Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-5973-2020
© Author(s) 2020. 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-13-5973-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
01 Dec 2020
Model description paper |
| 01 Dec 2020
| 01 Dec 2020
Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0
Virginie Moreaux
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
CNRS, UMR IGE 5001, Université de Grenoble-Alpes, Grenoble, 38058, France
Simon Martel
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
CNPF-IDF, Paris, 75000, France
Alexandre Bosc
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Delphine Picart
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
David Achat
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Christophe Moisy
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Raphael Aussenac
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Christophe Chipeaux
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Jean-Marc Bonnefond
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Soisick Figuères
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Pierre Trichet
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Rémi Vezy
AMAP, Univ. Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, France
Vincent Badeau
INRAE, UMR SILVA 1434, Champenoux, 54280, France
Bernard Longdoz
INRAE, UMR SILVA 1434, Champenoux, 54280, France
André Granier
INRAE, UMR SILVA 1434, Champenoux, 54280, France
Olivier Roupsard
Eco&Sols, Univ. Montpellier, CIRAD, INRAE, IRD, Montpellier SupAgro, Montpellier, France
Manuel Nicolas
ONF, Département RDI, Fontainebleau, 77300, France
Kim Pilegaard
Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
Giorgio Matteucci
CNR,ISAFOM, 80056 Ercolano (NA), Italy
Claudy Jolivet
INRAE, US1106 InfoSol, Orléans, 45075, France
Andrew T. Black
Faculty of Land and Food Systems, Vancouver, BC V6T 1Z4, Canada
Olivier Picard
CNPF-IDF, Paris, 75000, France
Denis Loustau
CORRESPONDING AUTHOR
Bordeaux-Sciences-Agro, INRAE, UMR ISPA, Villenave d'Ornon, 33140, France
Related authors
No articles found.
Sylvain Dupont, Eric Lamaud, Mark R. Irvine, Jean-Marc Bonnefond, Adolfo González-Romero, Andrés Alastuey, Cristina González-Flórez, Xavier Querol, Konrad Kandler, Martina Klose, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 18, 2183–2200, https://doi.org/10.5194/amt-18-2183-2025, https://doi.org/10.5194/amt-18-2183-2025, 2025
Short summary
Short summary
Low-cost optical particle counters (OPCs) offer new opportunities to monitor dust particles from wind soil erosion. Their price, size, and power consumption are lower than those of traditional OPCs. We tested the ability of the low-cost OPC-N3 from Alphasense to estimate dust emission flux during erosion events in Jordan. N3 estimated the dust flux well, with differences of less than 30 % compared to a traditional OPC. Our results confirm the potential of low-cost OPCs for dust erosion research.
Espoir Koudjo Gaglo, Emeline Chaste, Sebastiaan Luyssaert, Olivier Roupsard, Christophe Jourdan, Sidy Sow, Nadeige Vandewalle, Frédéric Do, Daouda Ngom, and Aude Valade
EGUsphere, https://doi.org/10.5194/egusphere-2025-1102, https://doi.org/10.5194/egusphere-2025-1102, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Agroforestry in the Sahel help store carbon and support food production, but land surface models struggle to capture their dynamics. We adapted the ORCHIDEE model to simulate Faidherbia albida, a tree that taps deep groundwater. This work highlights the need to integrate deep water uptake in land surface models for groundwater-dependent ecosystems, as it could enhance predictions, helping to sustain agroforestry in a changing climate.
Benjamin Loubet, Nicolas P. Saby, Maryam Gebleh, Pauline Buysse, Jean-Philippe Chenu, Céline Ratie, Claudy Jolivet, Carmen Kalalian, Florent Levavasseur, Jose-Luis Munera-Echeverri, Sebastien Lafont, Denis Loustau, Dario Papale, Giacomo Nicolini, Bruna Winck, and Dominique Arrouays
EGUsphere, https://doi.org/10.5194/egusphere-2025-592, https://doi.org/10.5194/egusphere-2025-592, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Soil is a large pool of carbon storing globally from two to three times more carbon than the atmosphere and vegetation. We compute the soil stock evolution from 2005 to 2019 for a wheat-maize-barley-oilseed-rape crop rotation at a French crop site. The soil carbon stock decreased by around 70 ± 16 g C m-2 yr-1 over the period, leading to a total loss of around 8 % of the initial soil stock. This strong destocking is primarily explained by a decrease in the residue return to the site.
Amicie A. Delahaie, Lauric Cécillon, Marija Stojanova, Samuel Abiven, Pierre Arbelet, Dominique Arrouays, François Baudin, Antonio Bispo, Line Boulonne, Claire Chenu, Jussi Heinonsalo, Claudy Jolivet, Kristiina Karhu, Manuel Martin, Lorenza Pacini, Christopher Poeplau, Céline Ratié, Pierre Roudier, Nicolas P. A. Saby, Florence Savignac, and Pierre Barré
SOIL, 10, 795–812, https://doi.org/10.5194/soil-10-795-2024, https://doi.org/10.5194/soil-10-795-2024, 2024
Short summary
Short summary
This paper compares the soil organic carbon fractions obtained from a new thermal fractionation scheme and a well-known physical fractionation scheme on an unprecedented dataset of French topsoil samples. For each fraction, we use a machine learning model to determine its environmental drivers (pedology, climate, and land cover). Our results suggest that these two fractionation schemes provide different fractions, which means they provide complementary information.
Yélognissè Agbohessou, Claire Delon, Manuela Grippa, Eric Mougin, Daouda Ngom, Espoir Koudjo Gaglo, Ousmane Ndiaye, Paulo Salgado, and Olivier Roupsard
Biogeosciences, 21, 2811–2837, https://doi.org/10.5194/bg-21-2811-2024, https://doi.org/10.5194/bg-21-2811-2024, 2024
Short summary
Short summary
Emissions of greenhouse gases in the Sahel are not well represented because they are considered weak compared to the rest of the world. However, natural areas in the Sahel emit carbon dioxide and nitrous oxides, which need to be assessed because of extended surfaces. We propose an assessment of such emissions in Sahelian silvopastoral systems and of how they are influenced by environmental characteristics. These results are essential to inform climate change strategies in the region.
Christophe Djemiel, Samuel Dequiedt, Walid Horrigue, Arthur Bailly, Mélanie Lelièvre, Julie Tripied, Charles Guilland, Solène Perrin, Gwendoline Comment, Nicolas P. A. Saby, Claudy Jolivet, Antonio Bispo, Line Boulonne, Antoine Pierart, Patrick Wincker, Corinne Cruaud, Pierre-Alain Maron, Sébastien Terrat, and Lionel Ranjard
SOIL, 10, 251–273, https://doi.org/10.5194/soil-10-251-2024, https://doi.org/10.5194/soil-10-251-2024, 2024
Short summary
Short summary
The fungal kingdom has been diversifying for more than 800 million years by colonizing a large number of habitats on Earth. Based on a unique dataset (18S rDNA meta-barcoding), we described the spatial distribution of fungal diversity at the scale of France and the environmental drivers by tackling biogeographical patterns. We also explored the fungal network interactions across land uses and climate types.
Jérémy Mayen, Pierre Polsenaere, Éric Lamaud, Marie Arnaud, Pierre Kostyrka, Jean-Marc Bonnefond, Philippe Geairon, Julien Gernigon, Romain Chassagne, Thomas Lacoue-Labarthe, Aurore Regaudie de Gioux, and Philippe Souchu
Biogeosciences, 21, 993–1016, https://doi.org/10.5194/bg-21-993-2024, https://doi.org/10.5194/bg-21-993-2024, 2024
Short summary
Short summary
We deployed an atmospheric eddy covariance system to measure continuously the net ecosystem CO2 exchanges (NEE) over a salt marsh and determine the major biophysical drivers. Our results showed an annual carbon sink mainly due to photosynthesis of the marsh plants. Our study also provides relevant information on NEE fluxes during marsh immersion by decreasing daytime CO2 uptake and night-time CO2 emissions at the daily scale, whereas the immersion did not affect the annual marsh C balance.
Martin Schwartz, Philippe Ciais, Aurélien De Truchis, Jérôme Chave, Catherine Ottlé, Cedric Vega, Jean-Pierre Wigneron, Manuel Nicolas, Sami Jouaber, Siyu Liu, Martin Brandt, and Ibrahim Fayad
Earth Syst. Sci. Data, 15, 4927–4945, https://doi.org/10.5194/essd-15-4927-2023, https://doi.org/10.5194/essd-15-4927-2023, 2023
Short summary
Short summary
As forests play a key role in climate-related issues, their accurate monitoring is critical to reduce global carbon emissions effectively. Based on open-access remote-sensing sensors, and artificial intelligence methods, we created high-resolution tree height, wood volume, and biomass maps of metropolitan France that outperform previous products. This study, based on freely available data, provides essential information to support climate-efficient forest management policies at a low cost.
