Articles | Volume 16, issue 6
https://doi.org/10.5194/gmd-16-1661-2023
© 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-16-1661-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
23 Mar 2023
Model evaluation paper |
| 23 Mar 2023
| 23 Mar 2023
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Arthur Guignabert
CORRESPONDING AUTHOR
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, Belgium
Quentin Ponette
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, Belgium
Frédéric André
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, Belgium
Christian Messier
Centre d'Étude de la Forêt, Université du Québec
à Montréal, Montréal, QC, Canada
Institut des Sciences de la Forêt Tempérée,
Université du Québec en Outaouais, Ripon, QC, Canada
Philippe Nolet
Centre d'Étude de la Forêt, Université du Québec
à Montréal, Montréal, QC, Canada
Institut des Sciences de la Forêt Tempérée,
Université du Québec en Outaouais, Ripon, QC, Canada
Mathieu Jonard
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, Belgium
Related authors
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Jeanne Rezsöhazy, Hugues Goosse, Joël Guiot, Fabio Gennaretti, Etienne Boucher, Frédéric André, and Mathieu Jonard
Clim. Past, 16, 1043–1059, https://doi.org/10.5194/cp-16-1043-2020, https://doi.org/10.5194/cp-16-1043-2020, 2020
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Tree rings are the main data source for climate reconstructions over the last millennium. Statistical tree-growth models have limitations that process-based models could overcome. Here, we investigate the possibility of using a process-based ecophysiological model (MAIDEN) as a complex proxy system model for palaeoclimate applications. We show its ability to simulate tree-growth index time series that can fit robustly tree-ring width observations under certain conditions.
Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
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Given their key role in the simulation of climate impacts on tree growth, phenological and water balance processes must be integrated in models simulating forest dynamics under a changing environment. Here, we describe these processes integrated in HETEROFOR, a model accounting simultaneously for the functional, structural and spatial complexity to explore the forest response to forestry practices. The model evaluation using phenological and soil water content observations is quite promising.
Mathieu Jonard, Frédéric André, François de Coligny, Louis de Wergifosse, Nicolas Beudez, Hendrik Davi, Gauthier Ligot, Quentin Ponette, and Caroline Vincke
Geosci. Model Dev., 13, 905–935, https://doi.org/10.5194/gmd-13-905-2020, https://doi.org/10.5194/gmd-13-905-2020, 2020
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To explore the forest response to new forestry practices under a changing environment, one needs models combining a process-based approach with a detailed spatial representation, which is very rare. We decided to develop our own model according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). A first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size–growth relationships.
Zhun Mao, Delphine Derrien, Markus Didion, Jari Liski, Thomas Eglin, Manuel Nicolas, Mathieu Jonard, and Laurent Saint-André
Biogeosciences, 16, 1955–1973, https://doi.org/10.5194/bg-16-1955-2019, https://doi.org/10.5194/bg-16-1955-2019, 2019
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In a context of global changes, modeling and predicting the dynamics of soil carbon stocks in forest ecosystems are vital but challenging. Yasso07 is considered to be one of the most promising models for such a purpose. We examine the accuracy of its prediction of soil carbon dynamics over the whole French metropolitan territory at a decennial timescale. We revealed how the bottleneck in soil carbon modeling is linked with the lack of knowledge on soil carbon quality and fine-root litter.
Marta Camino-Serrano, Elisabeth Graf Pannatier, Sara Vicca, Sebastiaan Luyssaert, Mathieu Jonard, Philippe Ciais, Bertrand Guenet, Bert Gielen, Josep Peñuelas, Jordi Sardans, Peter Waldner, Sophia Etzold, Guia Cecchini, Nicholas Clarke, Zoran Galić, Laure Gandois, Karin Hansen, Jim Johnson, Uwe Klinck, Zora Lachmanová, Antti-Jussi Lindroos, Henning Meesenburg, Tiina M. Nieminen, Tanja G. M. Sanders, Kasia Sawicka, Walter Seidling, Anne Thimonier, Elena Vanguelova, Arne Verstraeten, Lars Vesterdal, and Ivan A. Janssens
Biogeosciences, 13, 5567–5585, https://doi.org/10.5194/bg-13-5567-2016, https://doi.org/10.5194/bg-13-5567-2016, 2016
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We investigated the long-term trends of dissolved organic carbon (DOC) in soil solution and the drivers of changes in over 100 forest monitoring plots across Europe. An overall increasing trend was detected in the organic layers, but no overall trend was found in the mineral horizons. There are strong interactions between controls acting at local and regional scales. Our findings are relevant for researchers focusing on the link between terrestrial and aquatic ecosystems and for C-cycle models.
