Articles | Volume 19, issue 16
https://doi.org/10.5194/bg-19-3739-2022
© 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/bg-19-3739-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Aug 2022
Research article |
| 16 Aug 2022
| 16 Aug 2022
Variability and uncertainty in flux-site-scale net ecosystem exchange simulations based on machine learning and remote sensing: a systematic evaluation
Haiyang Shi
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Geping Luo
CORRESPONDING AUTHOR
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Research Center for Ecology and Environment of Central Asia,
Chinese Academy of Sciences, Ürümqi, 830011, China
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Olaf Hellwich
CORRESPONDING AUTHOR
Department of Computer Vision & Remote Sensing, Technische
Universität Berlin, 10587 Berlin, Germany
Mingjuan Xie
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Chen Zhang
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Yu Zhang
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Yuangang Wang
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Xiuliang Yuan
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
Xiaofei Ma
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
Wenqiang Zhang
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Alishir Kurban
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Research Center for Ecology and Environment of Central Asia,
Chinese Academy of Sciences, Ürümqi, 830011, China
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Philippe De Maeyer
State Key Laboratory of Desert and Oasis Ecology, Xinjiang
Institute of Ecology and Geography, Chinese Academy of Sciences, Ürümqi,
Xinjiang, 830011, China
College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
Tim Van de Voorde
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory for Geo-Information, Ghent 9000, Belgium
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Molecules released from plant pollen induce the formation of ice from supercooled water at temperatures warm enough to suggest an underlying function for this activity. In this study we show that ice nucleators are ubiquitous in pollen. We suggest the molecules responsible fulfil some unrelated biological function and nucleate ice incidentally. The ubiquity of ice-nucleating molecules in pollen and particularly active examples reveal a greater potential for pollen to impact weather and climate.
Max Gaber, Yanghui Kang, Guy Schurgers, and Trevor Keenan
Biogeosciences, 21, 2447–2472, https://doi.org/10.5194/bg-21-2447-2024, https://doi.org/10.5194/bg-21-2447-2024, 2024
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Gross primary productivity (GPP) describes the photosynthetic carbon assimilation, which plays a vital role in the carbon cycle. We can measure GPP locally, but producing larger and continuous estimates is challenging. Here, we present an approach to extrapolate GPP to a global scale using satellite imagery and automated machine learning. We benchmark different models and predictor variables and achieve an estimate that can capture 75 % of the variation in GPP.
Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
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Porous materials are known to reversibly trap water from the air, even at low humidity. However, this behavior is poorly understood for soils. In this analysis, we test whether eddy covariance is able to measure the so-called adsorption of atmospheric water vapor by soils. We find that this flux occurs frequently during dry nights in a Mediterranean ecosystem, while EC detects downwardly directed vapor fluxes. These results can help to map moisture uptake globally.
Luana Krebs, Susanne Burri, Iris Feigenwinter, Mana Gharun, Philip Meier, and Nina Buchmann
Biogeosciences, 21, 2005–2028, https://doi.org/10.5194/bg-21-2005-2024, https://doi.org/10.5194/bg-21-2005-2024, 2024
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This study explores year-round forest-floor greenhouse gas (GHG) fluxes in a Swiss spruce forest. Soil temperature and snow depth affected forest-floor respiration, while CH4 uptake was linked to snow cover. Negligible N2O fluxes were observed. In 2022, a warm year, CO2 emissions notably increased. The study suggests rising forest-floor GHG emissions due to climate change, impacting carbon sink behavior. Thus, for future forest management, continuous year-round GHG flux measurements are crucial.
Archana Dayalu, Marikate Mountain, Bharat Rastogi, John B. Miller, and Luciana Gatti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1082, https://doi.org/10.5194/egusphere-2024-1082, 2024
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The Amazon is facing unprecedented disturbance. Determining trends in Amazonia’s carbon balance and its sensitivity to disturbance requires reliable vegetation models that adequately capture how its ecosystems exchange carbon with the atmosphere. Our work presents novel estimates of vegetation carbon exchange with the atmosphere across the Amazon, estimated using ground- and satellite-based ecosystem measurements. Our model agrees with independent aircraft observations from discrete locations.
Simone Rodrigues, Glauber Cirino, Demerval Moreira, Andrea Pozzer, Rafael Palácios, Sung-Ching Lee, Breno Imbiriba, José Nogueira, Maria Isabel Vitorino, and George Vourlitis
Biogeosciences, 21, 843–868, https://doi.org/10.5194/bg-21-843-2024, https://doi.org/10.5194/bg-21-843-2024, 2024
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The radiative effects of atmospheric particles are still unknown for a wide variety of species and types of vegetation present in Amazonian biomes. We examined the effects of aerosols on solar radiation and their impacts on photosynthesis in an area of semideciduous forest in the southern Amazon Basin. Under highly smoky-sky conditions, our results show substantial photosynthetic interruption (20–70 %), attributed specifically to the decrease in solar radiation and leaf canopy temperature.
Ruben B. Schulte, Jordi Vilà-Guerau de Arellano, Susanna Rutledge-Jonker, Shelley van der Graaf, Jun Zhang, and Margreet C. van Zanten
Biogeosciences, 21, 557–574, https://doi.org/10.5194/bg-21-557-2024, https://doi.org/10.5194/bg-21-557-2024, 2024
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We analyzed measurements with the aim of finding relations between the surface atmosphere exchange of NH3 and the CO2 uptake and transpiration by vegetation. We found a high correlation of daytime NH3 emissions with both latent heat flux and photosynthetically active radiation. Very few simultaneous measurements of NH3, CO2 fluxes and meteorological variables exist at sub-diurnal timescales. This study paves the way to finding more robust relations between the NH3 exchange flux and CO2 uptake.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Carolina Voigt, Nick Rutter, Paul Mann, Jean-Daniel Sylvain, and Alexandre Roy
Biogeosciences, 20, 5087–5108, https://doi.org/10.5194/bg-20-5087-2023, https://doi.org/10.5194/bg-20-5087-2023, 2023
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We present an analysis of soil CO2 emissions in boreal and tundra regions during the non-growing season. We show that when the soil is completely frozen, soil temperature is the main control on CO2 emissions. When the soil is around the freezing point, with a mix of liquid water and ice, the liquid water content is the main control on CO2 emissions. This study highlights that the vegetation–snow–soil interactions must be considered to understand soil CO2 emissions during the non-growing season.
