Articles | Volume 26, issue 3
https://doi.org/10.5194/nhess-26-1479-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1479-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Mar 2026
Research article |
| 24 Mar 2026
| 24 Mar 2026
What controls fire size in the South American Gran Chaco? Exploring atmospheric and landscape drivers through Remote Sensing
Rodrigo San Martín
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Invited contribution by Rodrigo San Martín, recipient of the EGU Biogeosciences Outstanding Student and PhD candidate Presentation Award 2023.
Catherine Ottlé
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Anna Sorenssön
Centro de Investigaciones del Mar y la Atmósfera (CIMA), CONICET – Universidad de Buenos Aires, Buenos Aires, Argentina
CNRS, CNRS – IRD – CONICET – UBA, Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires, Argentina
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Pradeebane Vaittinada Ayar
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Florent Mouillot
UMR CEFE, University of Montpellier, CNRS, EPHE, IRD, Montpellier, France
Marielle Malfante
Univ. Grenoble Alpes, CEA, List, Grenoble, France
Related authors
Kandice L. Harper, Céline Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, https://doi.org/10.5194/essd-15-1465-2023, 2023
Short summary
Short summary
We built a spatially explicit annual plant-functional-type (PFT) dataset for 1992–2020 exhibiting intra-class spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs, each split into leaf type and seasonality. Model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new set.
Jean-Baptiste Brenner, Aurélien Quiquet, Didier M. Roche, Didier Paillard, and Pradeebane Vaittinada Ayar
Geosci. Model Dev., 19, 1075–1101, https://doi.org/10.5194/gmd-19-1075-2026, https://doi.org/10.5194/gmd-19-1075-2026, 2026
Short summary
Short summary
Due to the limited spatial and temporal coverage of observations, global models are essential tools to study climate. However, long-term climate data at fine spatial scale are difficult to obtain because of elevated computational costs such algorithms involve. This paper presents a simple model based on the description of climate/topography interactions to generate local precipitation fields at low cost. The objective is to provide a flexible and easy to use method for paleoclimate studies.
Jon Cranko Page, Martin G. De Kauwe, Andy J. Pitman, Isaac R. Towers, Gabriele Arduini, Martin J. Best, Craig R. Ferguson, Jürgen Knauer, Hyungjun Kim, David M. Lawrence, Tomoko Nitta, Keith W. Oleson, Catherine Ottlé, Anna Ukkola, Nicholas Vuichard, Xiaoni Wang-Faivre, and Gab Abramowitz
Biogeosciences, 23, 263–282, https://doi.org/10.5194/bg-23-263-2026, https://doi.org/10.5194/bg-23-263-2026, 2026
Short summary
Short summary
This paper used a large dataset of observations, machine learning predictions, and computer model simulations to test how well land surface models represent the water, energy, and carbon cycles. We found that the models work well under "normal" weather but do not meet performance expectations during coinciding extreme conditions. Since these extremes are relatively rare, targeted model improvements could deliver major performance gains.
Pradeebane Vaittinada Ayar, Stella Bourdin, Davide Faranda, and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 25, 4655–4672, https://doi.org/10.5194/nhess-25-4655-2025, https://doi.org/10.5194/nhess-25-4655-2025, 2025
Short summary
Short summary
Tracking tropical cyclones (TCs) remains a matter of interest for investigating observed and simulated tropical cyclones. In this study, Random Forest (RF), a machine learning approach, is considered to track TCs. RF associates the TC occurrence or absence with different atmospheric configurations. Compared to trackers found in the literature, it shows similar performance for tracking TCs, better control over false alarms, more flexibility, and reveals key variables for TCs' detection.
Paul C. Astagneau, Raul R. Wood, Mathieu Vrac, Sven Kotlarski, Pradeebane Vaittinada Ayar, Bastien François, and Manuela I. Brunner
Hydrol. Earth Syst. Sci., 29, 5695–5718, https://doi.org/10.5194/hess-29-5695-2025, https://doi.org/10.5194/hess-29-5695-2025, 2025
Short summary
Short summary
To study floods and droughts that are likely to change in the future, we use climate projections from climate models. However, we first need to adjust the systematic biases of these projections at the catchment scale before using them in hydrological models. Our study compares statistical methods that can adjust these biases but specifically for climate projections that enable a quantification of internal climate variability. We provide recommendations on the most appropriate methods.
Eric Pohl, Christophe Grenier, Antoine Séjourné, Frédéric Bouchard, Emmanuel Léger, Albane Saintenoy, Pavel Konstantinov, Amélie Cuynet, Catherine Ottlé, Christine Hatté, Aurélie Noret, Kensheri Danilov, Kirill Bazhin, Ivan Khristoforov, Daniel Fortier, Alexander Fedorov, and Emmanuel Mouche
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-134, https://doi.org/10.5194/essd-2025-134, 2025
Preprint under review for ESSD
Short summary
Short summary
Permafrost is widespread in the Northern Hemisphere and is thawing due to climate warming, impacting energy and mass transfers. Small streams emerge alongside lakes when ice in the ground melts away, potentially accelerating thawing and biogeochemical activity in a positive feedback cycle. This study provides a comprehensive dataset on these little-studied streams, including thermally and hydrologically important variables essential for improving numerical models.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
Short summary
Short summary
To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Zacharie Titus, Amélie Cuynet, Elodie Salmon, and Catherine Ottlé
The Cryosphere, 19, 2105–2114, https://doi.org/10.5194/tc-19-2105-2025, https://doi.org/10.5194/tc-19-2105-2025, 2025
Short summary
Short summary
The representation of lake ice dynamics is key to model water–atmosphere energy and mass transfers in cold environments. The use of albedo satellite products to constrain the modeling of ice coverage appears to be very suitable and valuable. In this work, we show how the modeling of lake albedo and ice phenology in the land surface model ORCHIDEE was improved by accounting for fractional ice cover calibrated against lake surface albedo data.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
Short summary
Short summary
We propose a set of six plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Luis-Enrique Olivera-Guerra, Catherine Ottlé, Nina Raoult, and Philippe Peylin
Hydrol. Earth Syst. Sci., 29, 261–290, https://doi.org/10.5194/hess-29-261-2025, https://doi.org/10.5194/hess-29-261-2025, 2025
Short summary
Short summary
We assimilate the recent ESA-CCI land surface temperature (LST) product to optimize parameters of a land surface model (ORCHIDEE). We test different assimilation strategies to evaluate the best strategy over various in situ stations across Europe. We also provide advice on how to assimilate this LST product to better simulate LST and surface energy fluxes. Finally, we demonstrate the effectiveness of this optimization, which is essential to better simulate future projections.