Related subject area
Biogeosciences
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
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
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
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible and integrated plankton community modeling environment in Python
The community-centered aquatic biogeochemistry model unified RIVE v1.0: a unified version for water column
SAMM version 1.0: A numerical model for microbial mediated soil aggregate formation
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
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
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
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
Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0)
Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon
SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level
Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation
Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP)
CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5)
The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0
A validation standard for area of habitat maps for terrestrial birds and mammals
Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9
Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
A map of global peatland extent created using machine learning (Peat-ML)
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
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The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
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We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
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Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
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We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
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Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
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In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
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Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
EGUsphere, https://doi.org/10.5194/egusphere-2023-1697, https://doi.org/10.5194/egusphere-2023-1697, 2023
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Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool-set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool-set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models, to find the most appropriate one.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-135, https://doi.org/10.5194/gmd-2023-135, 2023
Revised manuscript accepted for GMD
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This paper presents unified RIVE v1.0, a unified version of aquatic biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganisms’ 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.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
EGUsphere, https://doi.org/10.5194/egusphere-2023-1414, https://doi.org/10.5194/egusphere-2023-1414, 2023
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To manage soil organic matter sustainably, we need to better understand the role that soil microbes play in aggregate protection. Here, we propose a 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.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
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Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
EGUsphere, https://doi.org/10.5194/egusphere-2023-1075, https://doi.org/10.5194/egusphere-2023-1075, 2023
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Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-107, https://doi.org/10.5194/gmd-2023-107, 2023
Revised manuscript accepted for GMD
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Rémy Fieuzal, and Eric Ceschia
EGUsphere, https://doi.org/10.5194/egusphere-2023-48, https://doi.org/10.5194/egusphere-2023-48, 2023
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Quantification of Carbon fluxes of crops is an essential brick for the construction of a Monitoring, Reporting and Verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates through an efficient 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, yield maps, and analysed at regional scale.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Marcus Falls, Raffaele Bernardello, Miguel Castrillo, Mario Acosta, Joan Llort, and Martí Galí
Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, https://doi.org/10.5194/gmd-15-5713-2022, 2022
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This paper describes and tests a method which uses a genetic algorithm (GA), a type of optimisation algorithm, on an ocean biogeochemical model. The aim is to produce a set of numerical parameters that best reflect the observed data of particulate organic carbon in a specific region of the ocean. We show that the GA can provide optimised model parameters in a robust and efficient manner and can also help detect model limitations, ultimately leading to a reduction in the model uncertainties.
Julien Ruffault, François Pimont, Hervé Cochard, Jean-Luc Dupuy, and Nicolas Martin-StPaul
Geosci. Model Dev., 15, 5593–5626, https://doi.org/10.5194/gmd-15-5593-2022, https://doi.org/10.5194/gmd-15-5593-2022, 2022
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A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
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Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jiaying Zhang, Rafael L. Bras, Marcos Longo, and Tamara Heartsill Scalley
Geosci. Model Dev., 15, 5107–5126, https://doi.org/10.5194/gmd-15-5107-2022, https://doi.org/10.5194/gmd-15-5107-2022, 2022
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We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105, https://doi.org/10.5194/gmd-15-5093-2022, https://doi.org/10.5194/gmd-15-5093-2022, 2022
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This paper describes the validation of area of habitat (AOH) maps produced for terrestrial birds and mammals. The main objective was to assess the accuracy of the maps based on independent data. We used open access data from repositories, such as ebird and gbif to check if our maps were a better reflection of species' distribution than random. When points were not available we used logistic models to validate the AOH maps. The majority of AOH maps were found to have a high accuracy.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
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Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
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We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
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Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Cited articles
Acton, D. F., Ryder, J. M., French, H., Slaymaker, O., and Brookes, I. A.:
Physiographic Regions, in: The Canadian Encyclopedia, https://www.thecanadianencyclopedia.ca/en/article/physiographic-regions (last access: 1 March 2021), 2015.
Ameztegui, A., Paquette, A., Shipley, B., Heym, M., Messier, C., and Gravel,
D.: Shade tolerance and the functional trait: demography relationship in
temperate and boreal forests, Funct. Ecol., 31, 821–830,
https://doi.org/10.1111/1365-2435.12804, 2017.
Anderson-Teixeira, K. J., McGarvey, J. C., Muller-Landau, H. C., Park, J.
Y., Gonzalez-Akre, E. B., Herrmann, V., Bennett, A. C., So, C. V., Bourg, N.
A., Thompson, J. R., McMahon, S. M., and McShea, W. J.: Size-related scaling
of tree form and function in a mixed-age forest, Funct. Ecol., 29,
1587–1602, https://doi.org/10.1111/1365-2435.12470, 2015.
André, F., Jonard, M., and Ponette, Q.: Influence of species and rain
event characteristics on stemflow volume in a temperate mixed oak-beech
stand, Hydrol. Process., 22, 4455–4466, https://doi.org/10.1002/hyp.7048,
2008.
André, F., de Wergifosse, L., de Coligny, F., Beudez, N., Ligot, G.,
Gauthray-Guyénet, V., Courbaud, B., and Jonard, M.: Radiative transfer
modeling in structurally complex stands: towards a better understanding of
parametrization, Ann. For. Sci., 78, 92,
https://doi.org/10.1007/s13595-021-01106-8, 2021.
Andrews, C., Weiskittel, A., D'Amato, A. W., and Simons-Legaard, E.:
Variation in the maximum stand density index and its linkage to climate in
mixed species forests of the North American Acadian Region, Forest Ecol.
Manag., 417, 90–102, https://doi.org/10.1016/j.foreco.2018.02.038, 2018.