Amicie A. Delahaie, Pierre Barré, François Baudin, Dominique Arrouays, Antonio Bispo, Line Boulonne, Claire Chenu, Claudy Jolivet, Manuel P. Martin, Céline Ratié, Nicolas P. A. Saby, Florence Savignac, and Lauric Cécillon
SOIL, 9, 209–229, https://doi.org/10.5194/soil-9-209-2023, https://doi.org/10.5194/soil-9-209-2023, 2023
Short summary
Short summary
We characterized organic matter in French soils by analysing samples from the French RMQS network using Rock-Eval thermal analysis. We found that thermal analysis is appropriate to characterize large set of samples (ca. 2000) and provides interpretation references for Rock-Eval parameter values. This shows that organic matter in managed soils is on average more oxidized and more thermally stable and that some Rock-Eval parameters are good proxies for organic matter biogeochemical stability.
Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, https://doi.org/10.5194/gmd-15-3041-2022, 2022
Short summary
Short summary
This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Lena Wohlgemuth, Pasi Rautio, Bernd Ahrends, Alexander Russ, Lars Vesterdal, Peter Waldner, Volkmar Timmermann, Nadine Eickenscheidt, Alfred Fürst, Martin Greve, Peter Roskams, Anne Thimonier, Manuel Nicolas, Anna Kowalska, Morten Ingerslev, Päivi Merilä, Sue Benham, Carmen Iacoban, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 19, 1335–1353, https://doi.org/10.5194/bg-19-1335-2022, https://doi.org/10.5194/bg-19-1335-2022, 2022
Short summary
Short summary
Gaseous mercury is present in the atmosphere all over the globe. During the growing season, plants take up mercury from the air in a similar way as CO2. We investigated which factors impact this vegetational mercury uptake by analyzing a large dataset of leaf mercury uptake rates of trees in Europe. As a result, we conclude that mercury uptake is foremost controlled by tree-intrinsic traits like physiological activity but also by climatic factors like dry conditions in the air and in soils.
Sung-Ching Lee, Sara H. Knox, Ian McKendry, and T. Andrew Black
Atmos. Chem. Phys., 22, 2333–2349, https://doi.org/10.5194/acp-22-2333-2022, https://doi.org/10.5194/acp-22-2333-2022, 2022
Short summary
Short summary
Wildfire smoke alters land–atmosphere exchange. Here, measurements in a forest and a wetland during four smoke episodes over four summers showed that impacts on radiation and heat budget were the greatest when smoke arrived in late summer. Both sites sequestered more CO2 under smoky days, partly due to diffuse light, but emitted CO2 when smoke was dense. This kind of field study is important for validating predictions of smoke–productivity feedbacks and has climate change implications.
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021, https://doi.org/10.5194/amt-14-7835-2021, 2021
Short summary
Short summary
Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.
Yeonuk Kim, Monica Garcia, Laura Morillas, Ulrich Weber, T. Andrew Black, and Mark S. Johnson
Hydrol. Earth Syst. Sci., 25, 5175–5191, https://doi.org/10.5194/hess-25-5175-2021, https://doi.org/10.5194/hess-25-5175-2021, 2021
Short summary
Short summary
Here, we present a novel physically based evaporation model to demonstrate that vertical relative humidity (RH) gradients from the land surface to the atmosphere tend to evolve towards zero due to land–atmosphere equilibration processes. Collapsing RH gradients on daily to yearly timescales indicate an emergent land–atmosphere equilibrium, making it possible to determine evapotranspiration using only meteorological information, independent of land surface conditions and vegetation controls.
Jaber Rahimi, Expedit Evariste Ago, Augustine Ayantunde, Sina Berger, Jan Bogaert, Klaus Butterbach-Bahl, Bernard Cappelaere, Jean-Martial Cohard, Jérôme Demarty, Abdoul Aziz Diouf, Ulrike Falk, Edwin Haas, Pierre Hiernaux, David Kraus, Olivier Roupsard, Clemens Scheer, Amit Kumar Srivastava, Torbern Tagesson, and Rüdiger Grote
Geosci. Model Dev., 14, 3789–3812, https://doi.org/10.5194/gmd-14-3789-2021, https://doi.org/10.5194/gmd-14-3789-2021, 2021
Short summary
Short summary
West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange, and they provide valuable food and fodder resources. Therefore, we simulated net ecosystem exchange and aboveground biomass of typical ecosystems in this region with an improved process-based biogeochemical model, LandscapeDNDC. Carbon stocks and exchange rates were particularly correlated with the abundance of trees. Grass and crop yields increased under humid climatic conditions.
Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers
Geosci. Model Dev., 14, 3361–3382, https://doi.org/10.5194/gmd-14-3361-2021, https://doi.org/10.5194/gmd-14-3361-2021, 2021
Short summary
Short summary
The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
Short summary
Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Claire Froger, Nicolas P. A. Saby, Claudy C. Jolivet, Line Boulonne, Giovanni Caria, Xavier Freulon, Chantal de Fouquet, Hélène Roussel, Franck Marot, and Antonio Bispo
SOIL, 7, 161–178, https://doi.org/10.5194/soil-7-161-2021, https://doi.org/10.5194/soil-7-161-2021, 2021
Short summary
Short summary
Pollution of French soils by polycyclic aromatic hydrocarbons (PAHs), known as carcinogenic pollutants, was quantified in this work using an extended data set of 2154 soils sampled across France. The map of PAH concentrations in French soils revealed strong trends in regions with heavy industries and around cities. The PAH signatures indicated the influence of PAH emissions in Europe during the industrial revolution. Health risks posed by PAHs in soils were low but need to be considered.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
Short summary
Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
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.
Waly Faye, Awa Niang Fall, Didier Orange, Frédéric Do, Olivier Roupsard, and Alioune Kane
Proc. IAHS, 383, 391–399, https://doi.org/10.5194/piahs-383-391-2020, https://doi.org/10.5194/piahs-383-391-2020, 2020
Short summary
Short summary
People from the Senegalese Peanut Basin deal with a dramatic increase of water scarcity due both to a rain deficit and a surface water salinization. We carried out the analysis of daily rain from 1950 to 2015 and water salinity of 78 wells on 300 km2. We confirm a climatic break in 1970 leaded a long dry period until 2009, with a decreased of the rainy day number per year, probably driving a large extension of well salinization and salt soil crusting accelerated by a large tidal event in 1984.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
Short summary
Short summary
Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Daniel Berveiller, Bogdan H. Chojnicki, Ulrich Dämmgen, Nicolas Delpierre, Vesna Djuricic, Julia Drewer, Eric Dufrêne, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Biogeosciences, 17, 1583–1620, https://doi.org/10.5194/bg-17-1583-2020, https://doi.org/10.5194/bg-17-1583-2020, 2020
Short summary
Short summary
Experimental evidence from a network of 40 monitoring sites in Europe suggests that atmospheric nitrogen deposition to forests and other semi-natural vegetation impacts the carbon sequestration rates in ecosystems, as well as the net greenhouse gas balance including other greenhouse gases such as nitrous oxide and methane. Excess nitrogen deposition in polluted areas also leads to other environmental impacts such as nitrogen leaching to groundwater and other pollutant gaseous emissions.
Chris R. Flechard, Marcel van Oijen, David R. Cameron, Wim de Vries, Andreas Ibrom, Nina Buchmann, Nancy B. Dise, Ivan A. Janssens, Johan Neirynck, Leonardo Montagnani, Andrej Varlagin, Denis Loustau, Arnaud Legout, Klaudia Ziemblińska, Marc Aubinet, Mika Aurela, Bogdan H. Chojnicki, Julia Drewer, Werner Eugster, André-Jean Francez, Radosław Juszczak, Barbara Kitzler, Werner L. Kutsch, Annalea Lohila, Bernard Longdoz, Giorgio Matteucci, Virginie Moreaux, Albrecht Neftel, Janusz Olejnik, Maria J. Sanz, Jan Siemens, Timo Vesala, Caroline Vincke, Eiko Nemitz, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Ute M. Skiba, and Mark A. Sutton
Biogeosciences, 17, 1621–1654, https://doi.org/10.5194/bg-17-1621-2020, https://doi.org/10.5194/bg-17-1621-2020, 2020
Short summary
Short summary
Nitrogen deposition from the atmosphere to unfertilized terrestrial vegetation such as forests can increase carbon dioxide uptake and favour carbon sequestration by ecosystems. However the data from observational networks are difficult to interpret in terms of a carbon-to-nitrogen response, because there are a number of other confounding factors, such as climate, soil physical properties and fertility, and forest age. We propose a model-based method to untangle the different influences.