Lilian Vallet, Charbel Abdallah, Thomas Lauvaux, Lilian Joly, Michel Ramonet, Philippe Ciais, Morgan Lopez, Irène Xueref-Remy, and Florent Mouillot
Biogeosciences, 22, 213–242, https://doi.org/10.5194/bg-22-213-2025, https://doi.org/10.5194/bg-22-213-2025, 2025
Short summary
Short summary
The 2022 fire season had a huge impact on European temperate forest, with several large fires exhibiting prolonged soil combustion reported. We analyzed CO and CO2 concentration recorded at nearby atmospheric towers, revealing intense smoldering combustion. We refined a fire emission model to incorporate this process. We estimated 7.95 Mteq CO2 fire emission, twice the global estimate. Fires contributed to 1.97 % of France's annual carbon footprint, reducing forest carbon sink by 30 % this year.
Arsène Druel, Julien Ruffault, Hendrik Davi, André Chanzy, Olivier Marloie, Miquel De Cáceres, Albert Olioso, Florent Mouillot, Christophe François, Kamel Soudani, and Nicolas K. Martin-StPaul
Biogeosciences, 22, 1–18, https://doi.org/10.5194/bg-22-1-2025, https://doi.org/10.5194/bg-22-1-2025, 2025
Short summary
Short summary
Accurate radiation data are essential for understanding ecosystem functions and dynamics. Traditional large-scale data lack the precision needed for complex terrain. This study introduces a new model, which accounts for sub-daily direct and diffuse radiation effects caused by terrain features, to enhance the radiation data resolution using elevation maps. Tested on a mountainous area, this method significantly improved radiation estimates, benefiting predictions of forest functions.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
Short summary
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
Short summary
Short summary
The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
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.
Mickaël Lalande, Martin Ménégoz, Gerhard Krinner, Catherine Ottlé, and Frédérique Cheruy
The Cryosphere, 17, 5095–5130, https://doi.org/10.5194/tc-17-5095-2023, https://doi.org/10.5194/tc-17-5095-2023, 2023
Short summary
Short summary
This study investigates the impact of topography on snow cover parameterizations using models and observations. Parameterizations without topography-based considerations overestimate snow cover. Incorporating topography reduces snow overestimation by 5–10 % in mountains, in turn reducing cold biases. However, some biases remain, requiring further calibration and more data. Assessing snow cover parameterizations is challenging due to limited and uncertain data in mountainous regions.
Martin Schwartz, Philippe Ciais, Aurélien De Truchis, Jérôme Chave, Catherine Ottlé, Cedric Vega, Jean-Pierre Wigneron, Manuel Nicolas, Sami Jouaber, Siyu Liu, Martin Brandt, and Ibrahim Fayad
Earth Syst. Sci. Data, 15, 4927–4945, https://doi.org/10.5194/essd-15-4927-2023, https://doi.org/10.5194/essd-15-4927-2023, 2023
Short summary
Short summary
As forests play a key role in climate-related issues, their accurate monitoring is critical to reduce global carbon emissions effectively. Based on open-access remote-sensing sensors, and artificial intelligence methods, we created high-resolution tree height, wood volume, and biomass maps of metropolitan France that outperform previous products. This study, based on freely available data, provides essential information to support climate-efficient forest management policies at a low cost.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782, https://doi.org/10.5194/gmd-16-5755-2023, https://doi.org/10.5194/gmd-16-5755-2023, 2023
Short summary
Short summary
The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
Short summary
Short summary
This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
Nina Raoult, Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, and Vladislav Bastrikov
The Cryosphere, 17, 2705–2724, https://doi.org/10.5194/tc-17-2705-2023, https://doi.org/10.5194/tc-17-2705-2023, 2023
Short summary
Short summary
Greenland ice sheet melting due to global warming could significantly impact global sea-level rise. The ice sheet's albedo, i.e. how reflective the surface is, affects the melting speed. The ORCHIDEE computer model is used to simulate albedo and snowmelt to make predictions. However, the albedo in ORCHIDEE is lower than that observed using satellites. To correct this, we change model parameters (e.g. the rate of snow decay) to reduce the difference between simulated and observed values.
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottlé, and Jérôme Servonnat
Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023, https://doi.org/10.5194/gmd-16-2583-2023, 2023
Short summary
Short summary
The proposed graphs of hydrological sub-grid elements for atmospheric models allow us to integrate the topographical elements needed in land surface models for a realistic representation of horizontal water and energy transport. The study demonstrates the numerical properties of the automatically built graphs and the simulated water flows.
Kandice L. Harper, Céline Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, https://doi.org/10.5194/essd-15-1465-2023, 2023
Short summary
Short summary
We built a spatially explicit annual plant-functional-type (PFT) dataset for 1992–2020 exhibiting intra-class spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs, each split into leaf type and seasonality. Model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new set.
Phillip Papastefanou, Christian S. Zang, Zlatan Angelov, Aline Anderson de Castro, Juan Carlos Jimenez, Luiz Felipe Campos De Rezende, Romina C. Ruscica, Boris Sakschewski, Anna A. Sörensson, Kirsten Thonicke, Carolina Vera, Nicolas Viovy, Celso Von Randow, and Anja Rammig
Biogeosciences, 19, 3843–3861, https://doi.org/10.5194/bg-19-3843-2022, https://doi.org/10.5194/bg-19-3843-2022, 2022
Short summary
Short summary
The Amazon rainforest has been hit by multiple severe drought events. In this study, we assess the severity and spatial extent of the extreme drought years 2005, 2010 and 2015/16 in the Amazon. Using nine different precipitation datasets and three drought indicators we find large differences in drought stress across the Amazon region. We conclude that future studies should use multiple rainfall datasets and drought indicators when estimating the impact of drought stress in the Amazon region.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
Short summary
Short summary
The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Anthony Bernus and Catherine Ottlé
Geosci. Model Dev., 15, 4275–4295, https://doi.org/10.5194/gmd-15-4275-2022, https://doi.org/10.5194/gmd-15-4275-2022, 2022
Short summary
Short summary
The lake model FLake was coupled to the ORCHIDEE land surface model to simulate lake energy balance at global scale with a multi-tile approach. Several simulations were performed with various atmospheric reanalyses and different lake depth parameterizations. The simulated lake surface temperature showed good agreement with observations (RMSEs of the order of 3 °C). We showed the large impact of the atmospheric forcing on lake temperature. We highlighted systematic errors on ice cover phenology.
Boris Sakschewski, Werner von Bloh, Markus Drüke, Anna Amelia Sörensson, Romina Ruscica, Fanny Langerwisch, Maik Billing, Sarah Bereswill, Marina Hirota, Rafael Silva Oliveira, Jens Heinke, and Kirsten Thonicke
Biogeosciences, 18, 4091–4116, https://doi.org/10.5194/bg-18-4091-2021, https://doi.org/10.5194/bg-18-4091-2021, 2021
Short summary
Short summary
This study shows how local adaptations of tree roots across tropical and sub-tropical South America explain patterns of biome distribution, productivity and evapotranspiration on this continent. By allowing for high diversity of tree rooting strategies in a dynamic global vegetation model (DGVM), we are able to mechanistically explain patterns of mean rooting depth and the effects on ecosystem functions. The approach can advance DGVMs and Earth system models.
