Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7573-2022
© Author(s) 2022. 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-15-7573-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
Félicien Meunier
CORRESPONDING AUTHOR
Computational and Applied Vegetation Ecology, Department of Environment, Ghent University, Ghent, 9000, Belgium
Wim Verbruggen
Computational and Applied Vegetation Ecology, Department of Environment, Ghent University, Ghent, 9000, Belgium
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
Hans Verbeeck
Computational and Applied Vegetation Ecology, Department of Environment, Ghent University, Ghent, 9000, Belgium
Marc Peaucelle
Computational and Applied Vegetation Ecology, Department of Environment, Ghent University, Ghent, 9000, Belgium
INRAE, Université de Bordeaux, UMR 1391 ISPA, 33140 Villenave-d'Ornon, France
Related authors
Wim Verbruggen, David Wårlind, Stéphanie Horion, Félicien Meunier, Hans Verbeeck, and Guy Schurgers
EGUsphere, https://doi.org/10.5194/egusphere-2025-1259, https://doi.org/10.5194/egusphere-2025-1259, 2025
Short summary
Short summary
We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Inês Vieira, Félicien Meunier, Maria Carolina Duran Rojas, Stephen Sitch, Flossie Brown, Giacomo Gerosa, Silvano Fares, Pascal Boeckx, Marijn Bauters, and Hans Verbeeck
EGUsphere, https://doi.org/10.5194/egusphere-2025-1375, https://doi.org/10.5194/egusphere-2025-1375, 2025
Short summary
Short summary
We used a computer model to study how ozone pollution reduces plant growth in six European forests, from Finland to Italy. Combining field data and simulations, we found that ozone can lower carbon uptake by up to 6 % each year, especially in Mediterranean areas. Our study shows that local climate and forest type influence ozone damage and highlights the need to include ozone effects in forest and climate models.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
Short summary
Short summary
Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
Short summary
Short summary
We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Jan Vanderborght, Valentin Couvreur, Felicien Meunier, Andrea Schnepf, Harry Vereecken, Martin Bouda, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 25, 4835–4860, https://doi.org/10.5194/hess-25-4835-2021, https://doi.org/10.5194/hess-25-4835-2021, 2021
Short summary
Short summary
Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implementing root hydraulics in macroscopic soil water flow and land surface models.
Hannes P. T. De Deurwaerder, Marco D. Visser, Matteo Detto, Pascal Boeckx, Félicien Meunier, Kathrin Kuehnhammer, Ruth-Kristina Magh, John D. Marshall, Lixin Wang, Liangju Zhao, and Hans Verbeeck
Biogeosciences, 17, 4853–4870, https://doi.org/10.5194/bg-17-4853-2020, https://doi.org/10.5194/bg-17-4853-2020, 2020
Short summary
Short summary
The depths at which plants take up water is challenging to observe directly. To do so, scientists have relied on measuring the isotopic composition of xylem water as this provides information on the water’s source. Our work shows that this isotopic composition changes throughout the day, which complicates the interpretation of the water’s source and has been currently overlooked. We build a model to help understand the origin of these composition changes and their consequences for science.
Derrick Muheki, Bas Vercruysse, Krishna Kumar Thirukokaranam Chandrasekar, Christophe Verbruggen, Julie M. Birkholz, Koen Hufkens, Hans Verbeeck, Pascal Boeckx, Seppe Lampe, Ed Hawkins, Peter Thorne, Dominique Kankonde Ntumba, Olivier Kapalay Moulasa, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2024-3779, https://doi.org/10.5194/egusphere-2024-3779, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Archives worldwide host vast records of observed weather data crucial for understanding climate variability. However, most of these records are still in paper form, limiting their use. To address this, we developed MeteoSaver, an open-source tool, to transcribe these records to machine-readable format. Applied to ten handwritten temperature sheets, it achieved a median accuracy of 74%. This tool offers a promising solution to preserve records from archives and unlock historical weather insights.
Wim Verbruggen, David Wårlind, Stéphanie Horion, Félicien Meunier, Hans Verbeeck, and Guy Schurgers
EGUsphere, https://doi.org/10.5194/egusphere-2025-1259, https://doi.org/10.5194/egusphere-2025-1259, 2025
Short summary
Short summary
We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Inês Vieira, Félicien Meunier, Maria Carolina Duran Rojas, Stephen Sitch, Flossie Brown, Giacomo Gerosa, Silvano Fares, Pascal Boeckx, Marijn Bauters, and Hans Verbeeck
EGUsphere, https://doi.org/10.5194/egusphere-2025-1375, https://doi.org/10.5194/egusphere-2025-1375, 2025
Short summary
Short summary
We used a computer model to study how ozone pollution reduces plant growth in six European forests, from Finland to Italy. Combining field data and simulations, we found that ozone can lower carbon uptake by up to 6 % each year, especially in Mediterranean areas. Our study shows that local climate and forest type influence ozone damage and highlights the need to include ozone effects in forest and climate models.
Flossie Brown, Gerd Folberth, Stephen Sitch, Paulo Artaxo, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Matteo Detto, Ninong Komala, Luciana Rizzo, Nestor Rojas, Ines dos Santos Vieira, Steven Turnock, Hans Verbeeck, and Alfonso Zambrano
Atmos. Chem. Phys., 24, 12537–12555, https://doi.org/10.5194/acp-24-12537-2024, https://doi.org/10.5194/acp-24-12537-2024, 2024
Short summary
Short summary
Ozone is a pollutant that is detrimental to human and plant health. Ozone monitoring sites in the tropics are limited, so models are often used to understand ozone exposure. We use measurements from the tropics to evaluate ozone from the UK Earth system model, UKESM1. UKESM1 is able to capture the pattern of ozone in the tropics, except in southeast Asia, although it systematically overestimates it at all sites. This work highlights that UKESM1 can capture seasonal and hourly variability.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
Short summary
Short summary
Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
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.
