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306 results on '"Ciais, Philippe"'

1. Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle

Author

He, Xianjin, Abs, Elsa, Allison, Steven D, Tao, Feng, Huang, Yuanyuan, Manzoni, Stefano, Abramoff, Rose, Bruni, Elisa, Bowring, Simon PK, Chakrawal, Arjun, Ciais, Philippe, Elsgaard, Lars, Friedlingstein, Pierre, Georgiou, Katerina, Hugelius, Gustaf, Holm, Lasse Busk, Li, Wei, Luo, Yiqi, Marmasse, Gaëlle, Nunan, Naoise, Qiu, Chunjing, Sitch, Stephen, Wang, Ying-Ping, and Goll, Daniel S

Subjects
Agricultural, Veterinary and Food Sciences, Biological Sciences, Forestry Sciences, Life on Land, Carbon Cycle, Soil Microbiology, Carbon, Soil, Ecosystem, Bacteria
Abstract

Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

Published
2024

2. Reconstructing Global Daily CO2 Emissions via Machine Learning

Author

Li, Tao, Wang, Lixing, Qiu, Zihan, Ciais, Philippe, Sun, Taochun, Jones, Matthew W., Andrew, Robbie M., Peters, Glen P., ke, Piyu, Huang, Xiaoting, Jackson, Robert B., and Liu, Zhu

Subjects
Physics - Atmospheric and Oceanic Physics, Computer Science - Machine Learning, Statistics - Applications
Abstract

High temporal resolution CO2 emission data are crucial for understanding the drivers of emission changes, however, current emission dataset is only available on a yearly basis. Here, we extended a global daily CO2 emissions dataset backwards in time to 1970 using machine learning algorithm, which was trained to predict historical daily emissions on national scales based on relationships between daily emission variations and predictors established for the period since 2019. Variation in daily CO2 emissions far exceeded the smoothed seasonal variations. For example, the range of daily CO2 emissions equivalent to 31% of the year average daily emissions in China and 46% of that in India in 2022, respectively. We identified the critical emission-climate temperature (Tc) is 16.5 degree celsius for global average (18.7 degree celsius for China, 14.9 degree celsius for U.S., and 18.4 degree celsius for Japan), in which negative correlation observed between daily CO2 emission and ambient temperature below Tc and a positive correlation above it, demonstrating increased emissions associated with higher ambient temperature. The long-term time series spanning over fifty years of global daily CO2 emissions reveals an increasing trend in emissions due to extreme temperature events, driven by the rising frequency of these occurrences. This work suggests that, due to climate change, greater efforts may be needed to reduce CO2 emissions.

Published
2024

3. Low latency carbon budget analysis reveals a large decline of the land carbon sink in 2023

Author

Ke, Piyu, Ciais, Philippe, Sitch, Stephen, Li, Wei, Bastos, Ana, Liu, Zhu, Xu, Yidi, Gui, Xiaofan, Bian, Jiang, Goll, Daniel S, Xi, Yi, Li, Wanjing, O'Sullivan, Michael, de Souza, Jeffeson Goncalves, Friedlingstein, Pierre, and Chevallier, Frederic

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

In 2023, the CO2 growth rate was 3.37 +/- 0.11 ppm at Mauna Loa, 86% above the previous year, and hitting a record high since observations began in 1958, while global fossil fuel CO2 emissions only increased by 0.6 +/- 0.5%. This implies an unprecedented weakening of land and ocean sinks, and raises the question of where and why this reduction happened. Here we show a global net land CO2 sink of 0.44 +/- 0.21 GtC yr-1, the weakest since 2003. We used dynamic global vegetation models, satellites fire emissions, an atmospheric inversion based on OCO-2 measurements, and emulators of ocean biogeochemical and data driven models to deliver a fast-track carbon budget in 2023. Those models ensured consistency with previous carbon budgets. Regional flux anomalies from 2015-2022 are consistent between top-down and bottom-up approaches, with the largest abnormal carbon loss in the Amazon during the drought in the second half of 2023 (0.31 +/- 0.19 GtC yr-1), extreme fire emissions of 0.58 +/- 0.10 GtC yr-1 in Canada and a loss in South-East Asia (0.13 +/- 0.12 GtC yr-1). Since 2015, land CO2 uptake north of 20 degree N declined by half to 1.13 +/- 0.24 GtC yr-1 in 2023. Meanwhile, the tropics recovered from the 2015-16 El Nino carbon loss, gained carbon during the La Nina years (2020-2023), then switched to a carbon loss during the 2023 El Nino (0.56 +/- 0.23 GtC yr-1). The ocean sink was stronger than normal in the equatorial eastern Pacific due to reduced upwelling from La Nina's retreat in early 2023 and the development of El Nino later. Land regions exposed to extreme heat in 2023 contributed a gross carbon loss of 1.73 GtC yr-1, indicating that record warming in 2023 had a strong negative impact on the capacity of terrestrial ecosystems to mitigate climate change.

