Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-735-2021
© Author(s) 2021. 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-14-735-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
03 Feb 2021
Model description paper |
| 03 Feb 2021
| 03 Feb 2021
CoupModel (v6.0): an ecosystem model for coupled phosphorus, nitrogen, and carbon dynamics – evaluated against empirical data from a climatic and fertility gradient in Sweden
Department of Biological and Environmental Sciences, University of
Gothenburg, P.O. Box 460, Gothenburg 40530, Sweden
Per-Erik Jansson
Department of Land and Water Resources Engineering, Royal Institute of
Technology (KTH), Stockholm 10044, Sweden
Annemieke I. Gärdenäs
CORRESPONDING AUTHOR
Department of Biological and Environmental Sciences, University of
Gothenburg, P.O. Box 460, Gothenburg 40530, Sweden
Related authors
Hongxing He, Ian B. Strachan, and Nigel T. Roulet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2679, https://doi.org/10.5194/egusphere-2024-2679, 2024
Short summary
Short summary
This study applied the CoupModel to simulate carbon dynamics and ecohydrology for a restored peatland and evaluated the responses of the simulated carbon fluxes to varying acrotelm thickness and climate. The results show that CoupModel can simulate the coupled carbon and ecohydrology dynamics for the restored peatland system, and the restored peatland has less resilience in its C uptake functions than pristine peatlands under a changing climate.
Jyrki Jauhiainen, Juha Heikkinen, Nicholas Clarke, Hongxing He, Lise Dalsgaard, Kari Minkkinen, Paavo Ojanen, Lars Vesterdal, Jukka Alm, Aldis Butlers, Ingeborg Callesen, Sabine Jordan, Annalea Lohila, Ülo Mander, Hlynur Óskarsson, Bjarni D. Sigurdsson, Gunnhild Søgaard, Kaido Soosaar, Åsa Kasimir, Brynhildur Bjarnadottir, Andis Lazdins, and Raija Laiho
Biogeosciences, 20, 4819–4839, https://doi.org/10.5194/bg-20-4819-2023, https://doi.org/10.5194/bg-20-4819-2023, 2023
Short summary
Short summary
The study looked at published data on drained organic forest soils in boreal and temperate zones to revisit current Tier 1 default emission factors (EFs) provided by the IPCC Wetlands Supplement. We examined the possibilities of forming more site-type specific EFs and inspected the potential relevance of environmental variables for predicting annual soil greenhouse gas balances by statistical models. The results have important implications for EF revisions and national emission reporting.
Hongxing He, Tim Moore, Elyn R. Humphreys, Peter M. Lafleur, and Nigel T. Roulet
Hydrol. Earth Syst. Sci., 27, 213–227, https://doi.org/10.5194/hess-27-213-2023, https://doi.org/10.5194/hess-27-213-2023, 2023
Short summary
Short summary
We applied CoupModel to quantify the impacts of natural and human disturbances to adjacent water bodies in regulating net CO2 uptake of northern peatlands. We found that 1 m drops of the water level at the beaver pond lower the peatland water table depth 250 m away by 0.15 m and reduce the peatland net CO2 uptake by 120 g C m-2 yr-1. Therefore, although bogs are ombrotrophic rainfed systems, the boundary hydrological conditions play an important role in regulating water storage and CO2 uptake.
Balázs Grosz, Reinhard Well, Rene Dechow, Jan Reent Köster, Mohammad Ibrahim Khalil, Simone Merl, Andreas Rode, Bianca Ziehmer, Amanda Matson, and Hongxing He
Biogeosciences, 18, 5681–5697, https://doi.org/10.5194/bg-18-5681-2021, https://doi.org/10.5194/bg-18-5681-2021, 2021
Short summary
Short summary
To assure quality predictions biogeochemical models must be current. We use data measured using novel incubation methods to test the denitrification sub-modules of three models. We aim to identify limitations in the denitrification modeling to inform next steps for development. Several areas are identified, most urgently improved denitrification control parameters and further testing with high-temporal-resolution datasets. Addressing these would significantly improve denitrification modeling.
Jyrki Jauhiainen, Jukka Alm, Brynhildur Bjarnadottir, Ingeborg Callesen, Jesper R. Christiansen, Nicholas Clarke, Lise Dalsgaard, Hongxing He, Sabine Jordan, Vaiva Kazanavičiūtė, Leif Klemedtsson, Ari Lauren, Andis Lazdins, Aleksi Lehtonen, Annalea Lohila, Ainars Lupikis, Ülo Mander, Kari Minkkinen, Åsa Kasimir, Mats Olsson, Paavo Ojanen, Hlynur Óskarsson, Bjarni D. Sigurdsson, Gunnhild Søgaard, Kaido Soosaar, Lars Vesterdal, and Raija Laiho
Biogeosciences, 16, 4687–4703, https://doi.org/10.5194/bg-16-4687-2019, https://doi.org/10.5194/bg-16-4687-2019, 2019
Short summary
Short summary
We collated peer-reviewed publications presenting GHG flux data for drained organic forest soils in boreal and temperate climate zones, focusing on data that have been used, or have the potential to be used, for estimating net annual soil GHG emission/removals. We evaluated the methods in data collection and identified major gaps in background/environmental data. Based on these, we developed suggestions for future GHG data collection to increase data applicability in syntheses and inventories.
Hongxing He, Per-Erik Jansson, Magnus Svensson, Jesper Björklund, Lasse Tarvainen, Leif Klemedtsson, and Åsa Kasimir
Biogeosciences, 13, 2305–2318, https://doi.org/10.5194/bg-13-2305-2016, https://doi.org/10.5194/bg-13-2305-2016, 2016
Short summary
Short summary
We simulate CO2 and N2O dynamics over a full forest rotation on drained agricultural peatland, using CoupModel. Data used for validation include tree ring-derived biomass data (1966–2011) and measured abiotic and soil emission data (2006–2011). The results show that the C fixed in forest biomass is slightly larger than the soil losses over the full rotation period. However when including N2O and indirect emissions from forest thinning products, the forest system switches to a large GHG source.
