Articles | Volume 6, issue 7
https://doi.org/10.5194/bg-6-1181-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/bg-6-1181-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
17 Jul 2009
CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands
U. Rascher
Institute of Chemistry and Dynamics of the Geosphere, ICG-3: Phytosphere, Forschungszentrum Jülich, Leo-Brandt-Str., 52425 Jülich, Germany
G. Agati
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
L. Alonso
Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner, 50, 46100 Burjassot, Valencia, Spain
G. Cecchi
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
S. Champagne
Laboratoire de Météorologie Dynamique, CNRS, Ecole Polytechnique, 91128 Palaiseau, France
R. Colombo
Remote Sensing of Environmental Dynamics Lab., DISAT, University of Milan-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
A. Damm
Geomatics Lab, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
F. Daumard
Laboratoire de Météorologie Dynamique, CNRS, Ecole Polytechnique, 91128 Palaiseau, France
E. de Miguel
Remote Sensing Laboratory. Instituto Nacional de Técnica Aeroespacial. Carr. de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
G. Fernandez
Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner, 50, 46100 Burjassot, Valencia, Spain
B. Franch
Global Change Unit, Imaging Processing Laboratory, University of Valencia, Pol. "La Coma", s/n, 46980 Paterna, Valencia, Spain
J. Franke
Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Walter-Flex-Strasse 3, 53113 Bonn, Germany
C. Gerbig
Max Planck Institute for Biogeochemistry, Hans Knoell Str. 10, 07745 Jena, Germany
B. Gioli
11IBIMET-CNR, Instituto di Biometeorologia, Consiglia Nazionale delle Ricerche, Via G. Caproni 8, 50145 Firenze, Italy
J. A. Gómez
Remote Sensing Laboratory. Instituto Nacional de Técnica Aeroespacial. Carr. de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
Y. Goulas
Laboratoire de Météorologie Dynamique, CNRS, Ecole Polytechnique, 91128 Palaiseau, France
L. Guanter
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Department 1 – Geodesy and Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany
Ó. Gutiérrez-de-la-Cámara
Remote Sensing Laboratory. Instituto Nacional de Técnica Aeroespacial. Carr. de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
K. Hamdi
Institute of Chemistry and Dynamics of the Geosphere, ICG-3: Phytosphere, Forschungszentrum Jülich, Leo-Brandt-Str., 52425 Jülich, Germany
P. Hostert
Geomatics Lab, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
M. Jiménez
Remote Sensing Laboratory. Instituto Nacional de Técnica Aeroespacial. Carr. de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
M. Kosvancova
Laboratory of Plants Ecological Physiology, Division of Ecosystem Processes, Institute of Systems Biology and Ecology, Počíčí 3b, 60300 Brno, Czech Republic
D. Lognoli
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
M. Meroni
Remote Sensing of Environmental Dynamics Lab., DISAT, University of Milan-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
F. Miglietta
11IBIMET-CNR, Instituto di Biometeorologia, Consiglia Nazionale delle Ricerche, Via G. Caproni 8, 50145 Firenze, Italy
A. Moersch
Institute of Chemistry and Dynamics of the Geosphere, ICG-3: Phytosphere, Forschungszentrum Jülich, Leo-Brandt-Str., 52425 Jülich, Germany
J. Moreno
Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner, 50, 46100 Burjassot, Valencia, Spain
I. Moya
Laboratoire de Météorologie Dynamique, CNRS, Ecole Polytechnique, 91128 Palaiseau, France
B. Neininger
Metair AG, Flugpaltzm, 8915 Hausen am Albis, Switzerland
A. Okujeni
Geomatics Lab, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
A. Ounis
Laboratoire de Météorologie Dynamique, CNRS, Ecole Polytechnique, 91128 Palaiseau, France
L. Palombi
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
V. Raimondi
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
A. Schickling
Institute for Geophysics and Meteorology, University of Cologne, Kerpener Str. 13, 50937 Cologne, Germany
J. A. Sobrino
Global Change Unit, Imaging Processing Laboratory, University of Valencia, Pol. "La Coma", s/n, 46980 Paterna, Valencia, Spain