Wei Min Hao, Matthew C. Reeves, L. Scott Baggett, Yves Balkanski, Philippe Ciais, Bryce L. Nordgren, Alexander Petkov, Rachel E. Corley, Florent Mouillot, Shawn P. Urbanski, and Chao Yue
Biogeosciences, 18, 2559–2572, https://doi.org/10.5194/bg-18-2559-2021, https://doi.org/10.5194/bg-18-2559-2021, 2021
Short summary
Short summary
We examined the trends in the spatial and temporal distribution of the area burned in northern Eurasia from 2002 to 2016. The annual area burned in this region declined by 53 % during the 15-year period under analysis. Grassland fires in Kazakhstan dominated the fire activity, comprising 47 % of the area burned but accounting for 84 % of the decline. A wetter climate and the increase in grazing livestock in Kazakhstan are the major factors contributing to the decline in the area burned.
Cited articles
Adámoli, J., Sennhauser, E., Acero, J. M., and Rescia, A.: Stress and Disturbance: Vegetation Dynamics in the Dry Chaco Region of Argentina, J. Biogeogr., 17, 491–500, https://doi.org/10.2307/2845381, 1990.
Alencar, A. A., Brando, P. M., Asner, G. P., and Putz, F. E.: Landscape fragmentation, severe drought, and the new Amazon forest fire regime, Ecol. Appl., 25, 1493–1505, https://doi.org/10.1890/14-1528.1, 2015.
Alessio, G. A., Peñuelas, J., Llusià, J., Ogaya, R., Estiarte, M., and De Lillis, M.: Influence of water and terpenes on flammability in some dominant Mediterranean species, Int. J. Wildland Fire, 17, 274–286, https://doi.org/10.1071/WF07038, 2008.
Alinari, J., von Muller, A., and Renison, D.: The contribution of fire damage to restricting high mountain Polylepis australis forests to ravines: Insights from an un-replicated comparison, Ecología Austral., 25, 11–18, https://doi.org/10.25260/EA.15.25.1.0.53, 2015.
Andela, N. and van der Werf, G. R.: Recent trends in African fires driven by cropland expansion and El Niño to La Niña transition, Nat. Clim. Change, 4, 791–795, https://doi.org/10.1038/nclimate2313, 2014.
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., and Randerson, J. T.: A human-driven decline in global burned area, Science, 356, 1356–1362, https://doi.org/10.1126/science.aal4108, 2017.
Andela, N., Morton, D. C., Giglio, L., Paugam, R., Chen, Y., Hantson, S., van der Werf, G. R., and Randerson, J. T.: The Global Fire Atlas of individual fire size, duration, speed and direction, Earth Syst. Sci. Data, 11, 529–552, https://doi.org/10.5194/essd-11-529-2019, 2019.
Archibald, S., Roy, D. P., Van WILGEN, B. W., and Scholes, R. J.: What limits fire? An examination of drivers of burnt area in Southern Africa, Glob. Change Biol., 15, 613–630, https://doi.org/10.1111/j.1365-2486.2008.01754.x, 2009.
Archibald, S., Lehmann, C. E. R., Gómez-Dans, J. L., and Bradstock, R. A.: Defining pyromes and global syndromes of fire regimes, P. Natl. Acad. Sci. USA, 110, 6442–6447, https://doi.org/10.1073/pnas.1211466110, 2013.
Archibald, S., Lehmann, C. E. R., Belcher, C. M., Bond, W. J., Bradstock, R. A., Daniau, A.-L., Dexter, K. G., Forrestel, E. J., Greve, M., He, T., Higgins, S. I., Hoffmann, W. A., Lamont, B. B., McGlinn, D. J., Moncrieff, G. R., Osborne, C. P., Pausas, J. G., Price, O., Ripley, B. S., Rogers, B. M., Schwilk, D. W., Simon, M. F., Turetsky, M. R., Van der Werf, G. R., and Zanne, A. E.: Biological and geophysical feedbacks with fire in the Earth system, Environ. Res. Lett., 13, 033003, https://doi.org/10.1088/1748-9326/aa9ead, 2018.
Arenas, P.: ARENAS, Pastor, Etnografía y alimentación entre los toba-ñachilamole#ek y wichí-lhuku'tas del Chaco Central (Argentina), Buenos Aires, Edición del autor, 562 p., ISBN 987-43-6483-1, 2003.
Argañaraz, Pizarro, G. G., Zak, M., Landi, M. A., and Bellis, L. M.: Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina, Sci. Total Environ., 520, 1–12, https://doi.org/10.1016/j.scitotenv.2015.02.081, 2015.
Argañaraz, Landi, M. A., Bravo, S. J., Gavier-Pizarro, G. I., Scavuzzo, C. M., and Bellis, L. M.: Estimation of Live Fuel Moisture Content From MODIS Images for Fire Danger Assessment in Southern Gran Chaco, IEEE J. Sel. Top. Appl. Earth Obs., 9, 5339–5349, https://doi.org/10.1109/JSTARS.2016.2575366, 2016.
Argañaraz, Landi, M. A., Scavuzzo, C. M., and Bellis, L. M.: Determining fuel moisture thresholds to assess wildfire hazard: A contribution to an operational early warning system, PLoS ONE, 13, e0204889, https://doi.org/10.1371/journal.pone.0204889, 2018.
Arias, P. A., Rivera, J. A., Sörensson, A. A., Zachariah, M., Barnes, C., Philip, S., Kew, S., Vautard, R., Koren, G., Pinto, I., Vahlberg, M., Singh, R., Raju, E., Li, S., Yang, W., Vecchi, G. A., and Otto, F. E. L.: Interplay between climate change and climate variability: the 2022 drought in Central South America, Climatic Change, 177, https://doi.org/10.1007/s10584-023-03664-4, 2024.
Barros, A. M. G. and Pereira, J. M. C.: Wildfire Selectivity for Land Cover Type: Does Size Matter?, PLOS ONE, 9, e84760, https://doi.org/10.1371/journal.pone.0084760, 2014.
Barros, V., Clarke, R., and Silva Dias, P.: Climate Change in the La Plata Basin, Inter-American Institute for Global Change Research (IAI), São José dos Campos, Brazil, http://www-atmo.at.fcen.uba.ar/cordex/Barrosetal2006ChapterII.pdf (last access: 10 March 2026), 2006.
Baumann, M., Levers, C., Macchi, L., Bluhm, H., Waske, B., Gasparri, N. I., and Kuemmerle, T.: Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data, Remote Sens. Environ., 216, 201–211, https://doi.org/10.1016/j.rse.2018.06.044, 2018.
Baumann, M., Gasparri, I., Buchadas, A., Oeser, J., Meyfroidt, P., Levers, C., Romero-Muñoz, A., le Polain de Waroux, Y., Müller, D., and Kuemmerle, T.: Frontier metrics for a process-based understanding of deforestation dynamics, Environ. Res. Lett., 17, 095010, https://doi.org/10.1088/1748-9326/ac8b9a, 2022.
Belhadj-Khedher, C., El-Melki, T., and Mouillot, F.: Saharan Hot and Dry Sirocco Winds Drive Extreme Fire Events in Mediterranean Tunisia (North Africa), Atmosphere, 11, 590, https://doi.org/10.3390/atmos11060590, 2020.
