Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4155-2023
© Author(s) 2023. 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-16-4155-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Jul 2023
Model description paper |
| 25 Jul 2023
| 25 Jul 2023
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
Hideki Ninomiya
Graduate School of Global Food Resources, Hokkaido University,
Sapporo, Hokkaido 060-0809, Japan
Tomomichi Kato
CORRESPONDING AUTHOR
Research Faculty of Agriculture, Hokkaido University, Sapporo,
Hokkaido 060-8589, Japan
Lea Végh
Research Faculty of Agriculture, Hokkaido University, Sapporo,
Hokkaido 060-8589, Japan
Lan Wu
College of Ecology and Environment, Hainan University, Hainan, China
Related authors
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
EGUsphere, https://doi.org/10.5194/egusphere-2024-105, https://doi.org/10.5194/egusphere-2024-105, 2024
Short summary
Short summary
SPITFIRE fire module was integrated into SEIB Dynamic Global Vegetation Model to improve the model's accuracy in depicting forest fire frequency, intensity, and extent in Siberia. Projected fires showed a continuous increase in higher emissions of greenhouse gases and aerosols from 2023 to 2100 under all RCP scenarios. This study contributes to a better understanding of fire dynamics, land ecosystem-climate interactions, and global material cycles under the threat of escalating fires in Siberia.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
EGUsphere, https://doi.org/10.5194/egusphere-2024-105, https://doi.org/10.5194/egusphere-2024-105, 2024
Short summary
Short summary
SPITFIRE fire module was integrated into SEIB Dynamic Global Vegetation Model to improve the model's accuracy in depicting forest fire frequency, intensity, and extent in Siberia. Projected fires showed a continuous increase in higher emissions of greenhouse gases and aerosols from 2023 to 2100 under all RCP scenarios. This study contributes to a better understanding of fire dynamics, land ecosystem-climate interactions, and global material cycles under the threat of escalating fires in Siberia.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
Short summary
Short summary
We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020, https://doi.org/10.5194/gmd-13-4041-2020, 2020
Short summary
Short summary
Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. The canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind SIF emission from complex forest canopies.
Related subject area
Biogeosciences
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
Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0
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
A global behavioural model of human fire use and management: WHAM! v1.0
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)
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): calibration-free calculations of water and energy fluxes
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
In-silico calculation of soil pH by SCEPTER v1.0
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: Simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling
Impact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02
FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics
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.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles D. Koven, Ryan G. Knox, Lara M. Kueppers, and Chonggang Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-191, https://doi.org/10.5194/gmd-2023-191, 2023
Revised manuscript accepted for GMD
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.
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.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James Millington
EGUsphere, https://doi.org/10.5194/egusphere-2023-2162, https://doi.org/10.5194/egusphere-2023-2162, 2023
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.
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.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
EGUsphere, https://doi.org/10.5194/egusphere-2023-1626, https://doi.org/10.5194/egusphere-2023-1626, 2023
Short summary
Short summary
Numerous estimations of water and energy balances heavily depend on empirical equations that necessitate site-specific calibration. This equifinality poses the risk of obtaining 'right answers for wrong reasons.' In this paper, we introduce novel formulations based on first-principles to calculate calibration-free quantities, such as net radiation, evapotranspiration, condensation, soil water content, surface runoff, subsurface lateral flow, and snow-water equivalent.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-137, https://doi.org/10.5194/gmd-2023-137, 2023
Revised manuscript accepted for GMD
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 pH and bulk soil pH is thus crucial to accurate evaluation of alkalinity required to counteract soil acidification and resulting capture of anthropogenic carbon dioxide through the Enhanced Rock Weathering technique. This has been enabled by the updated reactive-transport SCEPTER code and newly developed framework to simulate soil pH.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
EGUsphere, https://doi.org/10.5194/egusphere-2023-1287, https://doi.org/10.5194/egusphere-2023-1287, 2023
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predict their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that important questions related to plant-atmosphere interactions can be addressed, such as the effects of rising CO2 and ozone pollution on carbon uptake of the biosphere. The model has been well validated with both ground and satellite observations.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
Short summary
Short summary
We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
Short summary
Short summary
To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
Short summary
Short summary
Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
Short summary
Short summary
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
Short summary
Short summary
The coastal marine environment serves as a transition zone in the land–ocean continuum and is susceptible to episodic phenomena such as flash floods, which cause massive organic matter deposition. Here, we present a model of sediment early diagenesis that explicitly describes this type of deposition while also incorporating unique flood deposit characteristics. This model can be used to investigate the temporal evolution of marine sediments following abrupt changes in environmental conditions.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022, https://doi.org/10.5194/gmd-15-6863-2022, 2022
Short summary
Short summary
Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.
