Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3789-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3789-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
24 Jun 2021
Model evaluation paper |
| 24 Jun 2021
| 24 Jun 2021
Modeling gas exchange and biomass production in West African Sahelian and Sudanian ecological zones
Jaber Rahimi
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Expedit Evariste Ago
Laboratoire d'Ecologie Appliquée, Faculté des Sciences
Agronomiques, Université d'Abomey-Calavi, Cotonou, Benin
Biodiversity and Landscape Unit, Université de Liège Gembloux
Agro-Bio Tech, Gembloux, Belgium
Augustine Ayantunde
International Livestock Research Institute (ILRI), Ouagadougou,
Burkina Faso
Sina Berger
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Regional Climate and Hydrology Research
Group, University of Augsburg, Augsburg, Germany
Jan Bogaert
Biodiversity and Landscape Unit, Université de Liège Gembloux
Agro-Bio Tech, Gembloux, Belgium
Klaus Butterbach-Bahl
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
International Livestock Research Institute (ILRI), Nairobi, Kenya
Bernard Cappelaere
HydroSciences Montpellier, Université Montpellier, IRD, CNRS,
Montpellier, France
Jean-Martial Cohard
IRD, CNRS, Université Grenoble Alpes, Grenoble, France
Jérôme Demarty
HydroSciences Montpellier, Université Montpellier, IRD, CNRS,
Montpellier, France
Abdoul Aziz Diouf
Centre de Suivi Ecologique (CSE), Dakar, Senegal
Ulrike Falk
Satellite-based Climate Monitoring, Deutscher Wetterdienst (DWD),
Offenbach, Germany
Edwin Haas
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Pierre Hiernaux
Géosciences Environnement Toulouse (GET), CNRS, IRD, UPS,
Toulouse, France
Pastoralisme Conseil, Caylus, France
David Kraus
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Olivier Roupsard
CIRAD, UMR Eco&Sols, BP1386, CP18524, Dakar, Senegal
Eco&Sols, Université Montpellier, CIRAD, INRAE, IRD,
Institut Agro, Montpellier, France
LMI IESOL, Centre IRD-ISRA de Bel Air, BP1386, CP18524, Dakar,
Senegal
Clemens Scheer
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Amit Kumar Srivastava
Institute of Crop Science and Resource Conservation, University of
Bonn, Bonn, Germany
Torbern Tagesson
Department of Geosciences and Natural Resource Management,
University of Copenhagen, Copenhagen, Denmark
Department of Physical Geography and Ecosystem Sciences, Lund
University, Lund, Sweden
Karlsruhe Institute of Technology, Institute of Meteorology and
Climate Research, Atmospheric Environmental Research (IMK-IFU),
Garmisch-Partenkirchen, Germany
Related authors
No articles found.
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.
Erwan Le Roux, Valentin Wendling, Gérémy Panthou, Océane Dubas, Jean-Pierre Vandervaere, Basile Hector, Guillaume Favreau, Jean-Martial Cohard, Caroline Pierre, Luc Descroix, Eric Mougin, Manuela Grippa, Laurent Kergoat, Jérôme Demarty, Nathalie Rouche, Jordi Etchanchu, and Christophe Peugeot
EGUsphere, https://doi.org/10.5194/egusphere-2025-1965, https://doi.org/10.5194/egusphere-2025-1965, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
In hydrological science, better accounting for regime shift (abrupt and/or irreversible changes) remains a challenge that could lead to a new paradigm for the adaptation to extreme events (flood , drought). In this article, we present a simple model that can account for a hydrological regime shift in Sahelian watersheds. Based on this model, we find that the Dargol, Nakanbé, and Sirba watersheds have shifted during the droughts of the '70s–'80s, while the Gorouol watershed has shifted before.
Roxanne Daelman, Marijn Bauters, Matti Barthel, Emmanuel Bulonza, Lodewijk Lefevre, José Mbifo, Johan Six, Klaus Butterbach-Bahl, Benjamin Wolf, Ralf Kiese, and Pascal Boeckx
Biogeosciences, 22, 1529–1542, https://doi.org/10.5194/bg-22-1529-2025, https://doi.org/10.5194/bg-22-1529-2025, 2025
Short summary
Short summary
The increase in atmospheric concentrations of several greenhouse gases (GHGs) since 1750 is attributed to human activity. However, natural ecosystems, such as tropical forests, also contribute to GHG budgets. The Congo Basin hosts the second largest tropical forest and is understudied. In this study, measurements of soil GHG exchange were carried out during 16 months in a tropical forest in the Congo Basin. Overall, the soil acted as a major source of CO2 and N2O and a minor sink of CH4.
Dilli Paudel, Michiel Kallenberg, Stella Ofori-Ampofo, Hilmy Baja, Ron van Bree, Aike Potze, Pratishtha Poudel, Abdelrahman Saleh, Weston Anderson, Malte von Bloh, Andres Castellano, Oumnia Ennaji, Raed Hamed, Rahel Laudien, Donghoon Lee, Inti Luna, Michele Meroni, Janet Mumo Mutuku, Siyabusa Mkuhlani, Jonathan Richetti, Alex C. Ruane, Ritvik Sahajpal, Guanyuan Shai, Vasileios Sitokonstantinou, Rogério de Souza Nóia Júnior, Amit Kumar Srivastava, Robert Strong, Lily-belle Sweet, Petar Vojnovic, and Ioannis N. Athanasiadis
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-83, https://doi.org/10.5194/essd-2025-83, 2025
Preprint under review for ESSD
Short summary
Short summary
Improving crop yield predictions is crucial for food security. Prior research relied on case studies, making it hard to compare methods & track progress. We introduce CY-Bench, a global dataset for forecasting maize and wheat yields across diverse farming systems in over 25 countries. It includes standardized weather, soil, and satellite data, curated by a diverse set of experts. CY-Bench supports the development of better forecasting tools to help decision-makers plan for global food security.
Fawad Khan, Samuel Franco Luesma, Frederik Hartmann, Michael Dannenmann, Rainer Gasche, Clemens Scheer, Andreas Gattinger, Wiebke Niether, Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Ralf Kiese, and Benjamin Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2025-292, https://doi.org/10.5194/egusphere-2025-292, 2025
Short summary
Short summary
Crop rotations with legumes and use of organic and mineral fertilizers show potential to reduce agricultural N losses. This study examined N losses, including direct N2 flux, on two adjacent sites with different management history: organic farming (OF) with legume cultivation and integrated farming (IF) using synthetic and organic N inputs. IF increased soil organic carbon and nitrogen content, 15N recovery and showed a balanced N budget, i.e., more efficient N cycling compared to OF.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
Short summary
Short summary
Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Carolin Boos, Sophie Reinermann, Raul Wood, Ralf Ludwig, Anne Schucknecht, David Kraus, and Ralf Kiese
EGUsphere, https://doi.org/10.5194/egusphere-2024-2864, https://doi.org/10.5194/egusphere-2024-2864, 2024
Preprint archived
Short summary
Short summary
We applied a biogeochemical model on grasslands in the pre-Alpine Ammer region in Germany and analyzed the influence of soil and climate on annual yields. In drought affected years, total yields were decreased by 4 %. Overall, yields decrease with rising elevation, but less so in drier and hotter years, whereas soil organic carbon has a positive impact on yields, especially in drier years. Our findings imply, that adapted management in the region allows to mitigate yield losses from drought.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
Short summary
Short summary
A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
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.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
Short summary
Short summary
We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Odysseas Sifounakis, Edwin Haas, Klaus Butterbach-Bahl, and Maria P. Papadopoulou
Biogeosciences, 21, 1563–1581, https://doi.org/10.5194/bg-21-1563-2024, https://doi.org/10.5194/bg-21-1563-2024, 2024
Short summary
Short summary
We performed a full assessment of the carbon and nitrogen cycles of a cropland ecosystem. An uncertainty analysis and quantification of all carbon and nitrogen fluxes were deployed. The inventory simulations include greenhouse gas emissions of N2O, NH3 volatilization and NO3 leaching from arable land cultivation in Greece. The inventory also reports changes in soil organic carbon and nitrogen stocks in arable soils.
Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl
Biogeosciences, 20, 5029–5067, https://doi.org/10.5194/bg-20-5029-2023, https://doi.org/10.5194/bg-20-5029-2023, 2023
Short summary
Short summary
Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
Ricky Mwangada Mwanake, Gretchen Maria Gettel, Elizabeth Gachibu Wangari, Clarissa Glaser, Tobias Houska, Lutz Breuer, Klaus Butterbach-Bahl, and Ralf Kiese
Biogeosciences, 20, 3395–3422, https://doi.org/10.5194/bg-20-3395-2023, https://doi.org/10.5194/bg-20-3395-2023, 2023
Short summary
Short summary
Despite occupying <1 %; of the globe, streams are significant sources of greenhouse gas (GHG) emissions. In this study, we determined anthropogenic effects on GHG emissions from streams. We found that anthropogenic-influenced streams had up to 20 times more annual GHG emissions than natural ones and were also responsible for seasonal peaks. Anthropogenic influences also altered declining GHG flux trends with stream size, with potential impacts on stream-size-based spatial upscaling techniques.
Joseph Okello, Marijn Bauters, Hans Verbeeck, Samuel Bodé, John Kasenene, Astrid Françoys, Till Engelhardt, Klaus Butterbach-Bahl, Ralf Kiese, and Pascal Boeckx
Biogeosciences, 20, 719–735, https://doi.org/10.5194/bg-20-719-2023, https://doi.org/10.5194/bg-20-719-2023, 2023
Short summary
Short summary
The increase in global and regional temperatures has the potential to drive accelerated soil organic carbon losses in tropical forests. We simulated climate warming by translocating intact soil cores from higher to lower elevations. The results revealed increasing temperature sensitivity and decreasing losses of soil organic carbon with increasing elevation. Our results suggest that climate warming may trigger enhanced losses of soil organic carbon from tropical montane forests.
Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Reed Maxwell, Jean-Gabriel Valay, and Didier Voisin
Hydrol. Earth Syst. Sci., 27, 191–212, https://doi.org/10.5194/hess-27-191-2023, https://doi.org/10.5194/hess-27-191-2023, 2023
Short summary
Short summary
Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Ulrike Falk and Adrián Silva-Busso
Hydrol. Earth Syst. Sci., 25, 3227–3244, https://doi.org/10.5194/hess-25-3227-2021, https://doi.org/10.5194/hess-25-3227-2021, 2021
Short summary
Short summary
This paper focuses on the groundwater flow aspects of a small hydrological catchment at the northern tip of the Antarctic Peninsula. This region has experienced drastic climatological changes in the recent past. The basin is representative for the rugged coastline of the peninsula. It is discussed as a case study for possible future evolution of similar basins further south. Results include a quantitative analysis of glacial and groundwater contribution to total discharge into coastal waters.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
Short summary
Short summary
In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Wim Verbruggen, Guy Schurgers, Stéphanie Horion, Jonas Ardö, Paulo N. Bernardino, Bernard Cappelaere, Jérôme Demarty, Rasmus Fensholt, Laurent Kergoat, Thomas Sibret, Torbern Tagesson, and Hans Verbeeck
Biogeosciences, 18, 77–93, https://doi.org/10.5194/bg-18-77-2021, https://doi.org/10.5194/bg-18-77-2021, 2021
Short summary
Short summary
A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO2 uptake.
Virginie Moreaux, Simon Martel, Alexandre Bosc, Delphine Picart, David Achat, Christophe Moisy, Raphael Aussenac, Christophe Chipeaux, Jean-Marc Bonnefond, Soisick Figuères, Pierre Trichet, Rémi Vezy, Vincent Badeau, Bernard Longdoz, André Granier, Olivier Roupsard, Manuel Nicolas, Kim Pilegaard, Giorgio Matteucci, Claudy Jolivet, Andrew T. Black, Olivier Picard, and Denis Loustau
Geosci. Model Dev., 13, 5973–6009, https://doi.org/10.5194/gmd-13-5973-2020, https://doi.org/10.5194/gmd-13-5973-2020, 2020
Short summary
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.
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.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
Short summary
Short summary
The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
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.
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.
Genki Katata, Rüdiger Grote, Matthias Mauder, Matthias J. Zeeman, and Masakazu Ota
Biogeosciences, 17, 1071–1085, https://doi.org/10.5194/bg-17-1071-2020, https://doi.org/10.5194/bg-17-1071-2020, 2020
Short summary
Short summary
In this paper, we demonstrate that high physiological activity levels during the extremely warm winter are allocated into the below-ground biomass and only to a minor extent used for additional plant growth during early spring. This process is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, and it may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.
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.
Erkan Ibraim, Benjamin Wolf, Eliza Harris, Rainer Gasche, Jing Wei, Longfei Yu, Ralf Kiese, Sarah Eggleston, Klaus Butterbach-Bahl, Matthias Zeeman, Béla Tuzson, Lukas Emmenegger, Johan Six, Stephan Henne, and Joachim Mohn
Biogeosciences, 16, 3247–3266, https://doi.org/10.5194/bg-16-3247-2019, https://doi.org/10.5194/bg-16-3247-2019, 2019
Short summary
Short summary
Nitrous oxide (N2O) is an important greenhouse gas and the major stratospheric ozone-depleting substance; therefore, mitigation of anthropogenic N2O emissions is needed. To trace N2O-emitting source processes, in this study, we observed N2O isotopocules above an intensively managed grassland research site with a recently developed laser spectroscopy method. Our results indicate that the domain of denitrification or nitrifier denitrification was the major N2O source.
Eric Mougin, Mamadou Oumar Diawara, Nogmana Soumaguel, Ali Amadou Maïga, Valérie Demarez, Pierre Hiernaux, Manuela Grippa, Véronique Chaffard, and Abdramane Ba
Earth Syst. Sci. Data, 11, 675–686, https://doi.org/10.5194/essd-11-675-2019, https://doi.org/10.5194/essd-11-675-2019, 2019
Short summary
Short summary
The leaf area index of Sahelian rangelands was measured between 2005 and 2017 in northern Mali. These observations collected over more than a decade, in a remote and not very accessible region, provide a relevant and unique data set that can be used for a better understanding of the Sahelian vegetation response to the current rainfall changes. The collected data can also be used for satellite product evaluation and land surface model validation.
Claire Delon, Corinne Galy-Lacaux, Dominique Serça, Erwan Personne, Eric Mougin, Marcellin Adon, Valérie Le Dantec, Benjamin Loubet, Rasmus Fensholt, and Torbern Tagesson
Biogeosciences, 16, 2049–2077, https://doi.org/10.5194/bg-16-2049-2019, https://doi.org/10.5194/bg-16-2049-2019, 2019
Short summary
Short summary
In the Sahel region during the wet season, CO2 and NO are released to the atmosphere, and NH3 is deposited on the soil. During the dry season, processes are strongly reduced. This paper shows the temporal variation in these soil–atmosphere exchanges of trace gases for 2 years, their sharp increase when the first rains fall onto dry soils, and how microbial processes are involved. We use a modelling approach, which is necessary when continuous measurements are not possible in remote regions.
Basile Hector, Jean-Martial Cohard, Luc Séguis, Sylvie Galle, and Christophe Peugeot
Hydrol. Earth Syst. Sci., 22, 5867–5888, https://doi.org/10.5194/hess-22-5867-2018, https://doi.org/10.5194/hess-22-5867-2018, 2018
Short summary
Short summary
The hydrological functioning of western African headwater wetlands remains poorly understood, despite their potential for small-scale farming and their role in streamflow production. We found that land cover changes significantly affect water budgets, and pedo-geological features control dry season baseflow. These are the results of virtual experiments with a physically based critical zone model evaluated against streamflow, evapotranspiration, soil moisture, water table and water storage data.
Martin Rückamp, Ulrike Falk, Katja Frieler, Stefan Lange, and Angelika Humbert
Earth Syst. Dynam., 9, 1169–1189, https://doi.org/10.5194/esd-9-1169-2018, https://doi.org/10.5194/esd-9-1169-2018, 2018
Short summary
Short summary
Sea-level rise associated with changing climate is expected to pose a major challenge for societies. Based on the efforts of COP21 to limit global warming to 2.0 °C by the end of the 21st century (Paris Agreement), we simulate the future contribution of the Greenland ice sheet (GrIS) to sea-level change. The projected sea-level rise ranges between 21–38 mm by 2100
and 36–85 mm by 2300. Our results indicate that uncertainties in the projections stem from the underlying climate data.
Suzanne R. Jacobs, Edison Timbe, Björn Weeser, Mariana C. Rufino, Klaus Butterbach-Bahl, and Lutz Breuer
Hydrol. Earth Syst. Sci., 22, 4981–5000, https://doi.org/10.5194/hess-22-4981-2018, https://doi.org/10.5194/hess-22-4981-2018, 2018
Short summary
Short summary
This study investigated how land use affects stream water sources and flow paths in an East African tropical montane area. Rainfall was identified as an important stream water source in the forest and smallholder agriculture sub-catchments, while springs were more important in the commercial tea plantation sub-catchment. However, 15 % or less of the stream water consisted of water with an age of less than 3 months, indicating that groundwater plays an important role in all land use types.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
Short summary
Short summary
This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Ulrike Falk, Damián A. López, and Adrián Silva-Busso
The Cryosphere, 12, 1211–1232, https://doi.org/10.5194/tc-12-1211-2018, https://doi.org/10.5194/tc-12-1211-2018, 2018
Short summary
Short summary
The present study address the glacier–atmosphere relation on King George Island (South Shetland Islands) at the northern Antarctic Peninsula. The focus is on 5 years of glacier mass balance observations and the adaptation of a spatially distributed, physically based mass balance model. The focus is on the analysis of equilibrium line altitude and catchment runoff. The observed changes are expected to have a direct impact on environmental conditions in coastal waters and biota.
Francisco Fernandoy, Dieter Tetzner, Hanno Meyer, Guisella Gacitúa, Kirstin Hoffmann, Ulrike Falk, Fabrice Lambert, and Shelley MacDonell
The Cryosphere, 12, 1069–1090, https://doi.org/10.5194/tc-12-1069-2018, https://doi.org/10.5194/tc-12-1069-2018, 2018
Short summary
Short summary
Through the geochemical analysis of the surface snow of a glacier at the northern tip of the Antarctic Peninsula, we aimed to investigate how atmosphere and ocean conditions of the surrounding region are varying under the present climate scenario. We found that meteorological conditions strongly depend on the extension of sea ice. Our results show a slight cooling of the surface air during the last decade at this site. However, the general warming tendency for the region is still on-going.
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.
Laetitia Gal, Manuela Grippa, Pierre Hiernaux, Léa Pons, and Laurent Kergoat
Hydrol. Earth Syst. Sci., 21, 4591–4613, https://doi.org/10.5194/hess-21-4591-2017, https://doi.org/10.5194/hess-21-4591-2017, 2017
Short summary
Short summary
The intense, prolonged Sahel drought has caused a widespread increase in surface runoff and surface waters like lakes or rivers, against all expectations. Using long-term observations and the Kineros2 hydrological model, we show that the runoff coefficient of the Agoufou watershed increased from ~ 0 to 5.5 % in 1950–2011. We attribute this phenomenon to a change in vegetation and soil surface properties, in response to the drought, rather than land–use change or rainfall regime intensification.
Tobias Houska, David Kraus, Ralf Kiese, and Lutz Breuer
Biogeosciences, 14, 3487–3508, https://doi.org/10.5194/bg-14-3487-2017, https://doi.org/10.5194/bg-14-3487-2017, 2017
Short summary
Short summary
CO2 and N2O are two prominent GHGs contributing to global warming. We combined measurement and modelling to quantify GHG emissions from adjacent arable, forest and grassland sites in Germany. Measured emissions reveal seasonal patterns and management effects like fertilizer application, tillage, harvest and grazing. Modelling helps to estimate the magnitude and uncertainty of not measurable C and N fluxes and indicates missing input source, e.g. nitrate uptake from groundwater.