Published
2024

4. Open-Canopy: A Country-Scale Benchmark for Canopy Height Estimation at Very High Resolution

Author

Fogel, Fajwel, Perron, Yohann, Besic, Nikola, Saint-André, Laurent, Pellissier-Tanon, Agnès, Schwartz, Martin, Boudras, Thomas, Fayad, Ibrahim, d'Aspremont, Alexandre, Landrieu, Loic, and Ciais, Philippe

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Estimating canopy height and canopy height change at meter resolution from satellite imagery has numerous applications, such as monitoring forest health, logging activities, wood resources, and carbon stocks. However, many existing forest datasets are based on commercial or closed data sources, restricting the reproducibility and evaluation of new approaches. To address this gap, we introduce Open-Canopy, the first open-access and country-scale benchmark for very high resolution (1.5 m) canopy height estimation. Covering more than 87,000 km$^2$ across France, Open-Canopy combines SPOT satellite imagery with high resolution aerial LiDAR data. We also propose Open-Canopy-$\Delta$, the first benchmark for canopy height change detection between two images taken at different years, a particularly challenging task even for recent models. To establish a robust foundation for these benchmarks, we evaluate a comprehensive list of state-of-the-art computer vision models for canopy height estimation. The dataset and associated codes can be accessed at https://github.com/fajwel/Open-Canopy., Comment: 22 pages, 8 figures, Submitted to NeurIPS 2024 Datasets and Benchmarks Track

Published
2024

5. Estimating Canopy Height at Scale

Author

Pauls, Jan, Zimmer, Max, Kelly, Una M., Schwartz, Martin, Saatchi, Sassan, Ciais, Philippe, Pokutta, Sebastian, Brandt, Martin, and Gieseke, Fabian

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss function designed to counter geolocation inaccuracies inherent in the ground-truth height measurements, and employs data from the Shuttle Radar Topography Mission to effectively filter out erroneous labels in mountainous regions, enhancing the reliability of our predictions in those areas. A comparison between predictions and ground-truth labels yields an MAE / RMSE of 2.43 / 4.73 (meters) overall and 4.45 / 6.72 (meters) for trees taller than five meters, which depicts a substantial improvement compared to existing global-scale maps. The resulting height map as well as the underlying framework will facilitate and enhance ecological analyses at a global scale, including, but not limited to, large-scale forest and biomass monitoring., Comment: ICML Camera-Ready, 17 pages, 14 figures, 7 tables

Published
2024

6. Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest Monitoring

Author

Li, Sizhuo, Gominski, Dimitri, Brandt, Martin, Tong, Xiaoye, and Ciais, Philippe

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Image-level regression is an important task in Earth observation, where visual domain and label shifts are a core challenge hampering generalization. However, cross-domain regression within remote sensing data remains understudied due to the absence of suited datasets. We introduce a new dataset with aerial and satellite imagery in five countries with three forest-related regression tasks. To match real-world applicative interests, we compare methods through a restrictive setup where no prior on the target domain is available during training, and models are adapted with limited information during testing. Building on the assumption that ordered relationships generalize better, we propose manifold diffusion for regression as a strong baseline for transduction in low-data regimes. Our comparison highlights the comparative advantages of inductive and transductive methods in cross-domain regression., Comment: Updated with review comments

Published
2024

10. Overconfidence in climate overshoot

Author

Schleussner, Carl-Friedrich, Ganti, Gaurav, Lejeune, Quentin, Zhu, Biqing, Pfleiderer, Peter, Prütz, Ruben, Ciais, Philippe, Frölicher, Thomas L., Fuss, Sabine, Gasser, Thomas, Gidden, Matthew J., Kropf, Chahan M., Lacroix, Fabrice, Lamboll, Robin, Martyr, Rosanne, Maussion, Fabien, McCaughey, Jamie W., Meinshausen, Malte, Mengel, Matthias, Nicholls, Zebedee, Quilcaille, Yann, Sanderson, Benjamin, Seneviratne, Sonia I., Sillmann, Jana, Smith, Christopher J., Steinert, Norman J., Theokritoff, Emily, Warren, Rachel, Price, Jeff, and Rogelj, Joeri