Hongxing He, Ian B. Strachan, and Nigel T. Roulet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2679, https://doi.org/10.5194/egusphere-2024-2679, 2024
Short summary
Short summary
This study applied the CoupModel to simulate carbon dynamics and ecohydrology for a restored peatland and evaluated the responses of the simulated carbon fluxes to varying acrotelm thickness and climate. The results show that CoupModel can simulate the coupled carbon and ecohydrology dynamics for the restored peatland system, and the restored peatland has less resilience in its C uptake functions than pristine peatlands under a changing climate.
Jyrki Jauhiainen, Juha Heikkinen, Nicholas Clarke, Hongxing He, Lise Dalsgaard, Kari Minkkinen, Paavo Ojanen, Lars Vesterdal, Jukka Alm, Aldis Butlers, Ingeborg Callesen, Sabine Jordan, Annalea Lohila, Ülo Mander, Hlynur Óskarsson, Bjarni D. Sigurdsson, Gunnhild Søgaard, Kaido Soosaar, Åsa Kasimir, Brynhildur Bjarnadottir, Andis Lazdins, and Raija Laiho
Biogeosciences, 20, 4819–4839, https://doi.org/10.5194/bg-20-4819-2023, https://doi.org/10.5194/bg-20-4819-2023, 2023
Short summary
Short summary
The study looked at published data on drained organic forest soils in boreal and temperate zones to revisit current Tier 1 default emission factors (EFs) provided by the IPCC Wetlands Supplement. We examined the possibilities of forming more site-type specific EFs and inspected the potential relevance of environmental variables for predicting annual soil greenhouse gas balances by statistical models. The results have important implications for EF revisions and national emission reporting.
Hongxing He, Tim Moore, Elyn R. Humphreys, Peter M. Lafleur, and Nigel T. Roulet
Hydrol. Earth Syst. Sci., 27, 213–227, https://doi.org/10.5194/hess-27-213-2023, https://doi.org/10.5194/hess-27-213-2023, 2023
Short summary
Short summary
We applied CoupModel to quantify the impacts of natural and human disturbances to adjacent water bodies in regulating net CO2 uptake of northern peatlands. We found that 1 m drops of the water level at the beaver pond lower the peatland water table depth 250 m away by 0.15 m and reduce the peatland net CO2 uptake by 120 g C m-2 yr-1. Therefore, although bogs are ombrotrophic rainfed systems, the boundary hydrological conditions play an important role in regulating water storage and CO2 uptake.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
Short summary
Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Balázs Grosz, Reinhard Well, Rene Dechow, Jan Reent Köster, Mohammad Ibrahim Khalil, Simone Merl, Andreas Rode, Bianca Ziehmer, Amanda Matson, and Hongxing He
Biogeosciences, 18, 5681–5697, https://doi.org/10.5194/bg-18-5681-2021, https://doi.org/10.5194/bg-18-5681-2021, 2021
Short summary
Short summary
To assure quality predictions biogeochemical models must be current. We use data measured using novel incubation methods to test the denitrification sub-modules of three models. We aim to identify limitations in the denitrification modeling to inform next steps for development. Several areas are identified, most urgently improved denitrification control parameters and further testing with high-temporal-resolution datasets. Addressing these would significantly improve denitrification modeling.
Adrian Wicki, Per-Erik Jansson, Peter Lehmann, Christian Hauck, and Manfred Stähli
Hydrol. Earth Syst. Sci., 25, 4585–4610, https://doi.org/10.5194/hess-25-4585-2021, https://doi.org/10.5194/hess-25-4585-2021, 2021
Short summary
Short summary
Soil moisture information was shown to be valuable for landslide prediction. Soil moisture was simulated at 133 sites in Switzerland, and the temporal variability was compared to the regional occurrence of landslides. We found that simulated soil moisture is a good predictor for landslides, and that the forecast goodness is similar to using in situ measurements. This encourages the use of models for complementing existing soil moisture monitoring networks for regional landslide early warning.
Jyrki Jauhiainen, Jukka Alm, Brynhildur Bjarnadottir, Ingeborg Callesen, Jesper R. Christiansen, Nicholas Clarke, Lise Dalsgaard, Hongxing He, Sabine Jordan, Vaiva Kazanavičiūtė, Leif Klemedtsson, Ari Lauren, Andis Lazdins, Aleksi Lehtonen, Annalea Lohila, Ainars Lupikis, Ülo Mander, Kari Minkkinen, Åsa Kasimir, Mats Olsson, Paavo Ojanen, Hlynur Óskarsson, Bjarni D. Sigurdsson, Gunnhild Søgaard, Kaido Soosaar, Lars Vesterdal, and Raija Laiho
Biogeosciences, 16, 4687–4703, https://doi.org/10.5194/bg-16-4687-2019, https://doi.org/10.5194/bg-16-4687-2019, 2019
Short summary
Short summary
We collated peer-reviewed publications presenting GHG flux data for drained organic forest soils in boreal and temperate climate zones, focusing on data that have been used, or have the potential to be used, for estimating net annual soil GHG emission/removals. We evaluated the methods in data collection and identified major gaps in background/environmental data. Based on these, we developed suggestions for future GHG data collection to increase data applicability in syntheses and inventories.
Mousong Wu, Per-Erik Jansson, Jingwei Wu, Xiao Tan, Kang Wang, Peng Chen, and Jiesheng Huang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-466, https://doi.org/10.5194/hess-2018-466, 2018
Revised manuscript not accepted
Hongxing He, Astrid Meyer, Per-Erik Jansson, Magnus Svensson, Tobias Rütting, and Leif Klemedtsson
Geosci. Model Dev., 11, 725–751, https://doi.org/10.5194/gmd-11-725-2018, https://doi.org/10.5194/gmd-11-725-2018, 2018
Short summary
Short summary
Ectomycorrhizal fungi (ECM) have shown a major impact on forest C and N cycles, but are currently neglected in most ecosystem models. We thus implemented the previously developed ectomycorrhizal fungi model, MYCOFON, into a well-established ecosystem model, CoupModel. This paper describes the key components and features of Coup-MYCOFON. The new version of CoupModel can now simulate C and N fluxes and pools, explicitly accounting for links and feedbacks among plant, soil, and ECM.