Yuhao Cui, Eri Tachibana, Kimitaka Kawamura, and Yuzo Miyazaki
Biogeosciences, 20, 4969–4980, https://doi.org/10.5194/bg-20-4969-2023, https://doi.org/10.5194/bg-20-4969-2023, 2023
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Fatty alcohols (FAs) are major components of surface lipids in plant leaves and serve as surface-active aerosols. Our study on the aerosol size distributions in a forest suggests that secondary FAs (SFAs) originated from plant waxes and that leaf senescence status is likely an important factor controlling the size distribution of SFAs. This study provides new insights into the sources of primary biological aerosol particles (PBAPs) and their effects on the aerosol ice nucleation activity.
Joyson Ahongshangbam, Liisa Kulmala, Jesse Soininen, Yasmin Frühauf, Esko Karvinen, Yann Salmon, Anna Lintunen, Anni Karvonen, and Leena Järvi
Biogeosciences, 20, 4455–4475, https://doi.org/10.5194/bg-20-4455-2023, https://doi.org/10.5194/bg-20-4455-2023, 2023
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Urban vegetation is important for removing urban CO2 emissions and cooling. We studied the response of urban trees' functions (photosynthesis and transpiration) to a heatwave and drought at four urban green areas in the city of Helsinki. We found that tree water use was increased during heatwave and drought periods, but there was no change in the photosynthesis rates. The heat and drought conditions were severe at the local scale but were not excessive enough to restrict urban trees' functions.
Ryan Vella, Andrea Pozzer, Matthew Forrest, Jos Lelieveld, Thomas Hickler, and Holger Tost
Biogeosciences, 20, 4391–4412, https://doi.org/10.5194/bg-20-4391-2023, https://doi.org/10.5194/bg-20-4391-2023, 2023
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We investigated the effect of the El Niño–Southern Oscillation (ENSO) on biogenic volatile organic compound (BVOC) emissions from plants. ENSO events can cause a significant increase in these emissions, which have a long-term impact on the Earth's atmosphere. Persistent ENSO conditions can cause long-term changes in vegetation, resulting in even higher BVOC emissions. We link ENSO-induced emission anomalies with driving atmospheric and vegetational variables.
Nadav Bekin and Nurit Agam
Biogeosciences, 20, 3791–3802, https://doi.org/10.5194/bg-20-3791-2023, https://doi.org/10.5194/bg-20-3791-2023, 2023
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The mechanisms of soil CO2 flux in dry desert soils are not fully understood. Yet studies conducted in desert ecosystems rarely discuss potential errors related to using the commonly used flux chambers in dry and bare soils. In our study, the conventional deployment practice of the chambers underestimated the instantaneous CO2 flux by up to 50 % and the total daily CO2 uptake by 35 %. This suggests that desert soils are a larger carbon sink than previously reported.
Rosemary J. Eufemio, Ingrid de Almeida Ribeiro, Todd L. Sformo, Gary A. Laursen, Valeria Molinero, Janine Fröhlich-Nowoisky, Mischa Bonn, and Konrad Meister
Biogeosciences, 20, 2805–2812, https://doi.org/10.5194/bg-20-2805-2023, https://doi.org/10.5194/bg-20-2805-2023, 2023
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Lichens, the dominant vegetation in the Arctic, contain ice nucleators (INs) that enable freezing close to 0°C. Yet the abundance, diversity, and function of lichen INs is unknown. Our screening of lichens across Alaska reveal that most species have potent INs. We find that lichens contain two IN populations which retain activity under environmentally relevant conditions. The ubiquity and stability of lichen INs suggest that they may have considerable impacts on local atmospheric patterns.
Doaa Aboelyazeed, Chonggang Xu, Forrest M. Hoffman, Jiangtao Liu, Alex W. Jones, Chris Rackauckas, Kathryn Lawson, and Chaopeng Shen
Biogeosciences, 20, 2671–2692, https://doi.org/10.5194/bg-20-2671-2023, https://doi.org/10.5194/bg-20-2671-2023, 2023
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Photosynthesis is critical for life and has been affected by the changing climate. Many parameters come into play while modeling, but traditional calibration approaches face many issues. Our framework trains coupled neural networks to provide parameters to a photosynthesis model. Using big data, we independently found parameter values that were correlated with those in the literature while giving higher correlation and reduced biases in photosynthesis rates.
Norbert Pirk, Kristoffer Aalstad, Yeliz A. Yilmaz, Astrid Vatne, Andrea L. Popp, Peter Horvath, Anders Bryn, Ane Victoria Vollsnes, Sebastian Westermann, Terje Koren Berntsen, Frode Stordal, and Lena Merete Tallaksen
Biogeosciences, 20, 2031–2047, https://doi.org/10.5194/bg-20-2031-2023, https://doi.org/10.5194/bg-20-2031-2023, 2023
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We measured the land–atmosphere exchange of CO2 and water vapor in alpine Norway over 3 years. The extremely snow-rich conditions in 2020 reduced the total annual evapotranspiration to 50 % and reduced the growing-season carbon assimilation to turn the ecosystem from a moderate annual carbon sink to an even stronger source. Our analysis suggests that snow cover anomalies are driving the most consequential short-term responses in this ecosystem’s functioning.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, and Kamel Soudani
Biogeosciences, 20, 1473–1490, https://doi.org/10.5194/bg-20-1473-2023, https://doi.org/10.5194/bg-20-1473-2023, 2023
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This study focuses on the relationship between sun-induced chlorophyll fluorescence (SIF) and ecosystem gross primary productivity (GPP) across the ICOS European flux tower network. It shows that SIF, coupled with reflectance observations, explains over 80 % of the GPP variability across diverse ecosystems but fails to bring new information compared to reflectance alone at coarse spatial scales (~5 km). These findings have applications in agriculture and ecophysiological studies.