Tiphaine Chevallier, Kenji Fujisaki, Olivier Roupsard, Florian Guidat, Rintaro Kinoshita, Elias de Melo Viginio Filho, Peter Lehner, and Alain Albrecht
SOIL, 5, 315–332, https://doi.org/10.5194/soil-5-315-2019, https://doi.org/10.5194/soil-5-315-2019, 2019
Short summary
Short summary
Soil organic carbon (SOC) is the largest terrestrial C stock. Andosols of volcanic areas hold particularly large stocks (e.g. from 24 to 72 kgC m−2 in the upper 2 m of soil) as determined via MIR spectrometry at our Costa Rican study site: a 1 km2 basin covered by coffee agroforestry. Andic soil properties explained this high variability, which did not correlate with stocks in the upper 20 cm of soil. Topography and pedogenesis are needed to understand the SOC stocks at landscape scales.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
Short summary
Short summary
We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
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
Short summary
Short summary
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.
Anne Sofie Lansø, Thomas Luke Smallman, Jesper Heile Christensen, Mathew Williams, Kim Pilegaard, Lise-Lotte Sørensen, and Camilla Geels
Biogeosciences, 16, 1505–1524, https://doi.org/10.5194/bg-16-1505-2019, https://doi.org/10.5194/bg-16-1505-2019, 2019
Short summary
Short summary
Although coastal regions only amount to 7 % of the global oceans, their contribution to the global oceanic surface exchange of CO2 is much greater. In this study, we gain detailed insight into how these coastal marine fluxes compare to CO2 exchange from coastal land regions. Annually, the coastal marine exchanges are smaller than the total uptake of CO2 from the land surfaces within the study area but comparable in size to terrestrial fluxes from individual land cover classes of the region.
Ian G. McKendry, Andreas Christen, Sung-Ching Lee, Madison Ferrara, Kevin B. Strawbridge, Norman O'Neill, and Andrew Black
Atmos. Chem. Phys., 19, 835–846, https://doi.org/10.5194/acp-19-835-2019, https://doi.org/10.5194/acp-19-835-2019, 2019
Short summary
Short summary
Wildfire smoke in July 2015 had a significant impact on air quality, radiation, and energy budgets across British Columbia. With lighter smoke, a wetland and forested site showed enhanced photosynthetic activity (taking in carbon dioxide). However, with dense smoke the forested site became a strong source. These results suggest that smoke during the growing season potentially plays an important role in the carbon budget, and this effect will likely increase as climate changes.
Loris Deirmendjian, Denis Loustau, Laurent Augusto, Sébastien Lafont, Christophe Chipeaux, Dominique Poirier, and Gwenaël Abril
Biogeosciences, 15, 669–691, https://doi.org/10.5194/bg-15-669-2018, https://doi.org/10.5194/bg-15-669-2018, 2018
Short summary
Short summary
Carbon leaching to streams represents a very small (~ 2 %) fraction of forest net ecosystem exchange (NEE). Such weak export of carbon from forest ecosystems, at least in temperate regions, is at odds with recent studies that attempt to integrate the contribution of inland waters in the continent carbon budget. Understanding why local and global carbon mass balances strongly diverge on the proportion of land NEE exported to aquatic systems is a major challenge for research in this field.
Clifton R. Sabajo, Guerric le Maire, Tania June, Ana Meijide, Olivier Roupsard, and Alexander Knohl
Biogeosciences, 14, 4619–4635, https://doi.org/10.5194/bg-14-4619-2017, https://doi.org/10.5194/bg-14-4619-2017, 2017
Short summary
Short summary
From the analysis of MODIS and Landsat satellite data of the Jambi province in Indonesia, this first study on the effects of oil palm expansion on the surface temperature in Indonesia shows shows a local and regional warming effect caused by the expansion of oil palm plantations and other cash or tree crops between 2000 and 2015. The observed warming effects may affect ecosystem services, reduce water availabilty in the dry period and increase the vulnerability to fires in the province.
Sung-Ching Lee, Andreas Christen, Andrew T. Black, Mark S. Johnson, Rachhpal S. Jassal, Rick Ketler, Zoran Nesic, and Markus Merkens
Biogeosciences, 14, 2799–2814, https://doi.org/10.5194/bg-14-2799-2017, https://doi.org/10.5194/bg-14-2799-2017, 2017
Short summary
Short summary
Burns Bog in Vancouver is the largest peatland on North America's west coast. It is undergoing rewetting as a restoration management after peat harvesting. Rewetting of disturbed areas facilitates their ecological recovery but has an immediate impact on carbon dioxide and methane exchange. On the floating flux tower, we quantified annual carbon dioxide and methane exchange to inform future management. Our results suggested that the study area was a net carbon sink after 7-year rewetting.
Andreas Brændholt, Klaus Steenberg Larsen, Andreas Ibrom, and Kim Pilegaard
Biogeosciences, 14, 1603–1616, https://doi.org/10.5194/bg-14-1603-2017, https://doi.org/10.5194/bg-14-1603-2017, 2017
Short summary
Short summary
In this study we found that CO2 fluxes from soil measured by the closed-chamber technique were overestimated during low atmospheric turbulence. This resulted in biased courses of CO2 fluxes during a day. We removed CO2 fluxes measured at low turbulence, which gave better flux estimates. We furthermore tested a novel technique that provided good measurement during low turbulence, thereby giving better estimates of CO2 emissions from soils, which is a crucial part of the global carbon cycle.
Loise Wandera, Kaniska Mallick, Gerard Kiely, Olivier Roupsard, Matthias Peichl, and Vincenzo Magliulo
Hydrol. Earth Syst. Sci., 21, 197–215, https://doi.org/10.5194/hess-21-197-2017, https://doi.org/10.5194/hess-21-197-2017, 2017
Short summary
Short summary
Upscaling instantaneous to daily evapotranspiration (ETi–ETd) is one of the central challenges in regional vegetation water-use mapping using polar orbiting satellites. Here we developed a robust ETi upscaling for global studies using the ratio between daily and instantaneous global radiation (RSd/RSi). Using data from 126 FLUXNET tower sites, this study demonstrated the RSd/RSi ratio to be the most robust factor explaining ETd/ETi variability across variable sky conditions and multiple biomes.
Yiying Chen, James Ryder, Vladislav Bastrikov, Matthew J. McGrath, Kim Naudts, Juliane Otto, Catherine Ottlé, Philippe Peylin, Jan Polcher, Aude Valade, Andrew Black, Jan A. Elbers, Eddy Moors, Thomas Foken, Eva van Gorsel, Vanessa Haverd, Bernard Heinesch, Frank Tiedemann, Alexander Knohl, Samuli Launiainen, Denis Loustau, Jérôme Ogée, Timo Vessala, and Sebastiaan Luyssaert
Geosci. Model Dev., 9, 2951–2972, https://doi.org/10.5194/gmd-9-2951-2016, https://doi.org/10.5194/gmd-9-2951-2016, 2016
Short summary
Short summary
In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types. An adequate parametrization approach has been presented for the global-scale land surface model (ORCHIDEE-CAN). Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.
Y. Fan, O. Roupsard, M. Bernoux, G. Le Maire, O. Panferov, M. M. Kotowska, and A. Knohl
Geosci. Model Dev., 8, 3785–3800, https://doi.org/10.5194/gmd-8-3785-2015, https://doi.org/10.5194/gmd-8-3785-2015, 2015
Short summary
Short summary
A perennial crop model CLM-Palm is developed, including multilayer structure, phenology, and carbon and nitrogen allocation functions, for modeling an important oil palm agricultural system in the tropical regions. Simulated LAI, yield and NPP were calibrated and validated with multiple sites in Sumatra, Indonesia. The new model allows exploring the effects of tropical land use change, from natural ecosystems to monoculture plantations on carbon, water and energy cycles and regional climate.