Wenxin Zhang, Per-Erik Jansson, and Bo Elberling
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-382, https://doi.org/10.5194/bg-2017-382, 2017
Manuscript not accepted for further review
Christine Metzger, Mats B. Nilsson, Matthias Peichl, and Per-Erik Jansson
Geosci. Model Dev., 9, 4313–4338, https://doi.org/10.5194/gmd-9-4313-2016, https://doi.org/10.5194/gmd-9-4313-2016, 2016
Short summary
Short summary
Many interactions between various abiotic and biotic processes and their parameters were identified by global sensitivity analysis, revealing strong dependence of a certain model output (e.g. CO2 or heat fluxes, leaf area index, radiation, water table, soil temperature or snow depth) to model set-up and parameterization in many different processes, a limited transferability of parameter values between models, and the importance of ancillary measurements for improving models and thus predictions.
Mousong Wu, Per-Erik Jansson, Xiao Tan, Jiesheng Huang, and Jingwei Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-507, https://doi.org/10.5194/hess-2016-507, 2016
Revised manuscript not accepted
Hongxing He, Per-Erik Jansson, Magnus Svensson, Jesper Björklund, Lasse Tarvainen, Leif Klemedtsson, and Åsa Kasimir
Biogeosciences, 13, 2305–2318, https://doi.org/10.5194/bg-13-2305-2016, https://doi.org/10.5194/bg-13-2305-2016, 2016
Short summary
Short summary
We simulate CO2 and N2O dynamics over a full forest rotation on drained agricultural peatland, using CoupModel. Data used for validation include tree ring-derived biomass data (1966–2011) and measured abiotic and soil emission data (2006–2011). The results show that the C fixed in forest biomass is slightly larger than the soil losses over the full rotation period. However when including N2O and indirect emissions from forest thinning products, the forest system switches to a large GHG source.
C. Metzger, P.-E. Jansson, A. Lohila, M. Aurela, T. Eickenscheidt, L. Belelli-Marchesini, K. J. Dinsmore, J. Drewer, J. van Huissteden, and M. Drösler
Biogeosciences, 12, 125–146, https://doi.org/10.5194/bg-12-125-2015, https://doi.org/10.5194/bg-12-125-2015, 2015
Short summary
Short summary
To identify site specific differences in CO2-related processes in open peatlands, we calibrated a process oriented model to fit to detailed measurements of carbon fluxes and compared the resulting parameter ranges between the sites. For most processes a common configuration could be applied. Site specific differences were identified for soil respiration coefficients, plant radiation-use efficiencies and plant storage fractions for spring regrowth.
S. H. Wu and P.-E. Jansson
Hydrol. Earth Syst. Sci., 17, 735–749, https://doi.org/10.5194/hess-17-735-2013, https://doi.org/10.5194/hess-17-735-2013, 2013
Related subject area
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
Short summary
Short summary
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
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
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
Short summary
Short summary
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
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
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
Short summary
Short summary
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
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie Fisher, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2024-978, https://doi.org/10.5194/egusphere-2024-978, 2024
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land Surface Models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes and variability of carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research on these processes.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
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
Short summary
Short summary
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
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Cited articles
Aerts, R.: Nutrient resorption from senescing leaves of perennials: are
there general patterns?, J. Ecol., 84, 597–608, 1996.
Akselsson, C., Pihl Karlsson, G., Karlsson, P.-E., and Ahlstrand, J.:
Miljöövervakning på Obsytorna 1984–2013, Beskrivning, resultat,
utvärdering och framtid, Skogsstyrelsen Rapport 2015:1, 142 pp., available at: https://shopcdn.textalk.se/shop/9098/art21/25828721-150940-Obsytor_webb.pdf (last access: 28 January 2021), 2015.
Akselsson, C., Westling, O., Alveteg, M., Thelin, G., Fransson, A. M., and
Hellsten, S.: The influence of N load and harvest intensity on the risk of P
limitation in Swedish forest soils, Sci. Total Environ., 404, 284–289,
https://doi.org/10.1016/j.scitotenv.2007.11.017, 2008.
Almeida, J. P., Rosenstock, N. P., Forsmark, B., Bergh, J., and Wallander,
H.: Ectomycorrhizal community composition and function in a spruce forest
transitioning between nitrogen and phosphorus limitation, Fungal Ecol.,
40, 20–31,
https://doi.org/10.1016/j.funeco.2018.05.008, 2019.
Andersson, M., Carlsson, M., Ladenberger, A., Morris, G., Sadeghl, M., and
Uhlbäck, J.: Geokemisk atlas över sverige, Sveriges Geologiska Undersökning, Uppsala, Sweden, 2014.
Arheimer, B., Dahné, J., Donnelly, C., Lindström, G., and
Strömqvist, J.: Water and nutrient simulations using the HYPE model for
Sweden vs. the Baltic Sea basin – influence of input-data quality and
scale, Hydrol. Res., 43, 315–329, https://doi.org/10.2166/nh.2012.010, 2012.
Arnold, J. G., Daniel, N. M., Gassman, P. W., Abbaspour, K. C., and White,
M. J.: SWAT: Model use, calibration, and validation, Transactions of the
American Society of Agricultural and Biological Engineers, 55, 1491–1508,
2012.
Averill, C., Turner, B. L., and Finzi, A. C.: Mycorrhiza-mediated
competition between plants and decomposers drives soil carbon storage,
Nature, 505, 543–545, https://doi.org/10.1038/nature12901, 2014.
Bahr, A., Ellström, M., Bergh, J., and Wallander, H.: Nitrogen leaching
and ectomycorrhizal nitrogen retention capacity in a Norway spruce forest
fertilized with nitrogen and phosphorus, Plant Soil, 390, 323–335,
https://doi.org/10.1007/s11104-015-2408-6, 2015.
Barrow, N. J.: The description of desorption of phosphate from soil, J. Soil.
Sci., 30, 259–270, 1979.
Bell, C., Carrillo, Y., Boot, C. M., Rocca, J. D., Pendall, E., and
Wallenstein, M. D.: Rhizosphere stoichiometry: are C : N : P ratios of
plants, soils, and enzymes conserved at the plant species-level?, New
Phytol., 201, 505–517, https://doi.org/10.1111/nph.12531, 2014.
Bolan, N. S.: A critical review on the role of mycorrhizal fungi in the
uptake of phosphorus by plants, Plant Soil, 134, 189–207, 1991.
Braun, S., Thomas, V. F., Quiring, R., and Fluckiger, W.: Does nitrogen
deposition increase forest production? The role of phosphorus, Environ.