Aquilué, N., Messier, C., Martins, K. T., Dumais-Lalonde, V., and Mina,
M.: A simple-to-use management approach to boost adaptive capacity of
forests to global uncertainty, Forest Ecol. Manag., 481,
https://doi.org/10.1016/j.foreco.2020.118692, 2021.
Aubin, I., Beaudet, M., and Messier, C.: Light extinction coefficients
specific to the understory vegetation of the southern boreal forest, Quebec,
Can. J. Forest Res., 30, 168–177, https://doi.org/10.1139/x99-185, 2000.
Aubin, I., Munson, A. D., Cardou, F., Burton, P. J., Isabel, N., Pedlar, J.
H., Paquette, A., Taylor, A. R., Delagrange, S., Kebli, H., Messier, C.,
Shipley, B., Valladares, F., Kattge, J., Boisvert-Marsh, L., and McKenney,
D.: Traits to stay, traits to move: a review of functional traits to assess
sensitivity and adaptive capacity of temperate and boreal trees to climate
change, Environ. Rev., 24, 164–186, https://doi.org/10.1139/er-2015-0072,
2016.
Bell, B., Hersbach, H., Simmons, A., Berrisford, P., Dahlgren, P.,
Horányi, A., Muñoz-Sabater, J., Nicolas, J., Radu, R., Schepers, D.,
Soci, C., Villaume, S., Bidlot, J., Haimberger, L., Woollen, J., Buontempo,
C., and Thépaut, J.: The ERA5 global reanalysis: Preliminary extension
to 1950, Q. J. Roy. Meteor. Soc., 147, 4186–4227, https://doi.org/10.1002/qj.4174, 2021.
Bohn, F. J., Frank, K., and Huth, A.: Of climate and its resulting tree
growth: Simulating the productivity of temperate forests, Ecol. Modell.,
278, 9–17, https://doi.org/10.1016/J.ECOLMODEL.2014.01.021, 2014.
Bokalo, M., Stadt, K., Comeau, P., and Titus, S.: The Validation of the
Mixedwood Growth Model (MGM) for Use in Forest Management Decision Making,
Forests, 4, 1–27, https://doi.org/10.3390/f4010001, 2013.
Bolstad, P. V. and Gower, S. T.: Estimation of leaf area index in fourteen
southern Wisconsin forest stands using a portable radiometer, Tree Physiol.,
7, 115–124, https://doi.org/10.1093/treephys/7.1-2-3-4.115, 1990.
Bond-Lamberty, B., Wang, C., and Gower, S. T.: Aboveground and belowground
biomass and sapwood area allometric equations for six boreal tree species of
northern Manitoba, Can. J. Forest Res., 32, 1441–1450,
https://doi.org/10.1139/x02-063, 2002.
Bovard, B. D., Curtis, P. S., Vogel, C. S., Su, H.-B., and Schmid, H. P.:
Environmental controls on sap flow in a northern hardwood forest, Tree
Physiol., 25, 31–38, https://doi.org/10.1093/treephys/25.1.31, 2005.
Bréda, N. J. J.: Ground-based measurements of leaf area index: a review of
methods, instruments and current controversies, J. Exp. Bot., 54,
2403–2417, https://doi.org/10.1093/jxb/erg263, 2003.
Brockerhoff, E. G., Barbaro, L., Castagneyrol, B., Forrester, D. I.,
Gardiner, B., González-Olabarria, J. R., Lyver, P. O. B., Meurisse, N.,
Oxbrough, A., Taki, H., Thompson, I. D., van der Plas, F., and Jactel, H.:
Forest biodiversity, ecosystem functioning and the provision of ecosystem
services, Biodivers. Conserv., 26, 3005–3035,
https://doi.org/10.1007/s10531-017-1453-2, 2017.
Carpentier, J.-P.: Modélisation de la croissance et du rendement des
peuplements d'érable à sucre, Gouvernement du Québec,
Ministère de l'Energie et des Ressources, Direction de la recherche et
du développement, Mémoire de recherche forestière no. 91, 1987.
Chuine, I.: A Unified Model for Budburst of Trees, J. Theor. Biol., 207,
337–347, https://doi.org/10.1006/jtbi.2000.2178, 2000.
Chuine, I., de Cortazar-Atauri, I. G., Kramer, K., and Hänninen, H.:
Plant Development Models, in: Phenology: An Integrative Environmental
Science, Springer Netherlands, Dordrecht, 275–293,
https://doi.org/10.1007/978-94-007-6925-0_15, 2013.
Coates, K. D., Canham, C. D., Beaudet, M., Sachs, D. L., and Messier, C.:
Use of a spatially explicit individual-tree model (SORTIE/BC) to explore the
implications of patchiness in structurally complex forests, Forest Ecol.
Manag., 186, 297–310, https://doi.org/10.1016/S0378-1127(03)00301-3, 2003.
Coleman, M. D., Dickson, R. E., and Isebrands, J. G.: Contrasting fine-root
production, survival and soil CO2 efflux in pine and poplar plantations,
Plant Soil, 225, 129–139, https://doi.org/10.1023/A:1026564228951, 2000.
Courbaud, B., de Coligny, F., and Cordonnier, T.: Simulating radiation
distribution in a heterogeneous Norway spruce forest on a slope, Agr. Forest
Meteorol., 116, 1–18, https://doi.org/10.1016/S0168-1923(02)00254-X, 2003.