John T. Walker, Xi Chen, Zhiyong Wu, Donna Schwede, Ryan Daly, Aleksandra Djurkovic, A. Christopher Oishi, Eric Edgerton, Jesse Bash, Jennifer Knoepp, Melissa Puchalski, John Iiames, and Chelcy F. Miniat
Biogeosciences, 20, 971–995, https://doi.org/10.5194/bg-20-971-2023, https://doi.org/10.5194/bg-20-971-2023, 2023
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Better estimates of atmospheric nitrogen (N) deposition are needed to accurately assess ecosystem risk and impacts from deposition of nutrients and acidity. Using measurements and modeling, we estimate total N deposition of 6.7 kg N ha−1 yr−1 at a forest site in the southern Appalachian Mountains, a region sensitive to atmospheric deposition. Reductions in deposition of reduced forms of N (ammonia and ammonium) will be needed to meet the lowest estimates of N critical loads for the region.
Yi-Ying Chen and Sebastiaan Luyssaert
Biogeosciences, 20, 349–363, https://doi.org/10.5194/bg-20-349-2023, https://doi.org/10.5194/bg-20-349-2023, 2023
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Tropical cyclones are typically assumed to be associated with ecosystem damage. This study challenges this assumption and suggests that instead of reducing leaf area, cyclones in East Asia may increase leaf area by alleviating water stress.
Deborah F. McGlynn, Graham Frazier, Laura E. R. Barry, Manuel T. Lerdau, Sally E. Pusede, and Gabriel Isaacman-VanWertz
Biogeosciences, 20, 45–55, https://doi.org/10.5194/bg-20-45-2023, https://doi.org/10.5194/bg-20-45-2023, 2023
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Using a custom-made gas chromatography flame ionization detector, 2 years of speciated hourly biogenic volatile organic compound data were collected in a forest in central Virginia. We identify diurnal and seasonal variability in the data, which is shown to impact atmospheric oxidant budgets. A comparison with emission models identified discrepancies with implications for model outcomes. We suggest increased monitoring of speciated biogenic volatile organic compounds to improve modeled results.
Luke D. Schiferl, Jennifer D. Watts, Erik J. L. Larson, Kyle A. Arndt, Sébastien C. Biraud, Eugénie S. Euskirchen, Jordan P. Goodrich, John M. Henderson, Aram Kalhori, Kathryn McKain, Marikate E. Mountain, J. William Munger, Walter C. Oechel, Colm Sweeney, Yonghong Yi, Donatella Zona, and Róisín Commane
Biogeosciences, 19, 5953–5972, https://doi.org/10.5194/bg-19-5953-2022, https://doi.org/10.5194/bg-19-5953-2022, 2022
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As the Arctic rapidly warms, vast stores of thawing permafrost could release carbon dioxide (CO2) into the atmosphere. We combined observations of atmospheric CO2 concentrations from aircraft and a tower with observed CO2 fluxes from tundra ecosystems and found that the Alaskan North Slope in not a consistent source nor sink of CO2. Our study shows the importance of using both site-level and atmospheric measurements to constrain regional net CO2 fluxes and improve biogenic processes in models.
Pascal Wintjen, Frederik Schrader, Martijn Schaap, Burkhard Beudert, Richard Kranenburg, and Christian Brümmer
Biogeosciences, 19, 5287–5311, https://doi.org/10.5194/bg-19-5287-2022, https://doi.org/10.5194/bg-19-5287-2022, 2022
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For the first time, we compared four methods for estimating the annual dry deposition of total reactive nitrogen into a low-polluted forest ecosystem. In our analysis, we used 2.5 years of flux measurements, an in situ modeling approach, a large-scale chemical transport model (CTM), and canopy budget models. Annual nitrogen dry deposition budgets ranged between 4.3 and 6.7 kg N ha−1 a−1, depending on the applied method.
Michael Staudt, Juliane Daussy, Joseph Ingabire, and Nafissa Dehimeche
Biogeosciences, 19, 4945–4963, https://doi.org/10.5194/bg-19-4945-2022, https://doi.org/10.5194/bg-19-4945-2022, 2022
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We studied the short- and long-term effects of CO2 as a function of temperature on monoterpene emissions from holm oak. Similarly to isoprene, emissions decreased non-linearly with increasing CO2, with no differences among compounds and chemotypes. The CO2 response was modulated by actual leaf and growth temperature but not by growth CO2. Estimates of annual monoterpene release under double CO2 suggest that CO2 inhibition does not offset the increase in emissions due to expected warming.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Valery A. Isidorov and Andrej A. Zaitsev
Biogeosciences, 19, 4715–4746, https://doi.org/10.5194/bg-19-4715-2022, https://doi.org/10.5194/bg-19-4715-2022, 2022
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Biogenic volatile organic compounds (VOCs) play a critical role in earth-system processes: they are
main playersin the formation of tropospheric O3 and secondary aerosols, which have a significant impact on climate, human health and crops. A complex mixture of VOCs, formed as a result of physicochemical and biological processes, is released into the atmosphere from the forest floor. This review presents data on the composition of VOCs and contribution of various processes to their emissions.