Torbern Tagesson, Jonas Ardö, Bernard Cappelaere, Laurent Kergoat, Abdulhakim Abdi, Stéphanie Horion, and Rasmus Fensholt
Biogeosciences, 14, 1333–1348, https://doi.org/10.5194/bg-14-1333-2017, https://doi.org/10.5194/bg-14-1333-2017, 2017
Short summary
Short summary
Vegetation growth in semi-arid regions is an important sink for human-induced fossil fuel emissions of CO2 and this study addresses the strong need for improved understanding and spatially explicit estimates of CO2 uptake by semi-arid ecosystems. We show that a model incorporating photosynthetic parameters upscaled using satellite-based earth observation simulates CO2 uptake well for the Sahel, one of the largest semi-arid regions in the world.
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.
Rosa Maria Roman-Cuesta, Martin Herold, Mariana C. Rufino, Todd S. Rosenstock, Richard A. Houghton, Simone Rossi, Klaus Butterbach-Bahl, Stephen Ogle, Benjamin Poulter, Louis Verchot, Christopher Martius, and Sytze de Bruin
Biogeosciences, 13, 5799–5819, https://doi.org/10.5194/bg-13-5799-2016, https://doi.org/10.5194/bg-13-5799-2016, 2016
Short summary
Short summary
The land use sector (AFOLU) is a pivotal component of countries' mitigation commitments under the Paris Agreement. Global land use data are therefore important to complement and fill in countries' data gaps. But how different are the existing AFOLU datasets and why? Here we contrast six AFOLU datasets for the tropics at different levels of aggregation (spatial, gases, emission sources) and point out possible reasons for the observed differences and the next steps to improve land use emissions.
Rosa Maria Roman-Cuesta, Mariana C. Rufino, Martin Herold, Klaus Butterbach-Bahl, Todd S. Rosenstock, Mario Herrero, Stephen Ogle, Changsheng Li, Benjamin Poulter, Louis Verchot, Christopher Martius, John Stuiver, and Sytze de Bruin
Biogeosciences, 13, 4253–4269, https://doi.org/10.5194/bg-13-4253-2016, https://doi.org/10.5194/bg-13-4253-2016, 2016
Short summary
Short summary
This research provides spatial data on gross emissions from the land use sector for the tropical region for the period 2000–2005. This sector contributes up to 24 % of the global emissions, but there is little understanding of where the hotspots of emissions are, how uncertain they are, and what the human activities behind these emissions are. Data provided here should assist countries to identify priority areas for mitigation action and contrast the effectiveness of their current measures.
Boris Bonn, Erika von Schneidemesser, Dorota Andrich, Jörn Quedenau, Holger Gerwig, Anja Lüdecke, Jürgen Kura, Axel Pietsch, Christian Ehlers, Dieter Klemp, Claudia Kofahl, Rainer Nothard, Andreas Kerschbaumer, Wolfgang Junkermann, Rüdiger Grote, Tobias Pohl, Konradin Weber, Birgit Lode, Philipp Schönberger, Galina Churkina, Tim M. Butler, and Mark G. Lawrence
Atmos. Chem. Phys., 16, 7785–7811, https://doi.org/10.5194/acp-16-7785-2016, https://doi.org/10.5194/acp-16-7785-2016, 2016
Short summary
Short summary
The distribution of air pollutants (gases and particles) have been investigated in different environments in Potsdam, Germany. Remarkable variations of the pollutants have been observed for distances of tens of meters by bicycles, vans and aircraft. Vegetated areas caused reductions depending on the pollutants, the vegetation type and dimensions. Our measurements show the pollutants to be of predominantly local origin, resulting in a huge challenge for common models to resolve.
Andrea Ghirardo, Junfei Xie, Xunhua Zheng, Yuesi Wang, Rüdiger Grote, Katja Block, Jürgen Wildt, Thomas Mentel, Astrid Kiendler-Scharr, Mattias Hallquist, Klaus Butterbach-Bahl, and Jörg-Peter Schnitzler
Atmos. Chem. Phys., 16, 2901–2920, https://doi.org/10.5194/acp-16-2901-2016, https://doi.org/10.5194/acp-16-2901-2016, 2016
Short summary
Short summary
Trees can impact urban air quality. Large emissions of plant volatiles are emitted in Beijing as a stress response to the urban polluted environment, but their impacts on secondary particulate matter remain relatively low compared to those originated from anthropogenic activities. The present study highlights the importance of including stress-induced compounds when studying plant volatile emissions.
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
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.
M. Liu, M. Dannenmann, S. Lin, G. Saiz, G. Yan, Z. Yao, D. E. Pelster, H. Tao, S. Sippel, Y. Tao, Y. Zhang, X. Zheng, Q. Zuo, and K. Butterbach-Bahl
Biogeosciences, 12, 4831–4840, https://doi.org/10.5194/bg-12-4831-2015, https://doi.org/10.5194/bg-12-4831-2015, 2015
Short summary
Short summary
We demonstrate for the first time that a ground cover rice production system (GCRPS) significantly increased soil organic C and total N stocks at spatially representative paired sites under varying edaphic conditions. Our results suggest that GCRPS is a stable and sustainable technique that maintains key soil functions, while increasing rice yield and expanding the cultivation into regions where it has been hampered by low seasonal temperatures and/or a lack of irrigation water.
T. Tagesson, R. Fensholt, S. Huber, S. Horion, I. Guiro, A. Ehammer, and J. Ardö
Biogeosciences, 12, 4621–4635, https://doi.org/10.5194/bg-12-4621-2015, https://doi.org/10.5194/bg-12-4621-2015, 2015
Short summary
Short summary
Relationships between ecosystem properties of semi-arid savanna and reflected solar radiance between 35 and 1800nm were investigated. Normalised combinations of reflectance for the near infrared, shortwave infrared, and 600 to 700nm were strongly affected by solar and viewing angle effects. Ecosystem properties of savannas were strongly correlated with reflectance at 350-1800nm, and normalised combinations of reflectance were strong predictors of the savanna ecosystem properties.
C. Leauthaud, J. Demarty, B. Cappelaere, M. Grippa, L. Kergoat, C. Velluet, F. Guichard, E. Mougin, S. Chelbi, and B. Sultan
Proc. IAHS, 371, 195–201, https://doi.org/10.5194/piahs-371-195-2015, https://doi.org/10.5194/piahs-371-195-2015, 2015
Z. Yao, Y. Du, Y. Tao, X. Zheng, C. Liu, S. Lin, and K. Butterbach-Bahl
Biogeosciences, 11, 6221–6236, https://doi.org/10.5194/bg-11-6221-2014, https://doi.org/10.5194/bg-11-6221-2014, 2014
C. Werner, K. Reiser, M. Dannenmann, L. B. Hutley, J. Jacobeit, and K. Butterbach-Bahl
Biogeosciences, 11, 6047–6065, https://doi.org/10.5194/bg-11-6047-2014, https://doi.org/10.5194/bg-11-6047-2014, 2014
Short summary
Short summary
Atmospheric loss of N from savanna soil was dominated by N2 emissions (82-99% of total N loss to atmosphere). Nitric oxide emissions significantly contributed at 50% WFPS; high temperatures and N2O emissions were negligible. Based on a simple upscale approach we estimated annual loss of N to the atmosphere at 7.5kg yr-1. N2O emission was low for most samples, but high for a small subset of cores at 75% WFPS (due to short periods where such conditions occur this has little effect on totals).
G. J. Luo, R. Kiese, B. Wolf, and K. Butterbach-Bahl
Biogeosciences, 10, 3205–3219, https://doi.org/10.5194/bg-10-3205-2013, https://doi.org/10.5194/bg-10-3205-2013, 2013
S. Metzger, W. Junkermann, M. Mauder, K. Butterbach-Bahl, B. Trancón y Widemann, F. Neidl, K. Schäfer, S. Wieneke, X. H. Zheng, H. P. Schmid, and T. Foken
Biogeosciences, 10, 2193–2217, https://doi.org/10.5194/bg-10-2193-2013, https://doi.org/10.5194/bg-10-2193-2013, 2013
D. R. Cameron, M. Van Oijen, C. Werner, K. Butterbach-Bahl, R. Grote, E. Haas, G. B. M. Heuvelink, R. Kiese, J. Kros, M. Kuhnert, A. Leip, G. J. Reinds, H. I. Reuter, M. J. Schelhaas, W. De Vries, and J. Yeluripati
Biogeosciences, 10, 1751–1773, https://doi.org/10.5194/bg-10-1751-2013, https://doi.org/10.5194/bg-10-1751-2013, 2013
N. Gharahi Ghehi, C. Werner, K. Hufkens, R. Kiese, E. Van Ranst, D. Nsabimana, G. Wallin, L. Klemedtsson, K. Butterbach-Bahl, and P. Boeckx
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-1483-2013, https://doi.org/10.5194/bgd-10-1483-2013, 2013
Revised manuscript not accepted
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
Ago, E. E.: Dynamique des flux de carbone entre l'atmosphère et des
écosystèmes ouest-africains: cas des forêts et savanes sous
climat soudanien au Bénin, Doctorat en Sciences Agronomiques et
Ingénierie Biologique, Université de Liège, Gembloux, Belgique,
184 pp., 2016.
Ago, E. E., Agbossou, E. K., Galle, S., Cohard, J.-M., Heinesch, B., and
Aubinet, M.: Long term observations of carbon dioxide exchange over
cultivated savanna under a Sudanian climate in Benin (West Africa), Agric.
Forest Meteorol., 197, 13–25, https://doi.org/10.1016/j.agrformet.2014.06.005, 2014.
Ago, E. E., Agbossou, E. K., Cohard, J.-M., Galle, S., and Aubinet, M.:
Response of CO2 fluxes and productivity to water availability in two
contrasting ecosystems in northern Benin (West Africa), Ann. For. Sci., 73,
483–500, https://doi.org/10.1007/s13595-016-0542-9, 2016.
Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A.,
Jung, M., Reichstein, M., Canadell, J. G., Friedlingstein, P., Jain, A. K.,
Kato, E., Poulter, B., Sitch, S., Stocker, B. D., Viovy, N., Wang, Y. P.,
Wiltshire, A., Zaehle, S., and Zeng, N.: The dominant role of semi-arid
ecosystems in the trend and variability of the land CO2 sink, Science,
348, 895–899, https://doi.org/10.1126/science.aaa1668, 2015.