Pollut., 158, 2043–2052, https://doi.org/10.1016/j.envpol.2009.11.030, 2010.
Bucher, M.: Functional biology of plant phosphate uptake at root and
mycorrhiza interfaces, New Phytol., 173, 11–26,
https://doi.org/10.1111/j.1469-8137.2006.01935.x, 2007.
Bünemann, E. K.: Enzyme additions as a tool to assess the potential
bioavailability of organically bound nutrients, Soil Biol. Biochem., 40,
2116–2129, https://doi.org/10.1016/j.soilbio.2008.03.001, 2008.
Bünemann, E. K.: Assessment of gross and net mineralization rates of
soil organic phosphorus-A review, Soil Biol. Biochem., 89, 82–98,
https://doi.org/10.1016/j.soilbio.2015.06.026, 2015.
Cintas, O., Berndes, G., Hansson, J., Poudel, B. C., Bergh, J.,
Börjesson, P., Egnell, G., Lundmark, T., and Nordin, A.: The potential
role of forest management in Swedish scenarios towards climate neutrality by
mid century, Forest Ecol. Manag., 383, 73–84, https://doi.org/10.1016/j.foreco.2016.07.015, 2017.
Clemmensen, K. E., Bahr, A., Ovaskainen, O., Dahlberg, A., Ekblad, A.,
Wallander, H., Stenlid, J., Finlay, R. D., Wardle, D. A., and Lindahl, B.
D.: Roots and associated fungi drive long-term carbon sequestration in
boreal forest, Science, 339, 1615–1618, https://doi.org/10.1126/science.1231923, 2013.
Cleveland, C. C. and Liptzin, D.: C:N:P stoichiometry in soil: is there a
“Redfield ratio” for the microbial biomass?, Biogeochemistry, 85, 235–252,
https://doi.org/10.1007/s10533-007-9132-0, 2007.
Cole, C. V., Innis, G. S., and Stewart, J. W. B.: Simulation of Phosphorus
cycling in semiarid grasslands, Ecology, 58, 2–15, 1977.
Crowley, K. F., McNeil, B. E., Lovett, G. M., Canham, C. D., Driscoll, C.
T., Rustad, L. E., Denny, E., Hallett, R. A., Arthur, M. A., Boggs, J. L.,
Goodale, C. L., Kahl, J. S., McNulty, S. G., Ollinger, S. V., Pardo, L. H.,
Schaberg, P. G., Stoddard, J. L., Weand, M. P., and Weathers, K. C.: Do
nutrient limitation patterns shift from Nitrogen toward Phosphorus with
increasing Nitrogen deposition across the northeastern United States?,
Ecosystems, 15, 940–957, https://doi.org/10.1007/s10021-012-9550-2, 2012.
Deng, Q., Hui, D., Dennis, S., and Reddy, K. C.: Responses of terrestrial
ecosystem phosphorus cycling to nitrogen addition: A meta-analysis, Global
Ecol. Biogeogr., 26, 713–728, https://doi.org/10.1111/geb.12576, 2017.
Du, E., Terrer, C., Pellegrini, A. F. A., Ahlström, A., van Lissa, C. J.,
Zhao, X., Xia N., Wu, X., and Jackson, R. B.: Global patterns of terrestrial
nitrogen and phosphorus limitation, Nat. Geosci., 13, 221–226.
https://doi.org/10.1038/s41561-019-0530-4, 2020.
Eckersten, H. and Beier, C.: Comparison of N and C dynamics in two Norway
spruce stands using a process oriented simulation model, Eniron. Pollut., 102,
395–401, https://doi.org/10.1016/S0269-7491(98)80059-6, 1998.
Elser, J. J., Bracken, M. E., Cleland, E. E., Gruner, D. S., Harpole, W. S.,
Hillebrand, H., Ngai, J. T., Seabloom, E. W., Shurin, J. B., and Smith, J.
E.: Global analysis of nitrogen and phosphorus limitation of primary
producers in freshwater, marine and terrestrial ecosystems, Ecol. Lett., 10,
1135–1142, https://doi.org/10.1111/j.1461-0248.2007.01113.x, 2007.
Ericsson, T.: Growth and shoot: root ratio of seedlings in relation to
nutrient availability, Plant Soil, 168, 205–214, 1995.
Fleischer, K., Rammig, A., De Kauwe, M. G., Walker, A. P., Domingues, T. F.,
Fuchslueger, L., Garcia, S., Goll, D. S., Grandis, A., Jiang, M., Haverd,
V., Hofhansl, F., Holm, J. A., Kruijt, B., Leung, F., Medlyn, B. E.,
Mercado, L. M., Norby, R. J., Pak, B., von Randow, C., Quesada, C. A.,
Schaap, K. J., Valverde-Barrantes, O. J., Wang, Y.-P., Yang, X., Zaehle, S.,
Zhu, Q., and Lapola, D. M.: Amazon forest response to CO2 fertilization
dependent on plant phosphorus acquisition, Nat. Geosci., 12, 736–741,
https://doi.org/10.1038/s41561-019-0404-9, 2019.
Fransson, A.-M. and Bergkvist, B.: Phosphorus fertilisation causes durable
enhancement of phosphorus concentrations in forest soil, Forest Ecol. Manag.,
130, 69–76, https://doi.org/10.1016/S0378-1127(99)00184-X, 2000.
Gärdenäs, A., Eckersten, H., and Lillemägi, M.: Modeling
long-term effects of N fertilization and N deposition on the N balances of
forest stands in Sweden, Swedish University of Agricultural Sciences,
34, 1651–7210, 2003.
Gärdenäs, A., Jansson, P.-E., and Karlberg, L.: A model of
accumulation of radionuclides in biosphere originating from groundwater
contamination, SKB report R-06-47, SKB, Solna, Sweden, 2006.
Gärdenäs, A., Ågren, G., Bird, J., Clarholm, M., Hallin, S.,
Ineson, P., Kätterer, T., Knicker, H., Nilsson, I., Näsholm, T.,
Ogle, S., Paustian, K., Persson, T., and Stendahl, J.: Knowledge gaps in
soil carbon and nitrogen interactions – From molecular to global scale,
Soil Biol. Biochem., 43, 702–717,
https://doi.org/10.1016/j.soilbio.2010.04.006, 2011.