David S. McLagan, Harald Biester, Tomas Navrátil, Stephan M. Kraemer, and Lorenz Schwab
Biogeosciences, 19, 4415–4429, https://doi.org/10.5194/bg-19-4415-2022, https://doi.org/10.5194/bg-19-4415-2022, 2022
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Spruce and larch trees are effective archiving species for historical atmospheric mercury using growth rings of bole wood. Mercury stable isotope analysis proved an effective tool to characterise industrial mercury signals and assess mercury uptake pathways (leaf uptake for both wood and bark) and mercury cycling within the trees. These data detail important information for understanding the mercury biogeochemical cycle particularly in forest systems.
Xin Yu, René Orth, Markus Reichstein, Michael Bahn, Anne Klosterhalfen, Alexander Knohl, Franziska Koebsch, Mirco Migliavacca, Martina Mund, Jacob A. Nelson, Benjamin D. Stocker, Sophia Walther, and Ana Bastos
Biogeosciences, 19, 4315–4329, https://doi.org/10.5194/bg-19-4315-2022, https://doi.org/10.5194/bg-19-4315-2022, 2022
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Identifying drought legacy effects is challenging because they are superimposed on variability driven by climate conditions in the recovery period. We develop a residual-based approach to quantify legacies on gross primary productivity (GPP) from eddy covariance data. The GPP reduction due to legacy effects is comparable to the concurrent effects at two sites in Germany, which reveals the importance of legacy effects. Our novel methodology can be used to quantify drought legacies elsewhere.
Anders Lindroth, Norbert Pirk, Ingibjörg S. Jónsdóttir, Christian Stiegler, Leif Klemedtsson, and Mats B. Nilsson
Biogeosciences, 19, 3921–3934, https://doi.org/10.5194/bg-19-3921-2022, https://doi.org/10.5194/bg-19-3921-2022, 2022
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We measured the fluxes of carbon dioxide and methane between a moist moss tundra and the atmosphere on Svalbard in order to better understand how such ecosystems are affecting the climate and vice versa. We found that the system was a small sink of carbon dioxide and a small source of methane. These fluxes are small in comparison with other tundra ecosystems in the high Arctic. Analysis of temperature sensitivity showed that respiration was more sensitive than photosynthesis above about 6 ℃.
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
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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.
Siqi Li, Wei Zhang, Xunhua Zheng, Yong Li, Shenghui Han, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, and Chong Zhang
Biogeosciences, 19, 3001–3019, https://doi.org/10.5194/bg-19-3001-2022, https://doi.org/10.5194/bg-19-3001-2022, 2022
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The CNMM–DNDC model was modified to simulate ammonia volatilization (AV) from croplands. AV from cultivated uplands followed the first-order kinetics, which was jointly regulated by the factors of soil properties and meteorological conditions. AV simulation from rice paddy fields was improved by incorporating Jayaweera–Mikkelsen mechanisms. The modified model performed well in simulating the observed cumulative AV measured from 63 fertilization events in China.
Matthias Volk, Matthias Suter, Anne-Lena Wahl, and Seraina Bassin
Biogeosciences, 19, 2921–2937, https://doi.org/10.5194/bg-19-2921-2022, https://doi.org/10.5194/bg-19-2921-2022, 2022
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Because soils are an important sink for greenhouse gasses, we subjected sub-alpine grassland to a six-level climate change treatment.
Two independent methods showed that at warming > 1.5 °C the grassland ecosystem lost ca. 14 % or ca. 1 kg C m−2 in 5 years.
This shrinking of the terrestrial C sink implies a substantial positive feedback to the atmospheric greenhouse effect.
It is likely that this dramatic C loss is a transient effect before a new, climate-adjusted steady state is reached.
Johan A. Eckdahl, Jeppe A. Kristensen, and Daniel B. Metcalfe
Biogeosciences, 19, 2487–2506, https://doi.org/10.5194/bg-19-2487-2022, https://doi.org/10.5194/bg-19-2487-2022, 2022
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This study found climate to be a driving force for increasing per area emissions of greenhouse gases and removal of important nutrients from high-latitude forests due to wildfire. It used detailed direct measurements over a large area to uncover patterns and mechanisms of restructuring of forest carbon and nitrogen pools that are extrapolatable to larger regions. It also takes a step forward in filling gaps in global knowledge of northern forest response to climate-change-strengthened wildfires.
Sparkle L. Malone, Youmi Oh, Kyle A. Arndt, George Burba, Roisin Commane, Alexandra R. Contosta, Jordan P. Goodrich, Henry W. Loescher, Gregory Starr, and Ruth K. Varner
Biogeosciences, 19, 2507–2522, https://doi.org/10.5194/bg-19-2507-2022, https://doi.org/10.5194/bg-19-2507-2022, 2022
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To understand the CH4 flux potential of natural ecosystems and agricultural lands in the United States of America, a multi-scale CH4 observation network focused on CH4 flux rates, processes, and scaling methods is required. This can be achieved with a network of ground-based observations that are distributed based on climatic regions and land cover.
Bruna R. F. Oliveira, Jan J. Keizer, and Thomas Foken
Biogeosciences, 19, 2235–2243, https://doi.org/10.5194/bg-19-2235-2022, https://doi.org/10.5194/bg-19-2235-2022, 2022
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This study analyzes the impacts of this windthrow on the aerodynamic characteristics of zero-plane displacement and roughness length and, ultimately, their implications for the turbulent fluxes. The turbulent fluxes were only affected to a minor degree by the windthrow, but the footprint area of the flux tower changed markedly so that the target area of the measurements had to be redetermined.
Minttu Havu, Liisa Kulmala, Pasi Kolari, Timo Vesala, Anu Riikonen, and Leena Järvi
Biogeosciences, 19, 2121–2143, https://doi.org/10.5194/bg-19-2121-2022, https://doi.org/10.5194/bg-19-2121-2022, 2022
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The carbon sequestration potential of two street tree species and the soil beneath them was quantified with the urban land surface model SUEWS and the soil carbon model Yasso. The street tree plantings turned into a modest sink of carbon from the atmosphere after 14 years. Overall, the results indicate the importance of soil in urban carbon sequestration estimations, as soil respiration exceeded the carbon uptake in the early phase, due to the high initial carbon loss from the soil.