Crimmins, T. M. and Crimmins, M. A.: Plant Phenology Site Phenometrics +
Accumulated Growing Degree Day Calculations for the continental United
States (2009–2016): U.S. Geological Survey data release, GS ScienceBase [data set],
https://doi.org/10.5066/F7XG9Q0X, 2017.
Deleuze, C., Morneau, F., Renaud, J. P., Vivien, Y., Rivoire, M.,
Santenoise, P., Longuetaud, F., Mothe, F., and Hervé, J. C.: Estimation
harmonisée du volume de tige à différentes découpes,
Rendez-vous Tech. ONF, 44, 33–42, 2014a.
Deleuze, C., Morneau, F., Renaud, J. P., Vivien, Y., Rivoire, M.,
Santenoise, P., Longuetaud, F., Mothe, F., Hervé, J. C., and Vallet, P.:
Estimer le volume total d'un arbre, quelles que soient l'essence, la taille,
la sylviculture, la station, Rendez-vous Tech. ONF, 44, 22–32,
2014b.
del Río, M., Löf, M., Bravo-Oviedo, A., and Jactel, H.:
Understanding the complexity of mixed forest functioning and management:
Advances and perspectives, Forest Ecol. Manag., 489, 119138,
https://doi.org/10.1016/j.foreco.2021.119138, 2021.
de Wergifosse, L., André, F., Beudez, N., de Coligny, F., Goosse, H., Jonard, F., Ponette, Q., Titeux, H., Vincke, C., and Jonard, M.: HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 2: Phenology and water cycle, Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, 2020.
de Wergifosse, L., André, F., Goosse, H., Boczon, A., Cecchini, S.,
Ciceu, A., Collalti, A., Cools, N., D'Andrea, E., De Vos, B., Hamdi, R.,
Ingerslev, M., Knudsen, M. A., Kowalska, A., Leca, S., Matteucci, G.,
Nord-Larsen, T., Sanders, T. G., Schmitz, A., Termonia, P., Vanguelova, E.,
Van Schaeybroeck, B., Verstraeten, A., Vesterdal, L., and Jonard, M.:
Simulating tree growth response to climate change in structurally diverse
oak and beech forests, Sci. Total Environ., 806, 150422,
https://doi.org/10.1016/j.scitotenv.2021.150422, 2022.
Dufour-Kowalski, S., Courbaud, B., Dreyfus, P., Meredieu, C., and de
Coligny, F.: Capsis: an open software framework and community for forest
growth modelling, Ann. Forest Sci., 69, 221–233,
https://doi.org/10.1007/s13595-011-0140-9, 2012.
Dufrêne, E., Davi, H., François, C., Maire, G. le, Dantec, V. Le,
and Granier, A.: Modelling carbon and water cycles in a beech forest, Ecol.
Modell., 185, 407–436, https://doi.org/10.1016/j.ecolmodel.2005.01.004,
2005.
Eyre, F. H.: Forest cover types of United States and Canada, edited by:
Society of American Foresters, Washington, DC, 148 pp., ISBN 9780686306979, 1980.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149,
78–90, https://doi.org/10.1007/BF00386231, 1980.
Fontes, L., Bontemps, J.-D., Bugmann, H., Van Oijen, M., Gracia, C., Kramer,
K., Lindner, M., Rötzer, T., and Skovsgaard, J. P.: Models for
supporting forest management in a changing environment, For. Syst., 3, 8–29,
https://doi.org/10.5424/fs/201019S-9315, 2010.
Forrester, D. I.: The spatial and temporal dynamics of species interactions
in mixed-species forests: From pattern to process, Forest Ecol. Manag., 312,
282–292, https://doi.org/10.1016/j.foreco.2013.10.003, 2014.
Forrester, D. I.: Linking forest growth with stand structure: Tree size
inequality, tree growth or resource partitioning and the asymmetry of
competition, Forest Ecol. Manag., 447, 139–157,
https://doi.org/10.1016/j.foreco.2019.05.053, 2019.
Forrester, D. I., Hobi, M. L., Mathys, A. S., Stadelmann, G., and Trotsiuk,
V.: Calibration of the process-based model 3-PG for major central European
tree species, Eur. J. Forest Res., 140, 847–868,
https://doi.org/10.1007/s10342-021-01370-3, 2021.
Gonzalez-Benecke, C. A., Jokela, E. J., Cropper, W. P., Bracho, R., and
Leduc, D. J.: Parameterization of the 3-PG model for Pinus elliottii stands
using alternative methods to estimate fertility rating, biomass
partitioning and canopy closure, Forest Ecol. Manag., 327, 55–75,
https://doi.org/10.1016/j.foreco.2014.04.030, 2014.
Gonzalez-Benecke, C. A., Teskey, R. O., Martin, T. A., Jokela, E. J., Fox,
T. R., Kane, M. B., and Noormets, A.: Regional validation and improved
parameterization of the 3-PG model for Pinus taeda stands, Forest Ecol. Manag., 361, 237–256,
https://doi.org/10.1016/j.foreco.2015.11.025, 2016.
Grote, R. and Pretzsch, H.: A Model for Individual Tree Development Based on
Physiological Processes, Plant Biol., 4, 167–180,
https://doi.org/10.1055/s-2002-25743, 2002.