Published
2024
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13. Aligning long-term climate mitigation with enhanced methane action

Author

Tanaka, Katsumasa, Tibrewal, Kushal, Ciais, Philippe, and Boucher, Olivier

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

The Global Methane Pledge and other methane measures may potentially undermine CO2 mitigation in certain countries, unless they are considered as additional to the existing Nationally Determined Contributions to strengthen overall greenhouse gas emission targets. Maintaining the progress on CO2 mitigation in the revision of Nationally Determined Contributions after the first Global Stocktake, while pursuing the immediate benefits from methane mitigation, is necessary to address climate change in the long-term.

Published
2024

14. Drivers of natural gas use in U.S. residential buildings.

Author

Mittakola, Rohith, Ciais, Philippe, Schubert, Jochen, Makowski, David, Zhou, Chuanlong, Bazzi, Hassan, Sun, Taochun, Liu, Zhu, and Davis, Steven

Abstract

Natural gas is the primary fuel used in U.S. residences, yet little is known about its consumption patterns and drivers. We use daily county-level gas consumption data to assess the spatial patterns of the relationships and the sensitivities of gas consumption to outdoor air temperature across U.S. households. We fitted linear-plus-plateau functions to daily gas consumption data in 1000 counties, and derived two key coefficients: the heating temperature threshold (Tcrit) and the gas consumption rate change per 1°C temperature drop (Slope). We identified the main predictors of Tcrit and Slope (like income, employment rate, and building type) using interpretable machine learning models built on census data. Finally, we estimated a potential 2.47 million MtCO2 annual emission reduction in U.S. residences by gas savings due to household insulation improvements and hypothetical behavioral change toward reduced consumption by adopting a 1°C lower Tcrit than the current value.

Published
2024

15. Microbial evolution-An under-appreciated driver of soil carbon cycling.

Author

Abs, Elsa, Chase, Alexander B, Manzoni, Stefano, Ciais, Philippe, and Allison, Steven D

Subjects
biogeochemistry, carbon cycle, evolution, global change, microbe, Environmental Sciences, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.

Published
2024

18. Microbial Evolution Drives Adaptation of Substrate Degradation on Decadal to Centennial Time Scales Relevant to Global Change

Author

Abs, Elsa, Coulette, David, Ciais, Philippe, and Allison, Steven D

Subjects
climate change, dispersal, litter decay, microbial evolution, Climate Change, Soil Microbiology, Biological Evolution, Adaptation, Physiological, Models, Biological, Ecosystem, Mutation, Ecological Applications, Ecology, Evolutionary Biology, Ecological applications, Environmental management
Abstract

Understanding microbial adaptation is crucial for predicting how soil carbon dynamics and global biogeochemical cycles will respond to climate change. This study employs the DEMENT model of microbial decomposition, along with empirical mutation and dispersal rates, to explore the roles of mutation and dispersal in the adaptation of soil microbial populations to shifts in litter chemistry, changes that are anticipated with climate-driven vegetation dynamics. Following a change in litter chemistry, mutation generally allows for a higher rate of litter decomposition than dispersal, especially when dispersal predominantly introduces genotypes already present in the population. These findings challenge the common idea that mutation rates are too low to affect ecosystem processes on ecological timescales. These results demonstrate that evolutionary processes, such as mutation, can help maintain ecosystem functioning as the climate changes.

Published
2024

19. Reply to: Model uncertainty obscures major driver of soil carbon

Author

Tao, Feng, Houlton, Benjamin Z., Frey, Serita D., Lehmann, Johannes, Manzoni, Stefano, Huang, Yuanyuan, Jiang, Lifen, Mishra, Umakant, Hungate, Bruce A., Schmidt, Michael W. I., Reichstein, Markus, Carvalhais, Nuno, Ciais, Philippe, Wang, Ying-Ping, Ahrens, Bernhard, Hugelius, Gustaf, Hocking, Toby D., Lu, Xingjie, Shi, Zheng, Viatkin, Kostiantyn, Vargas, Ronald, Yigini, Yusuf, Omuto, Christian, Malik, Ashish A., Peralta, Guillermo, Cuevas-Corona, Rosa, Di Paolo, Luciano E., Luotto, Isabel, Liao, Cuijuan, Liang, Yi-Shuang, Saynes, Vinisa S., Huang, Xiaomeng, and Luo, Yiqi