Jarmo Mäkelä, Laila Melkas, Ivan Mammarella, Tuomo Nieminen, Suyog Chandramouli, Rafael Savvides, and Kai Puolamäki
Biogeosciences, 19, 2095–2099, https://doi.org/10.5194/bg-19-2095-2022, https://doi.org/10.5194/bg-19-2095-2022, 2022
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Causal structure discovery algorithms have been making headway into Earth system sciences, and they can be used to increase our understanding on biosphere–atmosphere interactions. In this paper we present a procedure on how to utilize prior knowledge of the domain experts together with these algorithms in order to find more robust causal structure models. We also demonstrate how to avoid pitfalls such as over-fitting and concept drift during this process.
Makoto Saito, Tomohiro Shiraishi, Ryuichi Hirata, Yosuke Niwa, Kazuyuki Saito, Martin Steinbacher, Doug Worthy, and Tsuneo Matsunaga
Biogeosciences, 19, 2059–2078, https://doi.org/10.5194/bg-19-2059-2022, https://doi.org/10.5194/bg-19-2059-2022, 2022
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This study tested combinations of two sources of AGB data and two sources of LCC data and used the same burned area satellite data to estimate BB CO emissions. Our analysis showed large discrepancies in annual mean CO emissions and explicit differences in the simulated CO concentrations among the BB emissions estimates. This study has confirmed that BB emissions estimates are sensitive to the land surface information on which they are based.
Johannes Gensheimer, Alexander J. Turner, Philipp Köhler, Christian Frankenberg, and Jia Chen
Biogeosciences, 19, 1777–1793, https://doi.org/10.5194/bg-19-1777-2022, https://doi.org/10.5194/bg-19-1777-2022, 2022
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We develop a convolutional neural network, named SIFnet, that increases the spatial resolution of SIF from TROPOMI by a factor of 10 to a spatial resolution of 0.005°. SIFnet utilizes coarse SIF observations, together with a broad range of high-resolution auxiliary data. The insights gained from interpretable machine learning techniques allow us to make quantitative claims about the relationships between SIF and other common parameters related to photosynthesis.
Shihan Sun, Amos P. K. Tai, David H. Y. Yung, Anthony Y. H. Wong, Jason A. Ducker, and Christopher D. Holmes
Biogeosciences, 19, 1753–1776, https://doi.org/10.5194/bg-19-1753-2022, https://doi.org/10.5194/bg-19-1753-2022, 2022
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We developed and used a terrestrial biosphere model to compare and evaluate widely used empirical dry deposition schemes with different stomatal approaches and found that using photosynthesis-based stomatal approaches can reduce biases in modeled dry deposition velocities in current chemical transport models. Our study shows systematic errors in current dry deposition schemes and the importance of representing plant ecophysiological processes in models under a changing climate.
Ka Ming Fung, Maria Val Martin, and Amos P. K. Tai
Biogeosciences, 19, 1635–1655, https://doi.org/10.5194/bg-19-1635-2022, https://doi.org/10.5194/bg-19-1635-2022, 2022
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Fertilizer-induced ammonia detrimentally affects the environment by not only directly damaging ecosystems but also indirectly altering climate and soil fertility. To quantify these secondary impacts, we enabled CESM to simulate ammonia emission, chemical evolution, and deposition as a continuous cycle. If synthetic fertilizer use is to soar by 30 % from today's level, we showed that the counteracting impacts will increase the global ammonia emission by 3.3 Tg N per year.
Lena Wohlgemuth, Pasi Rautio, Bernd Ahrends, Alexander Russ, Lars Vesterdal, Peter Waldner, Volkmar Timmermann, Nadine Eickenscheidt, Alfred Fürst, Martin Greve, Peter Roskams, Anne Thimonier, Manuel Nicolas, Anna Kowalska, Morten Ingerslev, Päivi Merilä, Sue Benham, Carmen Iacoban, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 19, 1335–1353, https://doi.org/10.5194/bg-19-1335-2022, https://doi.org/10.5194/bg-19-1335-2022, 2022
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Gaseous mercury is present in the atmosphere all over the globe. During the growing season, plants take up mercury from the air in a similar way as CO2. We investigated which factors impact this vegetational mercury uptake by analyzing a large dataset of leaf mercury uptake rates of trees in Europe. As a result, we conclude that mercury uptake is foremost controlled by tree-intrinsic traits like physiological activity but also by climatic factors like dry conditions in the air and in soils.
Junqi Wei, Xiaoyan Li, Lei Liu, Torben Røjle Christensen, Zhiyun Jiang, Yujun Ma, Xiuchen Wu, Hongyun Yao, and Efrén López-Blanco
Biogeosciences, 19, 861–875, https://doi.org/10.5194/bg-19-861-2022, https://doi.org/10.5194/bg-19-861-2022, 2022
Short summary
Short summary
Although water availability has been linked to the response of ecosystem carbon (C) sink–source to climate warming, the mechanisms by which C uptake responds to soil moisture remain unclear. We explored how soil water and other environmental drivers modulate net C uptake in an alpine swamp meadow. Results reveal that nearly saturated soil conditions during warm seasons can help to maintain lower ecosystem respiration and therefore enhance the C sequestration capacity in this alpine swamp meadow.
Cited articles
Abbasian, H., Solgi, E., Mohsen Hosseini, S., and Hossein Kia, S.: Modeling
terrestrial net ecosystem exchange using machine learning techniques based
on flux tower measurements, Ecol. Model., 466, 109901,
https://doi.org/10.1016/j.ecolmodel.2022.109901, 2022.
Adams, D. C., Gurevitch, J., and Rosenberg, M. S.: Resampling tests for
meta analysis of ecological data, Ecology, 78, 1277–1283, 1997.