Ainsworth, E. A. and Rogers, A.: The response of photosynthesis and
stomatal conductance to rising [CO2]: mechanisms and environmental
interactions, Plant Cell Environ., 30, 258–270,
https://doi.org/10.1111/j.1365-3040.2007.01641.x, 2007.
Akponikpè, P. B. I., Gérard, B., Michels, K., and Bielders, C.: Use
of the APSIM model in long term simulation to support decision making
regarding nitrogen management for pearl millet in the Sahel, European
J. Agronomy, 32, 144–154, https://doi.org/10.1016/j.eja.2009.09.005, 2010.
Baldocchi, D. and Meyers, T.: On using eco-physiological,
micrometeorological and biogeochemical theory to evaluate carbon dioxide,
water vapor and trace gas fluxes over vegetation: a perspective, Agric.
Forest Meteorol., 90, 1–25, https://doi.org/10.1016/S0168-1923(97)00072-5, 1998.
Baldocchi, D. and Xu, L.: Carbon exchange of deciduous broadleaved forests
in temperate and Mediterranean regions, in: The Carbon Balance of Forest
Biomes, edited by: Griffiths, H. and Jarvis, P. J., Garland Science/BIOS
Scientific Publishers, London, 187–213, 2005.
Baldocchi, D. D., Xu, L., and Kiang, N.: How plant functional-type, weather,
seasonal drought, and soil physical properties alter water and energy fluxes
of an oak-grass savanna and an annual grassland, Agric. Forest Meteorol.,
123, 13–39, https://doi.org/10.1016/j.agrformet.2003.11.006, 2004.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A model predicting stomatal
conductance and its contribution to the control of photosynthesis under
different environmental conditions, in: Prog. Photosyn. Res., edited by:
Biggins, J., Martinus-Nijhoff Publishers, Dordrecht, the Netherlands,
221–224, 1987.
Batjes, N. H.: Harmonized soil profile data for applications at global and
continental scales: updates to the WISE database, Soil Use Manage.,
25, 124–127, https://doi.org/10.1111/j.1475-2743.2009.00202.x, 2008.
Baup, F., Mougin, E., de Rosnay, P., Timouk, F., and Chênerie, I.:
Surface soil moisture estimation over the AMMA Sahelian site in Mali using
ENVISAT/ASAR data, Remote. Sens. Environ., 109, 473–481,
https://doi.org/10.1016/j.rse.2007.01.015, 2007.
Bauters, M., Drake, T. W., Verbeeck, H., Bodé, S.,
Hervé-Fernández, P., Zito, P., Podgorski, D. C., Boyemba, F.,
Makelele, I., Cizungu Ntaboba, L., Spencer, R. G. M., and Boeckx, P.: High
fire-derived nitrogen deposition on central African forests, P. Natl. Acad. Sci. USA, 115,
549–554, https://doi.org/10.1073/pnas.1714597115, 2018.
Berger, S., Bliefernicht, J., Linstädter, A., Canak, K., Guug, S.,
Heinzeller, D., Hingerl, L., Mauder, M., Neidl, F., Quansah, E., Salack, S.,
Steinbrecher, R., and Kunstmann, H.: The impact of rain events on CO2
emissions from contrasting land use systems in semi-arid West African
savannas, Sci. Total Environ., 647, 1478–1489,
https://doi.org/10.1016/j.scitotenv.2018.07.397, 2019.
Bernacchi, C. J., Portis, A. R., Nakano, H., von Caemmerer, S., and Long, S.
P.: Temperature Response of Mesophyll Conductance. Implications for the
Determination of Rubisco Enzyme Kinetics and for Limitations to
Photosynthesis in Vivo, Plant Physiol., 130, 1992–1998, https://doi.org/10.1104/pp.008250,
2002.
Bliefernicht, J., Berger, S., Salack, S., Guug, S., Hingerl, L., Heinzeller,
D., Mauder, M., Steinbrecher, R., Steup, G., Bossa, A. Y., Waongo, M.,
Quansah, E., Balogun, A. A., Yira, Y., Arnault, J., Wagner, S., Klein, C.,
Gessner, U., Knauer, K., Straub, A., Schönrock, R., Kunkel, R., Okogbue,
E. C., Rogmann, A., Neidl, F., Jahn, C., Diekkrüger, B., Aduna, A.,
Barry, B., and Kunstmann, H.: The WASCAL Hydrometeorological Observatory in
the Sudan Savanna of Burkina Faso and Ghana, Vadose Zone J., 17, 180065,
https://doi.org/10.2136/vzj2018.03.0065, 2018.
Boke-Olén, N., Lehsten, V., Ardö, J., Beringer, J., Eklundh, L.,
Holst, T., Veenendaal, E., and Tagesson, T.: Estimating and Analyzing
Savannah Phenology with a Lagged Time Series Model, PLoS ONE, 11,
e0154615–e0154615, https://doi.org/10.1371/journal.pone.0154615, 2016.
Bocksberger, G., Schnitzler, J., Chatelain, C., Daget, P., Janssen, T.,
Schmidt, M., Thiombiano, A., and Zizka, G.: Climate and the distribution of
grasses in West Africa, J. Veg. Sci., 27, 306–317, https://doi.org/10.1111/jvs.12360, 2016.
Bombelli, A., Henry, M., Castaldi, S., Adu-Bredu, S., Arneth, A., de Grandcourt, A., Grieco, E., Kutsch, W. L., Lehsten, V., Rasile, A., Reichstein, M., Tansey, K., Weber, U., and Valentini, R.: An outlook on the Sub-Saharan Africa carbon balance, Biogeosciences, 6, 2193–2205, https://doi.org/10.5194/bg-6-2193-2009, 2009.
Boone, R. B., Galvin, K. A., Coughenour, M. B., Hudson, J. W., Weisberg, P.
J., Vogel, C. H., and Ellis, J. E.: Ecosystem modeling adds value to a south
african climate forecast, Clim. Change, 64, 317–340,
https://doi.org/10.1023/B:CLIM.0000025750.09629.48, 2004.
Boulain, N., Cappelaere, B., Ramier, D., Issoufou, H. B. A., Halilou, O.,
Seghieri, J., Guillemin, F., Oï, M., Gignoux, J., and Timouk, F.:
Towards an understanding of coupled physical and biological processes in the
cultivated Sahel – 2. Vegetation and carbon dynamics, J. Hydrol., 375,
190–203, https://doi.org/10.1016/j.jhydrol.2008.11.045, 2009.
Boyd, R. A., Gandin, A., and Cousins, A. B.: Temperature Responses of C4
Photosynthesis: Biochemical Analysis of Rubisco, Phosphoenolpyruvate
Carboxylase, and Carbonic Anhydrase in Setaria viridis, Plant Physiol., 169, 1850–1861,
https://doi.org/10.1104/pp.15.00586, 2015.
Brümmer, C., Falk, U., Papen, H., Szarzynski, J., Wassmann, R., and
Brüggemann, N.: Diurnal, seasonal, and interannual variation in carbon
dioxide and energy exchange in shrub savanna in Burkina Faso (West Africa),
J. Geophys. Res., 113, G02030, https://doi.org/10.1029/2007JG000583,
2008.
Buba, T.: Prediction equations for estimating tree height, crown diameter,
crown height and crown ratio of Parkia biglobosa in the Nigerian guinea savanna, Afr.
J. Agr. Res., 7, 6541–6543, https://doi.org/10.5897/AJAR12.276, 2013.
Buchhorn, M., Smets, B., Bertels, L., Lesiv, M., Tsendbazar, N.-E., Masiliunas, D., Linlin, L., Herold, M., and Fritz, S.: Copernicus Global Land Service: Land Cover 100m: Collection 3: epoch 2019: Globe (Version V3.0.1) [Data set], Zenodo, https://doi.org/10.5281/zenodo.3939050, 2020.
Butterbach-Bahl, K., Grote,
R., Haas,
E., Kiese,
R., Klatt,
S., and Kraus,
D.: LandscapeDNDC (v1.30.4) [code], Karlsruhe Institute of Technology (KIT), https://doi.org/10.35097/438, 2021.
Caldararu, S., Purves, D. W., and Smith, M. J.: The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0), Geosci. Model Dev., 10, 1679–1701, https://doi.org/10.5194/gmd-10-1679-2017, 2017.
Camargo, A. P., Marin, F. R., Sentelhas, P. C., and Picini, A. G.: Adjust of
the Thornthwaite's method to estimate the potential evapotranspiration for
arid and superhumid climates, based on daily temperature amplitude, Bras.
Agrometeorol., 7, 251–257, https://doi.org/10.1007/s00704-019-02873-1, 1999.
Cappelaere, B., Descroix, L., Lebel, T., Boulain, N., Ramier, D., Laurent,
J. P., Favreau, G., Boubkraoui, S., Boucher, M., Bouzou Moussa, I.,
Chaffard, V., Hiernaux, P., Issoufou, H. B. A., Le Breton, E., Mamadou, I.,
Nazoumou, Y., Oi, M., Ottlé, C., and Quantin, G.: The AMMA-CATCH
experiment in the cultivated Sahelian area of south-west Niger –
Investigating water cycle response to a fluctuating climate and changing
environment, J. Hydrol., 375, 34–51, https://doi.org/10.1016/j.jhydrol.2009.06.021, 2009.
Chandra, A. and Dubey, A.: Evaluation of genus Cenchrus based on
malondialdehyde, proline content, specific leaf area and carbon isotope
discrimination for drought tolerance and divergence of species at DNA level,
Acta Physiol. Plant., 30, 53–61, https://doi.org/10.1007/s11738-007-0090-x, 2008.
Chen, Q., Baldocchi, D., Gong, P., and Dawson, T.: Modeling radiation and
photosynthesis of a heterogeneous savanna woodland landscape with a
hierarchy of model complexities, Agric. Forest Meteorol., 148, 1005–1020,
https://doi.org/10.1016/j.agrformet.2008.01.020, 2008.
Collatz, G. J., Ribas-Carbo, M., and Berry, J. A.: Coupled
photosynthesis-stomatal conductance model for leaves of C4 plants, Aust. J.