Published
2024
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33. Central African biomass carbon losses and gains during 2010–2019

Author

Zhao, Zhe, Ciais, Philippe, Wigneron, Jean-Pierre, Santoro, Maurizio, Brandt, Martin, Kleinschroth, Fritz, Lewis, Simon L., Chave, Jerome, Fensholt, Rasmus, Laporte, Nadine, Sonwa, Denis Jean, Saatchi, Sassan S., Fan, Lei, Yang, Hui, Li, Xiaojun, Wang, Mengjia, Zhu, Lei, Xu, Yidi, He, Jiaying, and Li, Wei

Published
2024
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35. Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO2 fluxes in Europe

Author

Bazzi, Hassan, Ciais, Philippe, Abbessi, Ezzeddine, Makowski, David, Santaren, Diego, Ceschia, Eric, Brut, Aurore, Tallec, Tiphaine, Buchmann, Nina, Maier, Regine, Acosta, Manuel, Loubet, Benjamin, Buysse, Pauline, Léonard, Joël, Bornet, Frédéric, Fayad, Ibrahim, Lian, Jinghui, Baghdadi, Nicolas, Segura Barrero, Ricard, Brümmer, Christian, Schmidt, Marius, Heinesch, Bernard, Mauder, Matthias, and Gruenwald, Thomas

Published
2024
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42. Global nitrous oxide budget (1980–2020)

Author

Tian, Hanqin, primary, Pan, Naiqing, additional, Thompson, Rona L., additional, Canadell, Josep G., additional, Suntharalingam, Parvadha, additional, Regnier, Pierre, additional, Davidson, Eric A., additional, Prather, Michael, additional, Ciais, Philippe, additional, Muntean, Marilena, additional, Pan, Shufen, additional, Winiwarter, Wilfried, additional, Zaehle, Sönke, additional, Zhou, Feng, additional, Jackson, Robert B., additional, Bange, Hermann W., additional, Berthet, Sarah, additional, Bian, Zihao, additional, Bianchi, Daniele, additional, Bouwman, Alexander F., additional, Buitenhuis, Erik T., additional, Dutton, Geoffrey, additional, Hu, Minpeng, additional, Ito, Akihiko, additional, Jain, Atul K., additional, Jeltsch-Thömmes, Aurich, additional, Joos, Fortunat, additional, Kou-Giesbrecht, Sian, additional, Krummel, Paul B., additional, Lan, Xin, additional, Landolfi, Angela, additional, Lauerwald, Ronny, additional, Li, Ya, additional, Lu, Chaoqun, additional, Maavara, Taylor, additional, Manizza, Manfredi, additional, Millet, Dylan B., additional, Mühle, Jens, additional, Patra, Prabir K., additional, Peters, Glen P., additional, Qin, Xiaoyu, additional, Raymond, Peter, additional, Resplandy, Laure, additional, Rosentreter, Judith A., additional, Shi, Hao, additional, Sun, Qing, additional, Tonina, Daniele, additional, Tubiello, Francesco N., additional, van der Werf, Guido R., additional, Vuichard, Nicolas, additional, Wang, Junjie, additional, Wells, Kelley C., additional, Western, Luke M., additional, Wilson, Chris, additional, Yang, Jia, additional, Yao, Yuanzhi, additional, You, Yongfa, additional, and Zhu, Qing, additional

Published
2024
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43. Ensemble estimates of global wetland methane emissions over 2000–2020

Author

Zhang, Zhen, primary, Poulter, Benjamin, additional, Melton, Joe R., additional, Riley, William J., additional, Allen, George H., additional, Beerling, David J., additional, Bousquet, Philippe, additional, Canadell, Josep G., additional, Fluet-Chouinard, Etienne, additional, Ciais, Philippe, additional, Gedney, Nicola, additional, Hopcroft, Peter O., additional, Ito, Akihiko, additional, Jackson, Robert B., additional, Jain, Atul K., additional, Jensen, Katherine, additional, Joos, Fortunat, additional, Kleinen, Thomas, additional, Knox, Sara, additional, Li, Tingting, additional, Li, Xin, additional, Liu, Xiangyu, additional, McDonald, Kyle, additional, McNicol, Gavin, additional, Miller, Paul A., additional, Müller, Jurek, additional, Patra, Prabir K., additional, Peng, Changhui, additional, Peng, Shushi, additional, Qin, Zhangcai, additional, Riggs, Ryan M., additional, Saunois, Marielle, additional, Sun, Qing, additional, Tian, Hanqin, additional, Xu, Xiaoming, additional, Yao, Yuanzhi, additional, Yi, Xi, additional, Zhang, Wenxin, additional, Zhu, Qing, additional, Zhu, Qiuan, additional, and Zhuang, Qianlai, additional