X. Dou, B. Chen, T. A. Black, R. S. Jassal, M. Che, and Y. Liu
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2001-2014, https://doi.org/10.5194/bgd-11-2001-2014, 2014
Revised manuscript not accepted
A. Mathys, T. A. Black, Z. Nesic, G. Nishio, M. Brown, D. L. Spittlehouse, A. L. Fredeen, R. Bowler, R. S. Jassal, N. J. Grant, P. J. Burton, J. A. Trofymow, and G. Meyer
Biogeosciences, 10, 5451–5463, https://doi.org/10.5194/bg-10-5451-2013, https://doi.org/10.5194/bg-10-5451-2013, 2013
Related subject area
Biogeosciences
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
Development and assessment of the physical-biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
Parameterisation toolbox for physical-biogeochemical model compatible with FABM. Case study: the coupled 1D GOTM-ECOSMO E2E for the Sylt-Romo Bight, North Sea
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Estimation of above- and below-ground ecosystem parameters for the DVM-DOS-TEM v0.7.0 model using MADS v1.7.3: a synthetic case study
H2MV (v1.0): Global Physically-Constrained Deep Learning Water Cycle Model with Vegetation
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
ML4Fire-XGBv1.0: Improving North American wildfire prediction by integrating a machine-learning fire model in a land surface model
Alquimia v1.0: A generic interface to biogeochemical codes – A tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
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
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
Short summary
Short summary
The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
Short summary
Short summary
Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
Short summary
Short summary
We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
Short summary
Short summary
Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
Short summary
Short summary
Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Carolina Natel, David Martin Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
EGUsphere, https://doi.org/10.5194/egusphere-2024-4064, https://doi.org/10.5194/egusphere-2024-4064, 2025
Short summary
Short summary
Complex models predict forest carbon responses to future climate change but are slow and computationally intensive, limiting large-scale analyses. We used machine learning to accelerate predictions from the LPJ-GUESS vegetation model. Our emulators, based on random forests and neural networks, achieved 97 % faster simulations. This approach enables rapid exploration of climate mitigation strategies and supports informed policy decisions.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-223, https://doi.org/10.5194/gmd-2024-223, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions have changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
Short summary
Short summary
The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1509, https://doi.org/10.5194/egusphere-2024-1509, 2024
Short summary
Short summary
Physical–biogeochemical ocean global models is difficult to analyze oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The model is an important tool for studying physical–biogeochemical processes.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
Short summary
Short summary
We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2710, https://doi.org/10.5194/egusphere-2024-2710, 2024
Short summary
Short summary
Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
Short summary
Short summary
We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Elchin E. Jafarov, Helene Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-158, https://doi.org/10.5194/gmd-2024-158, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Thawing permafrost could greatly impact global climate. Our study improves modeling of carbon cycling in Arctic ecosystems. We developed an automated method to fine-tune a model that simulates carbon and nitrogen flows, using computer-generated data. Using computer-generated data, we tested our method and found it enhances accuracy and reduces the time needed for calibration. This work helps make climate predictions more reliable in sensitive permafrost regions.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
EGUsphere, https://doi.org/10.5194/egusphere-2024-2044, https://doi.org/10.5194/egusphere-2024-2044, 2024
Short summary
Short summary
We use an innovative approach to study the Earth's water cycle by blending advanced computer learning techniques with a traditional water cycle model. We developed a model that learns from meteorological data, with a special focus on understanding how vegetation influences water movement. Our model closely aligns with real-world observations, yet there are areas that need improvement. This study opens up new possibilities to better understand the water cycle and its interactions with vegetation.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-151, https://doi.org/10.5194/gmd-2024-151, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Sergi Molins, Benjamin Andre, Jeffrey Johnson, Glenn Hammond, Benjamin Sulman, Konstantin Lipnikov, Marcus Day, James Beisman, Daniil Svyatsky, Hang Deng, Peter Lichtner, Carl Steefel, and David Moulton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-108, https://doi.org/10.5194/gmd-2024-108, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
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.
Cited articles
Achat, D. L., Fortin, M., Landmann, G., Ringeval, B., and Augusto, L.: Forest soil carbon is threatened by intensive biomass harvesting, Sci. Rep.-UK, 5, 15991, https://doi.org/10.1038/srep15991, 2015.
Achat, D. L., Martel, S., Picart, D., Moisy, C., Augusto, L., Bakker, M. R., and Loustau, D.: Modelling the nutrient cost of biomass harvesting under different silvicultural and climate scenarios in production forests, Forest Ecol. Manag., 429, 642–653, https://doi.org/10.1016/j.foreco.2018.06.047, 2018.
Ahlswede, B. J. and Thomas, R. Q.: Community earth system model simulations reveal the relative importance of afforestation and forest management to surface temperature in Eastern North America, Forests, 8, 499, https://doi.org/10.3390/f8120499, 2017.
Arrouays, D. and Pelissier, P.: Changes in carbon storage in temperate humic loamy soils after forest clearing and continuous corn cropping in France, Plant Soil, 160, 215–223, 1994.
Atkin, O. K. and Tjoelker, M. G.: Thermal acclimation and the dynamic response of plant respiration to temperature, Trends Plant Sci., 8, 343–351, https://doi.org/10.1016/s1360-1385(03)00136-5, 2003.
Bala, G., Caldeira, K., Wickett, M., Phillips, T. J., Lobell, D. B., Delire, C., and Mirin, A.: Combined climate and carbon-cycle effects of large-scale deforestation, P. Natl. Acad. Sci. USA., 104, 6550–6555, https://doi.org/10.1073/pnas.0608998104, 2007.
Balesdent, J., Besnard, E., Arrouays, D., and Chenu, C.: The dynamics of carbon in particle-size fractions of soil in a forest-cultivation sequence, Plant Soil, 201, 49–57, 1998.
Bellassen, V., Le Maire, G., Dhôte, J. F., Ciais, P., and Viovy, N.: Modelling forest management within a global vegetation model – Part 1: Model structure and general behaviour, Ecol. Modell., 221, 2458–2474, https://doi.org/10.1016/j.ecolmodel.2010.07.008, 2010.
Bellassen, V., le Maire, G., Guin, O., Dhôte, J. F., Ciais, P., and Viovy, N.: Modelling forest management within a global vegetation model – Part 2: Model validation from a tree to a continental scale, Ecol. Modell., 222, 57–75, 2011.
Berbigier, P. and Bonnefond, J. M.: Measurement and Modeling of Radiation Transmission within a Stand of Maritime Pine (Pinus-Pinaster Ait), Ann. For. Sci., 52, 23–42, 1995.
Berbigier, P. and Loustau, D.: FLUXNET2015 FR-LBr Le Bray, Dataset, https://doi.org/10.18140/FLX/1440163, 1996–2008.
Berbigier, P., Bonnefond, J. M., and Mellmann, P.: CO2 and water vapour fluxes for 2 years above Euroflux forest site, Agric. For. Meteorol., 108, 183–197, 2001.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Betts, R. A.: Offset of the potential carbon sink from boreal forestation by decreases in surface albedo, Nature, 408, 187–190, https://doi.org/10.1038/35041545, 2000.
Bloomfield, K. J., Cernusak, L. A., Eamus, D., Ellsworth, D. S., Prentice, I. C., Wright, I. J., Boer, M. M., Bradford, M. G., Cale, P., Cleverly, J., Egerton, J. J. G., Evans, B. J., Hayes, L. S., Hutchinson, M. F., Liddell, M. J., Macfarlane, C., Meyer, W. S., Prober, S. M., Togashi, H. F., Wardlaw, T., Zhu, L. L., and Atkin, O. K.: A continental-scale assessment of variability in leaf traits: Within species, across sites and between seasons, Funct. Ecol., 32, 1492–1506, 2018.
Borys, A., Suckow, F., Reyer, C., Gutsch, M., and Lasch-Born, P.: The impact of climate change under different thinning regimes on carbon sequestration in a German forest district, Mitig. Adapt. Strat. Gl., 21, 861–881, https://doi.org/10.1007/s11027-014-9628-6, 2016.
Breda, N. J. J.: Ground-based measurements of leaf area index: a review of methods, instruments and current controversies, J. Exp. Bot., 54, 2403–2417, 2003.
Bright, R. M., Cherubini, F., and Strømman, A. H.: Climate impacts of bioenergy: Inclusion of carbon cycle and albedo dynamics in life cycle impact assessment, Environ. Impact Assess. Rev., 37, 2–11, https://doi.org/10.1016/j.eiar.2012.01.002, 2012.
Bright, R. M., Davin, E., O'Halloran, T., Pongratz, J., Zhao, K. G., and Cescatti, A.: Local temperature response to land cover and management change driven by non-radiative processes, Nat. Clim. Change, 7, 296, https://doi.org/10.1038/nclimate3250, 2017.
Campolongo, F. and Saltelli, A.: Sensitivity analysis of an environmental model an application of different analysis methods, Reliab. Eng. Syst. Safe., 57, 49–69, 1997.
Chave, J., Rejou-Mechain, M., Burquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B., Duque, A., Eid, T., Fearnside, P. M., Goodman, R. C., Henry, M., Martinez-Yrizar, A., Mugasha, W. A., Muller-Landau, H. C., Mencuccini, M., Nelson, B. W., Ngomanda, A., Nogueira, E. M., Ortiz-Malavassi, E., Pelissier, R., Ploton, P., Ryan, C. M., Saldarriaga, J. G., and Vieilledent, G.: Improved allometric models to estimate the aboveground biomass of tropical trees, Global Change Biol., 20, 3177–3190, https://doi.org/10.1111/gcb.12629, 2014.
Chen, C. R., Xu, Z. H., and Mathers, N. J.: Soil carbon pools in adjacent natural and plantation forests of subtropical Australia, Soil Sci. Soc. Am. J., 8, 282–291, https://doi.org/10.2136/sssaj2004.2820, 2004.