Bernardi, R. E., Staal, A., Xu, C., Scheffer, M., and Holmgren, M.: Livestock Herbivory Shapes Fire Regimes and Vegetation Structure Across the Global Tropics, Ecosystems, 22, 1457–1465, https://doi.org/10.1007/s10021-019-00349-x, 2019.
Bianchi, L., Defossé, G., Dentoni, M., Kunst, C., Ledesma, R., and Bravo, S.: Dynamics of fuel moisture and its relation to the ecology and management of fire in the western Chaco region (Argentina) I: basic concepts, IA – Revista de Investigaciones Agropecuarias, 40, 154–164, 2014.
Bistinas, I., Harrison, S. P., Prentice, I. C., and Pereira, J. M. C.: Causal relationships versus emergent patterns in the global controls of fire frequency, Biogeosciences, 11, 5087–5101, https://doi.org/10.5194/bg-11-5087-2014, 2014.
Boletta, P. E., Ravelo, A. C., Planchuelo, A. M., and Grilli, M.: Assessing deforestation in the Argentine Chaco, Forest Ecol. Manag., 228, 108–114, https://doi.org/10.1016/j.foreco.2006.02.045, 2006.
Bowman, Balch, J., Artaxo, P., Bond, W. J., Cochrane, M. A., D'Antonio, C. M., DeFries, R., Johnston, F. H., Keeley, J. E., Krawchuk, M. A., Kull, C. A., Mack, M., Moritz, M. A., Pyne, S., Roos, C. I., Scott, A. C., Sodhi, N. S., and Swetnam, T. W.: The human dimension of fire regimes on Earth: The human dimension of fire regimes on Earth, J. Biogeogr., 38, 2223–2236, https://doi.org/10.1111/j.1365-2699.2011.02595.x, 2011.
Bowman, D. M. J. S., Balch, J. K., Artaxo, P., Bond, W. J., Carlson, J. M., Cochrane, M. A., D'Antonio, C. M., DeFries, R. S., Doyle, J. C., Harrison, S. P., Johnston, F. H., Keeley, J. E., Krawchuk, M. A., Kull, C. A., Marston, J. B., Moritz, M. A., Prentice, I. C., Roos, C. I., Scott, A. C., Swetnam, T. W., van der Werf, G. R., and Pyne, S. J.: Fire in the Earth System, Science, 324, 481–484, https://doi.org/10.1126/science.1163886, 2009.
Bowring, S. P. K., Li, W., Mouillot, F., Rosan, T. M., and Ciais, P.: Road fragment edges enhance wildfire incidence and intensity, while suppressing global burned area, Nat. Commun., 15, 9176, https://doi.org/10.1038/s41467-024-53460-6, 2024.
Bravo, S., Kunst, C., Grau, R., and Aráoz, E.: Fire–rainfall relationships in Argentine Chaco savannas, J. Arid Environ., 74, 1319–1323, https://doi.org/10.1016/j.jaridenv.2010.04.010, 2010.
Bravo, S., Kunst, C., Leiva, M., and Ledesma, R.: Response of hardwood tree regeneration to surface fires, western Chaco region, Argentina, Forest Ecol. Manag., 326, 36–45, https://doi.org/10.1016/j.foreco.2014.04.009, 2014.
Bravo, S., Bogino, S., Leiva, M., Lepiscopo, M., Cendoya, M., Kunst, C., and Biurrun, F.: Wood anatomy, fire wounds and dendrochronological potential of Prosopis pugionata Burkart (Fabaceae) in arid Argentine Chaco, IAWA J., 42, 1–10, https://doi.org/10.1163/22941932-bja10056, 2021.
Bravo, S., Ledesma, R., Coria, D., and Loto, D.: Fire in the Chaco Region: Ecological Aspects and Land Management, in: Fire in the South American Ecosystems, edited by: Fidelis, A. and Pivello, V. R., Springer Nature Switzerland, Cham, 213–241, https://doi.org/10.1007/978-3-031-89372-8_8, 2025.
Bucher, E. H.: Chaco and Caatinga – South American Arid Savannas, Woodlands and Thickets, in: Ecology of Tropical Savannas, vol. 42, edited by: Huntley, B. J. and Walker, B. H., Springer Berlin Heidelberg, Berlin, Heidelberg, 48–79, https://doi.org/10.1007/978-3-642-68786-0_4, 1982.
Bucher, E. H. and Huszar, P. C.: Sustainable management of the Gran Chaco of South America: Ecological promise and economic constraints, J. Environ. Manage., 57, 99–108, https://doi.org/10.1006/jema.1999.0290, 1999.
Cabrera, A.: Regiones fitogeo-gráficas argentina, Enciclopedia Argentina de Agricultura y Jardinería, 2, https://www.sidalc.net/search/Record/KOHA-OAI-FCF:2863/Description (last access: 10 March 2026), 1976.
Castilla, M.: “ Ahora tenemos este virus, pero cuando tenés tantos problemas en la zona nada alcanza”: Extractivismo, segregación y pandemia en la provincia del Chaco, Quid 16 – Revista del Área de Estudios Urbanos, 16, 8–38, https://dialnet.unirioja.es/servlet/articulo?codigo=8239107 (last access: 10 March 2026), 2021.
Center For International Earth Science Information Network (CIESIN) Columbia University: Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11, Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC) [data set], https://doi.org/10.7927/H49C6VHW, 2017.
Chuvieco, E., Aguado, I., Salas, J., García, M., Yebra, M., and Oliva, P.: Satellite Remote Sensing Contributions to Wildland Fire Science and Management, Curr. Forestry Rep., 6, 81–96, https://doi.org/10.1007/s40725-020-00116-5, 2020.
Chuvieco, E., Roteta, E., Sali, M., Stroppiana, D., Boettcher, M., Kirches, G., Storm, T., Khairoun, A., Pettinari, M. L., Franquesa, M., and Albergel, C.: Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images, Sci. Total Environ., 845, 157139, https://doi.org/10.1016/j.scitotenv.2022.157139, 2022.
Cingolani, A. M., Vaieretti, M. V., Giorgis, M. A., La Torre, N., Whitworth-Hulse, J. I., and Renison, D.: Can livestock and fires convert the sub-tropical mountain rangelands of central Argentina into a rocky desert?, Rangel J., 35, 285–297, https://doi.org/10.1071/RJ12095, 2013.
Coria, R. D., Kunst, C. R., and Bravo, S. J.: A contribution to the understanding of the woody encroachment in grasslands/savannas from the South American Semiarid Chaco, Ecol. Austral., 31, 595–607, https://doi.org/10.25260/EA.21.31.3.0.1615, 2021.
Copernicus Climate Change Service, Climate Data Store: Land cover classification gridded maps from 1992 to present derived from satellite observation, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.006f2c9a, 2019.