Guignabert, A., Ponette, Q., André, F., Messier, C., Nolet, P., and
Jonard, M.: Validation of a new spatially-explicit process-based model
(HETEROFOR) to simulate structurally and compositionally complex stands in
Eastern North-America: Dataset (Version 1), Zenodo [data set],
https://doi.org/10.5281/zenodo.7225303, 2022.
Hadiwijaya, B., Pepin, S., Isabelle, P.-E., and Nadeau, D. F.: The Dynamics
of Transpiration to Evapotranspiration Ratio under Wet and Dry Canopy
Conditions in a Humid Boreal Forest, Forests, 11, 237,
https://doi.org/10.3390/f11020237, 2020.
Hernandez-Hernandez, A.: Effects of nutrient amendments on water use and
water use efficiency in a Northeastern forest ecosystem, University of New
Hampshire, 65 pp., 2014.
Hernandez-Santana, V., Hernandez-Hernandez, A., Vadeboncoeur, M. A., and
Asbjornsen, H.: Scaling from single-point sap velocity measurements to stand
transpiration in a multispecies deciduous forest: uncertainty sources, stand
structure effect, and future scenarios, Can. J. Forest Res., 45, 1489–1497,
https://doi.org/10.1139/cjfr-2015-0009, 2015.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Jactel, H., Moreira, X., and Castagneyrol, B.: Tree Diversity and Forest
Resistance to Insect Pests: Patterns, Mechanisms, and Prospects, Annu. Rev.
Entomol., 66, 277–296, https://doi.org/10.1146/annurev-ento-041720-075234,
2021.
Jonard, M., André, F., and de Wergifosse, L.: Code of HETEROFOR 1.0, Zenodo [code],
https://doi.org/10.5281/zenodo.3591348, 2019.
Jonard, M., André, F., de Coligny, F., de Wergifosse, L., Beudez, N., Davi, H., Ligot, G., Ponette, Q., and Vincke, C.: HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 1: Carbon fluxes and tree dimensional growth, Geosci. Model Dev., 13, 905–935, https://doi.org/10.5194/gmd-13-905-2020, 2020.
Jurjević, L., Liang, X., Gašparović, M., and Balenović, I.:
Is field-measured tree height as reliable as believed – Part II, A
comparison study of tree height estimates from conventional field
measurement and low-cost close-range remote sensing in a deciduous forest,
ISPRS J. Photogramm., 169, 227–241,
https://doi.org/10.1016/J.ISPRSJPRS.2020.09.014, 2020.
Kenefic, L. S. and Seymour, R. S.: Leaf area prediction models for Tsuga canadensis in
Maine, Can. J. Forest Res., 29, 1574–1582,
https://doi.org/10.1139/cjfr-29-10-1574, 1999.
Kitajima, K. and Fenner, M.: Ecology of seedling regeneration, in: Seeds:
the ecology of regeneration in plant communities, CAB International,
Wallingford, UK, 331–359, https://doi.org/10.1079/9780851994321.0331, 2000.
König, L. A., Mohren, F., Schelhaas, M.-J., Bugmann, H., and Nabuurs,
G.-J.: Tree regeneration in models of forest dynamics – Suitability to
assess climate change impacts on European forests, Forest Ecol. Manag., 520,
120390, https://doi.org/10.1016/J.FORECO.2022.120390, 2022.
Korol, R. L., Running, S. W., and Milner, K. S.: Incorporating intertree
competition into an ecosystem model, Can. J. Forest Res., 25, 413–424,
https://doi.org/10.1139/x95-046, 1995.
Krasowski, M. J., Lavigne, M. B., Szuter, M. A., Olesinski, J., Kershaw, J.
A., and McGarrigle, E.: Age-related changes in survival and turnover rates
of balsam fir (Abies balsamea (L.) Mill.) fine roots, Tree Physiol., 38, 865–876,
https://doi.org/10.1093/treephys/tpy010, 2018.
Kühn, N., Tovar, C., Carretero, J., Vandvik, V., Enquist, B. J., and
Willis, K. J.: Globally important plant functional traits for coping with
climate change, Front. Biogeogr., 13, 4, https://doi.org/10.21425/F5FBG53774,
2021.
Larocque, G. R., Archambault, L., and Delisle, C.: Development of the gap
model ZELIG-CFS to predict the dynamics of North American mixed forest types
with complex structures, Ecol. Modell., 222, 2570–2583,
https://doi.org/10.1016/j.ecolmodel.2010.08.035, 2011.
Lhotka, J. M. and Loewenstein, E. F.: An examination of species-specific
growing space utilization, Can. J. Forest Res., 38, 470–479,
https://doi.org/10.1139/X07-147, 2008.
Makela, A., Landsberg, J., Ek, A. R., Burk, T. E., Ter-Mikaelian, M., Agren,
G. I., Oliver, C. D., and Puttonen, P.: Process-based models for forest
ecosystem management: current state of the art and challenges for practical
implementation, Tree Physiol., 20, 289–298,
https://doi.org/10.1093/treephys/20.5-6.289, 2000.