Chen, Y., Ryder, J., Bastrikov, V., McGrath, M. J., Naudts, K., Otto, J., Ottlé, C., Peylin, P., Polcher, J., Valade, A., Black, A., Elbers, J. A., Moors, E., Foken, T., van Gorsel, E., Haverd, V., Heinesch, B., Tiedemann, F., Knohl, A., Launiainen, S., Loustau, D., Ogée, J., Vessala, T., and Luyssaert, S.: Evaluating the performance of land surface model ORCHIDEE-CAN v1.0 on water and energy flux estimation with a single- and multi-layer energy budget scheme, Geosci. Model Dev., 9, 2951–2972, https://doi.org/10.5194/gmd-9-2951-2016, 2016.
Ciais, P., Loustau, D., Bosc, A., Ogée, J., Dufrêne, E., François, C., Viovy, N., and Delage, F.: How will the production of French forests respond to climate change? An integrated analysis from site to country scale, in: Forests, carbon cycle and climate change, edited by: Loustau, D., Quae, Paris, 2010.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Coleman K. and Jenkinson, D. D.: RothC – 26.3 – A model for the turnover of carbon in soil, in: Evaluation of soil organic matter models using existing, long-term dataset, edited by: Powlson, D. S., Smith, P., and Smith, J. U., NATO ASI Series I, Springer Verlag, Heidelberg, Germany, 237–246, 1996.
Collalti, A., Marconi, S., Ibrom, A., Trotta, C., Anav, A., D'Andrea, E., Matteucci, G., Montagnani, L., Gielen, B., Mammarella, I., Grünwald, T., Knohl, A., Berninger, F., Zhao, Y., Valentini, R., and Santini, M.: Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites, Geosci. Model Dev., 9, 479–504, https://doi.org/10.5194/gmd-9-479-2016, 2016.
Davi, H., Dufrene, E., Granier, A., Le Dantec, V., Barbaroux, C., Francois, C., and Breda, N.: Modelling carbon and water cycles in a beech forest Part II: Validation of the main processes from organ to stand scale, Ecol. Modell., 185, 387–405, 2005.
Davi, H., Dufrêne, E., Francois, C., Le Maire, G., Loustau, D., Bosc, A., Rambal, S., Granier, A., and Moors, E.: Sensitivity of water and carbon fluxes to climate changes from 1960 to 2100 in European forest ecosystems, Agr. Forest. Meteorol., 141, 35–56, https://doi.org/10.1016/j.agrformet.2006.09.003, 2006.
Deckmyn, G., Verbeeck, H., de Beeck, M. O., Vansteenkiste, D., Steppe, K., and Ceulemans, R.: ANAFORE: A stand-scale process-based forest model that includes wood tissue development and labile carbon storage in trees, Ecol. Modell., 215, 345–368, https://doi.org/10.1016/j.ecolmodel.2008.04.007, 2008.
Delpierre, N., Dufrêne, E., Soudani, K., Ulrich, E., Cecchini, S., Boé, J., and François, C.: Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France, Agr. Forest. Meteorol., 149, 938–948, https://doi.org/10.1016/j.agrformet.2008.11.014, 2009.
Delpierre, N., Soudani, K., Francois, C., Le Maire, G., Bernhofer, C., Kutsch, W., Misson, L., Rambal, S., Vesala, T., and Dufrene, E.: Quantifying the influence of climate and biological drivers on the interannual variability of carbon exchanges in European forests through process-based modelling, Agr. Forest Meteorol., 154, 99–112, https://doi.org/10.1016/j.agrformet.2011.10.010, 2012.
Delzon, S. and Loustau, D.: Age-related decline in stand water use: sap flow and transpiration in a pine forest chronosequence, Agr. Forest Meteorol., 129, 105–119, https://doi.org/10.1016/j.agrformet.2005.01.002, 2005.
Delzon, S., Sartore, M., Burlett, R., Dewar, R., and Loustau, D.: Hydraulic responses to height growth in maritime pine trees, Plant Cell Environ., 27, 1077–1087, 2004.
de Pury, D. G. G. and Farquhar, G. D.: Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models, Plant Cell Environ., 20, 537–557, 1997.
Dobarco, M. R., Cousin, I., Le Bas, C., and Martin, M. P.: Pedotransfer functions for predicting available water capacity in French soils, their applicability domain and associated uncertainty, Geoderma, 336, 81–95, 2019.
Dondini, M., Jones, E. O., Richards, M., Pogson, M., Rowe, R. L., Keith, A. M., Perks, M. P., McNamara, N. P., Smith, J. U., and Smith, P.: Evaluation of the ECOSSE model for simulating soil carbon under short rotation forestry energy crops in Britain, GCB Bioenergy, 7, 527–540, https://doi.org/10.1111/gcbb.12154, 2015.
Dufrene, E., Davi, H., Francois, C., le Maire, G., Le Dantec, V., and Granier, A.: Modelling carbon and water cycles in a beech forest Part I: Model description and uncertainty analysis on modelled NEE, Ecol. Modell., 185, 407–436, 2005.
Ellsworth, D. S., Crous, K. Y., Lambers, H., and Cooke, J.: Phosphorus recycling in photorespiration maintains high photosynthetic capacity in woody species, Plant Cell Environ., 38, 1142–1156, 2015.
Erb, K.-H., Kastner, T., Plutzar, C., Bais, A. L. S., Carvalhais, N., Fetzel, T., Gingrich, S., Haberl, H., Lauk, C., Niedertscheider, M., Pongratz, J., Thurner, M., and Luyssaert, S.: Unexpectedly large impact of forest management and grazing on global vegetation biomass, Nature, 553, 73–76, 2017.
Fajardo, A. and Siefert, A.: Phenological variation of leaf functional traits within species, Oecologia, 180, 951–959, 2016.
Farquhar, G. D., von Caemmerer, S., and Berry, J.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, 1980.
Felzer, B. S. and Jiang, M.: Effect of Land Use and Land Cover Change in Context of Growth Enhancements in the United States Since 1700: Net Source or Sink?, J. Geophys. Res.-Biogeo., 123, 3439–3457, 2018.
Forrester, D. I., Tachauer, I. H. H., Annighoefer, P., Barbeito, I., Pretzsch, H., Ruiz-Peinado, R., Stark, H., Vacchiano, G., Zlatanov, T., Chakraborty, T., Saha, S., and Sileshi, G. W.: Generalized biomass and leaf area allometric equations for European tree species incorporating stand structure, tree age and climate, Forest Ecol. Manag., 396, 160–175, https://doi.org/10.1016/j.foreco.2017.04.011, 2017.
Garcia, M., Ozdogan, M., and Townsend, P. A.: Impacts of forest harvest on cold season land surface conditions and land-atmosphere interactions in northern Great Lakes states, J. Adv. Model. Earth Sy., 6, 923–937, https://doi.org/10.1002/2014ms000317, 2014.
Gash, J. H. C.: Analytical model of rainfall interception by forests, Q. J. Roy. Meteor. Soc., 105, 43–55, https://doi.org/10.1002/qj.49710544304, 1979.
Gbondo-Tugbawa, S. S., Driscoll, C. T., Aber, J. D., and Likens, G. E.: Evaluation of an integrated biogeochemical model (PnET-BGC) at a northern hardwood forest ecosystem, Water Resour. Res., 37, 1057–1070, https://doi.org/10.1029/2000WR900375, 2001.
Ghanbarian-Alavijeh, B., Liaghat, A., Huang, G.-H., and Van Genuchten, M. T.: Estimation of the van Genuchten Soil Water Retention Properties from Soil Textural Data, Pedosphere, 20, 456–465, 2010.
Gholz, H. L.: Limits on aboveground net primary production, leaf area, and biomass in vegetational zones of the Pacific Northwest, Dissertation, Oregon State University, Corvallis, Oregon, USA, 1979.
Gottschalk, P., Bellarby, J., Chenu, C., Foereid, B., Smith, P., Wattenbach, M., Zingore, S., and Smith, J.: Simulation of soil organic carbon response at forest cultivation sequences using C-13 measurements, Org. Geochem., 41, 41–54, https://doi.org/10.1016/j.orggeochem.2009.04.017, 2010.
Granier, A. and Bréda, N.: Modelling canopy conductance and stand transpiration of an oak forest from sap flow measurements, Ann. For. Sci., 53, 537–546, 1996.
Granier, A. and Loustau, D.: Measuring and modelling the transpiration of a maritime pine canopy from sap-flow data, Agr. Forest. Meteorol., 71, 61–81, 1994.
Granier, A., Ceschia, E., Damesin, C., Dufrene, E., Epron, D., Gross, P., Lebaube, S., Le Dantec, V., Le Goff, N., Lemoine, D., Lucot, E., Ottorini, J. M., Pontailler, J. Y., and Saugier, B.: The carbon balance of a young Beech forest, Funct. Ecol., 14, 312–325, 2000a.