Cited articles
Adams, H. D., Germino, M. J., Breshears, D. D., Barron-Gafford, G. A.,
Guardiola-Claramonte, M., Zou, C. B., and Huxman, T. E.: Nonstructural leaf
carbohydrate dynamics of Pinus edulis during drought-induced tree mortality reveal role
for carbon metabolism in mortality mechanism, New Phytol., 197,
1142–1151, https://doi.org/10.1111/nph.12102, 2013.
Adams, H. D., Zeppel, M. J. B., Anderegg, W. R. L., Hartmann, H.,
Landhäusser, S. M., Tissue, D. T., Huxman, T. E., Hudson, P. J., Franz,
T. E., Allen, C. D., Anderegg, L. D. L., Barron-Gafford, G. A., Beerling, D.
J., Breshears, D. D., Brodribb, T. J., Bugmann, H., Cobb, R. C., Collins, A.
D., Dickman, L. T., Duan, H., Ewers, B. E., Galiano, L., Galvez, D. A.,
Garcia-Forner, N., Gaylord, M. L., Germino, M. J., Gessler, A., Hacke, U.
G., Hakamada, R., Hector, A., Jenkins, M. W., Kane, J. M., Kolb, T. E., Law,
D. J., Lewis, J. D., Limousin, J. M., Love, D. M., Macalady, A. K.,
Martínez-Vilalta, J., Mencuccini, M., Mitchell, P. J., Muss, J. D.,
O'Brien, M. J., O'Grady, A. P., Pangle, R. E., Pinkard, E. A., Piper, F. I.,
Plaut, J. A., Pockman, W. T., Quirk, J., Reinhardt, K., Ripullone, F., Ryan,
M. G., Sala, A., Sevanto, S., Sperry, J. S., Vargas, R., Vennetier, M., Way,
D. A., Xu, C., Yepez, E. A., and McDowell, N. G.: A multi-species synthesis
of physiological mechanisms in drought-induced tree mortality, Nat. Ecol.
Evol., 1, 1285–1291, https://doi.org/10.1038/s41559-017-0248-x, 2017.
Asaadi, A., Arora, V. K., Melton, J. R., and Bartlett, P.: An improved parameterization of leaf area index (LAI) seasonality in the Canadian Land Surface Scheme (CLASS) and Canadian Terrestrial Ecosystem Model (CTEM) modelling framework, Biogeosciences, 15, 6885–6907, https://doi.org/10.5194/bg-15-6885-2018, 2018.
Braakhekke, M. C., Doelman, J. C., Baas, P., Müller, C., Schaphoff, S., Stehfest, E., and van Vuuren, D. P.: Modeling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model, Earth Syst. Dynam., 10, 617–630, https://doi.org/10.5194/esd-10-617-2019, 2019.
Brutsaert, W.: On a derivable formula for long-wave radiation from clear
skies, Water Resour. Res., 11, 742–744, https://doi.org/10.1029/WR011i005p00742,
1975.
Carbone, M. S., Czimczik, C. I., Keenan, T. F., Murakami, P. F., Pederson,
N., Schaberg, P. G., Xu, X., and Richardson, A. D.: Age, allocation and
availability of nonstructural carbon in mature red maple trees, New Phytol.,
200, 1145–1155, https://doi.org/10.1111/nph.12448, 2013.
Canelles, Q., Aquilué, N., James, P. M. A., Lawler, J., and Brotons, L.:
Global review on interactions between insect pests and other forest
disturbances, Landsc. Ecol., 36, 945–972,
https://doi.org/10.1007/s10980-021-01209-7, 2021.
Chen, Z., Wang, L., Dai, Y., Wan, X., and Liu, S.: Phenology-dependent
variation in the non-structural carbohydrates of broadleaf evergreen species
plays an important role in determining tolerance to defoliation (or
herbivory), Sci. Rep., 7, 10125, https://doi.org/10.1038/s41598-017-09757-2, 2017.
Chuste, P. A., Maillard, P., Bréda, N., Levillain, J., Thirion, E.,
Wortemann, R., and Massonnet, C.: Sacrificing growth and maintaining a
dynamic carbohydrate storage are key processes for promoting beech survival
under prolonged drought conditions, Trees – Struct. Funct., 34, 381–394,
https://doi.org/10.1007/s00468-019-01923-5, 2020.