Baldocchi, D. D.: Assessing the eddy covariance technique for evaluating
carbon dioxide exchange rates of ecosystems: past, present and future, Global Change Biol., 9,
479–492, https://doi.org/10.1046/j.1365-2486.2003.00629.x, 2003.
Berryman, E. M., Vanderhoof, M. K., Bradford, J. B., Hawbaker, T. J., Henne,
P. D., Burns, S. P., Frank, J. M., Birdsey, R. A., and Ryan, M. G.:
Estimating soil respiration in a subalpine landscape using point, terrain,
climate, and greenness data, J. Geophys. Res.-Biogeo., 123, 3231–3249, 2018.
Borenstein, M., Hedges, L. V., Higgins, J. P., and Rothstein, H. R.:
Introduction to meta-analysis, John Wiley & Sons, https://doi.org/10.1002/9780470743386, 2011.
Cho, S., Kang, M., Ichii, K., Kim, J., Lim, J.-H., Chun, J.-H., Park, C.-W.,
Kim, H. S., Choi, S.-W., and Lee, S.-H.: Evaluation of forest carbon uptake
in South Korea using the national flux tower network, remote sensing, and
data-driven technology, Agr. Forest Meteorol., 311, 108653, https://doi.org/10.1016/j.agrformet.2021.108653,
2021.
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn,
M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi,
D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G.,
Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K.,
Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A.,
Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa,
H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T.,
Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick,
K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E.,
Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E.
S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C.,
Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A.,
Ueyama, M., Vargas, R., Wood, J. D., and Zona, D.: Representativeness of
Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites,
Agr. Forest Meteorol., 301–302, 108350,
https://doi.org/10.1016/j.agrformet.2021.108350, 2021.
Cleverly, J., Vote, C., Isaac, P., Ewenz, C., Harahap, M., Beringer, J.,
Campbell, D. I., Daly, E., Eamus, D., He, L., Hunt, J., Grace, P., Hutley,
L. B., Laubach, J., McCaskill, M., Rowlings, D., Rutledge Jonker, S.,
Schipper, L. A., Schroder, I., Teodosio, B., Yu, Q., Ward, P. R., Walker, J.
P., Webb, J. A., and Grover, S. P. P.: Carbon, water and energy fluxes in
agricultural systems of Australia and New Zealand, Agr. Forest Meteorol., 287, 107934,
https://doi.org/10.1016/j.agrformet.2020.107934, 2020.
Cranko Page, J., De Kauwe, M. G., Abramowitz, G., Cleverly, J., Hinko-Najera, N., Hovenden, M. J., Liu, Y., Pitman, A. J., and Ogle, K.: Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems, Biogeosciences, 19, 1913–1932, https://doi.org/10.5194/bg-19-1913-2022, 2022.
Cui, X., Goff, T., Cui, S., Menefee, D., Wu, Q., Rajan, N., Nair, S.,
Phillips, N., and Walker, F.: Predicting carbon and water vapor fluxes using
machine learning and novel feature ranking algorithms, Sci. Total
Environ., 775, 145130, https://doi.org/10.1016/j.scitotenv.2021.145130, 2021.
Don, A., Schumacher, J., and Freibauer, A.: Impact of tropical land-use
change on soil organic carbon stocks – a meta-analysis, Glob. Change Biol., 17, 1658–1670,
https://doi.org/10.1111/j.1365-2486.2010.02336.x, 2011.
Field, A. P. and Gillett, R.: How to do a meta analysis, British Journal of
Mathematical and Statistical Psychology, 63, 665–694, 2010.
Fu, D., Chen, B., Zhang, H., Wang, J., Black, T. A., Amiro, B. D., Bohrer,
G., Bolstad, P., Coulter, R., and Rahman, A. F.: Estimating landscape net
ecosystem exchange at high spatial–temporal resolution based on Landsat
data, an improved upscaling model framework, and eddy covariance flux
measurements, Remote Sens. Environ., 141, 90–104, 2014.
Fu, Z., Stoy, P. C., Poulter, B., Gerken, T., Zhang, Z., Wakbulcho, G., and
Niu, S.: Maximum carbon uptake rate dominates the interannual variability of
global net ecosystem exchange, Global Change Biology, 25, 3381–3394, 2019.
Hao, Y., Wang, Y., Mei, X., and Cui, X.: The response of ecosystem CO2
exchange to small precipitation pulses over a temperate steppe, Plant Ecol,
209, 335–347, https://doi.org/10.1007/s11258-010-9766-1, 2010.
Harris, N. L., Gibbs, D. A., Baccini, A., Birdsey, R. A., de Bruin, S.,
Farina, M., Fatoyinbo, L., Hansen, M. C., Herold, M., Houghton, R. A.,
Potapov, P. V., Suarez, D. R., Roman-Cuesta, R. M., Saatchi, S. S., Slay, C.
M., Turubanova, S. A., and Tyukavina, A.: Global maps of twenty-first
century forest carbon fluxes, Nat. Clim. Chang., 11, 234–240,
https://doi.org/10.1038/s41558-020-00976-6, 2021.
Huemmrich, K. F., Campbell, P., Landis, D., and Middleton, E.: Developing a
common globally applicable method for optical remote sensing of ecosystem
light use efficiency, Remote Sens. Environ., 230, 111190, https://doi.org/10.1016/j.rse.2019.05.009, 2019.
Jongen, M., Pereira, J. S., Aires, L. M. I., and Pio, C. A.: The effects of
drought and timing of precipitation on the inter-annual variation in
ecosystem-atmosphere exchange in a Mediterranean grassland, Agr. Forest Meteorol., 151, 595–606,
https://doi.org/10.1016/j.agrformet.2011.01.008, 2011.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D.,
Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., and Chen, J.: Global
patterns of land atmosphere fluxes of carbon dioxide, latent heat, and
sensible heat derived from eddy covariance, satellite, and meteorological
observations, J. Geophys. Res.-Biogeo., 116, G00J07, https://doi.org/10.1029/2010JG001566, 2011.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein,
P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B.,
Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y.-P.,
Weber, U., Zaehle, S., and Zeng, N.: Compensatory water effects link yearly
global land CO2 sink changes to temperature, Nature, 541, 516–520,
https://doi.org/10.1038/nature20780, 2017.