Plant Physiol., 19, 519–538, https://doi.org/10.1071/PP9920519 1992.
Dagbenonbakin, G. D.: Productivity and water use efficiency of important
crops in the upper Oueme Catchment: influence of nutrient limitations,
nutrient balances and soil fertility, PhD, Hohe Landwirtschaftliche
Fakultät, Rheinischen Friedrich-Wilhelms-Universität Bonn,
Bonn, 212 pp., 2005.
Da Matta, F. M., Loos, R. A., Rodrigues, R., and Barros, R.: Actual and
potential photosynthetic rates of tropical crop species, Revista Brasileira
de Fisiologia Vegetal, 13, 24–32, https://doi.org/10.1590/S0103-31312001000100003., 2001.
Dayamba, S. D., Djoudi, H., Zida, M., Sawadogo, L., and Verchot, L.:
Biodiversity and carbon stocks in different land use types in the Sudanian
Zone of Burkina Faso, West Africa, Agr. Ecosyst. Environ., 216, 61–72,
https://doi.org/10.1016/j.agee.2015.09.023, 2016.
de Jong, S. M. and Jetten, V. G.: Estimating spatial patterns of rainfall
interception from remotely sensed vegetation indices and spectral mixture
analysis, Int. J. Geogr. Inf. Sci., 21,
529–545, https://doi.org/10.1080/13658810601064884, 2007.
de Rosnay, P., Gruhier, C., Timouk, F., Baup, F., Mougin, E., Hiernaux, P.,
Kergoat, L., and LeDantec, V.: Multi-scale soil moisture measurements at the
Gourma meso-scale site in Mali, J. Hydrol., 375, 241–252,
https://doi.org/10.1016/j.jhydrol.2009.01.015, 2009.
Delon, C., Mougin, E., Serça, D., Grippa, M., Hiernaux, P., Diawara, M., Galy-Lacaux, C., and Kergoat, L.: Modelling the effect of soil moisture and organic matter degradation on biogenic NO emissions from soils in Sahel rangeland (Mali), Biogeosciences, 12, 3253–3272, https://doi.org/10.5194/bg-12-3253-2015, 2015.
Delon, C., Galy-Lacaux, C., Serça, D., Personne, E., Mougin, E., Adon, M., Le Dantec, V., Loubet, B., Fensholt, R., and Tagesson, T.: Modelling land–atmosphere daily exchanges of NO, NH3, and CO2 in a semi-arid grazed ecosystem in Senegal, Biogeosciences, 16, 2049–2077, https://doi.org/10.5194/bg-16-2049-2019, 2019.
de Souza Nóia Júnior, R., Amaral, G. C., Pezzopane, J. E. M.,
Fonseca, M. D. S., Câmara da Silva, A. P., and Xavier, T. M. T.:
Ecophysiological acclimatization to cyclic water stress in Eucalyptus, J. Forestry
Res., 31, 797–806, https://doi.org/10.1007/s11676-019-00926-9, 2020.
Dimobe, K., Kouakou, J. L. N. D., Tondoh, J. E., Zoungrana, B. J.-B.,
Forkuor, G., and Ouédraogo, K.: Predicting the Potential Impact of
Climate Change on Carbon Stock in Semi-Arid West African Savannas, Land, 7,
124, https://doi.org/10.3390/land7040124, 2018.
Diouf, A. A., Brandt, M., Verger, A., Jarroudi, M. E., Djaby, B., Fensholt,
R., Ndione, J. A., and Tychon, B.: Fodder Biomass Monitoring in Sahelian
Rangelands Using Phenological Metrics from FAPAR Time Series, Remote Sens.,
7, 9122–9148, https://doi.org/10.3390/rs70709122, 2015.
Dirnböck, T., Kraus, D., Grote, R., Klatt, S., Kobler, J.,
Schindlbacher, A., Seidl, R., Thom, D., and Kiese, R.: Substantial
understory contribution to the C sink of a European temperate mountain
forest landscape, Landscape Ecol., 35, 483–499, https://doi.org/10.1007/s10980-019-00960-2
2020.
Do, F. C., Goudiaby, V. A., Gimenez, O., Diagne, A. L., Diouf, M., Rocheteu,
A., and Akpo, L. E.: Environmental influence on canopy phenology in the dry
tropics, Forest Ecol. Manage., 215, 319–328, https://doi.org/10.1016/j.foreco.2005.05.022,
2005.
Elberling, B., Fensholt, R., Larsen, L., Petersen, A.-I. S., and Sandholt,
I.: Water content and land use history controlling soil CO2 respiration
and carbon stock in savanna soil and groundnut fields in semi-arid Senegal,
Danish J. Geogr., 103, 47–56, https://doi.org/10.1080/00167223.2003.10649491,
2003.
Epron, D., Nouvellon, Y., Roupsard, O., Mouvondy, W., Mabiala, A.,
Saint-Andre, L., Joffre, R., Jourdan, C., Bonnefond, J. M., Berbigier, P.,
and Hamel, O.: Spatial and temporal variations of soil respiration in a
Eucalyptus plantation in Congo, Forest Ecol. Manage., 202, 149–160,
https://doi.org/10.1016/j.foreco.2004.07.019, 2004.
Farquhar, G. D., Von Caemmerer, S., and Berry, J. A.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta,
149, 78–90, https://doi.org/10.1007/BF00386231, 1980.
Faye, B., Webber, H., Naab, J. B., MacCarthy, D. S., Adam, M., Ewert, F.,
Lamers, J. P. A., Schleussner, C.-F., Ruane, A., Gessner, U., Hoogenboom,
G., Boote, K., Shelia, V., Saeed, F., Wisser, D., Hadir, S., Laux, P., and
Gaiser, T.: Impacts of 1.5 versus 2.0 ∘C on cereal yields in the
West African Sudan Savanna, Environ. Res. Lett., 13, 034014,
https://doi.org/10.1088/1748-9326/aaab40, 2018.
February, E. and Higgins, S.: The distribution of tree and grass roots in
savannas in relation to soil nitrogen and water, S. Afr. J. Bot., 76,
517–523, https://doi.org/10.1016/j.sajb.2010.04.001, 2010.
Feng, X. and Dietze, M.: Scale dependence in the effects of leaf
ecophysiological traits on photosynthesis: Bayesian parameterization of
photosynthesis models, New Phytol., 200, 1132–1144, https://doi.org/10.1111/nph.12454, 2013.
Fraser, F. C., Corstanje, R., Deeks, L. K., Harris, J. A., Pawlett, M.,
Todman, L. C., Whitmore, A. P., and Ritz, K.: On the origin of carbon
dioxide released from rewetted soils, Soil Biology and Biochemistry, 101,
1–5, https://doi.org/10.1016/j.soilbio.2016.06.032, 2016.
Fürstenau Togashi, H., Prentice, I. C., Atkin, O. K., Macfarlane, C., Prober, S. M., Bloomfield, K. J., and Evans, B. J.: Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis, Biogeosciences, 15, 3461–3474, https://doi.org/10.5194/bg-15-3461-2018, 2018.
Gallé, A. and Feller, U.: Changes of photosynthetic traits in beech saplings (Fagus sylvatica) under severe drought stress and during recovery, Physiol. Plant., 131, 412–421, 2007.
Galy-Lacaux, C., Delon, C., Solmon, F., Adon, M., Yoboué, V., Mphepya,
J., Pienaar, J. J., Diop, B., Sigha, L., Dungall, L., Akpo, A., Mougin, E.,
Gardrat, E., and Castera, P.: Dry and Wet Atmospheric Nitrogen Deposition in
West Central Africa, in: Nitrogen Deposition, Critical Loads and
Biodiversity, edited by: Sutton, M., Mason, K., Sheppard, L., Sverdrup, H.,
Haeuber, R., and Hicks, W., Springer, Dordrecht, 2014.
Gash, J. H. C., Lloyd, C. R., and Lachaud, G.: Estimating sparse forest
rainfall interception with an analytical model, J. Hydrol., 170, 79–86,
https://doi.org/10.1016/0022-1694(95)02697-N, 1995.
Geerling, C.: The status of the woody species of the Sudan and Sahel zones
of West Africa, Forest Ecol. Manage., 13, 247–255,
https://doi.org/10.1016/0378-1127(85)90038-6, 1985.
Gessner, U., Niklaus, M., Kuenzer, C., and Dech, S.: Intercomparison of Leaf
Area Index Products for a Gradient of Sub-Humid to Arid Environments in West
Africa, Remote Sens., 5, 1235–1257, https://doi.org/10.3390/rs5031235, 2013.
Gleason, S. M., Wiggans, D. R., Bliss, C. A., Comas, L. H., Cooper, M.,
DeJonge, K. C., Young, J. S., and Zhang, H.: Coordinated decline in
photosynthesis and hydraulic conductance during drought stress in Zea mays, Flora,
227, 1–9, https://doi.org/10.1016/j.flora.2016.11.017, 2017.
Groenendijk, M., Dolman, A. J., van der Molen, M. K., Leuning, R., Arneth,
A., Delpierre, N., Gash, J. H. C., Lindroth, A., Richardson, A. D.,
Verbeeck, H., and Wohlfahrt, G.: Assessing parameter variability in a
photosynthesis model within and between plant functional types using global
Fluxnet eddy covariance data, Agric. Forest Meteorol., 151, 22–38,
https://doi.org/10.1016/j.agrformet.2010.08.013, 2011.
Grossiord, C., Sevanto, S., Adams, H. D., Collins, A. D., Dickman, L. T.,
McBranch, N., Michaletz, S. T., Stockton, E. A., Vigil, M., and McDowell, N.
G.: Precipitation, not air temperature, drives functional responses of trees
in semi-arid ecosystems, J. Ecol., 105, 163–175, https://doi.org/10.1111/1365-2745.12662,
2017.
Grote, R.: Integrating dynamic morphological properties into forest growth
modeling. II. Allocation and mortality, Forest Ecol. Manage., 111, 193–210,
https://doi.org/10.1016/S0378-1127(98)00328-4, 1998.
