplands from 1700 to 1992, Global Biogeochem. Cy., 13, 997–1027,
https://doi.org/10.1029/1999GB900046, 1999.
Ridgwell, A. J., Marshall, S. J., and Gregson, K.: Consumption of atmospheric
methane by soils: A process-based model, Global Biogeochem. Cy., 13, 59–70,
https://doi.org/10.1029/1998GB900004, 1999.
Rigby, M., Prinn, R. G., Fraser, P. J., Simmonds, P. G., Langenfelds, R. L.,
Huang, J., Cunnold, D. M., Steele, L. P., Krummel, P. B., Weiss, R. F.,
O'Doherty, S., Salameh, P. K., Wang, H. J., Harth, C. M., Mühle, J., and
Porter, L. W.: Renewed growth of atmospheric methane, Geophys. Res. Lett.,
35, L22805, https://doi.org/10.1029/2008GL036037, 2008.
Rigler, E. and Zechmeister-Boltenstern, S.: Oxidation of ethylene and methane
in forest soils–effect of CO2 and mineral nitrogen, Geoderma, 90,
147–159, https://doi.org/10.1016/S0016-7061(98)00099-8, 1999.
Rosenkranz, P., Brüggemann, N., Papen, H., Xu, Z., Horváth, L., and
Butterbach-Bahl, K.: Soil N and C trace gas fluxes and microbial soil N
turnover in a sessile oak (Quercus petraea (Matt.) Liebl.) forest in Hungary,
Plant Soil, 286, 301–322, https://doi.org/10.1007/s11104-006-9045-z, 2006.
Sabrekov, A. F., Glagolev, M. V., Alekseychik, P. K., Smolentsev, B. A.,
Terentieva, I. E., Krivenok, L. A., and Maksyutov, S. S.: A process-based
model of methane consumption by upland soils, Environ. Res. Lett., 11,
075001, https://doi.org/10.1088/1748-9326/11/7/075001, 2016.
Saggar, S., Hedley, C. B., Giltrap, D. L., and Lambie, S. M.: Measured and
modelled estimates of nitrous oxide emission and methane consumption from a
sheep-grazed pasture, Agric. Ecosyst. Environ, 122, 357–365,
https://doi.org/10.1016/j.agee.2007.02.006, 2007.
Saxton, K. E., Rawls, W. J., Romberger, J. S., and Papendick, R. I.:
Estimating Generalized Soil-water Characteristics from Texture, Soil Sci.
Soc. Am. J., 50, 1031, https://doi.org/10.2136/sssaj1986.03615995005000040039x, 1986.
Schnell, S. and King, G. M.: Mechanistic Analysis of Ammonium Inhibition of
Atmospheric Methane Consumption in Forest Soils, Appl. Environ. Microbiol.,
60, 3514–3521, 1994.
Schnell, S. and King, G. M.: Responses of Methanotrophic Activity in Soils
and Cultures to Water Stress, Appl. Environ. Microbiol., 62, 3203–3209,
1996.
Shangguan, W., Dai, Y., Duan, Q., Liu, B., and Yuan, H.: A global soil data
set for earth system modelling, J. Adv. Model. Earth Syst., 6, 249–263,
https://doi.org/10.1002/2013MS000293, 2014.
Singh, B. K., Bardgett, R. D., Smith, P., and Reay, D. S.: Microorganisms and
climate change: terrestrial feedbacks and mitigation options, Nat. Rev.
Microbiol., 8, 779–790, https://doi.org/10.1038/nrmicro2439, 2010.
Singh, J. S., Singh, S., Raghubanshi, A. S., Singh, S., Kashyap, A. K., and
Reddy, V. S.: Effect of soil nitrogen, carbon and moisture on methane uptake
by dry tropical forest soils, Plant Soil, 196, 115–121,
https://doi.org/10.1023/A:1004233208325, 1997.
Sitaula, B. K., Hansen, S., Sitaula, J. I. B., and Bakken, L. R.: Methane
oxidation potentials and fluxes in agricultural soil: Effects of
fertilisation and soil compaction, Biogeochemistry, 48, 323–339,
https://doi.org/10.1023/A:1006262404600, 2000.
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo,
G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C.,
Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng,
N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais,
P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C.,
Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional
sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679,
https://doi.org/10.5194/bg-12-653-2015, 2015.
Smith, K. A., Dobbie, K. E., Ball, B. C., Bakken, L. R., Sitaula, B. K.,
Hansen, S., Brumme, R., Borken, W., Christensen, S., Priemé, A., Fowler,
D., Macdonald, J. A., Skiba, U., Klemedtsson, L., Kasimir-Klemedtsson, A.,
Degórska, A., and Orlanski, P.: Oxidation of atmospheric methane in
Northern European soils, comparison with other ecosystems, and uncertainties
in the global terrestrial sink, Global Change Biol., 6, 791–803,
https://doi.org/10.1046/j.1365-2486.2000.00356.x, 2000.
Spahni, R., Wania, R., Neef, L., van Weele, M., Pison, I., Bousquet, P.,
Frankenberg, C., Foster, P. N., Joos, F., Prentice, I. C., and van Velthoven,
P.: Constraining global methane emissions and uptake by ecosystems,
Biogeosciences, 8, 1643–1665, https://doi.org/10.5194/bg-8-1643-2011, 2011.
Steinkamp, R., Butterbach-Bahl, K., and Papen, H.: Methane oxidation by soils
of an N limited and N fertilized spruce forest in the Black Forest, Germany,
Soil Biol. Biochem., 33, 145–153, https://doi.org/10.1016/S0038-0717(00)00124-3, 2001.