Flossie Brown, Gerd A. Folberth, Stephen Sitch, Susanne Bauer, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Makoto Deushi, Inês Dos Santos Vieira, Corinne Galy-Lacaux, James Haywood, James Keeble, Lina M. Mercado, Fiona M. O'Connor, Naga Oshima, Kostas Tsigaridis, and Hans Verbeeck
Atmos. Chem. Phys., 22, 12331–12352, https://doi.org/10.5194/acp-22-12331-2022, https://doi.org/10.5194/acp-22-12331-2022, 2022
Short summary
Short summary
Surface ozone can decrease plant productivity and impair human health. In this study, we evaluate the change in surface ozone due to climate change over South America and Africa using Earth system models. We find that if the climate were to change according to the worst-case scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of ozone exposure, but other areas will experience a climate benefit.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
Short summary
Short summary
We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Jan Vanderborght, Valentin Couvreur, Felicien Meunier, Andrea Schnepf, Harry Vereecken, Martin Bouda, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 25, 4835–4860, https://doi.org/10.5194/hess-25-4835-2021, https://doi.org/10.5194/hess-25-4835-2021, 2021
Short summary
Short summary
Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implementing root hydraulics in macroscopic soil water flow and land surface models.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
Short summary
Short summary
Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
Paula Alejandra Lamprea Pineda, Marijn Bauters, Hans Verbeeck, Selene Baez, Matti Barthel, Samuel Bodé, and Pascal Boeckx
Biogeosciences, 18, 413–421, https://doi.org/10.5194/bg-18-413-2021, https://doi.org/10.5194/bg-18-413-2021, 2021
Short summary
Short summary
Tropical forest soils are an important source and sink of greenhouse gases (GHGs) with tropical montane forests having been poorly studied. In this pilot study, we explored soil fluxes of CO2, CH4, and N2O in an Ecuadorian neotropical montane forest, where a net consumption of N2O at higher altitudes was observed. Our results highlight the importance of short-term variations in N2O and provide arguments and insights for future, more detailed studies on GHG fluxes from montane forest soils.
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.
Hannes P. T. De Deurwaerder, Marco D. Visser, Matteo Detto, Pascal Boeckx, Félicien Meunier, Kathrin Kuehnhammer, Ruth-Kristina Magh, John D. Marshall, Lixin Wang, Liangju Zhao, and Hans Verbeeck
Biogeosciences, 17, 4853–4870, https://doi.org/10.5194/bg-17-4853-2020, https://doi.org/10.5194/bg-17-4853-2020, 2020
Short summary
Short summary
The depths at which plants take up water is challenging to observe directly. To do so, scientists have relied on measuring the isotopic composition of xylem water as this provides information on the water’s source. Our work shows that this isotopic composition changes throughout the day, which complicates the interpretation of the water’s source and has been currently overlooked. We build a model to help understand the origin of these composition changes and their consequences for science.
Cited articles
Ahlström, A., Schurgers, G., Arneth, A., and Smith, B.: Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections, Environ. Res. Lett., 7, 044008, https://doi.org/10.1088/1748-9326/7/4/044008, 2012.
Aragão, L. E. O. C., Malhi, Y., Metcalfe, D. B., Silva-Espejo, J. E., Jiménez, E., Navarrete, D., Almeida, S., Costa, A. C. L., Salinas, N., Phillips, O. L., Anderson, L. O., Alvarez, E., Baker, T. R., Goncalvez, P. H., Huamán-Ovalle, J., Mamani-Solórzano, M., Meir, P., Monteagudo, A., Patiño, S., Peñuela, M. C., Prieto, A., Quesada, C. A., Rozas-Dávila, A., Rudas, A., Silva Jr., J. A., and Vásquez, R.: Above- and below-ground net primary productivity across ten Amazonian forests on contrasting soils, Biogeosciences, 6, 2759–2778, https://doi.org/10.5194/bg-6-2759-2009, 2009.
Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N. J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley, E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A., Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry, S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R., Verbeeck, H., Wijaya, A., and Willcock, S.: An integrated pan-tropical biomass map using multiple reference datasets, Glob. Change Biol., 22, 1406–1420, https://doi.org/10.1111/gcb.13139, 2016.
Baker, I. T., Prihodko, L., Denning, A. S., Goulden, M., Miller, S., and da Rocha, H. R.: Seasonal drought stress in the Amazon: Reconciling models and observations, J. Geophys. Res., 113, G00B01, https://doi.org/10.1029/2007JG000644, 2008.
Barros, A. H. C. and de Jong van Lier, Q.: Pedotransfer Functions for Brazilian Soils, in: Application of Soil Physics in Environmental Analyses: Measuring, Modelling and Data Integration, edited by: Teixeira, W. G., Ceddia, M. B., Ottoni, M. V., and Donnagema, G. K., Springer International Publishing, Cham, 131–162, https://doi.org/10.1007/978-3-319-06013-2_6, 2014.