Manuilova, E., Schuetzenmeister, A., and Model, F.: mcr: Method Comparison
Regression, R package version 1.2.2,
https://CRAN.R-project.org/package=mcr (last access: 15 September 2022), 2021.
Maréchaux, I., Langerwisch, F., Huth, A., Bugmann, H., Morin, X., Reyer,
C. P. O., Seidl, R., Collalti, A., Dantas de Paula, M., Fischer, R., Gutsch,
M., Lexer, M. J., Lischke, H., Rammig, A., Rödig, E., Sakschewski, B.,
Taubert, F., Thonicke, K., Vacchiano, G., and Bohn, F. J.: Tackling
unresolved questions in forest ecology: The past and future role of
simulation models, Ecol. Evol., 11, 3746–3770,
https://doi.org/10.1002/ece3.7391, 2021.
McCormack, M. L., Adams, T. S., Smithwick, E. A. H., and Eissenstat, D. M.:
Predicting fine root lifespan from plant functional traits in temperate
trees, New Phytol., 195, 823–831,
https://doi.org/10.1111/j.1469-8137.2012.04198.x, 2012.
McCormack, M. L., Eissenstat, D. M., Prasad, A. M., and Smithwick, E. A. H.:
Regional scale patterns of fine root lifespan and turnover under current and
future climate, Glob. Change Biol., 19, 1697–1708,
https://doi.org/10.1111/gcb.12163, 2013.
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, 80, 368,
https://doi.org/10.1126/SCIENCE.AAZ9463, 2020.
McIntire, C. D.: Impacts and management of foliar pathogens of eastern white
pine (Pinus strobus) in the northeastern United States, University of New Hampshire,
Durham, Doctoral Dissertation 2397, 2018.
Messier, C., Bauhus, J., Doyon, F., Maure, F., Sousa-Silva, R., Nolet, P.,
Mina, M., Aquilué, N., Fortin, M.-J., and Puettmann, K.: The functional
complex network approach to foster forest resilience to global changes, Forest
Ecosyst., 6, 21, https://doi.org/10.1186/s40663-019-0166-2, 2019.
Messier, C., Bauhus, J., Sousa-Silva, R., Auge, H., Baeten, L., Barsoum, N.,
Bruelheide, H., Caldwell, B., Cavender-Bares, J., Dhiedt, E., Eisenhauer,
N., Ganade, G., Gravel, D., Guillemot, J., Hall, J. S., Hector, A.,
Hérault, B., Jactel, H., Koricheva, J., Kreft, H., Mereu, S., Muys, B.,
Nock, C. A., Paquette, A., Parker, J. D., Perring, M. P., Ponette, Q.,
Potvin, C., Reich, P. B., Scherer-Lorenzen, M., Schnabel, F., Verheyen, K.,
Weih, M., Wollni, M., and Zemp, D. C.: For the sake of resilience and
multifunctionality, let's diversify planted forests!, Conserv. Lett., 15, e12829,
https://doi.org/10.1111/conl.12829, 2021.
MFFP: Inventaire écoforestier, Ministère des Forêts, de la Faune et
des Parcs, Réseaux des placettes-échantillons permanentes du Québec, http://mffp.gouv.qc.ca/les-forets/inventaire-ecoforestier/, last access: January 2021.
Miles, P. D. and Smith, W. B.: Specific gravity and other properties of wood
and bark for 156 tree species found in North America, Res. Note. NRS-38, 35
pp., https://doi.org/10.2737/NRS-RN-38, 2009.
Mina, M., Messier, C., Duveneck, M. J., Fortin, M. J., and Aquilué, N.:
Managing for the unexpected: Building resilient forest landscapes to cope
with global change, Glob. Change Biol., 1–19,
https://doi.org/10.1111/gcb.16197, 2022.
Mori, A. S., Furukawa, T., and Sasaki, T.: Response diversity determines the
resilience of ecosystems to environmental change, Biol. Rev., 88, 349–364,
https://doi.org/10.1111/BRV.12004, 2013.
Morin, X., Lechowicz, M. J., Augspurger, C., O'Keefe, J., Viner, D., and
Chuine, I.: Leaf phenology in 22 North American tree species during the 21st
century, Glob. Change Biol., 15, 961–975,
https://doi.org/10.1111/j.1365-2486.2008.01735.x, 2009.
Morin, X., Bugmann, H., Coligny, F., Martin-StPaul, N., Cailleret, M.,
Limousin, J., Ourcival, J., Prevosto, B., Simioni, G., Toigo, M., Vennetier,
M., Catteau, E., and Guillemot, J.: Beyond forest succession: A gap model to
study ecosystem functioning and tree community composition under climate
change, Funct. Ecol., 35, 955–975, https://doi.org/10.1111/1365-2435.13760,
2021.
Niinemets, Ü. and Valladares, F.: Tolerance to shade, drought, and
waterlogging of temperate northern hemisphere trees and shrubs, Ecol.
Monogr., 76, 521–547,
https://doi.org/10.1890/0012-9615(2006)076[0521:TTSDAW]2.0.CO;2, 2006.
Nolet, P. and Boureima, I.: Indicateurs de qualité de site pour
l'érable à sucre., québécois d'Aménagment de la
Forêt feuillue, Ripon, Québec, 34 pp., 2009.