Grote, R.: Sensitivity of volatile monoterpene emission to changes in canopy
structure – A model based exercise with a process-based emission model, New
Phytol., 173, 550–561, https://doi.org/10.1111/j.1469-8137.2006.01946.x, 2007.
Grote, R., Lavoir, A. V., Rambal, S., Staudt, M., Zimmer, I., and
Schnitzler, J.-P.: Modelling the drought impact on monoterpene fluxes from
an evergreen Mediterranean forest canopy, Oecologia, 160, 213–223,
https://doi.org/10.1007/s00442-009-1298-9, 2009a.
Grote, R., Lehmann, E., Brümmer, C., Brüggemann, N., Szarzynski, J.,
and Kunstmann, H.: Modelling and observation of biosphere-atmosphere
interactions in natural savannah in Burkina Faso, West Africa, Phys. Chem.
Earth, 34, 251–260, https://doi.org/10.1016/j.pce.2008.05.003, 2009b.
Grote, R., Kiese, R., Grünwald, T., Ourcival, J.-M., and Granier, A.:
Modelling forest carbon balances considering tree mortality and removal,
Agric. Forest Meteorol., 151, 179–190, https://doi.org/10.1016/j.agrformet.2010.10.002,
2011a.
Grote, R., Korhonen, J., and Mammarella, I.: Challenges for evaluating
process-based models of gas exchange at forest sites with fetches of various
species, For. Syst., 20, 389–406, https://doi.org/10.5424/fs/20112003-11084, 2011b.
Grote, R., Kraus, D., Weis, W., Ettl, R., and Göttlein, A.: Dynamic
coupling of allometric ratios to a process-based forest growth model for
estimating the impacts of stand density changes, Forestry, 93, 601–615,
https://doi.org/10.1093/forestry/cpaa002, 2020.
Guenther, A., Otter, L., Zimmerman, P., Greenberg, J., Scholes, R., and
Scholes, M.: Biogenic hydrocarbon emissions from southern Africa savannas,
J. Geophys. Res., 101, 25859–25865, https://doi.org/10.1029/96JD02597, 1996.
Haas, E., Klatt, S., Fröhlich, A., Werner, C., Kiese, R., Grote, R., and
Butterbach-Bahl, K.: LandscapeDNDC: A process model for simulation of
biosphere-atmosphere-hydrosphere exchange processes at site and regional
scale, Landscape Ecol., 28, 615–636, https://doi.org/10.1007/s10980-012-9772-x, 2013.
Hartley, A. J., Parker, D. J., Garcia-Carreras, L., and Webster, S.:
Simulation of vegetation feedbacks on local and regional scale precipitation
in West Africa, Agric. Forest Meteorol., 222, 59–70,
https://doi.org/10.1016/j.agrformet.2016.03.001, 2016.
Hiernaux, P. and Ayantunde, A. A.: The Fakara: a semi-arid agro-ecosystem
under stress. Report of research activities, first phase (July 2002–June
2004) of the DMP-GEF Program ILRI, Nairobi (Kenya), GEF/2711-02-4516, 95,
2004.
Hiernaux, P., Mougin, E., Diarra, L., Soumaguel, N., Lavenu, F., Tracol, Y.,
and Diawara, M. O.: Sahelian rangeland response to changes in rainfall over
two decades in the Gourma region, Mali, J. Hydrol., 375, 114–127,
https://doi.org/10.1016/j.jhydrol.2008.11.005, 2009.
Holá, D., Benešová, M., Honnerová, J., Hnilička, F.,
Rothová, O., Kočová, M., and Hniličková, H.: The
evaluation of photosynthetic parameters in maize inbred lines subjected to
water deficiency: Can these parameters be used for the prediction of
performance of hybrid progeny?, Photosynthetica, 48, 545–558,
https://doi.org/10.1007/s11099-010-0072-x, 2010.
Ivanov, V. Y., Bras, R. L., and Vivoni, E. R.: Vegetation-hydrology dynamics
in complex terrain of semiarid areas: 1. A mechanistic approach to modeling
dynamic feedbacks, Water Resour. Res., 44, W03429, https://doi.org/10.1029/2006WR005588,
2008.
Jolly, W. M. and Running, S. W.: Effects of precipitation and soil water
potential on drought deciduous phenology in the Kalahari, Glob. Change
Biol., 10, 303–308, https://doi.org/10.1046/j.1365-2486.2003.00701.x, 2004.
Kahiu, M. N. and Hanan, N. P.: Estimation of Woody and Herbaceous Leaf Area
Index in Sub-Saharan Africa Using MODIS Data, J. Geophys. Res.-Biogeo.,
123, 3–17, https://doi.org/10.1002/2017JG004105, 2018.
Kalariya, K. A., Singh, A. L., Goswami, N., Mehta, D., Mahatma, M. K., Ajay,
B. C., Chakraborty, K., Zala, P. V., Chaudhary, V., and Patel, C. B.:
Photosynthetic characteristics of peanut genotypes under excess and deficit
irrigation during summer, Physiol. Mol. Biol. Plants, 21, 317–327,
https://doi.org/10.1007/s12298-015-0300-8, 2015.
Kaptue Tchuente, A. T., Roujean, J. L., and Faroux, S.: ECOCLIMAP-II: An
ecosystem classification and land surface parameters database of Western
Africa at 1 km resolution for the African Monsoon Multidisciplinary Analysis
(AMMA) project, Remote Sens. Environ., 114, 961–976,
https://doi.org/10.1016/j.rse.2009.12.008, 2010.
Kattge, J. and Knorr, W.: Temperature acclimation in a biochemical model of
photosynthesis: a reanalysis of data from 36 species, Plant Cell Environ.,
30, 1176–1190, https://doi.org/10.1111/j.1365-3040.2007.01690.x, 2007.
Kebbas, S., Lutts, S., and Aid, F.: Effect of drought stress on the
photosynthesis of Acacia tortilis subsp. raddiana at the young seedling stage,
Photosynthetica, 53, 288–298, https://doi.org/10.1007/s11099-015-0113-6, 2015.
Ker, A.: Farming Systems of the African Savanna, International Development Research Centre, Ottawa, Canada, 166 pp., 1995.
Kgope, B. S. and Musil, C. F.: Differential photosynthetic responses of
broad- and fine-leafed savanna trees to elevated temperatures, S. Afr. J.
Bot., 70, 760–766, https://doi.org/10.1016/S0254-6299(15)30177-0, 2004.
Kiese, R., Heinzeller, C., Werner, C., Wochele, S., Grote, R., and
Butterbach-Bahl, K.: Quantification of nitrate leaching from German forest
ecosystems by use of a process oriented biogeochemical model, Environ.
Pollut., 159, 3204–3214, https://doi.org/10.1016/j.envpol.2011.05.004, 2011.
Kim, J. and Verma, S. B.: Modeling canopy photosynthesis: scaling up from a
leaf to canopy in a temperate grassland ecosystem, Agric. Forest Meteorol.,
57, 187–208, https://doi.org/10.1016/0168-1923(91)90086-6, 1991.
Knauer, J., Werner, C., and Zaehle, S.: Evaluating stomatal models and their
atmospheric drought response in a land surface scheme: A multibiome
analysis, J. Geophys. Res.-Biogeo., 120, 1894–1911,
https://doi.org/10.1002/2015jg003114, 2015.
Körner, C., Scheel, J., and Bauer, H.: Maximum leaf diffusive
conductance in vascular plants, Photosynthetica, 13, 45–82, 1979.
Kothavala, Z., Arain, M. A., Black, T. A., and Verseghy, D.: The simulation
of energy, water vapor and carbon dioxide fluxes over common crops by the
Canadian Land Surface Scheme (CLASS), Agric. Forest Meteorol., 133, 89–108,
https://doi.org/10.1016/j.agrformet.2005.08.007, 2005.
Kraus, D., Weller, S., Klatt, S., Haas, E., Wassmann, R., Kiese, R., and
Butterbach-Bahl, K.: A new LandscapeDNDC biogeochemical module to predict
CH4 and N2O emissions from lowland rice and upland cropping
systems, Plant Soil, 386, 125–149, https://doi.org/10.1007/s11104-014-2255-x, 2015.
Kraus, D., Weller, S., Klatt, S., Santabárbara, I., Haas, E., Wassmann,
R., Werner, C., Kiese, R., and Butterbach-Bahl, K.: How well can we assess
impacts of agricultural land management changes on the total greenhouse gas
balance (CO2, CH4 and N2O) of tropical rice-cropping systems
with a biogeochemical model?, Agr. Ecosyst. Environ., 224, 104–115,
https://doi.org/10.1016/j.agee.2016.03.037, 2016.
Kucharik, C. J., Barford, C. C., El Maayar, M., Wofsy, S. C., Monson, R. K.,
and Baldocchi, D. D.: A multiyear evaluation of a Dynamic Global Vegetation
Model at three AmeriFlux forest sites: Vegetation structure, phenology, soil
temperature, and CO2 and H2O vapor exchange, Ecol. Modelling, 196,
1–31, https://doi.org/10.1016/j.ecolmodel.2005.11.031, 2006.
Leuning, R.: A critical appraisal of a combined stomatal-photosynthesis
model for C3 plants, Plant Cell Environ., 18, 339–355,
https://doi.org/10.1111/j.1365-3040.1995.tb00370.x, 1995.
Li, C., Frolking, S., and Frolking, T. A.: A model of nitrous oxide
evolution from soil driven by rainfall events: 1. Model structure and
Sensitivity, J. Geophys. Res., 97, 9759–9776, https://doi.org/10.1029/92JD00509, 1992.
Liebermann, R., Breuer, L., Houska, T., Kraus, D., Moser, G., and Kraft, P.:
Simulating Long-Term Development of Greenhouse Gas Emissions, Plant Biomass,
and Soil Moisture of a Temperate Grassland Ecosystem under Elevated
Atmospheric CO2, Agronomy, 10, 50, https://doi.org/10.3390/agronomy10010050, 2020.
Lindauer, M., Schmid, H. P., Grote, R., Mauder, M., Steinbrecher, R., and
Wolpert, B.: Net ecosystem exchange over a non-cleared wind-throw-disturbed
upland spruce forest – measurements and simulations Agric. Forest
Meteorol., 197, 219–234, https://doi.org/10.1016/j.agrformet.2014.07.005, 2014.