Gassman, P. W., Williams, J. R., Benson, V. W., César lzaurralde, R.,
Hauck, L. M., Jones, C. A., Atwood, J. D., Kiniry, J. D., and Flowers, J. D.:
Historical development and applications of the EPIC and APEX models, CARD
working paper 05-WP 397, Center for Agricultural and Rural Development, Iowa
State University, Ames, IA, USA, https://doi.org/10.13031/2013.17074, 2005.
Giesler, R., Petersson, T., and Högberg, P.: Phosphorus limitation in
boreal forests: effects of aluminum and iron accumulation in the humus
layer, Ecosystems, 5, 300–314, https://doi.org/10.1007/s10021-001-0073-5, 2002.
Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P. B., van Bodegom, P. M., and Niinemets, Ü.: Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling, Biogeosciences, 9, 3547–3569, https://doi.org/10.5194/bg-9-3547-2012, 2012.
Goll, D. S., Vuichard, N., Maignan, F., Jornet-Puig, A., Sardans, J., Violette, A., Peng, S., Sun, Y., Kvakic, M., Guimberteau, M., Guenet, B., Zaehle, S., Penuelas, J., Janssens, I., and Ciais, P.: A representation of the phosphorus cycle for ORCHIDEE (revision 4520), Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, 2017.
Gress, E. S., Nichols, T. D., Northcraft, C. C., and Peterjohn, W. T.:
Nutrient limitation in soils exhibiting differing nitrogenavailabilities:
what lies beyond nitrogen saturation?, Ecology, 88, 119–130,
https://doi.org/10.1890/0012-9658(2007)88[119:NLISED]2.0.CO;2, 2007.
Groenendijk, P., Renaud, L. V., and Roelsma, J.: Prediction of nitrogen and
phosphorus leaching to groundwater and surface waters; process descriptions
of the Animo4.0 model, Alterra–Report 983, 114 pp.,
Wageningen, The Netherlands, 2005.
Guidry, M. W. and Machenzie, F. T.: Apatite weathering and the phanerozoic
phosphorus cycle, Geology, 28, 631–634, 2000.
Güsewell, S.: N : P ratios in terrestrial plants: variation and
functional significance, New Phytol., 164, 243–266,
https://doi.org/10.1111/j.1469-8137.2004.01192.x, 2004.
He, H., Meyer, A., Jansson, P.-E., Svensson, M., Rütting, T., and Klemedtsson, L.: Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5), Geosci. Model Dev., 11, 725–751, https://doi.org/10.5194/gmd-11-725-2018, 2018.
He, H., Jansson, P.-E., and Gärdenäs, A.: CoupModel (v6.0): code and evaluating database (Version V 6.0), Zenodo, https://doi.org/10.5281/zenodo.3547628, 2020a.
He, H., Jansson, P.-E., and Gärdenäs, A.: CoupModel (v6.0): Global parameter sensitivity analysis (Version V 6.0), Zenodo, https://doi.org/10.5281/zenodo.4291963, 2020b.
Hinsinger, P.: Bioavailability of soil inorganic P in the rhizosphere as
affected by root-induced chemical changes: a review, Plant Soil, 237,
173–195, 2001.
Högberg, P., Näsholm, T., Franklin, O., and Högberg, M. N.: Tamm
Review: On the nature of the nitrogen limitation to plant growth in
Fennoscandian boreal forests, Forest Ecol. Manag., 403, 161–185,
https://doi.org/10.1016/j.foreco.2017.04.045, 2017.
Ingestad, T.: Mineral nutrient requirements of Pinus silvestris and Picea abies Seedlings,
Physiol. Plantarum, 45, 373–380, 1979.
Ingestad, T. and Ågren, G. I.: Theories and methods on plant nutrient
and growth, Physiol Plantarum, 84, 177–184, 1992.
Jackson-Blake, L. A., Wade, A. J., Futter, M. N., Butterfield, D., Couture,
R. M., Cox, B. A., Crossman, J., Ekholm, P., Halliday, S. J., Jin, L.,
Lawrence, D. S. L., Lepistö, A., Lin, Y., Rankinen, K., and Whitehead,
P. G.: The INtegrated CAtchment model of phosphorus dynamics (INCA-P):
Description and demonstration of new model structure and equations, Environ.
Model. Softw., 83, 356–386, https://doi.org/10.1016/j.envsoft.2016.05.022,
2016.
Jahn, R., Blume, H.-P., Asio, V.-B., Spaargaren, O., and Schad, P.:
Guidelines for soil description, Food and Agriculture
Organization of the United Nations, Rome, Italy, 2006.
Jansson, P. E.: CoupModel: model use, calibration, and validation, T. ASABE,
4, 1335–1344, 2012.
Jansson, P. E. and Karlberg, L.: User manual of Coupled heat and mass
transfer model for soil-plant-atmosphere systems, Royal Institute of
Technology, Department of Land and Water Resources, Stockholm, Sweden, 2011.
Johnson, A. H., Frizano, J., and Vann, D. R.: Biogeochemical implications of
labile phosphorus in forest soils determined by the Hedley fractionation
procedure, Oecologia, 135, 487–499, https://doi.org/10.1007/s00442-002-1164-5, 2003.
Jonard, M., Furst, A., Verstraeten, A., Thimonier, A., Timmermann, V.,
Potocic, N., Waldner, P., Benham, S., Hansen, K., Merila, P., Ponette, Q.,
de la Cruz, A. C., Roskams, P., Nicolas, M., Croise, L., Ingerslev, M.,
Matteucci, G., Decinti, B., Bascietto, M., and Rautio, P.: Tree mineral
nutrition is deteriorating in Europe, Glob. Change Biol., 21, 418–430,
https://doi.org/10.1111/gcb.12657, 2015.
Jones, C. A., Cole, C. V., Sharpley, A. N., and Williams, J. R.: A
simplified soil and plant phosphorus model: I. Documentation, Soil Sci. Soc.
Am. J., 48, 800–805, https://doi.org/10.2136/sssaj1984.03615995004800040020x, 1984.
Kaiser, K. and Kalbitz, K.: Cycling downwards – dissolved organic matter
in soils, Soil Biol. Biochem., 52, 29–32, https://doi.org/10.1016/j.soilbio.2012.04.002, 2012.