Batjes, N. H.: A world dataset of derived soil properties by FAO–UNESCO soil unit for global modelling, Soil Use Manage., 13, 9–16, https://doi.org/10.1111/j.1475-2743.1997.tb00550.x, 1997.
Bonan, G. B.: Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests, Science, 320, 1444–1449, 2008.
Brooks, R. H. and Corey, A. T.: Hydraulic Properties of Porous Media, Hydrology Paper, Vol. 3, Colorado State University, Fort Collins, 1964.
Carminati, A. and Javaux, M.: Soil Rather Than Xylem Vulnerability Controls Stomatal Response to Drought, Trends Plant Sci., 25, 868–880, https://doi.org/10.1016/j.tplants.2020.04.003, 2020.
Carsel, R. F. and Parrish, R. S.: Developing joint probability distributions of soil water retention characteristics, Water Resour. Res., 24, 755–769, https://doi.org/10.1029/WR024i005p00755, 1988.
Christoffersen, B. O., Gloor, M., Fauset, S., Fyllas, N. M., Galbraith, D. R., Baker, T. R., Kruijt, B., Rowland, L., Fisher, R. A., Binks, O. J., Sevanto, S., Xu, C., Jansen, S., Choat, B., Mencuccini, M., McDowell, N. G., and Meir, P.: Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro), Geosci. Model Dev., 9, 4227–4255, https://doi.org/10.5194/gmd-9-4227-2016, 2016.
Clapp, R. and Hornberger, G.: Empirical equations for some soil hydraulic properties, Water Resour. Res., 14, 601–604, https://doi.org/10.1029/WR014I004P00601, 1978.
Collier, N., Hoffman, F. M., Lawrence, D. M., Keppel-Aleks, G., Koven, C. D., Riley, W. J., Mu, M., and Randerson, J. T.: The International Land Model Benchmarking (ILAMB) System: Design, Theory, and Implementation, J. Adv. Model. Earth Sy., 10, 2731–2754, https://doi.org/10.1029/2018MS001354, 2018.
Combe, M., de Arellano, J. V.-G., Ouwersloot, H. G., and Peters, W.: Plant water-stress parameterization determines the strength of land–atmosphere coupling, Agr. Forest Meteorol., 217, 61–73, https://doi.org/10.1016/j.agrformet.2015.11.006, 2016.
Condit, R., Engelbrecht, B. M. J., Pino, D., Pérez, R., and Turner, B. L.: Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees, P. Natl. Acad. Sci. USA, 110, 5064–5068, https://doi.org/10.1073/pnas.1218042110, 2013.
Corlett, R. T.: The Impacts of Droughts in Tropical Forests, Trends Plant Sci., 21, 584–593, https://doi.org/10.1016/j.tplants.2016.02.003, 2016.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A Statistical Exploration of the Relationships of Soil Moisture Characteristics to the Physical Properties of Soils, Water Resour. Res., 20, 682–690, https://doi.org/10.1029/WR020i006p00682, 1984.
Darcy, H.: Les Fontaines Publiques de la Ville de Dijon: Exposition et Application des Principes a Suivre et des Formulesa Employer dans les Questions de Distribution d’Eau, edited by: Dalmont, V., Paris, 647 pp., ISBN 10 2012576001, ISBN 13 9782012576001,
1856.
De Deurwaerder, H. P. T., Visser, M. D., Meunier, F., Detto, M., Hervé-Fernández, P., Boeckx, P., and Verbeeck, H.: Robust Estimation of Absorbing Root Surface Distributions From Xylem Water Isotope Compositions With an Inverse Plant Hydraulic Model, Front. For. Glob. Change, 4, 76, https://doi.org/10.3389/ffgc.2021.689335, 2021.
de Rosnay, P., Polcher, J., Bruen, M., and Laval, K.: Impact of a physically based soil water flow and soil-plant interaction representation for modeling large-scale land surface processes, J. Geophys. Res.-Atmos., 107, 4118, https://doi.org/10.1029/2001JD000634, 2002.
d'Orgeval, T., Polcher, J., and de Rosnay, P.: Sensitivity of the West African hydrological cycle in ORCHIDEE to infiltration processes, Hydrol. Earth Syst. Sci., 12, 1387–1401, https://doi.org/10.5194/hess-12-1387-2008, 2008.
Doughty, C. E., Metcalfe, D. B., Girardin, C. A. J., Amézquita, F. F., Cabrera, D. G., Huasco, W. H., Silva-Espejo, J. E., Araujo-Murakami, A., da Costa, M. C., Rocha, W., Feldpausch, T. R., Mendoza, A. L. M., da Costa, A. C. L., Meir, P., Phillips, O. L., and Malhi, Y.: Drought impact on forest carbon dynamics and fluxes in Amazonia, Nature, 519, 78–82, https://doi.org/10.1038/nature14213, 2015.
Duffy, P. B., Brando, P., Asner, G. P., and Field, C. B.: Projections of future meteorological drought and wet periods in the Amazon, P. Natl. Acad. Sci. USA, 112, 13172–13177, https://doi.org/10.1073/pnas.1421010112, 2015.
Eleftheriadis, A., Lafuente, F., and Turrión, M.-B.: Effect of land use, time since deforestation and management on organic C and N in soil textural fractions, Soil Till. Res., 183, 1–7, https://doi.org/10.1016/j.still.2018.05.012, 2018.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Fan, Y., Miguez-Macho, G., Jobbágy, E. G., Jackson, R. B., and Otero-Casal, C.: Hydrologic regulation of plant rooting depth, P. Natl. Acad. Sci. USA, 114, 10572–10577, https://doi.org/10.1073/pnas.1712381114, 2017.