Livesley, S. J., Grover, S., Hutley, L. B., Jamali, H., Butterbach-Bahl, K.,
Fest, B., Beringer, J., and Arndt, S. K.: Seasonal variation and fire
effects on CH4, N2O and CO2 exchange in savanna soils of
northern Australia, Agric. Forest Meteorol., 151, 1440–1452,
https://doi.org/10.1016/j.agrformet.2011.02.001, 2011.
Loustau, D., Berbigier, P., Granier, A., and Moussa, F. E. H.: Interception
loss, throughfall and stemflow in a maritime pine stand. I. Variability of
throughfall and stemflow beneath the pine canopy, J. Hydrol., 138, 449–467,
https://doi.org/10.1016/0022-1694(92)90130-N, 1992.
Mamadou, O.: Etude des flux d'Evapotranspiration en climat soudanien:
comportement comparé de deux couverts végétaux au Bénin,
Université de Grenoble (France) et Université d'Abomey-Calavi
(Bénin), Abomey-Calavi, 2014.
Martin, M. J., Stirling, C. M., Humphries, S. W., and Long, S. P.: A
process-based model to predict the effects of climatic change on leaf
isoprene emission rates, Ecol. Model., 131, 161–174,
https://doi.org/10.1016/S0304-3800(00)00258-1, 2000.
Massad, R.-S., Tuzet, A., and Bethenod, O.: The effect of temperature on
C4-type leaf photosynthesis parameters, Plant Cell Environ., 30, 1191–1204,
https://doi.org/10.1111/j.1365-3040.2007.01691.x, 2007.
Massad, R. S., Lathière, J., Strada, S., Perrin, M., Personne, E., Stéfanon, M., Stella, P., Szopa, S., and de Noblet-Ducoudré, N.: Reviews and syntheses: influences of landscape structure and land uses on local to regional climate and air quality, Biogeosciences, 16, 2369–2408, https://doi.org/10.5194/bg-16-2369-2019, 2019.
Merbold, L., Ardö, J., Arneth, A., Scholes, R. J., Nouvellon, Y., de Grandcourt, A., Archibald, S., Bonnefond, J. M., Boulain, N., Brueggemann, N., Bruemmer, C., Cappelaere, B., Ceschia, E., El-Khidir, H. A. M., El-Tahir, B. A., Falk, U., Lloyd, J., Kergoat, L., Le Dantec, V., Mougin, E., Muchinda, M., Mukelabai, M. M., Ramier, D., Roupsard, O., Timouk, F., Veenendaal, E. M., and Kutsch, W. L.: Precipitation as driver of carbon fluxes in 11 African ecosystems, Biogeosciences, 6, 1027–1041, https://doi.org/10.5194/bg-6-1027-2009, 2009.
Mougin, E., Lo Seena, D., Rambal, S., Gaston, A., and Hiernaux, P.: A
regional Sahelian grassland model to be coupled with multispectral satellite
data. I: Model description and validation, Remote. Sens. Environ., 52,
181–193, https://doi.org/10.1016/0034-4257(94)00126-8, 1995.
Mougin, E., Hiernaux, P., Kergoat, L., Grippa, M., de Rosnay, P., Timouk,
F., Le Dantec, V., Demarez, V., Lavenu, F., Arjounin, M., Lebel, T.,
Soumaguel, N., Ceschia, E., Mougenot, B., Baup, F., Frappart, F., Frison, P.
L., Gardelle, J., Gruhier, C., Jarlan, L., Mangiarotti, S., Sanou, B.,
Tracol, Y., Guichard, F., Trichon, V., Diarra, L., Soumaré, A.,
Koité, M., Dembélé, F., Lloyd, C., Hanan, N. P., Damesin, C.,
Delon, C., Serça, D., Galy-Lacaux, C., Seghieri, J., Becerra, S., Dia,
H., Gangneron, F., and Mazzega, P.: The AMMA-CATCH Gourma observatory site
in Mali: Relating climatic variations to changes in vegetation, surface
hydrology, fluxes and natural resources, J. Hydrol., 375, 14–33,
https://doi.org/10.1016/j.jhydrol.2009.06.045, 2009.
Mougin, E., Diawara, M. O., Soumaguel, N., Maïga, A. A., Demarez, V., Hiernaux, P., Grippa, M., Chaffard, V., and Ba, A.: A leaf area index data set acquired in Sahelian rangelands of Gourma in Mali over the 2005–2017 period, Earth Syst. Sci. Data, 11, 675–686, https://doi.org/10.5194/essd-11-675-2019, 2019.
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A3H MODIS/Terra+Aqua Leaf Area Index/FPAR 4-day L4 Global 500 m SIN Grid V006 [data set], NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MCD15A3H.006 (last access: 16 June 2021), 2015.
Odekunle, T. O., Andrew, O., and Aremu, S. O.: Towards a wetter
Sudano-Sahelian ecological zone in twenty-first century Nigeria, Weather,
63, 66–70, https://doi.org/10.1002/wea.172, 2008.
Pallas, J. E. and Samish, Y. B.: Photosynthetic response of peanut, Crop
Sci., 14, 478–482, https://doi.org/10.2135/cropsci1974.0011183X001400030042x, 1974.
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., Isaac, P., Polidori, D., Ribeca, A., Ingen, C., Zhang, L., Amiro, B., Ammann, C., Arain, M., and Ardö, J.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data, Sci. Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020.
Pereira, A. R. and Pruitt, W. O.: Adaptation of the Thornthwaite scheme for
estimating daily reference evapotranspiration, Agric. Water
Manage., 66, 251–257, https://doi.org/10.1016/j.agwat.2003.11.003, 2004.
Pielke, R. A., Pitman, A., Niyogi, D., Mahmood, R., McAlpine, C., Hossain,
F., Goldewijk, K. K., Nair, U., Betts, R., Fall, S., Reichstein, M., Kabat,
P., and de Noblet, N.: Land use/land cover changes and climate: modeling
analysis and observational evidence, Wiley Interdisciplinary Reviews:
Climate Change, 2, 828–850, https://doi.org/10.1002/wcc.144, 2011.
Pitman, A. J.: The evolution of, and revolution in, land surface schemes
designed for climate models, Int. J. Climatol., 23, 479–510,
https://doi.org/10.1002/joc.893, 2003.
Quansah, E., Mauder, M., Balogun, A. A., Amekudzi, L. K., Hingerl, L.,
Bliefernicht, J., and Kunstmann, H.: Carbon dioxide fluxes from contrasting
ecosystems in the Sudanian Savanna in West Africa, Carbon Balance Manag.,
10, 1–17, https://doi.org/10.1186/s13021-014-0011-4, 2015.
Quenum, G. M. L. D., Klutse, N. A. B., Dieng, D., Laux, P., Arnault, J.,
Kodja, J. D., and Oguntunde, P. G.: Identification of Potential Drought
Areas in West Africa Under Climate Change and Variability, Earth Syst.
Environ., 3, 429–444, https://doi.org/10.1007/s41748-019-00133-w, 2019.
Rahimi, J., Ago, E. E., Ayantunde, A., Bogaert, J., Butterbach-Bahl,
K., Cappelaere,
B., Demarty,
J., Diouf,
A. A., Falk,
U., Haas,
E., Hiernaux,
P., Kraus,
D., Roupsard,
O., Scheer,
C., Srivastava,
A. K., Tagesson,
T., and Grote,
R.: Modelling Gas Exchange and Biomass Production in West African Sahelian and Sudanian Ecological Zones. Karlsruhe Institute of Technology (KIT) [data set], https://doi.org/10.35097/437, 2021.
Roupsard, O., Audebert, A., Ndour, A. P., Clermont-Dauphin, C., Agbohessou,
Y., Sanou, J., Koala, J., Faye, E., Sambakhe, D., Jourdan, C., le Maire, G.,
Tall, L., Sanogo, D., Seghieri, J., Cournac, L., and Leroux, L.: How far
does the tree affect the crop in agroforestry? New spatial analysis methods
in a Faidherbia parkland, Agr. Ecosyst. Environ., 296, 106928,
https://doi.org/10.1016/j.agee.2020.106928, 2020.
Running, S. W. and Coughlan, J. C.: A general model of forest ecosystem
processes for regional applications. I. Hydrologic balance, canopy gas
exchange and primary production processes, Ecol. Model., 42, 125–154,
https://doi.org/10.1016/0304-3800(88)90112-3, 1988.
Saleska, S. R., Miller, S. D., Matross, D. M., Goulden, M. L., Wofsy, S. C.,
da Rocha, H. R., de Camargo, P. B., Crill, P., Daube, B. C., de Freitas, H.
C., Hutyra, L., Keller, M., Kirchhoff, V., Menton, M., Munger, J. W., Pyle,
E. H., Rice, A. H., and Silva, H.: Carbon in amazon forests: Unexpected
seasonal fluxes and disturbance-induced losses, Science, 302, 1554–1557,
https://doi.org/10.1126/science.1091165, 2003.
Scheiter, S. and Higgins, S. I.: Impacts of climate change on the
vegetation of Africa: an adaptive dynamic vegetation modelling approach,
Glob. Change Biol., 15, 2224–2246, https://doi.org/10.1111/j.1365-2486.2008.01838.x, 2009.
Scholes, R. J. and Hall, D. O.: The carbon budget of tropical savannas,
woodlands and grasslands, in: Global change: effects on coniferous forests
and grasslands, edited by: Breymeyer, A. I., Hall, D. O., Melillo, J. M.,
and Ågren, G. I., Scope, John Wiley and Sons, Chichester, 69–100, 1996.
Sellers, P. J., Randall, D. A., Collatz, G. J., Berry, J. A., Field, C. B.,
Dazlich, D. A., Zhang, C., Collelo, G. D., and Bounoua, L.: A revised land
surface parameterization (SiB2) for atmospheric GCMs. Part I: model
formulation, J. Climate, 9, 676–705, https://doi.org/10.1175/1520-0442(1996)009<0676:ARLSPF>2.0.CO;2, 1996.