Nolet, P., Bouffard, D., Doyon, R., and Delagrange, S.: Relationship between
canopy disturbance history and current sapling density of Fagus grandifolia
and Acer saccharum in a northern hardwood landscape, Can. J. Forest Res., 38,
216–225, https://doi.org/10.1139/X07-160, 2008.
Nolet, P., Boureima, I., and Ostojic, S.: Rendement des érablières
sous aménagement équienne en Outaouais., Institut Québécois
d'Aménagement de la Forêt Feuillue, Ripon, Québec, 82 pp., 2010.
Nyland, R. D., Ray, D. G., and Yanai, R. D.: Height Development of
Upper-Canopy Trees Within Even-Aged Adirondack Northern Hardwood Stands,
North. J. Appl. For., 21, 117–122, https://doi.org/10.1093/njaf/21.3.117,
2004.
Oliver, T. H., Heard, M. S., Isaac, N. J. B., Roy, D. B., Procter, D.,
Eigenbrod, F., Freckleton, R., Hector, A., Orme, C. D. L., Petchey, O. L.,
Proença, V., Raffaelli, D., Suttle, K. B., Mace, G. M.,
Martín-López, B., Woodcock, B. A., and Bullock, J. M.: Biodiversity
and Resilience of Ecosystem Functions, Trends Ecol. Evol., 30, 673–684,
https://doi.org/10.1016/J.TREE.2015.08.009, 2015.
Peng, C., Liu, J., Dang, Q., Apps, M. J., and Jiang, H.: TRIPLEX: a generic
hybrid model for predicting forest growth and carbon and nitrogen dynamics,
Ecol. Modell., 153, 109–130, https://doi.org/10.1016/S0304-3800(01)00505-1,
2002.
Penner, M. and Deblonde, G.: The relationship between leaf area and basal
area growth in jack and red pine trees, Forest Chron., 72, 170–175,
https://doi.org/10.5558/tfc72170-2, 1996.
Porté, A. and Bartelink, H. H.: Modelling mixed forest growth: a review
of models for forest management, Ecol. Modell., 150, 141–188,
https://doi.org/10.1016/S0304-3800(01)00476-8, 2002.
Power, H.: Comparaison des biais et de la précision des estimations des
modèles Artémis-2009 et Artémis-2014 pour la surface
terrière totale des peuplements forestiers, avec et sans coupe
partielle, sur une période de 40 ans, Note de recherche forestière
no. 143, MFFP – Direction de la recherche forestière, 1–22, 2016.
Power, H., LeMay, V., Berninger, F., Sattler, D., and Kneeshaw, D.:
Differences in crown characteristics between black (Picea mariana) and white spruce
(Picea glauca), Can. J. Forest Res., 42, 1733–1743, https://doi.org/10.1139/x2012-106,
2012.
Pretzsch, H.: Application and Evaluation of the Growth Simulator SILVA 2.2
for Forest Stands, Forest Estates and Large Regions,
Forstwiss. Centralbl., 121, 28–51, 2002.
Pretzsch, H.: Facilitation and competition reduction in tree species
mixtures in Central Europe: Consequences for growth modeling and forest
management, Ecol. Modell., 464, 109812,
https://doi.org/10.1016/j.ecolmodel.2021.109812, 2022.
Pretzsch, H., Forrester, D. I., and Rötzer, T.: Representation of
species mixing in forest growth models. A review and perspective, Ecol.
Modell., 313, 276–292, https://doi.org/10.1016/j.ecolmodel.2015.06.044,
2015.
Purves, D. W., Lichstein, J. W., Strigul, N., and Pacala, S. W.: Predicting
and understanding forest dynamics using a simple tractable model, P.
Natl. Acad. Sci. USA, 105, 17018–17022,
https://doi.org/10.1073/pnas.0807754105, 2008.
Quiñonez-Piñón, M. and Valeo, C.: Allometry of Sapwood Depth in
Five Boreal Trees, Forests, 8, 457, https://doi.org/10.3390/f8110457, 2017.
Raulier, F., Bernier, P. Y., and Ung, C.-H.: Canopy photosynthesis of sugar
maple (Acer saccharum): comparing big-leaf and multilayer extrapolations of leaf-level
measurements, Tree Physiol., 19, 407–420,
https://doi.org/10.1093/treephys/19.7.407, 1999.
R Core Team: R: A language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria,
https://www.r-project.org/ (last access: 15 September 2022), 2021.
Reed, D. D., Pregitzer, K. S., Liechty, H. O., Burton, A. J., and Mroz, G.
D.: Productivity and growth efficiency in sugar maple forests, Forest Ecol. Manag., 70, 319–327, https://doi.org/10.1016/0378-1127(94)90097-3, 1994.
Reineke, L. H.: Perfecting a stand-density index for even-aged forests, J.
Agric. Res., 46, 627–638, 1933.
Ruiz-Benito, P., Vacchiano, G., Lines, E. R., Reyer, C. P. O., Ratcliffe,
S., Morin, X., Hartig, F., Mäkelä, A., Yousefpour, R., Chaves, J.
E., Palacios-Orueta, A., Benito-Garzón, M., Morales-Molino, C.,
Camarero, J. J., Jump, A. S., Kattge, J., Lehtonen, A., Ibrom, A., Owen, H.