Tate, K. R., Ross, D. J., Saggar, S., Hedley, C. B., Dando, J., Singh, B. K.,
and Lambie, S. M.: Methane uptake in soils from Pinus radiata plantations, a
reverting shrubland and adjacent pastures: Effects of land-use change, and
soil texture, water and mineral nitrogen, Soil Biol. Biochem., 39,
1437–1449, https://doi.org/10.1016/j.soilbio.2007.01.005, 2007.
Ueyama, M., Takeuchi, R., Takahashi, Y., Ide, R., Ataka, M., Kosugi, Y.,
Takahashi, K., and Saigusa, N.: Methane uptake in a temperate forest soil
using continuous closed-chamber measurements, Agric. For. Meteorol., 213,
1–9, https://doi.org/10.1016/j.agrformet.2015.05.004, 2015.
van den Pol-van Dasselaar, P., van Beusichem, M. L., and Oenema, O.: Effects
of soil moisture content and temperature on methane uptake by grasslands on
sandy soils, Plant Soil, 204, 213–222, https://doi.org/10.1023/A:1004371309361, 1998.
Vecherskaya, M. S., Galchenko, D. V. F., Sokolova, E. N., and Samarkin, V.
A.: Activity and species composition of aerobic methanotrophic communities in
tundra soils, Curr. Microbiol., 27, 181–184, https://doi.org/10.1007/BF01576018, 2013.
Veldkamp, E., Weitz, A. M., and Keller, M.: Management effects on methane
fluxes in humid tropical pasture soils, Soil Biol. Biochem., 33, 1493–1499,
https://doi.org/10.1016/S0038-0717(01)00060-8, 2001.
Visvanathan, C., Pokhrel, D., Cheimchaisri, W., Hettiaratchi, J. P. A., and
Wu, J. S.: Methanotrophic activities in tropical landfill cover soils:
effects of temperature, moisture content and methane concentration, Waste
Manag. Res., 17, 313–323, https://doi.org/10.1034/j.1399-3070.1999.00052.x, 1999.
von Fischer, J. C., Butters, G., Duchateau, P. C., Thelwell, R. J., and
Siller, R.: In situ measures of methanotroph activity in upland soils: A
reaction-diffusion model and field observation of water stress, J. Geophys.
Res.-Biogeo., 114, G01015, https://doi.org/10.1029/2008JG000731, 2009.
Wang, Y., Xue, M., Zheng, X., Ji, B., Du, R., and Wang, Y.: Effects of
environmental factors on N2O emission from and CH4 uptake by the
typical grasslands in the Inner Mongolia, Chemosphere, 58, 205–215,
https://doi.org/10.1016/j.chemosphere.2004.04.043, 2005.
Wang, Z.-P. and Ineson, P.: Methane oxidation in a temperate coniferous
forest soil: effects of inorganic N, Soil Biol. Biochem., 35, 427–433,
https://doi.org/10.1016/S0038-0717(02)00294-8, 2003.
Wania, R., Ross, I., and Prentice, I. C.: Implementation and evaluation of a
new methane model within a dynamic global vegetation model: LPJ-WHyMe v1.3.1,
Geosci. Model Dev., 3, 565–584, https://doi.org/10.5194/gmd-3-565-2010,
2010.
West, A. E., Brooks, P. D., Fisk, M. C., Smith, L. K., Holland, E. A., Iii,
C. H. J., Babcock, S., Lai, R. S., and Schmidt, S. K.: Landscape patterns of
CH4 fluxes in an alpine tundra ecosystem, Biogeochemistry, 45, 243–264,
https://doi.org/10.1023/A:1006130911046, 1999.
Whalen, S. C.: Influence of N and non-N salts on atmospheric methane
oxidation by upland boreal forest and tundra soils, Biol. Fertil. Soils, 31,
279–287, https://doi.org/10.1007/s003740050657, 2000.
Whalen, S. C. and Reeburgh, W. S.: Moisture and temperature sensitivity of
CH4 oxidation in boreal soils, Soil Biol. Biochem., 28, 1271–1281,
https://doi.org/10.1016/S0038-0717(96)00139-3, 1996.
Zhang, W., Mo, J., Zhou, G., Gundersen, P., Fang, Y., Lu, X., Zhang, T., and
Dong, S.: Methane uptake responses to nitrogen deposition in three tropical
forests in southern China, J. Geophys. Res.-Atmos., 113, D11116,
https://doi.org/10.1029/2007JD009195, 2008.
Zhuang, Q., Chen, M., Xu, K., Tang, J., Saikawa, E., Lu, Y., Melillo, J. M.,
Prinn, R. G., and McGuire, A. D.: Response of global soil consumption of
atmospheric methane to changes in atmospheric climate and nitrogen
deposition, Global Biogeochem. Cy., 27, 650–663, https://doi.org/10.1002/gbc.20057,
2013.
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Short summary
Soil bacteria known as methanotrophs are the only biological sink for atmospheric methane (CH4). Their activity depends on climatic and edaphic conditions, thus varies spatially and temporarily. Based on this, we developed a model (MeMo v1.0) to assess the global CH4 consumption by soils. The global CH4 uptake was 33.5 Tg CH4 yr-1 for 1990–2009, with an increasing trend of 0.1 Tg CH4 yr-2. The regional analysis proved that warm and semiarid regions represent the most efficient CH4 sink.
Soil bacteria known as methanotrophs are the only biological sink for atmospheric methane (CH4)....