Kalbitz, K., Solinger, S., Park, J.-H., Michalzik, B., and Matzner, E.:
Controls on the dynamics of dissolved organic matter in soils: a review,
Soil Sci., 165, 277–304, 2000.
Knisel, W. G. and Turtola, E.: Gleams model application on a heavy clay
soil in Finland, Agr. Water Manage., 43, 285–309,
https://doi.org/10.1016/S0378-3774(99)00067-0, 2000.
Kronnäs, V., Akselsson, C., and Belyazid, S.: Dynamic modelling of weathering rates – the benefit over steady-state modelling, SOIL, 5, 33–47, https://doi.org/10.5194/soil-5-33-2019, 2019.
Lagerström, A., Esberg, C., Wardle, D. A., and Giesler, R.: Soil
phosphorus and microbial response to a long-term wildfire chronosequence in
northern Sweden, Biogeochemistry, 95, 199–213, https://doi.org/10.1007/s10533-009-9331-y,
2009.
Laiho, R. and Prescott, C. E.: Decay and nutrient dynamics of coarse woody
debris in northern coniferous forests: a synthesis, Can. J. Forest Res., 34,
763–777, https://doi.org/10.1139/x03-241, 2004.
Lang, F., Bauhus, J., Frossard, E., George, E., Kaiser, K., Kaupenjohann,
M., Krüger, J., Matzner, E., Polle, A., Prietzel, J., Rennenberg, H.,
and Wellbrock, N.: Phosphorus in forest ecosystems: New insights from an
ecosystem nutrition perspective, J. Plant Nutr. Soil. Sci., 179, 129–135,
https://doi.org/10.1002/jpln.201500541, 2016.
Liebig, J.: Die Chemie in ihrer Andwendung auf Agrikultur und Physiologie,
Vieweg und Söhne, Braunschweig, Germany, 1840.
Linder, S.: Foliar analysis for detecting and correcting nutrient imbalances
in Norway spruce, Ecol. Bull., 44, 178–190, 1995.
Manzoni, S., Trofymow, J. A., Jackson, R. B., and Porporato, A.:
Stoichiometric controls on carbon, nitrogen, and phosphorus dynamics in
decomposing litter, Ecol. Monogr., 80, 89–106, https://doi.org/10.1890/09-0179.1, 2010.
McGill, W. B. and Cole, C. V.: Comparative aspects of cycling of organic C,
N, S and P through soil organic matter, Geoderma, 26, 267–286, 1981.
Medlyn, B. E., De Kauwe, M. G., Zaehle, S., Walker, A. P., Duursma, R. A.,
Luus, K., Mishurov, M., Pak, B., Smith, B., Wang, Y. P., Yang, X., Crous, K.
Y., Drake, J. E., Gimeno, T. E., Macdonald, C. A., Norby, R. J., Power, S.
A., Tjoelker, M. G., and Ellsworth, D. S.: Using models to guide field
experiments: a priori predictions for the CO2 response of a nutrient- and
water-limited native Eucalypt woodland, Glob. Change Biol., 22, 2834–2851,
https://doi.org/10.1111/gcb.13268, 2016.
Meyer, A., Grote, R., Polle, A., and Butterbach-Bahl, K.: Simulating
mycorrhiza contribution to forest C- and N cycling-the MYCOFON model, Plant
Soil, 327, 493–517, https://doi.org/10.1007/s11104-009-0017-y, 2009.
Monteith, J. L.: Evaporation and environment, Symp. Soc. Exp. Biol., 16,
205–234, 1965.
Nasholm, T., Hogberg, P., Franklin, O., Metcalfe, D., Keel, S. G., Campbell,
C., Hurry, V., Linder, S., and Hogberg, M. N.: Are ectomycorrhizal fungi
alleviating or aggravating nitrogen limitation of tree growth in boreal
forests?, New Phytol., 198, 214–221, https://doi.org/10.1111/nph.12139, 2013.
Nehls, U.: Mastering ectomycorrhizal symbiosis: the impact of carbohydrates,
J. Exp. Bot., 59, 1097–1108, https://doi.org/10.1093/jxb/erm334, 2008.
Olander, L. and Vitousek, P.: Short-term controls over inorganic phosphorus
during soil and ecosystem development, Soil Biol. Biochem., 37, 651–659,
https://doi.org/10.1016/j.soilbio.2004.08.022, 2005.
Olsson, M. T., Erlandsson, M., Lundin, L., Nilsson, T., Nilsson, Å., and
Stendahl, J.: Organic carbon stocks in Swedish Podzol soils in relation to
soil hydrology and other site characteristics, Silva Fennica, 43, 209–222,
2009.
Ortiz, C. A., Lundblad, M., Lundström, A., and Stendahl, J.: The effect
of increased extraction of forest harvest residues on soil organic carbon
accumulation in Sweden, Biomass Bioenergy, 70, 230–238,
https://doi.org/10.1016/j.biombioe.2014.08.030, 2014.
Orwin, K. H., Kirschbaum, M. U., St. John, M. G., and Dickie, I. A.: Organic
nutrient uptake by mycorrhizal fungi enhances ecosystem carbon storage: a
model-based assessment, Ecol. Lett., 14, 493–502,
https://doi.org/10.1111/j.1461-0248.2011.01611.x, 2011.
Oulehle, F., Chuman, T., Hruška, J., Krám, P., McDowell, W. H.,
Myška, O., Navrátil, T., and Tesař, M.: Recovery from
acidification alters concentrations and fluxes of solutes from Czech
catchments, Biogeochemistry, 132, 251–272, https://doi.org/10.1007/s10533-017-0298-9, 2017.
Penuelas, J., Poulter, B., Sardans, J., Ciais, P., van der Velde, M., Bopp,
L., Boucher, O., Godderis, Y., Hinsinger, P., Llusia, J., Nardin, E., Vicca,
S., Obersteiner, M., and Janssens, I. A.: Human-induced nitrogen-phosphorus
imbalances alter natural and managed ecosystems across the globe, Nat.
Commun., 4, 2934, https://doi.org/10.1038/ncomms3934, 2013.