Setterfield, S. A., Clifton, P. J., Hutley, L. B., Rossiter-Rachor, N. A.,
and Douglas, M. M.: Exotic grass invasion alters microsite conditions
limiting woody recruitment potential in an Australian savanna, Sci. Rep.-UK, 8,
6628–6628, https://doi.org/10.1038/s41598-018-24704-5, 2018.
Sibret, T.: The Sahelian Drylands under Pressure: Studying the Impact of
Environmental Factors on Vegetation in Dahra, Senegal, Master of Science in
Bioscience Engineering, Ghent University, Ghent, 113 pp., 2018.
Simioni, G., Le Roux, X., Gignoux, J., and Sinoquet, H.: Treegrass: a 3D,
process-based model for simulating plant interactions in tree-grass
ecosystems, Ecol. Model., 131, 47–63, https://doi.org/10.1016/S0304-3800(00)00243-X,
2000.
Sjöström, M., Ardö, J., Arneth, A., Boulain, N., Cappelaere, B.,
Eklundh, L., de Grandcourt, A., Kutsch, W. L., Merbold, L., Nouvellon, Y.,
Scholes, R. J., Schubert, P., Seaquist, J., and Veenendaal, E. M.: Exploring
the potential of MODIS EVI for modeling gross primary production across
African ecosystems, Remote. Sens. Environ., 115, 1081–1089,
https://doi.org/10.1016/j.rse.2010.12.013, 2011.
Sjöström, M., Zhao, M., Archibald, S., Arneth, A., Cappelaere, B.,
Falk, U., de Grandcourt, A., Hanan, N., Kergoat, L., Kutsch, W., Merbold,
L., Mougin, E., Nickless, A., Nouvellon, Y., Scholes, R. J., Veenendaal, E.
M., and Ardö, J.: Evaluation of MODIS gross primary productivity for
Africa using eddy covariance data, Remote. Sens. Environ., 131, 275–286,
https://doi.org/10.1016/j.rse.2012.12.023, 2013.
Snyman, H. A.: Rangeland degradation in a semi-arid South Africa – I:
influence on seasonal root distribution, root/shoot ratios and water-use
efficiency, J. Arid Environ., 60, 457–481,
https://doi.org/10.1016/j.jaridenv.2004.06.006, 2005.
Sobamowo, J. O.: Effect of harvesting dates and fertilizer application on
cassava productivity in rainforest and guinea savanna agroecological zones
of Nigeria, PhD, University of Cape Coast, Ghana, 2016.
Sonawane, B. V., Sharwood, R. E., von Caemmerer, S., Whitney, S. M., and
Ghannoum, O.: Short-term thermal photosynthetic responses of C4 grasses are
independent of the biochemical subtype, J. Exp. Bot., 68, 5583–5597,
https://doi.org/10.1093/jxb/erx350, 2017.
Sotelo Montes, C., Weber, J. C., Silva, D. A., Andrade, C., Muñiz, G.
B., Garcia, R. A., and Kalinganire, A.: Growth and fuelwood properties of
five tree and shrub species in the Sahelian and Sudanian ecozones of Mali:
relationships with mean annual rainfall and geographical coordinates, New
Forests, 45, 179–197, https://doi.org/10.1007/s11056-013-9401-9, 2014.
Tagesson, T., Fensholt, R., Guiro, I., Rasmussen, M. O., Huber, S., Mbow,
C., Garcia, M., Horion, S., Sandholt, I., Holm-Rasmussen, B., Göttsche,
F. M., Ridler, M.-E., Olén, N., Lundegard Olsen, J., Ehammer, A.,
Madsen, M., Olesen, F. S., and Ardö, J.: Ecosystem properties of
semiarid savanna grassland in West Africa and its relationship with
environmental variability, Glob. Change Biol., 21, 250–264,
https://doi.org/10.1111/gcb.12734, 2015.
Tagesson, T., Ardö, J., Guiro, I., Cropley, F., Mbow, C., Horion, S.,
Ehammer, A., Mougin, E., Delon, C., Corinne, G.-L., and Fensholt, R.: Very
high CO2 exchange fluxes at the peak of the rainy season in a West
African grazed semi-arid savanna ecosystem, Geografisk Tidsskrift-Danish
J. Geography, 116, 1–17, https://doi.org/10.1080/00167223.2016.1178072, 2016.
Tews, J. and Jeltsch, F.: Modelling the impact of climate change on woody
plant population dynamics in South African savanna, BMC Ecology, 4, 1–12,
https://doi.org/10.1186/1472-6785-4-17, 2004.
Tews, J., Esther, A., Milton, S. J., and Jeltsch, F.: Linking a population
model with an ecosystem model: Assessing the impact of land use and climate
change on savanna shrub cover dynamics, Ecol. Model., 195, 219–228,
https://doi.org/10.1016/j.ecolmodel.2005.11.025, 2006.
Thornley, J. H. M.: Instantaneous canopy photosynthesis: Analytical
expressions for sun and shade leaves based on exponential light decay down
the canopy and an acclimated non-rectangular hyperbola for leaf
photosynthesis, Ann. Bot., 89, 451–458, https://doi.org/10.1093/aob/mcf071, 2002.
Thornley, J. H. M. and Cannell, M. G. R.: Modelling the components of plant
respiration: Representation and realism, Ann. Bot., 85, 55–67,
https://doi.org/10.1006/anbo.1999.0997, 2000.
Thornthwaite, C. W.: An approach toward a rational classification of
climate, Geogr. Rev., 38, 55, https://doi.org/10.2307/210739, 1948.
Timouk, F., Kergoat, L., Mougin, E., Lloyd, C. R., Ceschia, E., Cohard, J.
M., Rosnay, P. d., Hiernaux, P., Demarez, V., and Taylor, C. M.: Response of
surface energy balance to water regime and vegetation development in a
Sahelian landscape, J. Hydrol., 375, 178–189, https://doi.org/10.1016/j.jhydrol.2009.04.022,
2009.
Ullmann, I.: Stomatal conductance and transpiration of Acacia under field
conditions: similarities and differences between leaves and phyllodes,
Trees-Struct. Funct., 3, 45–56, https://doi.org/10.1007/BF00202400, 1989.
Ünlü, M. and Steduto, P.: Comparison of Photosynthetic Water use
Efficiency of Sweet Sorghum at Canopy and Leaf Scales, Turkish Journal of
Agriculture and Forestry, 24, 519–526, 2000.
Velluet, C., Demarty, J., Cappelaere, B., Braud, I., Issoufou, H. B.-A., Boulain, N., Ramier, D., Mainassara, I., Charvet, G., Boucher, M., Chazarin, J.-P., Oï, M., Yahou, H., Maidaji, B., Arpin-Pont, F., Benarrosh, N., Mahamane, A., Nazoumou, Y., Favreau, G., and Seghieri, J.: Building a field- and model-based climatology of local water and energy cycles in the cultivated Sahel – annual budgets and seasonality, Hydrol. Earth Syst. Sci., 18, 5001–5024, https://doi.org/10.5194/hess-18-5001-2014, 2014.
Vico, G. and Porporato, A.: Modelling C3 and C4 photosynthesis under
water-stressed conditions, Plant Soil, 313, 187–203,
https://doi.org/10.1007/s11104-008-9691-4, 2008.
Vitasse, Y., Francois, C., Delpierre, N., Dufrene, E., Kremer, A., Chuine,
I., and Delzon, S.: Assessing the effects of climate change on the phenology
of European temperate trees, Agric. Forest Meteorol., 151, 969–980, 2011.
Vitkauskaitė, G. and Venskaitytė, L.: Differences between C3
(Hordeum vulgare L.) and C4 (Panicum miliaceum L.) plants with respect to their resistance to water deficit,
Žemdirbystė (Agriculture), 98, 349–356, 2011.
Von Caemmerer, S.: Biochemical models of leaf photosynthesis, Technicques in
Plant Sciences, CSIRO, Collingwood VIC 3066, Australia, 2000.
Vu, J. C. V.: Acclimation of peanut (Arachis hypogaea L.) leaf photosynthesis to elevated
growth CO2 and temperature, Environ. Exp. Bot., 53,
85–95, https://doi.org/10.1016/j.envexpbot.2004.03.006, 2005.
Werner, C., Haas, E., Grote, R., Gauder, M., Graeff-Hönninger, S.,
Claupein, W., and Butterbach-Bahl, K.: Biomass production potential from
Populus short rotation systems in Romania, GCB Bioenergy, 4, 642–653,
https://doi.org/10.1111/j.1757-1707.2012.01180.x, 2012.
Wesolowski, T. and Rowinski, P.: Timing of bud burst and tree-leaf
development in a multispecies temperate forest, Forest Ecol. Manage., 237,
387–393, 2006.
Whitley, R., Beringer, J., Hutley, L. B., Abramowitz, G., De Kauwe, M. G., Duursma, R., Evans, B., Haverd, V., Li, L., Ryu, Y., Smith, B., Wang, Y.-P., Williams, M., and Yu, Q.: A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas, Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, 2016.
Whitley, R., Beringer, J., Hutley, L. B., Abramowitz, G., De Kauwe, M. G., Evans, B., Haverd, V., Li, L., Moore, C., Ryu, Y., Scheiter, S., Schymanski, S. J., Smith, B., Wang, Y.-P., Williams, M., and Yu, Q.: Challenges and opportunities in land surface modelling of savanna ecosystems, Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, 2017.
Yao, N. g. R. and Goué, B.: Water use efficiency of a cassava crop as
affected by soil water balance, Agric. Forest Meteorol., 61, 187–203,
https://doi.org/10.1016/0168-1923(92)90049-A, 1992.
Yu, G.-R., Zhuang, J., and Yu, Z.-L.: An attempt to establish a synthetic
model of photosynthesis-transpiration based on stomatal behavior for maize
and soybean plants grown in field, J. Plant Physiol., 158,
861–874, https://doi.org/10.1078/0176-1617-00177, 2001.
Yuan, W., Zhou, G., Wang, Y., Han, X., and Wang, Y.: Simulating phenological
characteristics of two dominant grass species in a semi-arid steppe
ecosystem, Ecol. Res., 22, 784–791, https://doi.org/10.1007/s11284-006-0318-z,
2007.
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.
West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange,...