Published
2024
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44. Supplementary material to "Ensemble estimates of global wetland methane emissions over 2000–2020"

Author

Zhang, Zhen, primary, Poulter, Benjamin, additional, Melton, Joe R., additional, Riley, William J., additional, Allen, George H., additional, Beerling, David J., additional, Bousquet, Philippe, additional, Canadell, Josep G., additional, Fluet-Chouinard, Etienne, additional, Ciais, Philippe, additional, Gedney, Nicola, additional, Hopcroft, Peter O., additional, Ito, Akihiko, additional, Jackson, Robert B., additional, Jain, Atul K., additional, Jensen, Katherine, additional, Joos, Fortunat, additional, Kleinen, Thomas, additional, Knox, Sara, additional, Li, Tingting, additional, Li, Xin, additional, Liu, Xiangyu, additional, McDonald, Kyle, additional, McNicol, Gavin, additional, Miller, Paul A., additional, Müller, Jurek, additional, Patra, Prabir K., additional, Peng, Changhui, additional, Peng, Shushi, additional, Qin, Zhangcai, additional, Riggs, Ryan M., additional, Saunois, Marielle, additional, Sun, Qing, additional, Tian, Hanqin, additional, Xu, Xiaoming, additional, Yao, Yuanzhi, additional, Yi, Xi, additional, Zhang, Wenxin, additional, Zhu, Qing, additional, Zhu, Qiuan, additional, and Zhuang, Qianlai, additional

Published
2024
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45. Changes in above- versus belowground biomass distribution in permafrost regions in response to climate warming

Author

Yun, Hanbo, primary, Ciais, Philippe, additional, Zhu, Qing, additional, Chen, Deliang, additional, Zohner, Constantin M., additional, Tang, Jing, additional, Qu, Yang, additional, Zhou, Hao, additional, Schimel, Joshua, additional, Zhu, Peng, additional, Shao, Ming, additional, Christensen, Jens Hesselbjerg, additional, Wu, Qingbai, additional, Chen, Anping, additional, and Elberling, Bo, additional

Published
2024
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46. Supplementary material to "Global Methane Budget 2000–2020"

Author

Saunois, Marielle, primary, Martinez, Adrien, additional, Poulter, Benjamin, additional, Zhang, Zhen, additional, Raymond, Peter, additional, Regnier, Pierre, additional, Canadell, Joseph G., additional, Jackson, Robert B., additional, Patra, Prabir K., additional, Bousquet, Philippe, additional, Ciais, Philippe, additional, Dlugokencky, Edward J., additional, Lan, Xin, additional, Allen, George H., additional, Bastviken, David, additional, Beerling, David J., additional, Belikov, Dmitry A., additional, Blake, Donald R., additional, Castaldi, Simona, additional, Crippa, Monica, additional, Deemer, Bridget R., additional, Dennison, Fraser, additional, Etiope, Giuseppe, additional, Gedney, Nicola, additional, Höglund-Isaksson, Lena, additional, Holgerson, Meredith A., additional, Hopcroft, Peter O., additional, Hugelius, Gustaf, additional, Ito, Akihito, additional, Jain, Atul K., additional, Janardanan, Rajesh, additional, Johnson, Matthew S., additional, Kleinen, Thomas, additional, Krummel, Paul, additional, Lauerwald, Ronny, additional, Li, Tingting, additional, Liu, Xiangyu, additional, McDonald, Kyle C., additional, Melton, Joe R., additional, Mühle, Jens, additional, Müller, Jurek, additional, Murguia-Flores, Fabiola, additional, Niwa, Yosuke, additional, Noce, Sergio, additional, Pan, Shufen, additional, Parker, Robert J., additional, Peng, Changhui, additional, Ramonet, Michel, additional, Riley, William J., additional, Rocher-Ros, Gerard, additional, Rosentreter, Judith A., additional, Sasakawa, Motoki, additional, Segers, Arjo, additional, Smith, Steven J., additional, Stanley, Emily H., additional, Thanwerdas, Joel, additional, Tian, Hanquin, additional, Tsuruta, Aki, additional, Tubiello, Francesco N., additional, Weber, Thomas S., additional, van der Werf, Guido, additional, Worthy, Doug E., additional, Xi, Yi, additional, Yoshida, Yukio, additional, Zhang, Wenxin, additional, Zheng, Bo, additional, Zhu, Qing, additional, Zhu, Qiuan, additional, and Zhuang, Qianlai, additional