M. Stellmes
Remote Sensing Department, University of Trier, 54286 Trier, Germany
G. Toci
IFAC-CNR, Istituto di Fisica Applicata "Nello Carrara", Consiglio Nazionale delle Ricerche, via Madonna del Piano10, 50019, Sesto F. no, Firenze, Italy
P. Toscano
11IBIMET-CNR, Instituto di Biometeorologia, Consiglia Nazionale delle Ricerche, Via G. Caproni 8, 50145 Firenze, Italy
T. Udelhoven
CRP-Gabriel Lippmann, Département "Environnement et Agro-biotechnologies", Geomatic Platform, 41, rue du Brill, 4422 Belvaux, Luxembourg
S. van der Linden
Geomatics Lab, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
A. Zaldei
11IBIMET-CNR, Instituto di Biometeorologia, Consiglia Nazionale delle Ricerche, Via G. Caproni 8, 50145 Firenze, Italy
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Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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Prajwal Khanal, Anne J. Hoek Van Dijke, Timo Schaffhauser, Wantong Li, Sinikka J. Paulus, Chunhui Zhan, and René Orth
Biogeosciences, 21, 1533–1547, https://doi.org/10.5194/bg-21-1533-2024, https://doi.org/10.5194/bg-21-1533-2024, 2024
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Anna-Maria Virkkala, Pekka Niittynen, Julia Kemppinen, Maija E. Marushchak, Carolina Voigt, Geert Hensgens, Johanna Kerttula, Konsta Happonen, Vilna Tyystjärvi, Christina Biasi, Jenni Hultman, Janne Rinne, and Miska Luoto
Biogeosciences, 21, 335–355, https://doi.org/10.5194/bg-21-335-2024, https://doi.org/10.5194/bg-21-335-2024, 2024
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Thomas Baer, Gerhard Furrer, Stephan Zimmermann, and Patrick Schleppi
Biogeosciences, 20, 4577–4589, https://doi.org/10.5194/bg-20-4577-2023, https://doi.org/10.5194/bg-20-4577-2023, 2023
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Nitrogen (N) deposition to forest ecosystems is a matter of concern because it affects their nutrient status and makes their soil acidic. We observed an ongoing acidification in a montane forest in central Switzerland even if the subsoil of this site contains carbonates and is thus well buffered. We experimentally added N to simulate a higher pollution, and this increased the acidification. After 25 years of study, however, we can see the first signs of recovery, also under higher N deposition.
Huiying Xu, Han Wang, Iain Colin Prentice, and Sandy P. Harrison
Biogeosciences, 20, 4511–4525, https://doi.org/10.5194/bg-20-4511-2023, https://doi.org/10.5194/bg-20-4511-2023, 2023
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István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
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Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Keri L. Bowering, Kate A. Edwards, and Susan E. Ziegler
Biogeosciences, 20, 2189–2206, https://doi.org/10.5194/bg-20-2189-2023, https://doi.org/10.5194/bg-20-2189-2023, 2023
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Dissolved organic matter (DOM) mobilized from surface soils is a source of carbon (C) for deeper mineral horizons but also a mechanism of C loss. Composition of DOM mobilized in boreal forests varied more by season than as a result of forest harvesting. Results suggest reduced snowmelt and increased fall precipitation enhance DOM properties promoting mineral soil C stores. These findings, coupled with hydrology, can inform on soil C fate and boreal forest C balance in response to climate change.
Bharat Sharma, Jitendra Kumar, Auroop R. Ganguly, and Forrest M. Hoffman
Biogeosciences, 20, 1829–1841, https://doi.org/10.5194/bg-20-1829-2023, https://doi.org/10.5194/bg-20-1829-2023, 2023
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Rising atmospheric carbon dioxide increases vegetation growth and causes more heatwaves and droughts. The impact of such climate extremes is detrimental to terrestrial carbon uptake capacity. We found that due to overall climate warming, about 88 % of the world's regions towards the end of 2100 will show anomalous losses in net biospheric productivity (NBP) rather than gains. More than 50 % of all negative NBP extremes were driven by the compound effect of dry, hot, and fire conditions.