Coronel, G., Pastén, M., Breuer, N., Celeste, A., Rejalaga, L., Domecq, F. M., and Nagy, G. J.: Wildfires in Paraguay: Environmental and Human Impacts, in: Sustainability in Natural Resources Management and Land Planning, edited by: Leal Filho, W., Azeiteiro, U. M., and Setti, A. F. F., Springer International Publishing, Cham, 429–444, https://link.springer.com/chapter/10.1007/978-3-030-76624-5_25 (last access: 13 March 2026), 2021.
D'Antonio, C. M. and Vitousek, P. M.: Biological Invasions by Exotic Grasses, the Grass/Fire Cycle, and Global Change, Annu. Rev. Ecol. Syst., 23, 63–87, 1992.
De Marzo, T., Pflugmacher, D., Baumann, M., Lambin, E. F., Gasparri, I., and Kuemmerle, T.: Characterizing forest disturbances across the Argentine Dry Chaco based on Landsat time series, Int. J. Appl. Earth Obs., 98, 102310, https://doi.org/10.1016/j.jag.2021.102310, 2021.
De Marzo, T., Gasparri, N. I., Lambin, E. F., and Kuemmerle, T.: Agents of Forest Disturbance in the Argentine Dry Chaco, Remote Sens., 14, 1758, https://doi.org/10.3390/rs14071758, 2022.
De Marzo, T., Pratzer, M., Baumann, M., Gasparri, N. I., Pötzschner, F., and Kuemmerle, T.: Linking disturbance history to current forest structure to assess the impact of disturbances in tropical dry forests, Forest Ecol. Manag., 539, 120989, https://doi.org/10.1016/j.foreco.2023.120989, 2023.
Defourny, P., Lamarche, C., Brockmann, C., Boettcher, M., Bontemps, S., Maet, T., Duveiller, G., Kirches, G., Moreau, I., Peylin, P., Ottlé, C., Ramoino, F., Bogaert, E., Albergel, C., and Arino, O.: Observed annual global land-use change from 1992 to 2020 three times more dynamic than reported by inventory-based statistics, in preparation, 2023.
Devisscher, T., Boyd, E., and Malhi, Y.: Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia, Ecol. Soc., 21, https://doi.org/10.5751/ES-08599-210418, 2016.
Devisscher, T., Malhi, Y., and Boyd, E.: Deliberation for wildfire risk management: Addressing conflicting views in the Chiquitania, Bolivia, Geogr. J., 185, 38–54, https://doi.org/10.1111/geoj.12261, 2019.
Doblas-Reyes, F. J., Sörensson, A. A., Almazroui, M., Dosio, A., Gutowski, W. J., Haarsma, R., Hamdi, R., Hewitson, B., Kwon, W.-T., Lamptey, B. L., Maraun, D., Stephenson, T. S., Takayabu, I., Terray, L., Turner, A., and Zuo, Z.: Linking global to regional climate change, in: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1363–1512, https://doi.org/10.1017/9781009157896.012, 2021.
Druel, A., Ruffault, J., Davi, H., Chanzy, A., Marloie, O., De Cáceres, M., Olioso, A., Mouillot, F., François, C., Soudani, K., and Martin-StPaul, N. K.: Enhancing environmental models with a new downscaling method for global radiation in complex terrain, Biogeosciences, 22, 1–18, https://doi.org/10.5194/bg-22-1-2025, 2025.
Dujardin, J. and Lehning, M.: Wind-Topo: Downscaling near-surface wind fields to high-resolution topography in highly complex terrain with deep learning, Q. J. Roy. Meteor. Soc., 148, 1368–1388, https://doi.org/10.1002/qj.4265, 2022.
Eklund, J., Jones, J. P. G., Räsänen, M., Geldmann, J., Jokinen, A.-P., Pellegrini, A., Rakotobe, D., Rakotonarivo, O. S., Toivonen, T., and Balmford, A.: Elevated fires during COVID-19 lockdown and the vulnerability of protected areas, Nat. Sustain., 5, 603–609, https://doi.org/10.1038/s41893-022-00884-x, 2022.
Feron, S., Cordero, R. R., Damiani, A., MacDonell, S., Pizarro, J., Goubanova, K., Valenzuela, R., Wang, C., Rester, L., and Beaulieu, A.: South America is becoming warmer, drier, and more flammable, Commun. Earth Environ., 5, https://doi.org/10.1038/s43247-024-01654-7, 2024.
Fischer, M. A., Di Bella, C. M., and Jobbágy, E. G.: Fire patterns in central semiarid Argentina, J. Arid Environ., 78, 161–168, https://doi.org/10.1016/j.jaridenv.2011.11.009, 2012.
Garcia, L. C., Szabo, J. K., de Oliveira Roque, F., de Matos Martins Pereira, A., Nunes da Cunha, C., Damasceno-Júnior, G. A., Morato, R. G., Tomas, W. M., Libonati, R., and Ribeiro, D. B.: Record-breaking wildfires in the world's largest continuous tropical wetland: Integrative fire management is urgently needed for both biodiversity and humans, J. Environ. Manage., 293, 112870, https://doi.org/10.1016/j.jenvman.2021.112870, 2021.
García, M., Pettinari, M. L., Chuvieco, E., Salas, J., Mouillot, F., Chen, W., and Aguado, I.: Characterizing Global Fire Regimes from Satellite-Derived Products, Forests, 13, 699, https://doi.org/10.3390/f13050699, 2022.
Gasparri, N. I. and Baldi, G.: Regional patterns and controls of biomass in semiarid woodlands: lessons from the Northern Argentina Dry Chaco, Reg. Environ. Change, 13, 1131–1144, https://doi.org/10.1007/s10113-013-0422-x, 2013.
Gasparri, N. I., Grau, H. R., and Manghi, E.: Carbon Pools and Emissions from Deforestation in Extra-Tropical Forests of Northern Argentina Between 1900 and 2005, Ecosystems, 11, 1247–1261, https://doi.org/10.1007/s10021-008-9190-8, 2008.
Ginzburg, R., Adámoli, J., Herrera, P., and Torrella, S.: Los Humedales del Chaco: clasificación, inventario y mapeo a escala regional, Miscelánea, 14, 121–138, 2005.
Giorgis, M. A., Zeballos, S. R., Carbone, L., Zimmermann, H., von Wehrden, H., Aguilar, R., Ferreras, A. E., Tecco, P. A., Kowaljow, E., Barri, F., Gurvich, D. E., Villagra, P., and Jaureguiberry, P.: A review of fire effects across South American ecosystems: the role of climate and time since fire, Fire Ecol., 17, https://doi.org/10.1186/s42408-021-00100-9, 2021.
Gürtler, R. E.: Sustainability of vector control strategies in the Gran Chaco Region: current challenges and possible approaches, Memórias do Instituto Oswaldo Cruz, 104, 52–59, 2009.
Haas, O., Prentice, I. C., and Harrison, S. P.: Global environmental controls on wildfire burnt area, size, and intensity, Environ. Res. Lett., 17, 065004, https://doi.org/10.1088/1748-9326/ac6a69, 2022.