Dietze, M. C., Sala, A., Carbone, M. S., Czimczik, C. I., Mantooth, J. A.,
Richardson, A. D., and Vargas, R.: Nonstructural carbon in woody plants,
Annu. Rev. Plant Biol., 65, 667–687,
https://doi.org/10.1146/annurev-arplant-050213-040054, 2014.
Furze, M. E., Huggett, B. A., Aubrecht, D. M., Stolz, C. D., Carbone, M. S.,
and Richardson, A. D.: Whole-tree nonstructural carbohydrate storage and
seasonal dynamics in five temperate species, New Phytol., 221,
1466–1477, https://doi.org/10.1111/nph.15462, 2019.
Gough, C. M., Flower, C. E., Vogel, C. S., Dragoni, D., and Curtis, P. S.:
Whole-ecosystem labile carbon production in a north temperate deciduous
forest, Agric. For. Meteorol., 149, 1531–1540,
https://doi.org/10.1016/j.agrformet.2009.04.006, 2009.
Gough, C. M., Flower, C. E., Vogel, C. S., and Curtis, P. S.: Phenological
and temperature controls on the temporal non-structural carbohydrate
dynamics of Populus grandidentata and Quercus rubra, Forests, 1, 65–81, https://doi.org/10.3390/f1010065, 2010.
Gruber, A., Pirkebner, D., Oberhuber, W., and Wieser, G.: Spatial and
seasonal variations in mobile carbohydrates in Pinus cembra in the
timberline ecotone of the Central Austrian Alps, Eur. J. For. Res., 130,
173–179, https://doi.org/10.1007/s10342-010-0419-7, 2011.
Gruber, A., Pirkebner, D., Florian, C., and Oberhuber, W.: No evidence for
depletion of carbohydrate pools in Scots pine (Pinus sylvestris L.) under
drought stress, Plant Biol., 14, 142–148,
https://doi.org/10.1111/j.1438-8677.2011.00467.x, 2012.
Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister: 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.
Hartmann, H., Adams, H. D., Hammond, W. M., Hoch, G., Landhäusser, S.
M., Wiley, E., and Zaehle, S.: Identifying differences in carbohydrate
dynamics of seedlings and mature trees to improve carbon allocation in
models for trees and forests, Environ. Exp. Bot., 152,
7–18, https://doi.org/10.1016/j.envexpbot.2018.03.011, 2018.
Hartmann, H., Bahn, M., Carbone, M., and Richardson, A. D.: Plant carbon
allocation in a changing world – challenges and progress: introduction to a
Virtual Issue on carbon allocation: Introduction to a virtual issue on
carbon allocation, New Phytol., 227, 981–988, https://doi.org/10.1111/nph.16757,
2020.
Hatfield, J. L. and Prueger, J. H.: Temperature extremes: Effect on plant
growth and development, Weather Clim. Extrem., 10, 4–10,
https://doi.org/10.1016/j.wace.2015.08.001, 2015.
He, W., Liu, H., Qi, Y., Liu, F., and Zhu, X.: Patterns in nonstructural
carbohydrate contents at the tree organ level in response to drought
duration, Glob. Change Biol., 26, 3627–3638, https://doi.org/10.1111/gcb.15078,
2020.
Herrera-Ramírez, D., Muhr, J., Hartmann, H., Römermann, C.,
Trumbore, S., and Sierra, C. A.: Probability distributions of nonstructural
carbon ages and transit times provide insights into carbon allocation
dynamics of mature trees, New Phytol., 226, 1299–1311,
https://doi.org/10.1111/nph.16461, 2020.
Hickler, T., Smith, B., Sykes, M. T., Davis, M. B., Sugita, S., and Walker,
K.: Using a generalized vegetation model to simulate vegetation dynamics in
northeastern USA, Ecology, 85, 519–530, https://doi.org/10.1890/02-0344, 2004.
Hoch, G., Richter, A., and Körner, C.: Non-structural carbon compounds in
temperate forest trees, Plant, Cell Environ., 26, 1067–1081,
https://doi.org/10.1046/j.0016-8025.2003.01032.x, 2003.