Britta Greenshields, Barbara von der Lühe, Felix Schwarz, Harold J. Hughes, Aiyen Tjoa, Martyna Kotowska, Fabian Brambach, and Daniela Sauer
Biogeosciences, 20, 1259–1276, https://doi.org/10.5194/bg-20-1259-2023, https://doi.org/10.5194/bg-20-1259-2023, 2023
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Silicon (Si) can have multiple beneficial effects on crops such as oil palms. In this study, we quantified Si concentrations in various parts of an oil palm (leaflets, rachises, fruit-bunch parts) to derive Si storage estimates for the total above-ground biomass of an oil palm and 1 ha of an oil-palm plantation. We proposed a Si balance by identifying Si return (via palm fronds) and losses (via harvest) in the system and recommend management measures that enhance Si cycling.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Nagham Tabaja, David Amouroux, Lamis Chalak, François Fourel, Emmanuel Tessier, Ihab Jomaa, Milad El Riachy, and Ilham Bentaleb
Biogeosciences, 20, 619–633, https://doi.org/10.5194/bg-20-619-2023, https://doi.org/10.5194/bg-20-619-2023, 2023
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This study investigates the seasonality of the mercury (Hg) concentration of olive trees. Hg concentrations of foliage, stems, soil surface, and litter were analyzed on a monthly basis in ancient olive trees growing in two groves in Lebanon. Our study draws an adequate baseline for the eastern Mediterranean and for the region with similar climatic inventories on Hg vegetation uptake in addition to being a baseline for new studies on olive trees in the Mediterranean.
Allison N. Myers-Pigg, Karl Kaiser, Ronald Benner, and Susan E. Ziegler
Biogeosciences, 20, 489–503, https://doi.org/10.5194/bg-20-489-2023, https://doi.org/10.5194/bg-20-489-2023, 2023
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Boreal forests, historically a global sink for atmospheric CO2, store carbon in vast soil reservoirs. To predict how such stores will respond to climate warming we need to understand climate–ecosystem feedbacks. We find boreal forest soil carbon stores are maintained through enhanced nitrogen cycling with climate warming, providing direct evidence for a key feedback. Further application of the approach demonstrated here will improve our understanding of the limits of climate–ecosystem feedbacks.
Matthew P. Dannenberg, Mallory L. Barnes, William K. Smith, Miriam R. Johnston, Susan K. Meerdink, Xian Wang, Russell L. Scott, and Joel A. Biederman
Biogeosciences, 20, 383–404, https://doi.org/10.5194/bg-20-383-2023, https://doi.org/10.5194/bg-20-383-2023, 2023
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Earth's drylands provide ecosystem services to many people and will likely be strongly affected by climate change, but it is quite challenging to monitor the productivity and water use of dryland plants with satellites. We developed and tested an approach for estimating dryland vegetation activity using machine learning to combine information from multiple satellite sensors. Our approach excelled at estimating photosynthesis and water use largely due to the inclusion of satellite soil moisture.
Mark Pickering, Alessandro Cescatti, and Gregory Duveiller
Biogeosciences, 19, 4833–4864, https://doi.org/10.5194/bg-19-4833-2022, https://doi.org/10.5194/bg-19-4833-2022, 2022
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This study explores two of the most recent products in carbon productivity estimation, FLUXCOM gross primary productivity (GPP), calculated by upscaling local measurements of CO2 exchange, and remotely sensed sun-induced chlorophyll a fluorescence (SIF). High-resolution SIF data are valuable in demonstrating similarity in the SIF–GPP relationship between vegetation covers, provide an independent probe of the FLUXCOM GPP model and demonstrate the response of SIF to meteorological fluctuations.
Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, https://doi.org/10.5194/bg-19-2805-2022, 2022
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Elisabeth Mauclet, Yannick Agnan, Catherine Hirst, Arthur Monhonval, Benoît Pereira, Aubry Vandeuren, Maëlle Villani, Justin Ledman, Meghan Taylor, Briana L. Jasinski, Edward A. G. Schuur, and Sophie Opfergelt
Biogeosciences, 19, 2333–2351, https://doi.org/10.5194/bg-19-2333-2022, https://doi.org/10.5194/bg-19-2333-2022, 2022
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Arctic warming and permafrost degradation largely affect tundra vegetation. Wetter lowlands show an increase in sedges, whereas drier uplands favor shrub expansion. Here, we demonstrate that the difference in the foliar elemental composition of typical tundra vegetation species controls the change in local foliar elemental stock and potential mineral element cycling through litter production upon a shift in tundra vegetation.
Tiexi Chen, Renjie Guo, Qingyun Yan, Xin Chen, Shengjie Zhou, Chuanzhuang Liang, Xueqiong Wei, and Han Dolman
Biogeosciences, 19, 1515–1525, https://doi.org/10.5194/bg-19-1515-2022, https://doi.org/10.5194/bg-19-1515-2022, 2022
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Currently people are very concerned about vegetation changes and their driving factors, including natural and anthropogenic drivers. In this study, a general browning trend is found in Syria during 2001–2018, indicated by the vegetation index. We found that land management caused by social unrest is the main cause of this browning phenomenon. The mechanism initially reported here highlights the importance of land management impacts at the regional scale.
Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
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We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Anam M. Khan, Paul C. Stoy, James T. Douglas, Martha Anderson, George Diak, Jason A. Otkin, Christopher Hain, Elizabeth M. Rehbein, and Joel McCorkel
Biogeosciences, 18, 4117–4141, https://doi.org/10.5194/bg-18-4117-2021, https://doi.org/10.5194/bg-18-4117-2021, 2021
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Remote sensing has played an important role in the study of land surface processes. Geostationary satellites, such as the GOES-R series, can observe the Earth every 5–15 min, providing us with more observations than widely used polar-orbiting satellites. Here, we outline current efforts utilizing geostationary observations in environmental science and look towards the future of GOES observations in the carbon cycle, ecosystem disturbance, and other areas of application in environmental science.
Lydia Stolpmann, Caroline Coch, Anne Morgenstern, Julia Boike, Michael Fritz, Ulrike Herzschuh, Kathleen Stoof-Leichsenring, Yury Dvornikov, Birgit Heim, Josefine Lenz, Amy Larsen, Katey Walter Anthony, Benjamin Jones, Karen Frey, and Guido Grosse
Biogeosciences, 18, 3917–3936, https://doi.org/10.5194/bg-18-3917-2021, https://doi.org/10.5194/bg-18-3917-2021, 2021
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Our new database summarizes DOC concentrations of 2167 water samples from 1833 lakes in permafrost regions across the Arctic to provide insights into linkages between DOC and environment. We found increasing lake DOC concentration with decreasing permafrost extent and higher DOC concentrations in boreal permafrost sites compared to tundra sites. Our study shows that DOC concentration depends on the environmental properties of a lake, especially permafrost extent, ecoregion, and vegetation.
Gustaf Granath, Christopher D. Evans, Joachim Strengbom, Jens Fölster, Achim Grelle, Johan Strömqvist, and Stephan J. Köhler
Biogeosciences, 18, 3243–3261, https://doi.org/10.5194/bg-18-3243-2021, https://doi.org/10.5194/bg-18-3243-2021, 2021
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We measured element losses and impacts on water quality following a wildfire in Sweden. We observed the largest carbon and nitrogen losses during the fire and a strong pulse of elements 1–3 months after the fire that showed a fast (weeks) and a slow (months) release from the catchments. Total carbon export through water did not increase post-fire. Overall, we observed a rapid recovery of the biogeochemical cycling of elements within 3 years but still an annual net release of carbon dioxide.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Matthias Volk, Matthias Suter, Anne-Lena Wahl, and Seraina Bassin
Biogeosciences, 18, 2075–2090, https://doi.org/10.5194/bg-18-2075-2021, https://doi.org/10.5194/bg-18-2075-2021, 2021
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Grassland ecosystem services like forage production and greenhouse gas storage in the soil depend on plant growth.
In an experiment in the mountains with warming treatments, we found that despite dwindling soil water content, the grassland growth increased with up to +1.3 °C warming (annual mean) compared to present temperatures. Even at +2.4 °C the growth was still larger than at the reference site.
This suggests that plant growth will increase due to global warming in the near future.
Bernice C. Hwang and Daniel B. Metcalfe
Biogeosciences, 18, 1259–1268, https://doi.org/10.5194/bg-18-1259-2021, https://doi.org/10.5194/bg-18-1259-2021, 2021
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Despite growing recognition of herbivores as important ecosystem engineers, many major gaps remain in our understanding of how silicon and herbivory interact to shape biogeochemical processes. We highlight the need for more research particularly in natural settings as well as on the potential effects of herbivory on terrestrial silicon cycling to understand potentially critical animal–plant–soil feedbacks.