Hantson, S., Pueyo, S., and Chuvieco, E.: Global fire size distribution is driven by human impact and climate, Global Ecol. Biogeogr., 24, 77–86, https://doi.org/10.1111/geb.12246, 2015.
Hantson, S., Scheffer, M., Pueyo, S., Xu, C., Lasslop, G., Nes, E. H., and Mendelsohn, J.: Rare, Intense, Big fires dominate the global tropics under drier conditions, Sci. Rep., 7, 1–5, 2017.
Harper, K. L., Lamarche, C., Hartley, A., Peylin, P., Ottlé, C., Bastrikov, V., San Martín, R., Bohnenstengel, S. I., Kirches, G., Boettcher, M., Shevchuk, R., Brockmann, C., and Defourny, P.: A 29-year time series of annual 300 m resolution plant-functional-type maps for climate models, Earth Syst. Sci. Data, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, 2023.
Hernandez, C., Drobinski, P., and Turquety, S.: How much does weather control fire size and intensity in the Mediterranean region?, Ann. Geophys., 33, 931–939, https://doi.org/10.5194/angeo-33-931-2015, 2015.
Hernández, V., Florencia Fossa Riglos, M., and Vera, C.: Addressing climate services in SouthAmerican Chaco region through a knowledge coproduction process, Global Environ. Chang., 72, 102443, https://doi.org/10.1016/j.gloenvcha.2021.102443, 2022.
Higuera, P. E., Abatzoglou, J. T., Littell, J. S., and Morgan, P.: The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902–2008, PLOS ONE, 10, e0127563, https://doi.org/10.1371/journal.pone.0127563, 2015.
Horn, B. K. P.: Hill shading and the reflectance map, P. IEEE, 69, 14–47, https://doi.org/10.1109/PROC.1981.11918, 1981.
Hsu, A., Jones, M. W., Thurgood, J. R., Smith, A. J. P., Carmenta, R., Abatzoglou, J. T., Anderson, L. O., Clarke, H., Doerr, S. H., Fernandes, P. M., Kolden, C. A., Santín, C., Strydom, T., Le Quéré, C., Ascoli, D., Castellnou, M., Goldammer, J. G., Guiomar, N. R. G. N., Kukavskaya, E. A., Rigolot, E., Tanpipat, V., Varner, M., Yamashita, Y., Baard, J., Barreto, R., Becerra, J., Brunn, E., Bergius, N., Carlsson, J., Cheney, C., Druce, D., Elliot, A., Evans, J., De Moraes Falleiro, R., Prat-Guitart, N., Hiers, J. K., Kaiser, J. W., Macher, L., Morris, D., Park, J., Robles, C., Román-Cuesta, R. M., Rücker, G., Senra, F., Steil, L., Valverde, J. A. L., and Zerr, E.: A global assemblage of regional prescribed burn records – GlobalRx, Sci. Data, 12, 1083, https://doi.org/10.1038/s41597-025-04941-w, 2025.
Jones, Abatzoglou, J. T., Veraverbeke, S., Andela, N., Lasslop, G., and Forkel, M.: Global and regional trends and drivers of fire under climate change, Rev. Geophys., 60, e2020RG000726, https://doi.org/10.1029/2020RG000726, 2022.
Junk, W. J. and Nunes da Cunha, C.: Pasture clearing from invasive woody plants in the Pantanal: a tool for sustainable management or environmental destruction?, Wetl. Ecol. Manag., 20, 111–122, https://doi.org/10.1007/s11273-011-9246-y, 2012.
Kelley, D. I., Bistinas, I., Whitley, R., Burton, C., Marthews, T. R., and Dong, N.: How contemporary bioclimatic and human controls change global fire regimes, Nat. Clim. Change, 9, 690–696, https://doi.org/10.1038/s41558-019-0540-7, 2019.
Krawchuk, M. A. and Moritz, M. A.: Constraints on global fire activity vary across a resource gradient, Ecology, 92, 121–132, https://doi.org/10.1890/09-1843.1, 2011.
Kumar, S., Getirana, A., Libonati, R., Hain, C., Mahanama, S., and Andela, N.: Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes, Sci. Rep., 12, 964, https://doi.org/10.1038/s41598-022-05130-0, 2022.
Kunst, C. and Bravo, S.: Ecología y régimen de fuego en la región chaqueña argentina, in: Fuego en los ecosistemas argentinos, edited by: Kunst, C., Bravo, S., and Panigatti, J. L., Ediciones INTA, Buenos Aires, 109–118, 2003.
Kunst, C., Bravo, S., Monti, E., Cornacchione, M., and Godoy, J.: El fuego y el manejo de pasturas naturales y cultivadas de la región chaqueña, Fuego en los Ecosistemas Argentinos, Ediciones INTA, 21, 239–247, 2003.
Kunst, C., Navall, M., Ledesma, R., Silberman, J., Anríquez, A., Coria, D., Bravo, S., Gómez, A., Albanesi, A., Grasso, D., Nuñez, J. A. D., González, A., Tomsic, P., and Godoy, J.: Silvopastoral Systems in the Western Chaco Region, Argentina, in: Silvopastoral Systems in Southern South America, edited by: Peri, P. L., Dube, F., and Varella, A., Springer International Publishing, Cham, 63–87, https://doi.org/10.1007/978-3-319-24109-8_4, 2016.
Kusch, E. and Davy, R.: KrigR – A tool for downloading and statistically downscaling climate reanalysis data, Environ. Res. Lett., 17, https://doi.org/10.1088/1748-9326/ac48b3, 2022.
Laurent, P., Mouillot, F., Yue, C., Ciais, P., Moreno, M. V., and Nogueira, J. M. P.: FRY, a global database of fire patch functional traits derived from space-borne burned area products, Sci. Data, 5, 180132, https://doi.org/10.1038/sdata.2018.132, 2018.
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, Eos, Transactions American Geophysical Union, 89, 93–94, 2008.
Levers, C., Piquer-Rodríguez, M., Gollnow, F., Baumann, M., Camino, M., Gasparri, N. I., Gavier-Pizarro, G. I., le Polain de Waroux, Y., Müller, D., Nori, J., Pötzschner, F., Romero-Muñoz, A., and Kuemmerle, T.: What is still at stake in the Gran Chaco? Social-ecological impacts of alternative land-system futures in a global deforestation hotspot, Environ. Res. Lett., 19, 064003, https://doi.org/10.1088/1748-9326/ad44b6, 2024.
Linley, G. D., Jolly, C. J., Doherty, T. S., Geary, W. L., Armenteras, D., Belcher, C. M., Bliege Bird, R., Duane, A., Fletcher, M., Giorgis, M. A., Haslem, A., Jones, G. M., Kelly, L. T., Lee, C. K. F., Nolan, R. H., Parr, C. L., Pausas, J. G., Price, J. N., Regos, A., Ritchie, E. G., Ruffault, J., Williamson, G. J., Wu, Q., and Nimmo, D. G.: What do you mean, `megafire'?, Global Ecol. Biogeogr., 31, 1906–1922, https://doi.org/10.1111/geb.13499, 2022.