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020.
Kaur, H., Pannu, H. S., and Malhi, A. K.: A Systematic Review on Imbalanced
Data Challenges in Machine Learning: Applications and Solutions, ACM Comput.
Surv., 52, 1–36, https://doi.org/10.1145/3343440, 2019.
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP), Geosci. Model Dev., 8, 3695–3713, https://doi.org/10.5194/gmd-8-3695-2015, 2015.
Liu, Q., Zhang, Y., Liu, B., Amonette, J. E., Lin, Z., Liu, G., Ambus, P.,
and Xie, Z.: How does biochar influence soil N cycle?, A meta-analysis, Plant
Soil, 426, 211–225, 2018.
Luyssaert, S., Janssens, I. A., Sulkava, M., Papale, D., Dolman, A. J.,
Reichstein, M., Hollmén, J., Martin, J. G., Suni, T., Vesala, T.,
Loustau, D., Law, B. E., and Moors, E. J.: Photosynthesis drives anomalies
in net carbon-exchange of pine forests at different latitudes, Glob. Change Biol., 13,
2110–2127, https://doi.org/10.1111/j.1365-2486.2007.01432.x, 2007.
Marcot, B. G. and Hanea, A. M.: What is an optimal value of k in k-fold
cross-validation in discrete Bayesian network analysis?, Comput. Stat., 36,
2009–2031, https://doi.org/10.1007/s00180-020-00999-9, 2021.
Mitchell, S., Beven, K., and Freer, J.: Multiple sources of predictive
uncertainty in modeled estimates of net ecosystem CO2 exchange, Ecol. Model., 220, 3259–3270, https://doi.org/10.1016/j.ecolmodel.2009.08.021,
2009.
Moffat, A. M., Papale, D., Reichstein, M., Hollinger, D. Y., Richardson, A.
D., Barr, A. G., Beckstein, C., Braswell, B. H., Churkina, G., Desai, A. R.,
Falge, E., Gove, J. H., Heimann, M., Hui, D., Jarvis, A. J., Kattge, J.,
Noormets, A., and Stauch, V. J.: Comprehensive comparison of gap-filling
techniques for eddy covariance net carbon fluxes, Agr. Forest Meteorol., 147, 209–232,
https://doi.org/10.1016/j.agrformet.2007.08.011, 2007.
Moffat, A. M., Beckstein, C., Churkina, G., Mund, M., and Heimann, M.:
Characterization of ecosystem responses to climatic controls using
artificial neural networks, Glob. Change Biol., 16, 2737–2749,
https://doi.org/10.1111/j.1365-2486.2010.02171.x, 2010.
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., and Prisma Group:
Preferred reporting items for systematic reviews and meta-analyses: the
PRISMA statement, PLoS medicine, 6, e1000097, https://doi.org/10.1136/bmj.b2535, 2009.
Moon, T. K.: The expectation-maximization algorithm, IEEE Signal Processing Magazine, 13, 47–60, https://doi.org/10.1109/79.543975, 1996.
Papale, D. and Valentini, R.: A new assessment of European forests carbon
exchanges by eddy fluxes and artificial neural network spatialization, Glob. Change Biol., 9,
525–535, https://doi.org/10.1046/j.1365-2486.2003.00609.x, 2003.
Park, S.-B., Knohl, A., Lucas-Moffat, A. M., Migliavacca, M., Gerbig, C.,
Vesala, T., Peltola, O., Mammarella, I., Kolle, O., Lavrič, J. V.,
Prokushkin, A., and Heimann, M.: Strong radiative effect induced by clouds
and smoke on forest net ecosystem productivity in central Siberia,
Agr. Forest Meteorol., 250, 376–387,
https://doi.org/10.1016/j.agrformet.2017.09.009, 2018.
Pearl, J.: Bayesian netwcrks: A model cf self-activated memory for
evidential reasoning, in: Proceedings of the 7th Conference of the Cognitive
Science Society, University of California, Irvine, CA, USA, 15–17, 1985.
Peltola, O., Vesala, T., Gao, Y., Räty, O., Alekseychik, P., Aurela, M., Chojnicki, B., Desai, A. R., Dolman, A. J., Euskirchen, E. S., Friborg, T., Göckede, M., Helbig, M., Humphreys, E., Jackson, R. B., Jocher, G., Joos, F., Klatt, J., Knox, S. H., Kowalska, N., Kutzbach, L., Lienert, S., Lohila, A., Mammarella, I., Nadeau, D. F., Nilsson, M. B., Oechel, W. C., Peichl, M., Pypker, T., Quinton, W., Rinne, J., Sachs, T., Samson, M., Schmid, H. P., Sonnentag, O., Wille, C., Zona, D., and Aalto, T.: Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations, Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, 2019.
Reed, D. E., Poe, J., Abraha, M., Dahlin, K. M., and Chen, J.: Modeled
Surface-Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region
Using Neural Networks, J. Geophys. Res.-Biogeo., 126, e2021JG006363,
https://doi.org/10.1029/2021JG006363, 2021.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J.,
Carvalhais, N., and Prabhat: Deep learning and process understanding for
data-driven Earth system science, Nature, 566, 195–204,
https://doi.org/10.1038/s41586-019-0912-1, 2019.
Reitz, O., Graf, A., Schmidt, M., Ketzler, G., and Leuchner, M.: Upscaling
Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning,
J. Geophys. Res.-Biogeo., 126, e2020JG005814, https://doi.org/10.1029/2020JG005814, 2021.
Ruppert, J., Mauder, M., Thomas, C., and Lüers, J.: Innovative
gap-filling strategy for annual sums of CO2 net ecosystem exchange, Agr. Forest Meteorol., 138,
5–18, https://doi.org/10.1016/j.agrformet.2006.03.003, 2006.