Ali Asaadi and Vivek K. Arora
Biogeosciences, 18, 669–706, https://doi.org/10.5194/bg-18-669-2021, https://doi.org/10.5194/bg-18-669-2021, 2021
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More than a quarter of the current anthropogenic CO2 emissions are taken up by land, reducing the atmospheric CO2 growth rate. This is because of the CO2 fertilization effect which benefits 80 % of global vegetation. However, if nitrogen and phosphorus nutrients cannot keep up with increasing atmospheric CO2, the magnitude of this terrestrial ecosystem service may reduce in future. This paper implements nitrogen constraints on photosynthesis in a model to understand the mechanisms involved.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
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Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lena Wohlgemuth, Stefan Osterwalder, Carl Joseph, Ansgar Kahmen, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 17, 6441–6456, https://doi.org/10.5194/bg-17-6441-2020, https://doi.org/10.5194/bg-17-6441-2020, 2020
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Mercury uptake by trees from the air represents an important but poorly quantified pathway in the global mercury cycle. We determined mercury uptake fluxes by leaves and needles at 10 European forests which were 4 times larger than mercury deposition via rainfall. The amount of mercury taken up by leaves and needles depends on their age and growing height on the tree. Scaling up our measurements to the forest area of Europe, we estimate that each year 20 t of mercury is taken up by trees.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
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We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Jarmo Mäkelä, Francesco Minunno, Tuula Aalto, Annikki Mäkelä, Tiina Markkanen, and Mikko Peltoniemi
Biogeosciences, 17, 2681–2700, https://doi.org/10.5194/bg-17-2681-2020, https://doi.org/10.5194/bg-17-2681-2020, 2020
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We assess the relative magnitude of uncertainty sources on ecosystem indicators of the 21st century climate change on two boreal forest sites. In addition to RCP and climate model uncertainties, we included the overlooked model parameter uncertainty and management actions in our analysis. Management was the dominant uncertainty factor for the more verdant southern site, followed by RCP, climate and parameter uncertainties. The uncertainties were estimated with canonical correlation analysis.
Guido Kraemer, Gustau Camps-Valls, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 17, 2397–2424, https://doi.org/10.5194/bg-17-2397-2020, https://doi.org/10.5194/bg-17-2397-2020, 2020
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To closely monitor the state of our planet, we require systems that can monitor
the observation of many different properties at the same time. We create
indicators that resemble the behavior of many different simultaneous
observations. We apply the method to create indicators representing the
Earth's biosphere. The indicators show a productivity gradient and a water
gradient. The resulting indicators can detect a large number of changes and
extremes in the Earth system.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 flux is mostly controlled by temperature during the growing season and by radiation off season. We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia. Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
Stephanie C. Pennington, Nate G. McDowell, J. Patrick Megonigal, James C. Stegen, and Ben Bond-Lamberty
Biogeosciences, 17, 771–780, https://doi.org/10.5194/bg-17-771-2020, https://doi.org/10.5194/bg-17-771-2020, 2020
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Soil respiration (Rs) is the flow of CO2 from the soil surface to the atmosphere and is one of the largest carbon fluxes on land. This study examined the effect of local basal area (tree area) on Rs in a coastal forest in eastern Maryland, USA. Rs measurements were taken as well as distance from soil collar, diameter, and species of each tree within a 15 m radius. We found that trees within 5 m of our sampling points had a positive effect on how sensitive soil respiration was to temperature.
Keri L. Bowering, Kate A. Edwards, Karen Prestegaard, Xinbiao Zhu, and Susan E. Ziegler
Biogeosciences, 17, 581–595, https://doi.org/10.5194/bg-17-581-2020, https://doi.org/10.5194/bg-17-581-2020, 2020
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We examined the effects of season and tree harvesting on the flow of water and the organic carbon (OC) it carries from boreal forest soils. We found that more OC was lost from the harvested forest because more precipitation reached the soil surface but that during periods of flushing in autumn and snowmelt a limit on the amount of water-extractable OC is reached. These results contribute to an increased understanding of carbon loss from boreal forest soils.
Jason Philip Kaye, Susan L. Brantley, Jennifer Zan Williams, and the SSHCZO team
Biogeosciences, 16, 4661–4669, https://doi.org/10.5194/bg-16-4661-2019, https://doi.org/10.5194/bg-16-4661-2019, 2019
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Interdisciplinary teams can only capitalize on innovative ideas if members work well together through collegial and efficient use of field sites, instrumentation, samples, data, and model code. Thus, biogeoscience teams may benefit from developing a set of best practices for collaboration. We present one such example from a the Susquehanna Shale Hills critical zone observatory. Many of the themes from our example are universal, and they offer insights useful to other biogeoscience teams.