Fatichi, S., Or, D., Walko, R., Vereecken, H., Young, M. H., Ghezzehei, T. A., Hengl, T., Kollet, S., Agam, N., and Avissar, R.: Soil structure is an important omission in Earth System Models, Nat. Commun., 11, 522, https://doi.org/10.1038/s41467-020-14411-z, 2020.
Feldpausch, T. R., Phillips, O. L., Brienen, R. J. W., Gloor, E., Lloyd, J., Lopez-Gonzalez, G., Monteagudo-Mendoza, A., Malhi, Y., Alarcón, A., Álvarez Dávila, E., Alvarez-Loayza, P., Andrade, A., Aragao, L. E. O. C., Arroyo, L., Aymar C. G. A., Baker, T. R., Baraloto, C., Barroso, J., Bonal, D., Castro, W., Chama, V., Chave, J., Domingues, T. F., Fauset, S., Groot, N., Honorio Coronado, E., Laurance, S., Laurance, W. F., Lewis, S. L., Licona, J. C., Marimon, B. S., Marimon-Junior, B. H., Mendoza Bautista, C., Neill, D. A., Oliveira, E. A., Oliveira dos Santos, C., Pallqui Camacho, N. C., Pardo-Molina, G., Prieto, A., Quesada, C. A., Ramírez, F., Ramírez-Angulo, H., Réjou-Méchain, M., Rudas, A., Saiz, G., Salomão, R. P., Silva-Espejo, J. E., Silveira, M., ter Steege, H., Stropp, J., Terborgh, J., Thomas-Caesar, R., van der Heijden, G. M. F., Vásquez Martinez, R., Vilanova, E., and Vos, V. A.: Amazon forest response to repeated droughts, Global Biogeochem. Cy., 30, 964–982, https://doi.org/10.1002/2015GB005133, 2016.
Fisher, R. A. and Koven, C. D.: Perspectives on the Future of Land Surface Models and the Challenges of Representing Complex Terrestrial Systems, J. Adv. Model. Earth Sy., 12, e2018MS001453, https://doi.org/10.1029/2018MS001453, 2020.
Flack-Prain, S., Meir, P., Malhi, Y., Smallman, T. L., and Williams, M.: Does economic optimisation explain LAI and leaf trait distributions across an Amazon soil moisture gradient?, Glob. Change Biol., 27, 587–605, https://doi.org/10.1111/gcb.15368, 2021.
Franklin, O., Johansson, J., Dewar, R. C., Dieckmann, U., McMurtrie, R. E., Brännström, Å., and Dybzinski, R.: Modeling carbon allocation in trees: a search for principles, Tree Physiol., 32, 648–666, https://doi.org/10.1093/treephys/tpr138, 2012.
Fyllas, N. M., Patiño, S., Baker, T. R., Bielefeld Nardoto, G., Martinelli, L. A., Quesada, C. A., Paiva, R., Schwarz, M., Horna, V., Mercado, L. M., Santos, A., Arroyo, L., Jiménez, E. M., Luizão, F. J., Neill, D. A., Silva, N., Prieto, A., Rudas, A., Silviera, M., Vieira, I. C. G., Lopez-Gonzalez, G., Malhi, Y., Phillips, O. L., and Lloyd, J.: Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate, Biogeosciences, 6, 2677–2708, https://doi.org/10.5194/bg-6-2677-2009, 2009.
Gatti, L. V., Gloor, M., Miller, J. B., Doughty, C. E., Malhi, Y., Domingues, L. G., Basso, L. S., Martinewski, A., Correia, C. S. C., Borges, V. F., Freitas, S., Braz, R., Anderson, L. O., Rocha, H., Grace, J., Phillips, O. L., and Lloyd, J.: Drought sensitivity of Amazonian carbon balance revealed by atmospheric measurements, Nature, 506, 76–80, https://doi.org/10.1038/nature12957, 2014.
Gerten, D., Schaphoff, S., Haberlandt, U., Lucht, W., and Sitch, S.: Terrestrial vegetation and water balance – hydrological evaluation of a dynamic global vegetation model, J. Hydrol., 286, 249–270, https://doi.org/10.1016/j.jhydrol.2003.09.029, 2004.
Green, J. K., Berry, J., Ciais, P., Zhang, Y., and Gentine, P.: Amazon rainforest photosynthesis increases in response to atmospheric dryness, Sci. Adv., 6, eabb7232, https://doi.org/10.1126/sciadv.abb7232, 2020.
Harris, P. P., Huntingford, C., Cox, P. M., Gash, J. H. C., and Malhi, Y.: Effect of soil moisture on canopy conductance of Amazonian rainforest, Agr. Forest Meteorol., 3–4, 215–227, https://doi.org/10.1016/j.agrformet.2003.09.006, 2004.
Hassink, J.: Effects of soil texture and structure on carbon and nitrogen mineralization in grassland soils, Biol. Fert. Soils, 14, 126–134, https://doi.org/10.1007/BF00336262, 1992.
Haxeltine, A. and Prentice, I. C.: A General Model for the Light-Use Efficiency of Primary Production, Funct. Ecol., 10, 551–561, https://doi.org/10.2307/2390165, 1996.