Lizundia-Loiola, J., Otón, G., Ramo, R., and Chuvieco, E.: A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data, Remote Sens. Environ., 236, 111493, https://doi.org/10.1016/j.rse.2019.111493, 2020.
Loto, D. and Bravo, S.: Species composition, structure, and functional traits in Argentine Chaco forests under two different disturbance histories, Ecol. Indic., 113, 106232, https://doi.org/10.1016/j.ecolind.2020.106232, 2020.
MacQueen, J.: Some methods for classification and analysis of multivariate observations, in: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1: Statistics, edited by: Le Cam, L. M. and Neyman, J., University of California Press, Berkeley, CA, 281–297, https://projecteuclid.org/euclid.bsmsp/1200512992 (last access: 13 March 2026), 1967.
Marengo, J., Martinez, R., Tapia, B., Allen, T., Basantes, R., Hernandez-Espinoza, K., Alvarado, L., Baddour, O., Ransom, C., Silva, Á., Báez, J., Gomez, F., Costa, F., Avalos, G., Estella, J., and Kennedy, J.: State of the Climate in Latin America and the Caribbean 2021 (WMO-No. 1295), World Meteorological Organization, Geneva, ISBN 978-92-63-11295-8, 2022.
McDaniel, J., Kennard, D., and Fuentes, A.: Smokey the Tapir: Traditional Fire Knowledge and Fire Prevention Campaigns in Lowland Bolivia, Soc. Natur. Resour., 18, 921–931, https://doi.org/10.1080/08941920500248921, 2005.
Meinshausen, N.: Quantile Regression Forests, J. Mach. Learn. Res., 7, 983–999, 2006.
Morello, J. H. and Adámoli, J. M.: Las grandes unidades de vegetación y ambiente del Chaco argentino. Primera parte: objetivos y metodología, Serie Fitogeográfica, No. 10, Instituto Nacional de Tecnología Agropecuaria (INTA), Buenos Aires, 1–125, https://www.sidalc.net/search/Record/KOHA-OAI-FCF:1929/Description (last access: 13 March 2026), 1968.
Moreno, M. V., Laurent, P., and Mouillot, F.: Global intercomparison of functional pyrodiversity from two satellite sensors, Int. J. Remote Sens., 42, 9523–9541, https://doi.org/10.1080/01431161.2021.1999529, 2021.
Mouillot, F., Schultz, M. G., Yue, C., Cadule, P., Tansey, K., Ciais, P., and Chuvieco, E.: Ten years of global burned area products from spaceborne remote sensing – A review: Analysis of user needs and recommendations for future developments, Int. J. Appl. Earth Obs., 26, 64–79, https://doi.org/10.1016/j.jag.2013.05.014, 2014.
Mouillot, F., Chen, W., Campagnolo, M., and Ciais, P.: FRYv2.0 : a global fire patch morphology database from FireCCI51 and MCD64A1, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9575, https://doi.org/10.5194/egusphere-egu23-9575, 2023.
Muñoz Sabater, J.: ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac, 2019.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Musser, K.: Río de la Plata basin map, Wikimedia Commons, https://commons.wikimedia.org/wiki/File:Riodelaplatabasinmap.png (last access: 13 March 2026), 2010.
Myneni, R., Knyazikhin, Y., and Park, T.: MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061, NASA Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MOD15A2H.061, 2021a.
Myneni, R., Knyazikhin, Y., and Park, T.: MODIS/Terra+Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061, NASA Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD15A2H.061, 2021b.
Naumann, G., Podesta, G., Marengo, J., Luterbacher, J., Bavera, D., Acosta, N. J., Arias-Muñoz, C., Barbosa, P., Cammalleri, C., Cuartas, L. A., De, E. M., De, F. M., De, J. A., Escobar, C., Fioravanti, G., Giordano, L., Hrast, E. A., Hidalgo, C., Leal, D. M. O. L., Maetens, W., Magni, D., Masante, D., Mazzeschi, M., Osman, M., Rossi, L., Seluchi, M., De, L. M. S. M., Spennemann, P., Spinoni, J., Toreti, A., and Vera, C.: Extreme and long-term drought in the La Plata Basin: event evolution and impact assessment until September 2022, JRC Technical Report, Publications Office of the European Union, Luxembourg, https://doi.org/10.2760/62557, 2023.
Naval Fernández, Albornoz, J., Bellis, L. M., Baldini, C., Arcamone, J., Silvetti, L., Álvarez, M. P., and Argañaraz, J. P.: Megaincendios 2020 en Córdoba: Incidencia del fuego en áreas de valor ecológico y socioeconómico, Ecol. Austral, 33, 136–151, https://doi.org/10.25260/EA.23.33.1.0.2120, 2023.
Naval-Fernández, M. C., Elia, M., Giannico, V., Bellis, L. M., Bravo, S. J., and Argañaraz, J. P.: The Pyrogeography of the Gran Chaco's Dry Forest: A Comparison of Clustering Algorithms and the Scale of Analysis, Forests, 16, 1114, https://doi.org/10.3390/f16071114, 2025.
Nori, J., Torres, R., Lescano, J. N., Cordier, J. M., Periago, M. E., and Baldo, D.: Protected areas and spatial conservation priorities for endemic vertebrates of the Gran Chaco, one of the most threatened ecoregions of the world, Diversity and Distributions, 22, 1212–1219, https://doi.org/10.1111/ddi.12497, 2016.
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V., Underwood, E. C., and Kassem, K. R.: Terrestrial Ecoregions of the World: A New Map of Life on EarthA new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity, BioScience, 51, 933–938, 2001.
Oom, D., Silva, P. C., Bistinas, I., and Pereira, J. M. C.: Highlighting Biome-Specific Sensitivity of Fire Size Distributions to Time-Gap Parameter Using a New Algorithm for Fire Event Individuation, Remote Sens., 8, 663, https://doi.org/10.3390/rs8080663, 2016.
Paritsis, J., Landesmann, J. B., Kitzberger, T., Tiribelli, F., Sasal, Y., Quintero, C., Dimarco, R. D., Barrios-García, M. N., Iglesias, A. L., Diez, J. P., Sarasola, M., and Nuñez, M. A.: Pine Plantations and Invasion Alter Fuel Structure and Potential Fire Behavior in a Patagonian Forest-Steppe Ecotone, Forests, 9, 117, https://doi.org/10.3390/f9030117, 2018.
Paudel, J.: Short-run environmental effects of COVID-19: Evidence from forest fires, World Dev., 137, 105120, https://doi.org/10.1016/j.worlddev.2020.105120, 2021.
Pausas, J. G. and Bradstock, R. A.: Fire persistence traits of plants along a productivity and disturbance gradient in mediterranean shrublands of south-east Australia, Global Ecol. Biogeogr., 16, 330–340, https://doi.org/10.1111/j.1466-8238.2006.00283.x, 2007.
Pettinari, M. L., Lizundia-Loiola, J., and Chuvieco, E.: ESA CCI ECV fire disturbance: D4. 2.1 product user guide – MODIS, version 1.1, ESA Climate Change Initiative (Fire_cci), https://climate.esa.int/en/projects/fire/key-documents/ (last access: 13 March 2026), 2021.