Granier, A., Loustau, D., and Bréda, N.: A generic model of forest canopy conductance dependent of climate, soil water availability and leaf area index, Ann. For. Sci., 57, 755–765, 2000b.
Grassi, G., House, J., Dentener, F., Federici, S., den Elzen, M., and Penman, J.: The key role of forests in meeting climate targets requires science for credible mitigation, Nat. Clim. Change, 7, 220–226, 2017.
Griscom, B. W., Adams, J., Ellis, P. W., Houghton, R. A., Lomax, G., Miteva, D. A., Schlesinger, W. H., Shoch, D., Siikamaki, J. V., Smith, P., Woodbury, P., Zganjar, C., Blackman, A., Campari, J., Conant, R. T., Delgado, C., Elias, P., Gopalakrishna, T., Hamsik, M. R., Herrero, M., Kiesecker, J., Landis, E., Laestadius, L., Leavitt, S. M., Minnemeyer, S., Polasky, S., Potapov, P., Putz, F. E., Sanderman, J., Silvius, M., Wollenberg, E., and Fargione, J.: Natural climate solutions, P. Natl. Acad. Sci. USA., 114, 11645–11650, https://doi.org/10.1073/pnas.1710465114, 2017.
Guillemot, J., Delpierre, N., Vallet, P., François, C., Martin-StPaul, N. K., Soudani, K., Nicolas, M., Badeau, V., and Dufrêne, E.: Assessing the effects of management on forest growth across France: insights from a new functional–structural model, Ann. Bot., 114, 779–793, https://doi.org/10.1093/aob/mcu059, 2014.
Gutsch, M., Lasch, P., Suckow, F., and Reyer, C.: Management of mixed oak-pine forests under climate scenario uncertainty, Forest Syst., 20, 453–463, https://doi.org/10.5424/fs/20112003-11073, 2011.
Hamada, S., Kumagai, T., Kochi, K., Kobayashi, N., Hiyama, T., and Miyazawa, Y.: Spatial and temporal variations in photosynthetic capacity of a temperate deciduous-evergreen forest, Trees-Structure and Function, 30, 1083–1093, 2016.
Harley, P. C. and Baldocchi, D. D.: Scaling carbon-dioxide and water-vapour exchange from leaf to canopy in a deciduous forest .1. Leaf model parameterization, Plant. Cell Environ., 18, 1146–1156, https://doi.org/10.1111/j.1365-3040.1995.tb00625.x, 1995.
Harper, A. B., Wiltshire, A. J., Cox, P. M., Friedlingstein, P., Jones, C. D., Mercado, L. M., Sitch, S., Williams, K., and Duran-Rojas, C.: Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types, Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, 2018.
Hassika, P., Berbigier, P., and Bonnefond, J. M.: Measurement and modelling of the photosynthetically active radiation transmitted in a canopy of maritime pine, Ann. For. Sci., 54, 715–730, 1997.
Huang, L., Zhai, J., Liu, J. Y., and Sun, C. Y.: The moderating or amplifying biophysical effects of afforestation on CO2-induced cooling depend on the local background climate regimes in China, Agr. Forest. Meteorol., 260, 193–203, https://doi.org/10.1016/j.agrformet.2018.05.020, 2018.
Humphreys, E. R., Black, T. A., Morgenstern, K., Cai, T., Drewitt, G. B., Nesic, Z., and Trofymow, J. A.: Carbon dioxide fluxes in coastal Douglas-fir stands at different stages of development after clearcut harvesting, Agr. Forest Meteorol., 140, 6–22, 2006.
Ibrom, A. and Pilegaard, K.: FLUXNET2015 DK-Sor Soroe, Dataset, https://doi.org/10.18140/FLX/1440155, 1996–2014.
IPCC: Climate Change and Land. An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, available at: https://www.ipcc.ch/srccl-report-download-page/, last access: 19 September 2019.
Janssens, I. A., Lankreijer, H., Matteucci, G., Kowalski, A. S., Buchmann, N., Epron, D., Pilegaard, K., Kutsch, W., Longdoz, B., Grunwald, T., Montagnani, L., Dore, S., Rebmann, C., Moors, E. J., Grelle, A., Rannik, U., Morgenstern, K., Oltchev, S., Clement, R., Gudmundsson, J., Minerbi, S., Berbigier, P., Ibrom, A., Moncrieff, J., Aubinet, M., Bernhofer, C., Jensen, N. O., Vesala, T., Granier, A., Schulze, E. D., Lindroth, A., Dolman, A. J., Jarvis, P. G., Ceulemans, R., and Valentini, R.: Productivity overshadows temperature in determining soil and ecosystem respiration across European forests, Global Change Biol., 7, 269–278, https://doi.org/10.1046/j.1365-2486.2001.00412.x, 2001.
Jarvis, P. G.: The interpretation of the variation in leaf water potential and stomatal conductance found in canopies in the field, Phil. Trans. R. Soc. B, 273, 593–610, 1976.
Jolivet, C.: Le carbone organique des sols des Landes de Gascogne variabilité spatiale et effets des pratiques sylvicoles et agricoles, PhD Thesis, Université de Bourgogne, Dijon, 306 pp., 2000.
Jones, H. G.: Plants and microclimate: a quantitative approach to environmental plant physiology, Cambridge University Press, Cambridge, 1992.
Jurevics, A., Peichl, M., Olsson, B. A., Stromgren, M., and Egnell, G.: Slash and stump harvest have no general impact on soil and tree biomass C pools after 32–39 years, Forest Ecol. Manag., 371, 33–41, https://doi.org/10.1016/j.foreco.2016.01.008, 2016.
Karjalainen, T., Pussinen, A., Liski, J., Nabuurs, G. J., Eggers, T., Lapvetelainen, T., and Kaipainen, T.: Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget, Forest Policy Econ, 5, 141–155, 2003.
Knorr, W., Prentice, I. C., House, J. I., and Holland, E. A.: Long-term sensitivity of soil carbon turnover to warming, Nature, 433, 298–301, https://doi.org/10.1038/nature03226, 2005.
Kurz, W. A., Dymond, C. C., White, T. M., Stinson, G., Shaw, C. H., Rampley, G. J., Smyth, C., Simpson, B. N., Neilson, E. T., Tyofymow, J. A., Metsaranta, J., and Apps, M. J.: CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards, Ecol. Modell., 220, 480–504, 2009.
Kuusinen, N., Lukes, P., Stenberg, P., Levula, J., Nikinmaa, E., and Berninger, F.: Measured and modelled albedos in Finnish boreal forest stands of different species, structure and understory, Ecol. Modell., 284, 10–18, https://doi.org/10.1016/j.ecolmodel.2014.04.007, 2014.
Landsberg, J. J. and Waring, R. H.: A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning, Forest Ecol. Manag., 95, 209–228, 1997.
Lebourgeois, F., Pierrat, J.-C., Perez, V., Piedallu, C., Cecchini, S., Ulrich, E.: Phenological timing in French temperate forests – a study on stands in the renecofor network, Revue Forestiere Française, 60, 323–343, 2008.
Lee, X., Goulden, M. L., Hollinger, D. Y., Barr, A., Black, T. A., Bohrer, G., Bracho, R., Drake, B., Goldstein, A., Gu, L. H., Katul, G., Kolb, T., Law, B. E., Margolis, H., Meyers, T., Monson, R., Munger, W., Oren, R., Kyaw, T. P. U., Richardson, A. D., Schmid, H. P., Staebler, R., Wofsy, S., and Zhao, L.: Observed increase in local cooling effect of deforestation at higher latitudes, Nature, 479, 384–387, https://doi.org/10.1038/nature10588, 2011.
Le Moguedec, G. and Dhôte, J. F.: Fagacees: a tree-centered growth and yield model for sessile oak (Quercus petraea L.) and common beech (Fagus sylvatica L.), Ann. For. Sci., 69, 257–269, 2012.
Lindner, M., Bugmann, H., Lasch, P., Flechsig, M., and Cramer, W.: Regional impacts of Clim. Change on forests in the state of Brandenburg, Germany, Agr. Forest. Meteorol., 84, 123–135, 10.1016/s0168-1923(96)02381-7, 1997.
Loustau, D. and Cochard, H.: Use of a portable transpiration chamber for estimating evapotranspiration in the Molinia caerulea understorey of a maritime pine stand, Ann. For. Sci., 48, 29–45, 1991.
Loustau, D., Berbigier, P., Roumagnac, P., Ferreira, M. I., Pereira, J. S., Arruda-Pacheco, C., David, J. S., and Tavares, R.: Transpiration of a 64-year-old maritime pine stand in Portugal. I: Seasonal course of water flux through maritime pine, Oecologia, 107, 33–42, 1996.