Published
2024
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47. Global critical soil moisture thresholds of plant water stress

Author

Fu, Zheng, primary, Ciais, Philippe, additional, Wigneron, Jean-Pierre, additional, Gentine, Pierre, additional, Feldman, Andrew F., additional, Makowski, David, additional, Viovy, Nicolas, additional, Kemanian, Armen R., additional, Goll, Daniel S., additional, Stoy, Paul C., additional, Prentice, Iain Colin, additional, Yakir, Dan, additional, Liu, Liyang, additional, Ma, Hongliang, additional, Li, Xiaojun, additional, Huang, Yuanyuan, additional, Yu, Kailiang, additional, Zhu, Peng, additional, Li, Xing, additional, Zhu, Zaichun, additional, Lian, Jinghui, additional, and Smith, William K., additional

Published
2024
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48. Global Methane Budget 2000–2020

Author

Saunois, Marielle, primary, Martinez, Adrien, additional, Poulter, Benjamin, additional, Zhang, Zhen, additional, Raymond, Peter, additional, Regnier, Pierre, additional, Canadell, Joseph G., additional, Jackson, Robert B., additional, Patra, Prabir K., additional, Bousquet, Philippe, additional, Ciais, Philippe, additional, Dlugokencky, Edward J., additional, Lan, Xin, additional, Allen, George H., additional, Bastviken, David, additional, Beerling, David J., additional, Belikov, Dmitry A., additional, Blake, Donald R., additional, Castaldi, Simona, additional, Crippa, Monica, additional, Deemer, Bridget R., additional, Dennison, Fraser, additional, Etiope, Giuseppe, additional, Gedney, Nicola, additional, Höglund-Isaksson, Lena, additional, Holgerson, Meredith A., additional, Hopcroft, Peter O., additional, Hugelius, Gustaf, additional, Ito, Akihito, additional, Jain, Atul K., additional, Janardanan, Rajesh, additional, Johnson, Matthew S., additional, Kleinen, Thomas, additional, Krummel, Paul, additional, Lauerwald, Ronny, additional, Li, Tingting, additional, Liu, Xiangyu, additional, McDonald, Kyle C., additional, Melton, Joe R., additional, Mühle, Jens, additional, Müller, Jurek, additional, Murguia-Flores, Fabiola, additional, Niwa, Yosuke, additional, Noce, Sergio, additional, Pan, Shufen, additional, Parker, Robert J., additional, Peng, Changhui, additional, Ramonet, Michel, additional, Riley, William J., additional, Rocher-Ros, Gerard, additional, Rosentreter, Judith A., additional, Sasakawa, Motoki, additional, Segers, Arjo, additional, Smith, Steven J., additional, Stanley, Emily H., additional, Thanwerdas, Joel, additional, Tian, Hanquin, additional, Tsuruta, Aki, additional, Tubiello, Francesco N., additional, Weber, Thomas S., additional, van der Werf, Guido, additional, Worthy, Doug E., additional, Xi, Yi, additional, Yoshida, Yukio, additional, Zhang, Wenxin, additional, Zheng, Bo, additional, Zhu, Qing, additional, Zhu, Qiuan, additional, and Zhuang, Qianlai, additional

Published
2024
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49. Remote sensing-based high-resolution mapping of the forest canopy height: some models are useful, but might they be even more if combined?

Author

Besic, Nikola, primary, Picard, Nicolas, additional, Vega, Cédric, additional, Hertzog, Lionel, additional, Renaud, Jean-Pierre, additional, Fogel, Fajwel, additional, Pellissier-Tanon, Agnès, additional, Destouet, Gabriel, additional, Planells-Rodriguez, Milena, additional, and Ciais, Philippe, additional

Published
2024
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