Shi, H., Luo, G., Zheng, H., Chen, C., Bai, J., Liu, T., Ochege, F. U., and
De Maeyer, P.: Coupling the water-energy-food-ecology nexus into a Bayesian
network for water resources analysis and management in the Syr Darya River
basin, J. Hydrol., 581, 124387,
https://doi.org/10.1016/j.jhydrol.2019.124387, 2020.
Shi, H., Hellwich, O., Luo, G., Chen, C., He, H., Ochege, F. U., Van de
Voorde, T., Kurban, A., and de Maeyer, P.: A global meta-analysis of soil
salinity prediction integrating satellite remote sensing, soil sampling, and
machine learning, IEEE T. Geosci. Remote, 60, 1–15, https://doi.org/10.1109/TGRS.2021.3109819, 2021.
Tian, X., Yan, M., van der Tol, C., Li, Z., Su, Z., Chen, E., Li, X., Li,
L., Wang, X., Pan, X., Gao, L., and Han, Z.: Modeling forest above-ground
biomass dynamics using multi-source data and incorporated models: A case
study over the qilian mountains, Agr. Forest Meteorol., 246,
1–14, https://doi.org/10.1016/j.agrformet.2017.05.026, 2017.
Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, 2016.
Van Hulse, J., Khoshgoftaar, T. M., and Napolitano, A.: Experimental
perspectives on learning from imbalanced data, in: Proceedings of the 24th
international conference on Machine learning, New York, NY, USA, 935–942,
https://doi.org/10.1145/1273496.1273614, 2007.
Virkkala, A.-M., Aalto, J., Rogers, B. M., Tagesson, T., Treat, C. C.,
Natali, S. M., Watts, J. D., Potter, S., Lehtonen, A., Mauritz, M., Schuur,
E. A. G., Kochendorfer, J., Zona, D., Oechel, W., Kobayashi, H., Humphreys,
E., Goeckede, M., Iwata, H., Lafleur, P. M., Euskirchen, E. S., Bokhorst,
S., Marushchak, M., Martikainen, P. J., Elberling, B., Voigt, C., Biasi, C.,
Sonnentag, O., Parmentier, F.-J. W., Ueyama, M., Celis, G., St.Louis, V. L.,
Emmerton, C. A., Peichl, M., Chi, J., Järveoja, J., Nilsson, M. B.,
Oberbauer, S. F., Torn, M. S., Park, S.-J., Dolman, H., Mammarella, I.,
Chae, N., Poyatos, R., López-Blanco, E., Christensen, T. R., Kwon, M.
J., Sachs, T., Holl, D., and Luoto, M.: Statistical upscaling of ecosystem
CO2 fluxes across the terrestrial tundra and boreal domain: Regional
patterns and uncertainties, Global Change Biol., 27, 4040–4059,
https://doi.org/10.1111/gcb.15659, 2021.
Walther, S., Besnard, S., Nelson, J. A., El-Madany, T. S., Migliavacca, M., Weber, U., Carvalhais, N., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A. S., Panov, A. V., and Jung, M.: Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set, Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, 2022.
Wu, Z., Dijkstra, P., Koch, G. W., Peñuelas, J., and Hungate, B. A.:
Responses of terrestrial ecosystems to temperature and precipitation change:
a meta-analysis of experimental manipulation, Glob. Change Biol., 17, 927–942,
https://doi.org/10.1111/j.1365-2486.2010.02302.x, 2011.
Yan, J., Zhang, Y., Yu, G., Zhou, G., Zhang, L., Li, K., Tan, Z., and Sha,
L.: Seasonal and inter-annual variations in net ecosystem exchange of two
old-growth forests in southern China, Agr. Forest Meteorol.,
182, 257–265, https://doi.org/10.1016/j.agrformet.2013.03.002, 2013.
Zeng, J., Matsunaga, T., Tan, Z.-H., Saigusa, N., Shirai, T., Tang, Y.,
Peng, S., and Fukuda, Y.: Global terrestrial carbon fluxes of 1999–2019
estimated by upscaling eddy covariance data with a random forest, Sci. Data, 7, 313,
https://doi.org/10.1038/s41597-020-00653-5, 2020.
Zhang, C., Brodylo, D., Sirianni, M. J., Li, T., Comas, X., Douglas, T. A.,
and Starr, G.: Mapping CO2 fluxes of cypress swamp and marshes in the
Greater Everglades using eddy covariance measurements and Landsat data,
Remote Sens. Environ., 262, 112523,
https://doi.org/10.1016/j.rse.2021.112523, 2021.
Zhou, Y., Li, X., Gao, Y., He, M., Wang, M., Wang, Y., Zhao, L., and Li, Y.:
Carbon fluxes response of an artificial sand-binding vegetation system to
rainfall variation during the growing season in the Tengger Desert, J. Environ. Manage., 266, 110556,
https://doi.org/10.1016/j.jenvman.2020.110556, 2020.
Zhu, S., Clement, R., McCalmont, J., Davies, C. A., and Hill, T.: Stable
gap-filling for longer eddy covariance data gaps: A globally validated
machine-learning approach for carbon dioxide, water, and energy fluxes,
Agr. Forest Meteorol., 314, 108777,
https://doi.org/10.1016/j.agrformet.2021.108777, 2022.
Short summary
A number of studies have been conducted by using machine learning approaches to simulate carbon fluxes. We performed a meta-analysis of these net ecosystem exchange (NEE) simulations. Random forests and support vector machines performed better than other algorithms. Models with larger timescales had a lower accuracy. For different plant functional types (PFTs), there were significant differences in the predictors used and their effects on model accuracy.
A number of studies have been conducted by using machine learning approaches to simulate carbon...
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