Huang, J., Kautz, M., Trowbridge, A. M., Hammerbacher, A., Raffa, K. F.,
Adams, H. D., Goodsman, D. W., Xu, C., Meddens, A. J. H., Kandasamy, D.,
Gershenzon, J., Seidl, R., and Hartmann, H.: Tree defence and bark beetles in
a drying world: carbon partitioning, functioning and modelling, New Phytol.,
225, 26–36, https://doi.org/10.1111/nph.16173, 2020.
Hui, D., Deng, Q., Tian, H., and Luo, Y.: Climate Change and Carbon Sequestration in Forest Ecosystems, in: Handbook of Climate Change Mitigation and Adaptation, edited by: Chen, W. Y., Suzuki, T., and Lackner, M., Springer, Cham, 555–594, https://doi.org/10.1007/978-3-319-14409-2_13, 2017.
IPCC: 2014: Climate Change 2014: Synthesis Report. Contribution of Working
Groups I, II and III to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Core Writing Team, Pachauri, R. K., and
Meyer, L. A., IPCC, Geneva, Switzerland, https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf (last access: 5 April 2022), 2014.
Jones, S., Rowland, L., Cox, P., Hemming, D., Wiltshire, A., Williams, K., Parazoo, N. C., Liu, J., da Costa, A. C. L., Meir, P., Mencuccini, M., and Harper, A. B.: The impact of a simple representation of non-structural carbohydrates on the simulated response of tropical forests to drought, Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, 2020.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-Year Reanalysis Project, B. Am. Meteorol.
Soc., 77, 437–472, 1996
Klein, T. and Hoch, G.: Tree carbon allocation dynamics determined using a
carbon mass balance approach, New Phytol., 205, 147–159,
https://doi.org/10.1111/nph.12993, 2015.
Klein Tank, A. M. G., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée, G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L., Kern-Hansen, C., Heino, R., Bessemoulin, P., Müller-Westermeier, G., Tzanakou, M., Szalai, S., Pálsdóttir, T., Fitzgerald, D., Rubin, S., Capaldo, M., Maugeri, M., Leitass, A., Bukantis, A., Aberfeld, R., van Engelen, A. F. V., Forland, E., Mietus, M., Coelho, F., Mares, C., Razuvaev, V., Nieplova, E., Cegnar, T., Antonio López, J., Dahlström, B., Moberg, A., Kirchhofer, W., Ceylan, A., Pachaliuk, O., Alexander, L. V., and Petrovic, P.: Daily dataset of 20th-century
surface air temperature and precipitation series for the European Climate
Assessment, Int. J. Climatol., 22, 1441–1453, 2002.
Körner, C.: Carbon limitation in trees, J. Ecol., 91, 4–17,
https://doi.org/10.1046/j.1365-2745.2003.00742.x, 2003.
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher,
J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic
global vegetation model for studies of the coupled atmosphere-biosphere
system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199,
2005.
Landhäusser, S. M. and Lieffers, V. J.: Seasonal changes in carbohydrate
reserves in mature northern Populus tremuloides clones, Trees – Struct.
Funct., 17, 471–476, https://doi.org/10.1007/s00468-003-0263-1, 2003.
Madani, N., Parazoo, N. C., Kimball, J. S., Ballantyne, A. P., Reichle, R.
H., Maneta, M., Saatchi, S., Palmer, P. I., Liu, Z., and Tagesson, T.: Recent
Amplified Global Gross Primary Productivity Due to Temperature Increase Is
Offset by Reduced Productivity Due to Water Constraints, AGU Adv., 1, e2020AV000180,
https://doi.org/10.1029/2020av000180, 2020.
Martínez-Vilalta, J., Sala, A., Asensio, D., Galiano, L., Hoch, G.,
Palacio, S., Piper, F. I., and Lloret, F.: Dynamics of non-structural
carbohydrates in terrestrial plants: A global synthesis, Ecol. Monogr.,
86, 495–516, https://doi.org/10.1002/ecm.1231, 2016.
McDowell, N., Pockman, W. T., Allen, C. D., Breshears, D. D., Cobb, N.,
Kolb, T., Plaut, J., Sperry, J., West, A., Williams, D. G., and Yepez, E. A.:
Mechanisms of plant survival and mortality during drought: Why do some
plants survive while others succumb to drought?, New Phytol., 178,
719–739, https://doi.org/10.1111/j.1469-8137.2008.02436.x, 2008.
McDowell, N. G.: Mechanisms linking drought, hydraulics, carbon metabolism,
and vegetation mortality, Plant Physiol., 155, 1051–1059,
https://doi.org/10.1104/pp.110.170704, 2011.