Hengl, T., de Jesus, J. M., Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLOS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Hodnett, M. and Tomasella, J.: Marked differences between van Genuchten soil water-retention parameters for temperate and tropical soils: A new water-retention pedo-transfer functions developed for tropical soils, Geoderma, 108, 155–180, https://doi.org/10.1016/S0016-7061(02)00105-2, 2002.
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E., and Schulze, E. D.: A global analysis of root distributions for terrestrial biomes, Oecologia, 108, 389–411, https://doi.org/10.1007/BF00333714, 1996.
Jiménez, E. M., Peñuela-Mora, M. C., Sierra, C. A., Lloyd, J., Phillips, O. L., Moreno, F. H., Navarrete, D., Prieto, A., Rudas, A., Álvarez, E., Quesada, C. A., Grande-Ortíz, M. A., García-Abril, A., and Patiño, S.: Edaphic controls on ecosystem-level carbon allocation in two contrasting Amazon forests, J. Geophys. Res.-Biogeo., 119, 1820–1830, https://doi.org/10.1002/2014JG002653, 2014.
Jirka, S., McDonald, A. J., Johnson, M. S., Feldpausch, T. R., Couto, E. G., and Riha, S. J.: Relationships between soil hydrology and forest structure and composition in the southern Brazilian Amazon, J. Veg. Sci., 18, 183–194, https://doi.org/10.1111/j.1654-1103.2007.tb02529.x, 2007.
Joetzjer, E., Delire, C., Douville, H., Ciais, P., Decharme, B., Fisher, R., Christoffersen, B., Calvet, J. C., da Costa, A. C. L., Ferreira, L. V., and Meir, P.: Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models, Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, 2014.
Joetzjer, E., Maignan, F., Chave, J., Goll, D., Poulter, B., Barichivich, J., Maréchaux, I., Luyssaert, S., Guimberteau, M., Naudts, K., Bonal, D., and Ciais, P.: Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia, Ecol. Model., 469, 109969, https://doi.org/10.1016/j.ecolmodel.2022.109969, 2022.
Johnson, M. O., Galbraith, D., Gloor, M., De Deurwaerder, H., Guimberteau, M., Rammig, A., Thonicke, K., Verbeeck, H., von Randow, C., Monteagudo, A., Phillips, O. L., Brienen, R. J. W., Feldpausch, T. R., Lopez Gonzalez, G., Fauset, S., Quesada, C. A., Christoffersen, B., Ciais, P., Sampaio, G., Kruijt, B., Meir, P., Moorcroft, P., Zhang, K., Alvarez-Davila, E., Alves de Oliveira, A., Amaral, I., Andrade, A., Aragao, L. E. O. C., Araujo-Murakami, A., Arets, E. J. M. M., Arroyo, L., Aymard, G. A., Baraloto, C., Barroso, J., Bonal, D., Boot, R., Camargo, J., Chave, J., Cogollo, A., Cornejo Valverde, F., Lola da Costa, A. C., Di Fiore, A., Ferreira, L., Higuchi, N., Honorio, E. N., Killeen, T. J., Laurance, S. G., Laurance, W. F., Licona, J., Lovejoy, T., Malhi, Y., Marimon, B., Marimon Junior, B. H., Matos, D. C. L., Mendoza, C., Neill, D. A., Pardo, G., Peña-Claros, M., Pitman, N. C. A., Poorter, L., Prieto, A., Ramirez-Angulo, H., Roopsind, A., Rudas, A., Salomao, R. P., Silveira, M., Stropp, J., ter Steege, H., Terborgh, J., Thomas, R., Toledo, M., Torres-Lezama, A., van der Heijden, G. M. F., Vasquez, R., Guimarães Vieira, I. C., Vilanova, E., Vos, V. A., and Baker, T. R.: Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models, Glob. Change Biol., 22, 3996–4013, https://doi.org/10.1111/gcb.13315, 2016.
Kishné, A., Yimam, Y., Morgan, C., and Dornblaser, B.: Evaluation and improvement of the default soil hydraulic parameters for the Noah Land Surface Model, Geoderma, 285, 247–259, https://doi.org/10.1016/j.geoderma.2016.09.022, 2017.
Knox, R. G., Longo, M., Swann, A. L. S., Zhang, K., Levine, N. M., Moorcroft, P. R., and Bras, R. L.: Hydrometeorological effects of historical land-conversion in an ecosystem-atmosphere model of Northern South America, Hydrol. Earth Syst. Sci., 19, 241–273, https://doi.org/10.5194/hess-19-241-2015, 2015.
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005.
Laurance, W. F., Fearnside, P. M., Laurance, S. G., Delamonica, P., Lovejoy, T. E., Rankin-de Merona, J. M., Chambers, J. Q., and Gascon, C.: Relationship between soils and Amazon forest biomass: a landscape-scale study, Forest Ecol. Manag., 118, 127–138, https://doi.org/10.1016/S0378-1127(98)00494-0, 1999.
Li, L., Wang, Y.-P., Yu, Q., Pak, B., Eamus, D., Yan, J., van Gorsel, E., and Baker, I. T.: Improving the responses of the Australian community land surface model (CABLE) to seasonal drought: Improving CABLE in response to drought, J. Geophys. Res.-Biogeo., 117, G04002, https://doi.org/10.1029/2012JG002038, 2012.