Pielou, E. C.: The measurement of diversity in different types of biological collections, J. Theor. Biol., 13, 131–144, https://doi.org/10.1016/0022-5193(66)90013-0, 1966.
Poulter, B., Freeborn, P., Jolly, W., and Varner, J.: COVID-19 lockdowns drive decline in active fires in southeastern United States, P. Natl. Acad. Sci. USA, 118, e2105666118, https://doi.org/10.1073/pnas.2105666118, 2021.
Redford, K. H., Taber, A., and Simonetti, J. A.: There is More to Biodiversity than the Tropical Rain Forests, Conserv. Biol., 4, 328–330, 1990.
Ruffault, J. and Mouillot, F.: How a new fire-suppression policy can abruptly reshape the fire-weather relationship, Ecosphere, 6, 199, https://doi.org/10.1890/ES15-00182.1, 2015.
Ruffault, J. and Mouillot, F.: Contribution of human and biophysical factors to the spatial distribution of forest fire ignitions and large wildfires in a French Mediterranean region, Int. J. Wildland Fire, 26, 498–508, https://doi.org/10.1071/WF16181, 2017.
Ruffault, J., Moron, V., Trigo, R. M., and Curt, T.: Objective identification of multiple large fire climatologies: an application to a Mediterranean ecosystem, Environ. Res. Lett., 11, 075006, https://doi.org/10.1088/1748-9326/11/7/075006, 2016.
Ruffault, J., Curt, T., Moron, V., Trigo, R. M., Mouillot, F., Koutsias, N., Pimont, F., Martin-StPaul, N., Barbero, R., Dupuy, J.-L., Russo, A., and Belhadj-Khedher, C.: Increased likelihood of heat-induced large wildfires in the Mediterranean Basin, Sci. Rep., 10, 13790, https://doi.org/10.1038/s41598-020-70069-z, 2020.
San Martín, R.: Fires, land use, and forest loss in the South American Chaco: understanding the links between fires, climate, ecosystems, and human activity through remote sensing, PhD Thesis, Université Paris-Saclay, NNT: 2024UPASJ034, HAL Id: tel-04885407, https://theses.hal.science/tel-04885407 (last access: 13 March 2026), 2024.
San Martín, R., Ottlé, C., and Sörensson, A.: Fires in the South American Chaco, from dry forests to wetlands: response to climate depends on land cover, Fire Ecol., 19, https://doi.org/10.1186/s42408-023-00212-4, 2023.
Saucedo, G. I. and Kurtz, D. B.: Seasonality and post fire recovery in a wetland dominated region: Insights from satellite data analysis in northern Argentina, Remote Sensing Applications: Society and Environment, 37, 101480, https://doi.org/10.1016/j.rsase.2025.101480, 2025.
Schmidt, M. A. and Castilla, M.: La emergencia del fuego en un territorio hidrosocial: incendios en las provincias de Salta y Chaco, I Encuentro Territorios Hidrosociales en Disputa (ETHIS) (Chaco, 25 y 26 de agosto de 2022), Instituto de Investigaciones en Humanidades y Ciencias Sociales, 453–474, ISBN 978-987-48445-4-5, 2023.
Shannon, C. E.: A Mathematical Theory of Communication, Bell Syst. Tech. J., 27, 379–423, https://doi.org/10.1002/j.1538-7305.1948.tb01338.x, 1948.
Sugiyama, M. S., Mendoza, M., and Carpio, M. B.: Resilience and Recovery in the Dry Chaco: Ecological Knowledge Encoded in Forager Wildfire Narratives, J. Ethnobiol., 45, 76–94, https://doi.org/10.1177/02780771241303896, 2025.
Takacs, S., Schulte to Bühne, H., and Pettorelli, N.: What shapes fire size and spread in African savannahs?, Remote Sens. Ecol. Conserv., 7, 610–620, https://doi.org/10.1002/rse2.212, 2021.
Tálamo, A., Lopez De Casenave, J., Núñez-Regueiro, M., and Caziani, S. M.: Regeneración de plantas leñosas en el Chaco semiárido argentino: relación con factores bióticos y abióticos en micrositios creados por el aprovechamiento forestal, Bosque (Valdivia), 34, 13–14, https://doi.org/10.4067/S0717-92002013000100007, 2013.
Torrella, S. A. and Adámoli, J.: Situación ambiental de la ecorregión del Chaco Seco, in: La situación ambiental argentina 2005, edited by: Brown, A., Martínez Ortiz, U., Acerbi, M., and Corcuera, J., Fundación Vida Silvestre Argentina, Buenos Aires, 75–82, 2005.
Van Wagner, C. E.: Development and structure of the Canadian Forest Fire Weather Index System, Minister of Supply and Services Canada, Ottawa, 37 pp., ISBN 0-662-15198-4,, 1987.
Vidal-Riveros, C., Souza-Alonso, P., Bravo, S., Laino, R., and Ngo Bieng, M. A.: A review of wildfires effects across the Gran Chaco region, Forest Ecol. Manag., 549, 121432, https://doi.org/10.1016/j.foreco.2023.121432, 2023.
Vidal-Riveros, C., Watler Reyes, W. J., Ngo Bieng, M. A., and Souza-Alonso, P.: Assessing Fire Regimes in the Paraguayan Chaco: Implications for Ecological and Fire Management, Fire, 7, 347, https://doi.org/10.3390/fire7100347, 2024.
Vitolo, C., Di Giuseppe, F., Barnard, C., Coughlan, R., San-Miguel-Ayanz, J., Libertá, G., and Krzeminski, B.: ERA5-based global meteorological wildfire danger maps, Sci. Data, 7, 216, https://doi.org/10.1038/s41597-020-0554-z, 2020.
Wright, M. N. and Ziegler, A.: ranger: A Fast Implementation of Random Forests for High Dimensional Data in C
Yebra, M., Scortechini, G., Badi, A., Beget, M. E., Boer, M. M., Bradstock, R., Chuvieco, E., Danson, F. M., Dennison, P., Resco de Dios, V., Di Bella, C. M., Forsyth, G., Frost, P., Garcia, M., Hamdi, A., He, B., Jolly, M., Kraaij, T., Martín, M. P., Mouillot, F., Newnham, G., Nolan, R. H., Pellizzaro, G., Qi, Y., Quan, X., Riaño, D., Roberts, D., Sow, M., and Ustin, S.: Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications, Sci. Data, 6, 155, https://doi.org/10.1038/s41597-019-0164-9, 2019.
Short summary
We studied wildfires in the Gran Chaco, one of the world’s largest dry forests, to understand why some fires become much larger than others. By analyzing thousands of fires together with environmental and landscape data, we found that fire size is mainly shaped by topography and vegetation structure, which determine how continuous fuels are across the landscape. Weather and human factors play a secondary role in explaining final fire size.
We studied wildfires in the Gran Chaco, one of the world’s largest dry forests, to understand...
Altmetrics
Final-revised paper
Preprint