Anne Alexandre, Elizabeth Webb, Amaelle Landais, Clément Piel, Sébastien Devidal, Corinne Sonzogni, Martine Couapel, Jean-Charles Mazur, Monique Pierre, Frédéric Prié, Christine Vallet-Coulomb, Clément Outrequin, and Jacques Roy
Biogeosciences, 16, 4613–4625, https://doi.org/10.5194/bg-16-4613-2019, https://doi.org/10.5194/bg-16-4613-2019, 2019
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This calibration study shows that despite isotope heterogeneity along grass leaves, the triple oxygen isotope composition of bulk leaf phytoliths can be estimated from the Craig and Gordon model, a mixing equation and a mean leaf water–phytolith fractionation exponent (lambda) of 0.521. The results strengthen the reliability of the 17O–excess of phytoliths to be used as a proxy of atmospheric relative humidity and open tracks for its use as an imprint of leaf water 17O–excess.
Lina Teckentrup, Sandy P. Harrison, Stijn Hantson, Angelika Heil, Joe R. Melton, Matthew Forrest, Fang Li, Chao Yue, Almut Arneth, Thomas Hickler, Stephen Sitch, and Gitta Lasslop
Biogeosciences, 16, 3883–3910, https://doi.org/10.5194/bg-16-3883-2019, https://doi.org/10.5194/bg-16-3883-2019, 2019
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This study compares simulated burned area of seven global vegetation models provided by the Fire Model Intercomparison Project (FireMIP) since 1900. We investigate the influence of five forcing factors: atmospheric CO2, population density, land–use change, lightning and climate.
We find that the anthropogenic factors lead to the largest spread between models. Trends due to climate are mostly not significant but climate strongly influences the inter-annual variability of burned area.
Marcos A. S. Scaranello, Michael Keller, Marcos Longo, Maiza N. dos-Santos, Veronika Leitold, Douglas C. Morton, Ekena R. Pinagé, and Fernando Del Bon Espírito-Santo
Biogeosciences, 16, 3457–3474, https://doi.org/10.5194/bg-16-3457-2019, https://doi.org/10.5194/bg-16-3457-2019, 2019
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The coarse dead wood component of the tropical forest carbon pool is rarely measured. For the first time, we developed models for predicting coarse dead wood in Amazonian forests by using airborne laser scanning data. Our models produced site-based estimates similar to independent field estimates found in the literature. Our study provides an approach for estimating coarse dead wood pools from remotely sensed data and mapping those pools over large scales in intact and degraded forests.
James Brennan, Jose L. Gómez-Dans, Mathias Disney, and Philip Lewis
Biogeosciences, 16, 3147–3164, https://doi.org/10.5194/bg-16-3147-2019, https://doi.org/10.5194/bg-16-3147-2019, 2019
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We estimate the uncertainties associated with three global satellite-derived burned area estimates. The method provides unique uncertainties for the three estimates at the global scale for 2001–2013. We find uncertainties of 4 %–5.5 % in global burned area and uncertainties of 8 %–10 % in the frequently burning regions of Africa and Australia.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
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This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
Sophie V. J. van der Horst, Andrew J. Pitman, Martin G. De Kauwe, Anna Ukkola, Gab Abramowitz, and Peter Isaac
Biogeosciences, 16, 1829–1844, https://doi.org/10.5194/bg-16-1829-2019, https://doi.org/10.5194/bg-16-1829-2019, 2019
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Measurements of surface fluxes are taken around the world and are extremely valuable for understanding how the land and atmopshere interact, and how the land can amplify temerature extremes. However, do these measurements sample extreme temperatures, or are they biased to the average? We examine this question and highlight data that do measure surface fluxes under extreme conditions. This provides a way forward to help model developers improve their models.
Friederike Gerschlauer, Gustavo Saiz, David Schellenberger Costa, Michael Kleyer, Michael Dannenmann, and Ralf Kiese
Biogeosciences, 16, 409–424, https://doi.org/10.5194/bg-16-409-2019, https://doi.org/10.5194/bg-16-409-2019, 2019
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Mount Kilimanjaro is an iconic environmental asset under serious threat due to increasing human pressures and climate change constraints. We studied variations in the stable isotopic composition of carbon and nitrogen in plant, litter, and soil material sampled along a strong land-use and altitudinal gradient. Our results show that, besides management, increasing temperatures in a changing climate may promote carbon and nitrogen losses, thus altering the stability of Kilimanjaro ecosystems.
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