J. F., and Zavala, M. A.: Available and missing data to model impact of
climate change on European forests, Ecol. Modell., 416, 108870,
https://doi.org/10.1016/j.ecolmodel.2019.108870, 2020.
Ryelandt, B.: Modeling oak and beech regeneration in mixed and uneven-aged
forests: a process-based approach for changing environments, Université
Catholique de Louvain, Master thesis, 2019.
Saucier, J.-P.: Le point d'observation eìcologique: normes techniques,
Ministère des Ressources naturelles du Québec, ISBN 2551132738, 1994.
Schepaschenko, D., Shvidenko, A., Usoltsev, V., Lakyda, P., Luo, Y.,
Vasylyshyn, R., Lakyda, I., Myklush, Y., See, L., McCallum, I., Fritz, S.,
Kraxner, F., and Obersteiner, M.: A dataset of forest biomass structure for
Eurasia, Sci. Data, 4, 170070, https://doi.org/10.1038/sdata.2017.70, 2017.
Schmid, S., Zingg, A., Biber, P., and Bugmann, H.: Evaluation of the forest
growth model SILVA along an elevational gradient in Switzerland, Eur. J.
Forest Res., 125, 43–55, https://doi.org/10.1007/s10342-005-0076-4, 2006.
Schoeneberger, P. J., Wysocki, D. A., Benham, E. C., and Soil Survey Staff:
Field book for describing and sampling soils, Version 3.0, Natural Resources
Conservation Service, National Soil Survey Center, Lincoln, NE, ISBN 9781782664093, 2012.
Schwalm, C. R. and Ek, A. R.: A process-based model of forest ecosystems
driven by meteorology, Ecol. Modell., 179, 317–348,
https://doi.org/10.1016/j.ecolmodel.2004.04.016, 2004.
Seidl, R., Lexer, M. J., Jager, D., and Honninger, K.: Evaluating the
accuracy and generality of a hybrid patch model, Tree Physiol., 25,
939–951, https://doi.org/10.1093/treephys/25.7.939, 2005.
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.
Strigul, N., Pristinski, D., Purves, D., Dushoff, J., and Pacala, S.:
Scaling from trees to forests: tractable macroscopic equations for forest
dynamics, Ecol. Monogr., 78, 523–545, https://doi.org/10.1890/08-0082.1,
2008.
Strimbu, V. C., Bokalo, M., and Comeau, P. G.: Deterministic models of
growth and mortality for jack pine in boreal forests of Western Canada,
Forests, 8, 410, https://doi.org/10.3390/f8110410, 2017.
TNSDB: The National Soil Database: Canadian Soil Information Service, Government of Canada, https://sis.agr.gc.ca/cansis/nsdb/index.html, last access: 23 October 2021.
Thurner, M., Beer, C., Crowther, T., Falster, D., Manzoni, S., Prokushkin,
A., and Schulze, E.: Sapwood biomass carbon in northern boreal and temperate
forests, Global Ecol. Biogeogr., 28, 640–660,
https://doi.org/10.1111/geb.12883, 2019.
Trouvé, R., Bontemps, J.-D., Seynave, I., Collet, C., and Lebourgeois,
F.: Stand density, tree social status and water stress influence allocation
in height and diameter growth of Quercus petraea (Liebl.), Tree Physiol.,
35, 1035–1046, https://doi.org/10.1093/treephys/tpv067, 2015.
Trumbore, S., Brando, P., and Hartmann, H.: Forest health and global change,
Science, 349, 814–818, https://doi.org/10.1126/science.aac6759,
2015.
Ung, C.-H., Lambert, M. C., Raulier, F., Guo, J., and Bernier, P. Y.:
Biomass of trees sampled across Canada as part of the Energy from the Forest
Biomass (ENFOR) Program, Natural Resouces Canada,
https://doi.org/10.23687/fbad665e-8ac9-4635-9f84-e4fd53a6253c,
2017.
USDA – Forest Service: Section 2. Crown condition classification, in:
Forest Health Monitoring: field methods guide, USDA, Forest Service,
National Forest Health Monitoring Program: 2.1–2.7, Research Triangle Park,
NC, ISBN 1288804784, 1999.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z.,
Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer,
M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont,
B. B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M.-L., Niinemets,
Ü., Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov,
V. I., Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and
Villar, R.: The worldwide leaf economics spectrum, Nature, 428, 821–827,
https://doi.org/10.1038/nature02403, 2004.
Wullschleger, S. D., Hanson, P., and Todd, D.: Transpiration from a
multi-species deciduous forest as estimated by xylem sap flow techniques,
Forest Ecol. Manag., 143, 205–213,
https://doi.org/10.1016/S0378-1127(00)00518-1, 2001.
Zanne, A. E., Lopez-Gonzalez, G., Coomes, D. A., Ilic, J., Jansen, S.,
Lewis, S. L., Miller, R. B., Swenson, N. G., Wiemann, M. C., and Chave, J.:
Data from: Towards a worldwide wood economics spectrum, Dryad [data set],
https://doi.org/10.5061/dryad.234, 2009.
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.
Spatially explicit and process-based models are useful to test innovative forestry practices...