McDowell, N. G., Allen, C. D., Anderson-Teixeira, K., Aukema, B. H.,
Bond-Lamberty, B., Chini, L., Clark, J. S., Dietze, M., Grossiord, C.,
Hanbury-Brown, A., Hurtt, G. C., Jackson, R. B., Johnson, D. J., Kueppers,
L., Lichstein, J. W., Ogle, K., Poulter, B., Pugh, T. A. M., Seidl, R.,
Turner, M. G., Uriarte, M., Walker, A. P., and Xu, C.: Pervasive shifts in
forest dynamics in a changing world, Science, 368, eaaz9463,
https://doi.org/10.1126/science.aaz9463, 2020.
Mitchard, E. T. A.: The tropical forest carbon cycle and climate change,
Nature, 559, 527–534, https://doi.org/10.1038/s41586-018-0300-2, 2018.
Ninomiya, H., Kato, T., Végh, L., and Wu, L.: Modeling of non-structural carbohydrate dynamics by the spatially explicitly individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC ver1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.8080601, 2022.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A.,
Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., Ciais, P.,
Jackson, R. B., Pacala, S. W., McGuire, A. D., Piao, S., Rautiainen, A.,
Sitch, S., and Hayes, D.: A large and persistent carbon sink in the world's
forests, Science, 333, 988–993, https://doi.org/10.1126/science.1201609, 2011.
Rademacher, T., Fonti, P., LeMoine, J. M., Fonti, M. V., Basler, D., Chen,
Y., Friend, A. D., Seyednasrollah, B., Eckes-Shephard, A. H., and Richardson,
A. D.: Manipulating phloem transport affects wood formation but not local
nonstructural carbon reserves in an evergreen conifer, Plant Cell Environ.,
44, 2506–2521, https://doi.org/10.1111/pce.14117, 2021.
Richardson, A. D., Carbone, M. S., Keenan, T. F., Czimczik, C. I.,
Hollinger, D. Y., Murakami, P., Schaberg, P. G., and Xu, X.: Seasonal
dynamics and age of stemwood nonstructural carbohydrates in temperate forest
trees, New Phytol., 197, 850–861, https://doi.org/10.1111/nph.12042, 2013.
Sala, A., Woodruff, D. R., and Meinzer, F. C.: Carbon dynamics in trees:
Feast or famine?, Tree Physiol., 32, 764–775,
https://doi.org/10.1093/treephys/tpr143, 2012.
Sato, H. and Ise, T.: Effect of plant dynamic processes on African
vegetation responses to climate change: Analysis using the spatially
explicit individual-based dynamic global vegetation model (SEIB-DGVM), J.
Geophys. Res.-Biogeo., 117, G03017, https://doi.org/10.1029/2012JG002056, 2012.
Sato, H., Itoh, A., and Kohyama, T.: SEIB-DGVM: A new Dynamic Global
Vegetation Model using a spatially explicit individual-based approach, Ecol.
Modell., 200, 279–307, https://doi.org/10.1016/j.ecolmodel.2006.09.006, 2007.
Sato, H., Kobayashi, H., Iwahana, G., and Ohta, T.: Endurance of larch
forest ecosystems in eastern Siberia under warming trends, Ecol. Evol., 6,
5690–5704, https://doi.org/10.1002/ece3.2285, 2016.
Sato, H., Kobayashi, H., Beer, C., and Fedorov, A.: Simulating interactions
between topography, permafrost, and vegetation in Siberian larch forest,
Environ. Res. Lett., 15, 095006, https://doi.org/10.1088/1748-9326/ab9be4, 2020.
Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M.,
Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M. J.,
Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T. A., and Reyer,
C. P. O.: Forest disturbances under climate change, Nat. Clim. Change, 7,
395–402, https://doi.org/10.1038/nclimate3303, 2017.
Sevanto, S. and Dickman, L. T.: Where does the carbon go?-Plant carbon
allocation under climate change, Tree Physiol., 35, 581–584,
https://doi.org/10.1093/treephys/tpv059, 2015.