Longo, M., Knox, R. G., Levine, N. M., Alves, L. F., Bonal, D., Camargo, P. B., Fitzjarrald, D. R., Hayek, M. N., Restrepo-Coupe, N., Saleska, S. R., da Silva, R., Stark, S. C., Tapajós, R. P., Wiedemann, K. T., Zhang, K., Wofsy, S. C., and Moorcroft, P. R.: Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts, New Phytol., 219, 914–931, https://doi.org/10.1111/nph.15185, 2018.
Longo, M., Knox, R. G., Medvigy, D. M., Levine, N. M., Dietze, M. C., Kim, Y., Swann, A. L. S., Zhang, K., Rollinson, C. R., Bras, R. L., Wofsy, S. C., and Moorcroft, P. R.: The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description, Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, 2019a.
Longo, M., Knox, R., Medvigy, D. M., Levine, N. M., Dietze, M.,
Swann, A. L. S., Zhang, K., Rollinson, C., di Porcia e Brugnera, M., Scott, D., Serbin, S. P., Kooper, R., Pourmokhtarian, A.,
Shiklomanov, A., Viskari, T., and Moorcroft, P.: Ecosystem Demography Model, version 2.2 (ED-2.2) (rev-86), Zenodo [code], https://doi.org/10.5281/zenodo.3365659, 2019b.
Lu, J., Zhang, Q., Werner, A. D., Li, Y., Jiang, S., and Tan, Z.: Root-induced changes of soil hydraulic properties – A review, J. Hydrol., 589, 125203, https://doi.org/10.1016/j.jhydrol.2020.125203, 2020.
Maeda, E. E., Kim, H., Aragão, L. E. O. C., Famiglietti, J. S., and Oki, T.: Disruption of hydroecological equilibrium in southwest Amazon mediated by drought, Geophys. Res. Lett., 42, 7546–7553, https://doi.org/10.1002/2015GL065252, 2015.
Medeiros, J. C., Cooper, M., Dalla Rosa, J., Grimaldi, M., and Coquet, Y.: Assessment of pedotransfer functions for estimating soil water retention curves for the amazon region, Rev. Bras. Cienc. Solo, 38, 730–743, https://doi.org/10.1590/S0100-06832014000300005, 2014.
Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., and Moorcroft, P. R.: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2, J. Geophys. Res.-Biogeo., 114, G01002, https://doi.org/10.1029/2008JG000812, 2009.
Mencuccini, M., Manzoni, S., and Christoffersen, B.: Modelling water fluxes in plants: from tissues to biosphere, New Phytol., 222, 1207–1222, https://doi.org/10.1111/nph.15681, 2019.
Meunier, F.: Data for the publication “Low sensitivity of three terrestrial biosphere models to soil texture over the South-American tropics” (v1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.6226622, 2022.
Moeys, J.: The soil texture wizard: R functions for plotting, classifying, transforming and exploring soil texture data, 104,
https://cran.r-project.org/web/packages/soiltexture/vignettes/soiltexture_vignette.pdf (last access: 11 October 2022), 2018.
Montzka, C., Herbst, M., Weihermüller, L., Verhoef, A., and Vereecken, H.: A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves, Earth Syst. Sci. Data, 9, 529–543, https://doi.org/10.5194/essd-9-529-2017, 2017.
Mualem, Y.: A new model for predicting the hydraulic conductivity of unsaturated porous media, Water Resour. Res., 12, 513–522, https://doi.org/10.1029/WR012i003p00513, 1976.
Nachtergaele, F. O., van Velthuizen, H., Verelst, L., Batjes, N. H., Dijkshoorn, J. A., van Engelen, V. W. P., Fischer, G., Jones, A., Montanarella, L., Petri, M., Prieler, S., Teixeira, E., Wilberg, D., and Shi, X.: Harmonized World Soil Database (version 1.0), https://research.wur.nl/en/publications/harmonized-world-soil-database-version-10 (last access: 11 October 2022), 2008.
Negrón Juárez, R. I., Hodnett, M. G., Fu, R., Gouden, M. L., and von Randow, C.: Control of dry season evapotranspiration over the Amazonian forest as inferred from observation at a Southern Amazon forest site, J. Climate, 20, 2827–2839, https://doi.org/10.1175/JCLI4184.1, 2007.
Nepstad, D. C., de Carvalho, C. R., Davidson, E. A., Jipp, P. H., Lefebvre, P. A., Negreiros, G. H., da Silva, E. D., Stone, T. A., Trumbore, S. E., and Vieira, S.: The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures, Nature, 372, 666–669, https://doi.org/10.1038/372666a0, 1994.
Nepstad, D. C., Tohver, I. M., Ray, D., Moutinho, P., and Cardinot, G.: Mortality of Large Trees and Lianas Following Experimental Drought in an Amazon Forest, Ecology, 88, 2259–2269, https://doi.org/10.1890/06-1046.1, 2007.
Oberpriller, J., Herschlein, C., Anthoni, P., Arneth, A., Krause, A., Rammig, A., Lindeskog, M., Olin, S., and Hartig, F.: Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0), Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, 2022.
O'Connell, C. S., Ruan, L., and Silver, W. L.: Drought drives rapid shifts in tropical rainforest soil biogeochemistry and greenhouse gas emissions, Nat. Commun., 9, 1348, https://doi.org/10.1038/s41467-018-03352-3, 2018.
ORCHIDEE in tags/ORCHIDEE_2_0 – ORCHIDEE: http://forge.ipsl.jussieu.fr/orchidee/browser/tags/ORCHIDEE_2_0/ORCHIDEE/, last access: 23 February 2022.