Read, D. J. and Perez-Moreno, J.: Mycorrhizas and nutrient cycling in
ecosystems – a journey towards relevance?, New Phytol., 157, 475–492,
https://doi.org/10.1046/j.1469-8137.2003.00704.x, 2003.
Reed, S. C., Yang, X., and Thornton, P. E.: Incorporating phosphorus cycling
into global modeling efforts: a worthwhile, tractable endeavor, New Phytol.,
208, 324–329, https://doi.org/10.1111/nph.13521, 2015.
Richardson, A. E. and Simpson, R. J.: Soil microorganisms mediating
phosphorus availability update on microbial phosphorus, Plant Physiol., 156,
989–996, https://doi.org/10.1104/pp.111.175448, 2011.
Richardson, A. E., Barea, J.-M., McNeill, A. M., and Prigent-Combaret, C.:
Acquisition of phosphorus and nitrogen in the rhizosphere and plant growth
promotion by microorganisms, Plant Soil, 321, 305–339,
https://doi.org/10.1007/s11104-009-9895-2, 2009.
Rosengren-Brinck, U. and Nihlgård, B.: Nutritional status in needles of
Norway spruce in relation to water and nutrient supply, Ecol. Bull., 44,
168–177, 1995.
Rosling, A., Midgley, M. G., Cheeke, T., Urbina, H., Fransson, P., and
Phillips, R. P.: Phosphorus cycling in deciduous forest soil differs between
stands dominated by ecto- and arbuscular mycorrhizal trees, New Phytol., 209,
1184–1195, https://doi.org/10.1111/nph.13720, 2016.
Saito, M. A., Goepfert, T. J., and Ritt, J. T.: Some thoughts on the concept
of colimitation: three definitions and the importance of bioavailability,
Limnol. Oceanogr., 53, 276–290, 2008.
Schachtman, D. P., Reid, R. J., and Ayling, S. M.: Phosphorus uptake by
plants: from soil to cell, Plant Physiol., 116, 447–453, 1998.
Schlesinger, W. H.: Biogeochemistry. An analysis of global change,
Academic Press, Cambridge, MA, USA, 1997.
Schnepf, A. and Roose, T.: Modelling the contribution of arbuscular
mycorrhizal fungi to plant phosphate uptake, New Phytol., 171, 669–682,
https://doi.org/10.1111/j.1469-8137.2006.01771.x, 2006.
SLU: Skogsdata: Aktuella uppgifter om de svenska skogarna från
Riksskogstaxeringen, SLU, Umeå, Sweden, available at:
https://pub.epsilon.slu.se/9266/1/SkogsData2012_webb.pdf
(last access: 10 February 2020), 2012.
Smeck, N. E.: Phosphorus dynamics in soils and landscapes, Geoderma, 36,
185–199, 1985.
Smith, S. E.: Mycorrhizal fungi can dominate phosphate supply to plants
irrespective of growth responses, Plant Physiol., 133, 16–20,
https://doi.org/10.1104/pp.103.024380, 2003.
Smith, S. E. and Read, D. J.: Mycorrhizal symbiosis, 3rd ed., Academic
Press, Cambridge, MA, USA, 2008.
Staddon, P. L., Thompson, K., Jakobsen, I., Grime, J. P., Askew, A. P., and
Fitter, A. H.: Mycorrhizal fungal abundance is affected by long-term
climatic manipulations in the field, Glob. Change Biol., 9, 186–194,
https://doi.org/10.1046/j.1365-2486.2003.00593.x, 2003.
Stendahl, J., Johansson, M.-B., Eriksson, E., Nilsson, Å., and Langvall,
O.: Soil organic carbon in Swedish spruce and pine forests- differences in
stock levels and regional patterns, Silva Fennica, 44, 5–21, 2010.
Sundqvist, M. K., Liu, Z., Giesler, R., and Wardle, D. A.: Plant and
microbial responses to nitrogen and phosphorus addition across an
elevational gradient in subarctic tundra, Ecology, 95, 1819–1835, https://doi.org/10.1890/13-0869.1, 2014.
Svensson, M., Jansson, P.-E., and Berggren Kleja, D.: Modelling soil C
sequestration in spruce forest ecosystems along a Swedish transect based on
current conditions, Biogeochemistry, 89, 95–119, https://doi.org/10.1007/s10533-007-9134-y,
2008.
Sverdrup, H. and Warfvinge, P.: Calculating field weathering rates using a
mechanistic geochemical model PROFILE, Appl. Geochem., 8, 273–283,
https://doi.org/10.1016/0883-2927(93)90042-F, 1993.
Swedish Forest Agency: Grundbok for skogsbrukare, Swedish Forest Agency,
Jönköping, Sweden, 2005.
Talkner, U., Meiwes, K. J., Potočić, N., Seletković, I., Cools,
N., De Vos, B., and Rautio, P.: Phosphorus nutrition of beech (Fagus
sylvatica L.) is decreasing in Europe, Ann. For. Sci., 72, 919–928,
https://doi.org/10.1007/s13595-015-0459-8, 2015.
Tang, Z., Xu, W., Zhou, G., Bai, Y., Li, J., Tang, X., Chen, D., Liu, Q.,
Ma, W., Xiong, G., He, H., He, N., Guo, Y., Guo, Q., Zhu, J., Han, W., Hu,
H., Fang, J., and Xie, Z.: Patterns of plant carbon, nitrogen, and
phosphorus concentration in relation to productivity in China's terrestrial
ecosystems, P. Natl. Acad. Sci. USA, 115, 4033–4038, https://doi.org/10.1073/pnas.1700295114,
2018.
Tarvainen, L., Lutz, M., Rantfors, M., Nasholm, T., and Wallin, G.:
Increased needle nitrogen contents did not improve shoot photosynthetic
performance of mature nitrogen-poor Scots pine trees, Front. Plant Sci., 7,
1051, https://doi.org/10.3389/fpls.2016.01051, 2016.
Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P., and Prentice, I. C.:
Mycorrhizal association as a primary control of the CO2 fertilization
effect, Science, 353, 72–74, https://doi.org/10.1126/science.aaf4610, 2016.
Terrer, C., Jackson, R. B., Prentice, I. C., Keenan, T. F., Kaiser, C.,
Vicca, S., Fisher, J. B., Reich, P. B., Stocker, B. D., Hungate, B. A.,
Peñuelas, J., McCallum, I., Soudzilovskaia, N. A., Cernusak, L. A.,
Talhelm, A. F., Van Sundert, K., Piao, S., Newton, P. C. D., Hovenden, M.