Signori-Müller, C., Oliveira, R. S., Valentim Tavares, J., Carvalho
Diniz, F., Gilpin, M., de V. Barros, F., Marca Zevallos, M. J., Salas
Yupayccana, C. A., Nina, A., Brum, M., Baker, T. R., Cosio, E. G., Malhi,
Y., Monteagudo Mendoza, A., Phillips, O. L., Rowland, L., Salinas, N.,
Vasquez, R., Mencuccini, M., and Galbraith, D.: Variation of non-structural
carbohydrates across the fast–slow continuum in Amazon Forest canopy trees,
Funct. Ecol., 36, 341–355, https://doi.org/10.1111/1365-2435.13971, 2022.
Singh, K. P. and Srivastava, K.: Seasonal variation in the biomass and
non-structural carbohydrate content of fine roots of teak (Tectona grandis
L. f.) plantations in a dry tropical region, Tree Physiol., 1, 31–36,
https://doi.org/10.1093/treephys/1.1.31, 1986.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation
dynamics in the modelling of terrestrial ecosystems: Comparing two
contrasting approaches within European climate space, Glob. Ecol. Biogeogr.,
10, 621–637, https://doi.org/10.1046/j.1466-822X.2001.t01-1-00256.x, 2001.
Smith, M. G., Miller, R. E., Arndt, S. K., Kasel, S., and Bennett, L. T.:
Whole-tree distribution and temporal variation of non-structural
carbohydrates in broadleaf evergreen trees, Tree Physiol, 38, 570–581,
https://doi.org/10.1093/treephys/tpx141, 2018.
Stevens-Rumann, C. S., Kemp, K. B., Higuera, P. E., Harvey, B. J., Rother,
M. T., Donato, D. C., Morgan, P., and Veblen, T. T.: Evidence for declining
forest resilience to wildfires under climate change, Ecol. Lett., 21,
243–252, https://doi.org/10.1111/ele.12889, 2018.
Sveinbjörnsson, B., Smith, M., Traustason, T., Ruess, R. W., and
Sullivan, P. F.: Variation in carbohydrate source-sink relations of forest
and treeline white spruce in southern, interior and northern Alaska,
Oecologia, 163, 833–843, https://doi.org/10.1007/s00442-010-1597-1, 2010.
Tei, S., Sugimoto, A., Liang, M., Yonenobu, H., Matsuura, Y., Osawa, A.,
Sato, H., Fujinuma, J., and Maximov, T.: Radial Growth and Physiological
Response of Coniferous Trees to Arctic Amplification, J. Geophys. Res.-Biogeo., 122, 2786–2803, https://doi.org/10.1002/2016JG003745, 2017.
Wang, Z., Zhou, Z., and Wang, C.: Defoliation-induced tree growth declines
are jointly limited by carbon source and sink activities, Sci. Total
Environ., 762, 143077, https://doi.org/10.1016/j.scitotenv.2020.143077, 2021.
Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., Nozawa, T., Kawase, H., Abe, M., Yokohata, T., Ise, T., Sato, H., Kato, E., Takata, K., Emori, S., and Kawamiya, M.: MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments, Geosci. Model Dev., 4, 845–872, https://doi.org/10.5194/gmd-4-845-2011, 2011.
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and
Viterbo, P.: The WFDEI Meteorological Forcing Data, Research Data Archive at
the National Center for Atmospheric Research, Computational and Information
Systems Laboratory [data set], https://doi.org/10.5065/486N-8109, 2018.
Woodruff, D. R. and Meinzer, F. C.: Water stress, shoot growth and storage
of non-structural carbohydrates along a tree height gradient in a tall
conifer, Plant, Cell Environ., 34, 1920–1930,
https://doi.org/10.1111/j.1365-3040.2011.02388.x, 2011.
Würth, M. K. R., Peláez-Riedl, S., Wright, S. J., and Körner, C.:
Non-structural carbohydrate pools in a tropical forest, Oecologia, 143,
11–24, https://doi.org/10.1007/s00442-004-1773-2, 2005.
Xu, C., Liu, H., Anenkhonov, O. A., Korolyuk, A. Y., Sandanov, D. V.,
Balsanova, L. D., Naidanov, B. B., and Wu, X.: Long-term forest resilience to
climate change indicated by mortality, regeneration, and growth in semiarid
southern Siberia, Glob. Change Biol., 23, 2370–2382,
https://doi.org/10.1111/gcb.13582, 2017.
Zheng, Y., Shen, R., Wang, Y., Li, X., Liu, S., Liang, S., Chen, J. M., Ju, W., Zhang, L., and Yuan, W.: Improved estimate of global gross primary production for reproducing its long-term variation, 1982–2017, Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, 2020.
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of...