Patil, N. G. and Singh, S. K.: Pedotransfer Functions for Estimating Soil Hydraulic Properties: A Review, Pedosphere, 26, 417–430, https://doi.org/10.1016/S1002-0160(15)60054-6, 2016.
Peylin, P., Ghattas, J., Cadule, P., Cheruy, F., Ducharne, A., Guenet, B., Lathière, J., Luyssaert, S., Maignan, F., Maugis, P., Ottle, C., Polcher, J., Viovy, N., Vuichard, N., Bastrikov, V., Guimberteau, M., Lanso, A.-S., MacBean, N., Mcgrath, M., Tafasca, S., and Wang, F.: The global land surface model ORCHIDEE – Tag2.0, in preparation, 2022.
Phillips, O. L., Aragão, L. E. O. C., Lewis, S. L., Fisher, J. B., Lloyd, J., López-González, G., Malhi, Y., Monteagudo, A., Peacock, J., Quesada, C. A., van der Heijden, G., Almeida, S., Amaral, I., Arroyo, L., Aymard, G., Baker, T. R., Bánki, O., Blanc, L., Bonal, D., Brando, P., Chave, J., de Oliveira, Á. C. A., Cardozo, N. D., Czimczik, C. I., Feldpausch, T. R., Freitas, M. A., Gloor, E., Higuchi, N., Jiménez, E., Lloyd, G., Meir, P., Mendoza, C., Morel, A., Neill, D. A., Nepstad, D., Patiño, S., Peñuela, M. C., Prieto, A., Ramírez, F., Schwarz, M., Silva, J., Silveira, M., Thomas, A. S., ter Steege, H., Stropp, J., Vásquez, R., Zelazowski, P., Dávila, E. A., Andelman, S., Andrade, A., Chao, K.-J., Erwin, T., Di Fiore, A.,
Honorio, C. E., Keeling, H., Killeen, T. J., Laurance, W. F., Cruz, A. P., Pitman, N. C. A., Vargas, P. N., Ramírez-Angulo, H., Rudas, A., Salamão, R., Silva, N., Terborgh, J., and Torres-Lezama, A.: Drought Sensitivity of the Amazon Rainforest, Science, 323, 1344–1347, https://doi.org/10.1126/science.1164033, 2009.
Plante, A. F., Conant, R. T., Stewart, C. E., Paustian, K., and Six, J.: Impact of Soil Texture on the Distribution of Soil Organic Matter in Physical and Chemical Fractions, Soil Sci. Soc. Am. J., 70, 287–296, https://doi.org/10.2136/sssaj2004.0363, 2006.
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, https://doi.org/10.5194/soil-7-217-2021, 2021.
Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R., Bontemps, S., Boettcher, M., Brockmann, C., Defourny, P., Hagemann, S., Herold, M., Kirches, G., Lamarche, C., Lederer, D., Ottlé, C., Peters, M., and Peylin, P.: Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative, Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, 2015.
Prentice, I. C., Cramer, W., Harrison, S. P., Leemans, R., Monserud, R. A., and Solomon, A. M.: A global biome model based on plant physiology and dominance, soil properties and climate, J. Biogeogr., 19, 117–134, 1992.
Prentice, I. C., Dong, N., Gleason, S. M., Maire, V., and Wright, I. J.: Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology, Ecol. Lett., 17, 82–91, https://doi.org/10.1111/ele.12211, 2014.
Qu, W., Bogena, H. R., Huisman, J. A., Vanderborght, J., Schuh, M., Priesack, E., and Vereecken, H.: Predicting subgrid variability of soil water content from basic soil information, Geophys. Res. Lett., 42, 789–796, https://doi.org/10.1002/2014GL062496, 2015.
Richards, L. A.: Capillary conduction of liquids through porous mediums, Physics, 1, 318–333, https://doi.org/10.1063/1.1745010, 1931.
Rowland, L., da Costa, A. C. L., Galbraith, D. R., Oliveira, R. S., Binks, O. J., Oliveira, A. A. R., Pullen, A. M., Doughty, C. E., Metcalfe, D. B., Vasconcelos, S. S., Ferreira, L. V., Malhi, Y., Grace, J., Mencuccini, M., and Meir, P.: Death from drought in tropical forests is triggered by hydraulics not carbon starvation, Nature, 528, 119–122, https://doi.org/10.1038/nature15539, 2015.
Running, S., Mu, Q., and Zhao, M.: MOD17A2H MODIS/Terra Gross Primary Productivity 8-Day L4 Global 500m SIN Grid V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MOD17A2H.006, 2015.
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.
Silver, W. L., Neff, J., McGroddy, M., Veldkamp, E., Keller, M., and Cosme, R.: Effects of Soil Texture on Belowground Carbon and Nutrient Storage in a Lowland Amazonian Forest Ecosystem, Ecosystems, 3, 193–209, https://doi.org/10.1007/s100210000019, 2000.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space, Global Ecol. Biogeogr., 10, 621–637, https://doi.org/10.1046/j.1466-822X.2001.t01-1-00256.x, 2001.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014.
Soil and Survey Manual: https://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/soils/ref/?cid=nrcs142p2_054262 (last access: 22 February 2022), 2002.
SoilGrids web portal: https://soilgrids.org, last access: 11 October 2022.
Spinoni, J., Naumann, G., Carrao, H., Barbosa, P., and Vogt, J.: World drought frequency, duration, and severity for 1951–2010, Int. J. Climatol., 34, 2792–2804, https://doi.org/10.1002/joc.3875, 2014.