Loustau, D., Domec, J. C., and Bosc, A.: Interpreting the variations in xylem sap flux density within the trunk of maritime pine (Pinus pinaster Ait.): application of a model for calculating water flows at tree and stand levels, Ann. For. Sci., 55, 29–46, 1998.
Loustau, D., Bosc, A., Colin, A., Ogee, J., Davi, H., Francois, C., Dufrene, E., Deque, M., Cloppet, E., Arrouays, D., Le Bas, C., Saby, N., Pignard, G., Hamza, N., Granier, A., Breda, N., Ciais, P., Viovy, N., and Delage, F.: Modeling climate change effects on the potential production of French plains forests at the sub-regional level, Tree Physiol., 25, 813–823, 2005.
Loustau, D., Moisy, C., Bosc, A., Figuères, S., Martel, S., Moreaux, V., and Picart-Deshors, D.: GO+ v3.0 model code, Portail Data INRAE, V2, https://doi.org/10.15454/5K9HCS, 2020.
Luyssaert, S., Jammet, M., Stoy, P. C., Estel, S., Pongratz, J., Ceschia, E., Churkina, G., Don, A., Erb, K., Ferlicoq, M., Gielen, B., Grunwald, T., Houghton, R. A., Klumpp, K., Knohl, A., Kolb, T., Kuemmerle, T., Laurila, T., Lohila, A., Loustau, D., McGrath, M. J., Meyfroidt, P., Moors, E. J., Naudts, K., Novick, K., Otto, J., Pilegaard, K., Pio, C. A., Rambal, S., Rebmann, C., Ryder, J., Suyker, A. E., Varlagin, A., Wattenbach, M., and Dolman, A. J.: Land management and land-cover change have impacts of similar magnitude on surface temperature, Nat. Clim. Change, 4, 389–393, https://doi.org/10.1038/nclimate2196, 2014.
Luyssaert, S., Marie, G., Valade, A., Chen, Y.-Y., Njakou Djomo, S., Ryder, J., Otto, J., Naudts, K., Lansø, A. S., Ghattas, J., and McGrath, M. J.: Trade-offs in using European forests to meet climate objectives, Nature, 562, 259–262, https://doi.org/10.1038/s41586-018-0577-1, 2018.
Masera, O. R., Garza-Caligaris, J. F., Kanninen, M., Karjalainen, T., Liski, J., Nabuurs, G. J., Pussinen, A., de Jong, B. H. J., and Mohren, G. M. J.: Modeling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach, Ecol. Modell., 164, 177–199, 2003.
Matteucci, G.: FLUXNET2015 IT-Col Collelongo, Dataset, https://doi.org/10.18140/FLX/1440167, 1996–2014.
Medlyn, B. E., Barton, C. V. M., Broadmeadow, M. S. J., Ceulemans, R., De Angelis, P., Forstreuter, M., Freeman, M., Jackson, S. B., Kellomaki, S., Laitat, E., Rey, A., Roberntz, P., Sigurdsson, B. D., Strassemeyer, J., Wang, K., Curtis, P. S., and Jarvis, P. G.: Stomatal conductance of forest species after long-term exposure to elevated CO2 concentration: a synthesis, New Phytol., 149, 247–264, 2001.
Medlyn, B. E., Dreyer, E., Ellsworth, D., Forstreuter, M., Harley, P. C., Kirschbaum, M. U. F., Le Roux, X., Montpied, P., Strassemeyer, J., Walcroft, A., Wang, K., and Loustau, D.: Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data, Plant Cell Environ., 25, 1167–1179, 2002.
Medlyn, B. E., Berbigier, P., Clement, R., Grelle, A., Loustau, D., Linder, S., Wingate, L., Jarvis, P. G., Sigurdsson, B. D., and McMurtrie, R. E.: Carbon balance of coniferous forests growing in contrasting climates: Model-based analysis, Agric. Forest Meteorol., 131, 97–124, 2005.
Mencuccini, M., Minunno, F., Salmon, Y., Martínez-Vilalta, J., and Hölttä, T.: Coordination of physiological traits involved in drought-induced mortality of woody plants, New Phytol., 208, 396–409, https://doi.org/10.1111/nph.13461, 2015.
Moffat, A. M., Papale, D., Reichstein, M., Hollinger, D. Y., Richardson, A. D., Barr, A. G., Beckstein, C., Braswell, B. H., Churkina, G., Desai, A. R., Falge, E., Gove, J. H., Heimann, M., Hui, D. F., Jarvis, A. J., Kattge, J., Noormets, A., and Stauch, V. J.: Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes, Agric. Forest Meteorol., 147, 209–232, 2007.
Moreaux, V.: Observation et modélisation des échanges d'énergie et de masse de jeunes peuplements forestiers du Sud-Ouest de la France, PhD thesis, Ecole Doctorale 304 “Sciences et Environnements”, Thématique “Physique de l'Environnement”, Université de Bordeaux-1, Bordeaux, 262 pp., 2012.
Moreaux, V., Lamaud, E., Bosc, A., Bonnefond, J.-M., Medlyn, B. E., and Loustau, D.: Paired comparison of water, energy and carbon exchanges over two young maritime pine stands (Pinus pinaster Ait.): effects of thinning and weeding in the early stage of tree growth, Tree Physiol., 31, 903–921, 2011.
Moreaux, V., Longdoz, B., Berveiller, D., Delpierre, N., Dufrêne, E., Bonnefond, J.-M., Chipeaux, C., Joffre, R., Limousin, J.-M., Ourcival, J.-M., Klumpp, K., Darsonville, O., Brut, A., Tallec, T., Ceschia, E., Panthou, G., and Loustau, D.: Environmental control of land-atmosphere CO2 fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types, Tellus B, 72, 1–25, 2020.
Muzylo, A., Llorens, P., Valente, F., Keizer, J. J., Domingo, F., and Gash, J. H. C.: A review of rainfall interception modelling, J. Hydrol., 370, 191–206, https://doi.org/10.1016/j.jhydrol.2009.02.058, 2009.
Nakai, T., Sumida, A., Daikoku, K. I., Matsumoto, K., van der Molen, M. K., Kodama, Y., Kononov, A. V., Maximov, T. C., Dolman, A. J., Yabuki, H., Hara, T., and Ohta, T.: Parameterisation of aerodynamic roughness over boreal, cool- and warm-temperate forests, Agr. For. Meteorol., 148, 1916–1925, https://doi.org/10.1016/j.agrformet.2008.03.009, 2008.
Naudts, K., Ryder, J., McGrath, M. J., Otto, J., Chen, Y., Valade, A., Bellasen, V., Berhongaray, G., Bönisch, G., Campioli, M., Ghattas, J., De Groote, T., Haverd, V., Kattge, J., MacBean, N., Maignan, F., Merilä, P., Penuelas, J., Peylin, P., Pinty, B., Pretzsch, H., Schulze, E. D., Solyga, D., Vuichard, N., Yan, Y., and Luyssaert, S.: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geosci. Model Dev., 8, 2035–2065, https://doi.org/10.5194/gmd-8-2035-2015, 2015.
Naudts, K., Chen, Y. Y., McGrath, M. J., Ryder, J., Valade, A., Otto, J., and Luyssaert, S.: Europe's forest management did not mitigate climate warming, Science, 351, 597–600, https://doi.org/10.1126/science.aad7270, 2016.
Otto, J., Berveiller, D., Bréon, F.-M., Delpierre, N., Geppert, G., Granier, A., Jans, W., Knohl, A., Kuusk, A., Longdoz, B., Moors, E., Mund, M., Pinty, B., Schelhaas, M.-J., and Luyssaert, S.: Forest summer albedo is sensitive to species and thinning: how should we account for this in Earth system models?, Biogeosciences, 11, 2411–2427, https://doi.org/10.5194/bg-11-2411-2014, 2014.
Pan, Y. D., Birdsey, R. A., Fang, J. Y., 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. L., 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.
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Penning De Vries, F. W., Brunsting, A. H., and Van Laar, H. H.: Products, requirements and efficiency of biosynthesis – Quantitative approach, J. Theor. Biol., 45, 339–377, 1974.
Pichancourt, J. B., Manso, R., Ningre, F., and Fortin, M.: A carbon accounting tool for complex and uncertain greenhouse gas emission life cycles, Environ. Modell. Softw., 107, 158–174, 2018.
Pilegaard, K., Ibrom, A. Courtney, M. S., Hummelshøj, P., Jensen, N. O.: Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009, Agr. Forest Meteorol., 151, 934–946, https://doi.org/10.1016/j.agrformet.2011.02.013, 2011.
Pilli, R., Grassi, G., Kurz, W. A., Fiorese, G., and Cescatti, A.: The European forest sector: past and future carbon budget and fluxes under different management scenarios, Biogeosciences, 14, 2387–2405, https://doi.org/10.5194/bg-14-2387-2017, 2017.