J., Blumenthal, D. M., Liu, Y. Y., Müller, C., Winter, K., Field, C. B.,
Viechtbauer, W., Van Lissa, C. J., Hoosbeek, M. R., Watanabe, M., Koike, T.,
Leshyk, V. O., Polley, H. W., and Franklin, O.: Nitrogen and phosphorus
constrain the CO2 fertilization of global plant biomass, Nat. Clim. Change, 9, 684–689,
https://doi.org/10.1038/s41558-019-0545-2, 2019.
Tessier, J. T. and Raynal, D. J.: Use of nitrogen to phosphorus ratios in
plant tissue as an indicator of nutrient limitation and nitrogen saturation,
J. Appl. Ecol., 40, 523–534, https://doi.org/10.1046/j.1365-2664.2003.00820.x, 2003.
Thelin, G., Rosengren-Brinck, U., Nihlgård, B., and Barkman, A.: Trends
in needle and soil chemistry of Norway spruce and Scots pine stands in South
Sweden 1985–1994, Environ. Poll., 99, 149–158, https://doi.org/10.1016/S0269-7491(97)00192-9,
1998.
Thelin, G., Rosengren, U., Callesen, I., and Ingerslev, M.: The nutrient
status of Norway spruce in pure and in mixed-species stands, For. Ecol. Manage., 160, 115–125, https://doi.org/10.1016/S0378-1127(01)00464-9, 2002.
Thum, T., Caldararu, S., Engel, J., Kern, M., Pallandt, M., Schnur, R., Yu, L., and Zaehle, S.: A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996), Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, 2019.
Tipping, E., Benham, S., Boyle, J. F., Crow, P., Davies, J., Fischer, U.,
Guyatt, H., Helliwell, R., Jackson-Blake, L., Lawlor, A. J., Monteith, D.
T., Rowe, E. C., and Toberman, H.: Atmospheric deposition of phosphorus to
land and freshwater, Environ. Sci. Process. Impacts., 16, 1608–1617,
https://doi.org/10.1039/c3em00641g, 2014.
Van Sundert, K., Radujkovic, D., Cools, N., De Vos, B., Etzold, S.,
Fernandez-Martinez, M., Janssens, I., Merila, P., Penuelas, J., Sardans, J.,
Stendahl, J., Terrer, C., and Vicca, S.: Towards comparable assessment of
the soil nutrient status across scales – review and development of nutrient
metrics, Glob. Change Biol., e26, 392–409, https://doi.org/10.1111/gcb.14802, 2020.
Vincent, A. G., Sundqvist, M. K., Wardle, D. A., and Giesler, R.:
Bioavailable soil phosphorus decreases with increasing elevation in a
subarctic tundra landscape, PLoS One, 9, e92942,
https://doi.org/10.1371/journal.pone.0092942, 2014.
Vitousek, P. M., Porder, S., Houlton, B. Z., and Chadwick, O. A.:
Terrestrial phosphorus limitation: mechanisms, implications, and
nitrogen-phosphorus interactions, Ecol. Appl., 20, 5–15, 2010.
Wallander, H., Mahmood, S., Hagerberg, D., Johansson, L., and Pallon, J.:
Elemental composition of ectomycorrhizal mycelia identified by PCR-RFLP
analysis and grown in contact with apatite or wood ash in forest soil, FEMS
Microbiol. Ecol., 44, 57–65, https://doi.org/10.1111/j.1574-6941.2003.tb01090.x,
2003.
Wang, Y. P., Houlton, B. Z., and Field, C. B.: A model of biogeochemical
cycles of carbon, nitrogen, and phosphorus including symbiotic nitrogen
fixation and phosphatase production, Global Biogeochem. Cy., 21, GB1018,
https://doi.org/10.1029/2006gb002797, 2007.
Wang, Y. P., Law, R. M., and Pak, B.: A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere, Biogeosciences, 7, 2261–2282, https://doi.org/10.5194/bg-7-2261-2010, 2010.
Wijk, S.: Skogsvårdsorganisationens skogliga observationsytor,
Anvisningar för analys av markprover, version 1995-11-15,
Skogsstyrelsen, Jönköping, Sweden, 1995.
Wijk, S.: Skogsvårdsorganisationens skogliga observationsytor, Manual –
anvisningar för urval av träd för barrprovtagning, Version
1997-08-14, Skogsstyrelsen, Jönköping, Sweden, 1997.
Yanai, R. D.: Phosphorus budget of a 70-year-old northern hardwood forest,
Biogeochemistry, 17, 1–22, https://doi.org/10.1007/BF00002757,
1992.
Yang, X., Thornton, P. E., Ricciuto, D. M., and Post, W. M.: The role of phosphorus dynamics in tropical forests – a modeling study using CLM-CNP, Biogeosciences, 11, 1667–1681, https://doi.org/10.5194/bg-11-1667-2014, 2014.
Yu, L., Zanchi, G., Akselsson, C., Wallander, H., and Belyazid, S.: Modeling
the forest phosphorus nutrition in a southwestern Swedish forest site, Ecol.
Model., 369, 88–100, https://doi.org/10.1016/j.ecolmodel.2017.12.018, 2018.
Zhang, J. and Elser, J. J.: Carbon:Nitrogen:Phosphorus stoichiometry in
fungi: a meta-analysis, Front. Microbiol., 8, 1281, https://doi.org/10.3389/fmicb.2017.01281, 2017.
Zhu, Q., Riley, W. J., Tang, J., and Koven, C. D.: Multiple soil nutrient competition between plants, microbes, and mineral surfaces: model development, parameterization, and example applications in several tropical forests, Biogeosciences, 13, 341–363, https://doi.org/10.5194/bg-13-341-2016, 2016.
Short summary
This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, Coup-CNP). The extended Coup-CNP, which explicitly considers the symbiosis between soil microbes and plant roots, enables simulations of coupled C, N, and P dynamics for terrestrial ecosystems. Simulations from the new Coup-CNP model provide strong evidence that P fluxes need to be further considered in studies of how ecosystems and C turnover react to climate change.
This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, Coup-CNP)....