Staal, A., Flores, B. M., Aguiar, A. P. D., Bosmans, J. H. C., Fetzer, I., and Tuinenburg, O. A.: Feedback between drought and deforestation in the Amazon, Environ. Res. Lett., 10, 044024, https://doi.org/10.1088/1748-9326/ab738e, 2020.
Tafasca, S., Ducharne, A., and Valentin, C.: Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model, Hydrol. Earth Syst. Sci., 24, 3753–3774, https://doi.org/10.5194/hess-24-3753-2020, 2020.
Telles, E. C. C., de Camargo, P. B., Martinelli, L. A., Trumbore, S. E., da Costa, E. S., Santos, J., Higuchi, N., and Oliveira Jr., R. C.: Influence of soil texture on carbon dynamics and storage potential in tropical forest soils of Amazonia, Global Biogeochem. Cy., 17, 1040, https://doi.org/10.1029/2002GB001953, 2003.
Uribe, M. R., Sierra, C. A., and Dukes, J. S.: Seasonality of Tropical Photosynthesis: A Pantropical Map of Correlations With Precipitation and Radiation and Comparison to Model Outputs, J. Geophys. Res.-Biogeo., 126, e2020JG006123, https://doi.org/10.1029/2020JG006123, 2021.
van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S. I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M. J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D. M., Weedon, G. P., Ellis, R., Hagemann, S., Mao, J., Flanner, M. G., Zampieri, M., Materia, S., Law, R. M., and Sheffield, J.: LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome, Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, 2016.
van Genuchten, M. Th.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Van Looy, K., Bouma, J., Herbst, M., Koestel, J., Minasny, B., Mishra, U., Montzka, C., Nemes, A., Pachepsky, Y. A., Padarian, J., Schaap, M. G., Tóth, B., Verhoef, A., Vanderborght, J., van der Ploeg, M. J., Weihermüller, L., Zacharias, S., Zhang, Y., and Vereecken, H.: Pedotransfer Functions in Earth System Science: Challenges and Perspectives, Rev. Geophys., 55, 1199–1256, https://doi.org/10.1002/2017RG000581, 2017.
Vanderborght, J., Couvreur, V., Meunier, F., Schnepf, A., Vereecken, H., Bouda, M., and Javaux, M.: From hydraulic root architecture models to macroscopic representations of root hydraulics in soil water flow and land surface models, Hydrol. Earth Syst. Sci., 25, 4835–4860, https://doi.org/10.5194/hess-25-4835-2021, 2021.
Veldkamp, E., Schmidt, M., Powers, J. S., and Corre, M. D.: Deforestation and reforestation impacts on soils in the tropics, Nat. Rev. Earth Environ., 1, 590–605, https://doi.org/10.1038/s43017-020-0091-5, 2020.
Verbeeck, H., Peylin, P., Bacour, C., Bonal, D., Steppe, K., and Ciais, P.: Seasonal patterns of CO2 fluxes in Amazon forests: Fusion of eddy covariance data and the ORCHIDEE model, J. Geophys. Res., 116, G02018, https://doi.org/10.1029/2010jg001544, 2011.
Vereecken, H., Pachepsky, Y., Bogena, H., and Montzka, C.: Upscaling Issues in Ecohydrological Observations, in: Observation and Measurement of Ecohydrological Processes, edited by: Li, X. and Vereecken, H., Springer, Berlin, Heidelberg, 435–454, https://doi.org/10.1007/978-3-662-48297-1_14, 2019.
Viovy, N.: CRUNCEP Version 7 – Atmospheric Forcing Data for the Community Land Model, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/PZ8F-F017, 2018.
Walko, R. L., Band, L. E., Baron, J., Kittel, T. G. F., Lammers, R., Lee, T. J., Ojima, D., Pielke, R. A., Taylor, C., Tague, C., Tremback, C. J., and Vidale, P. L.: Coupled Atmosphere–Biophysics–Hydrology Models for Environmental Modeling, J. Appl. Meteorol., 39, 931–944, https://doi.org/10.1175/1520-0450(2000)039<0931:CABHMF>2.0.CO;2, 2000.
Xu, X., Medvigy, D., Powers, J. S., Becknell, J. M., and Guan, K.: Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests, New Phytol., 212, 80–95, https://doi.org/10.1111/nph.14009, 2016.
Yang, H., Ciais, P., Wigneron, J.-P., Chave, J., Cartus, O., Chen, X., Fan, L., Green, J. K., Huang, Y., Joetzjer, E., Kay, H., Makowski, D., Maignan, F., Santoro, M., Tao, S., Liu, L., and Yao, Y.: Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño, P. Natl. Acad. Sci. USA, 119, e2101388119, https://doi.org/10.1073/pnas.2101388119, 2022.
Yao, Y., Joetzjer, E., Ciais, P., Viovy, N., Cresto Aleina, F., Chave, J., Sack, L., Bartlett, M., Meir, P., Fisher, R., and Luyssaert, S.: Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA, r7236) and evaluation at the Caxiuanã drought experiment, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-362, in review, 2021.
Zinn, Y. L., Lal, R., Bigham, J. M., and Resck, D. V. S.: Edaphic Controls on Soil Organic Carbon Retention in the Brazilian Cerrado: Texture and Mineralogy, Soil Sci. Soc. Am. J., 71, 1204–1214, https://doi.org/10.2136/sssaj2006.0014, 2007.
Short summary
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the...