Pourmokhtarian, A., Driscoll, C. T., Campbell, J. L., and Hayhoe, K.: Modeling potential hydrochemical responses to climate change and increasing CO2 at the Hubbard Brook Experimental Forest using a dynamic biogeochemical model (PnET-BGC), Water Resour. Res., 48, W07514, https://doi.org/10.1029/2011WR011228, 2012.
Rasche, L., Fahse, L., and Bugmann, H.: Key factors affecting the future provision of tree-based forest ecosystem goods and services, Clim. Change, 118, 579–593, https://doi.org/10.1007/s10584-012-0664-5, 2013.
Rayment, M. B., Loustau, D., and Jarvis, P. G.: Measuring and modeling conductances of black spruce at three organizational scales: shoot, branch and canopy, Tree Physiol., 20, 713–723, 2000.
Rayment, M. B., Loustau, D., and Jarvis, P. J.: Photosynthesis and respiration of black spruce at three organizational scales: shoot, branch and canopy, Tree Physiol., 22, 219–229, 2002.
Reineke, L. H.: Perfecting a stand-density index for even-aged forests, J. Agric. Res., 46, 627–638, 1933.
Reyer, C., Lasch-Born, P., Suckow, F., Gutsch, M., Murawski, A., and Pilz, T.: Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide, Ann. For. Sci., 71, 211–225, 2014.
Reyer, C., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y., Noack, M., Lasch-Born, P., Rötzer, T., Pretzsch, H., Meesenburg, H., Fleck, S., Wagner, M., Bolte, A., Sanders, T., Kolari, P., Mäkelä, A., Vesala, T., Mammarella, I., Pumpanen, J., Matteucci, G., Collalti, A., D'Andrea, E., Foltýnová, L., Krejza, J., Ibrom, A., Pilegaard, K., Loustau, D., Bonnefond, J.-M., Berbigier, P., Picart, D., Lafont, S., Dietze, M., Cameron, D., Vieno, M., Tian, H., Palacios-Orueta, A., Cicuendez, V., Recuero, L., Wiese, K., Büchner, M., Lange, S., Volkholz, J., Kim, H., Weedon, G., Sheffield, J., Vega del Valle, I., Suckow, F., Horemans, J., Martel, S., Bohn, F., Steinkamp, J., Chikalanov, A., and Frieler, K.: The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests, V. 0.1.12, GFZ Data Services, https://doi.org/10.5880/PIK.2019.008, 2019.
Romanya, J., Cortina, J., Falloon, P., Coleman, K., and Smith, P.: Modelling changes in soil organic matter after planting fast-growing Pinus radiata on Mediterranean agricultural soils, Eur. J. Soil Sci., 51, 627–641, 2000.
Ryan, M. G.: Effects of climate change on plant respiration, Ecol. Appl., 1, 157–167, 1991.
Sathre, R. and O'Connor, J.: Meta-analysis of greenhouse gas displacement factors of wood product substitution, Environ. Sci. Policy, 13, 104–114, https://doi.org/10.1016/j.envsci.2009.12.005, 2010.
Scartazza, A., Moscatello, S., Matteucci, G., Battistelli, A., and Brugnoli, E.: Seasonal and inter-annual dynamics of growth, non-structural carbohydrates and C stable isotopes in a Mediterranean beech forest, Tree Physiol., 33, 730–742, 2013.
Schlamadinger, B. and Marland, G.: The role of forest and bioenergy strategies in the global carbon cycle, Biomass Bioenerg., 10, 275–300, https://doi.org/10.1016/0961-9534(95)00113-1, 1996.
Shaiek, O., Loustau, D., Trichet, P., Meredieu, C., Bachtobji, B., Garchi, S., and El Aouni, M. H.: Generalized biomass equations for the main aboveground biomass components of maritime pine across contrasting environments, Ann. For. Sci., 68, 443–452, 2011.
Smith, P., Smith, J., Wattenbach, M., Meyer, J., Lindner, M., Zaehle, S., Hiederer, R., Jones, R. J. A., Montanarella, L., Rounsevell, M., Reginster, I., and Kankaanpaa, S.: Projected changes in mineral soil carbon of European forests, 1990–2100, Can. J. Soil Sci., 86, 159–169, 2006.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014.
Stoy, P. C., Katul, G. G., Siqueira, M. B. S., Juang, J. Y., McCarthy, H. R., Kim, H. S., Oishi, A. C., and Oren, R.: Variability in net ecosystem exchange from hourly to inter-annual time scales at adjacent pine and hardwood forests: a wavelet analysis, Tree Physiol., 25, 887–902, https://doi.org/10.1093/treephys/25.7.887, 2005.
Stoy, P. C., Richardson, A. D., Baldocchi, D. D., Katul, G. G., Stanovick, J., Mahecha, M. D., Reichstein, M., Detto, M., Law, B. E., Wohlfahrt, G., Arriga, N., Campos, J., McCaughey, J. H., Montagnani, L., Paw U, K. T., Sevanto, S., and Williams, M.: Biosphere–atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales, Biogeosciences, 6, 2297–2312, https://doi.org/10.5194/bg-6-2297-2009, 2009.
Stromgren, M., Egnell, G., and Olsson, B. A.: Carbon stocks in four forest stands in Sweden 25 years after harvesting of slash and stumps, Forest Ecol. Manag., 290, 59–66, https://doi.org/10.1016/j.foreco.2012.06.052, 2013.
Subedi, P., Jokela, E. J., Vogel, J. G., and Martin, T. A.: Inter-rotational effects of fertilization and weed control on juvenile loblolly pine productivity and nutrient dynamics, Soil Sci. Soc. Am. J., 78, S152–S167, https://doi.org/10.2136/sssaj2013.08.0345nafsc, 2014.
Thum, T., MacBean, N., Peylin, P., Bacour, C., Santaren, D., Longdoz, B., Loustau, D., and Ciais, P.: The potential benefit of using forest biomass data in addition to carbon and water flux measurements to constrain ecosystem model parameters: Case studies at two temperate forest sites, Agr. Forest Meteorol., 234–235, 48–65, https://doi.org/10.1016/j.agrformet.2016.12.004, 2017.
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Van Wijk, M. T., Dekker, S. C., Bouten, W., Bosveld, F. C., Kohsiek, W., Kramer, K., and Mohren, G. M. J.: Modeling daily gas exchange of a Douglas-fir forest: comparison of three stomatal conductance models with and without a soil water stress function, Tree Physiol., 20, 115–122, 2000.
Wallach, D. and Goffinet, B.: Mean squared error of prediction as a criterion for evaluating and comparing system models, Ecol. Modell., 44, 299–306, https://doi.org/10.1016/0304-3800(89)90035-5, 1989.
Wang, Y. X., Zhu, X. D., Bai, S. B., Zhu, T. T., Qiu, W. T., You, Y. J., Wu, M. J., Berninger, F., Sun, Z. B., Zhang, H., and Zhang, X. H.: Effects of forest regeneration practices on the flux of soil CO2 after clear-cutting in subtropical China, J. Environ. Manage., 212, 332–339, https://doi.org/10.1016/j.jenvman.2018.02.038, 2018.
Wösten, J. H. M., Lilly, A., Nemes, A., and Le Bas, C.: Development and use of a database of hydraulic properties of European soils, Geoderma, 90, 169–185, 1999.
Wutzler, T., Wirth, C., and Schumacher, J.: Generic biomass functions for Common beech (Fagus sylvatica) in Central Europe: predictions and components of uncertainty, Can. J. For. Res., 38, 1661–1675, https://doi.org/10.1139/x07-194, 2008.
Yousefpour, R., Augustynczik, A. L. D., Reyer, C. P. O., Lasch-Born, P., Suckow, F., and Hanewinkel, M.: Realizing mitigation efficiency of European commercial forests by climate smart forestry, Sci. Rep.-UK, 8, 345, https://doi.org/10.1038/s41598-017-18778-w, 2018.
Zhang, X. Z., Guan, D. X., Li, W. B., Sun, D., Jin, C. J., Yuan, F. H., Wang, A. Z., and Wu, J. B.: The effects of forest thinning on soil carbon stocks and dynamics: A meta-analysis, Forest Ecol. Manag., 429, 36–43, https://doi.org/10.1016/j.foreco.2018.06.027, 2018.
Short summary
The model GO+ describes the functioning of managed forests based upon biophysical and biogeochemical processes. It accounts for the impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes versatile descriptions of management operations. Its sensitivity and uncertainty are detailed and predictions are compared with observations about mass and energy exchanges, hydrological data, and tree growth variables from different sites.
The model GO+ describes the functioning of managed forests based upon biophysical and...
