Articles | Volume 20, issue 2
https://doi.org/10.5194/bg-20-383-2023
© Author(s) 2023. 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-20-383-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jan 2023
Research article |
| 25 Jan 2023
| 25 Jan 2023
Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing
Matthew P. Dannenberg
CORRESPONDING AUTHOR
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52245, USA
Mallory L. Barnes
O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405, USA
William K. Smith
School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA
Miriam R. Johnston
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52245, USA
Susan K. Meerdink
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52245, USA
Xian Wang
O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405, USA
School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA
Russell L. Scott
Southwest Watershed Research Center, Agricultural Research Service, U.S. Department of Agriculture, Tucson, AZ 85719, USA
Joel A. Biederman
Southwest Watershed Research Center, Agricultural Research Service, U.S. Department of Agriculture, Tucson, AZ 85719, USA
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Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
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The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020, https://doi.org/10.5194/hess-24-5203-2020, 2020
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Jennifer K. Brooke, R. Chawn Harlow, Russell L. Scott, Martin J. Best, John M. Edwards, Jean-Claude Thelen, and Mark Weeks
Geosci. Model Dev., 12, 1703–1724, https://doi.org/10.5194/gmd-12-1703-2019, https://doi.org/10.5194/gmd-12-1703-2019, 2019
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This paper evaluates a significant cold land surface temperature bias in semi-arid regions in the Met Office Unified Model when compared with satellite observations. Sparse vegetation canopies are not well represented in ancillary datasets, in particular regions of cold bias are correlated with low bare soil cover fractions. The study demonstrates the difficulties in modelling land surface temperatures that match state-of-the-art satellite retrievals required for operational data assimilation.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
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Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Congsheng Fu, Guiling Wang, Michael L. Goulden, Russell L. Scott, Kenneth Bible, and Zoe G. Cardon
Hydrol. Earth Syst. Sci., 20, 2001–2018, https://doi.org/10.5194/hess-20-2001-2016, https://doi.org/10.5194/hess-20-2001-2016, 2016
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Hydraulic redistribution (HR) of plant root has important hydrological impact (on evapotranspiration, Bowen ratio, and soil moisture) in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.
W. Shen, G. D. Jenerette, D. Hui, and R. L. Scott
Biogeosciences, 13, 425–439, https://doi.org/10.5194/bg-13-425-2016, https://doi.org/10.5194/bg-13-425-2016, 2016
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This simulation study found that dry legacy imposed positive impacts on net ecosystem production (NEP) whereas wet legacy had negative impacts on NEP, indicating that dry legacy can foster more C sequestration and wet legacy more C release. The carryover of soil nitrogen was mainly responsible for the gross ecosystem production (GEP) responses, while the carryovers of plant biomass, litter and soil organic matter were mainly responsible for the ecosystem respiration (Re) responses.
S.-H. Hong, J. M. H. Hendrickx, J. Kleissl, R. G. Allen, W. G. M. Bastiaanssen, R. L. Scott, and A. L. Steinwand
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-13479-2014, https://doi.org/10.5194/hessd-11-13479-2014, 2014
Manuscript not accepted for further review
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Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
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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We present a methodology to detect inconsistencies in perhaps the most important data source for measurements of ecosystem–atmosphere carbon, water, and energy fluxes. We expect that the derived consistency flags will be relevant for data users and will help in improving our understanding of and our ability to model ecosystem–climate interactions.
Prajwal Khanal, Anne J. Hoek Van Dijke, Timo Schaffhauser, Wantong Li, Sinikka J. Paulus, Chunhui Zhan, and René Orth
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Water availability is essential for vegetation functioning, but the depth of vegetation water uptake is largely unknown due to sparse ground measurements. This study correlates vegetation growth with soil moisture availability globally to infer vegetation water uptake depth using only satellite-based data. We find that the vegetation water uptake depth varies across climate regimes and vegetation types and also changes during dry months at a global scale.
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We used a soil model to replicate two litterbag decomposition experiments to examine the implications of climate, litter quality, and soil microclimate representation. We found that macroclimate was more important than litter quality for modeled mass loss. By comparing different representations of soil temperature and moisture we found that using observed data did not improve model results. We discuss causes for this and suggest possible improvements to both model and experimental design.
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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Arctic greenhouse gas (GHG) fluxes of CO2, CH4, and N2O are important for climate feedbacks. We combined extensive in situ measurements and remote sensing data to develop machine-learning models to predict GHG fluxes at a 2 m resolution across a tundra landscape. The analysis revealed that the system was a net GHG sink and showed widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale.
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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Leaf carbon (C) and nitrogen (N) are crucial elements in leaf construction and physiological processes. This study reconciled the roles of phylogeny, species identity, and climate in stoichiometric traits at individual and community levels. The variations in community-level leaf N and C : N ratio were captured by optimality-based models using climate data. Our results provide an approach to improve the representation of leaf stoichiometry in vegetation models to better couple N with C cycling.
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.
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.
Boaz Hilman, Jan Muhr, Susan E. Trumbore, Norbert Kunert, Mariah S. Carbone, Päivi Yuval, S. Joseph Wright, Gerardo Moreno, Oscar Pérez-Priego, Mirco Migliavacca, Arnaud Carrara, José M. Grünzweig, Yagil Osem, Tal Weiner, and Alon Angert
Biogeosciences, 16, 177–191, https://doi.org/10.5194/bg-16-177-2019, https://doi.org/10.5194/bg-16-177-2019, 2019
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Combined measurement of CO2 / O2 fluxes in tree stems suggested that on average 41 % of the respired CO2 was not emitted locally to the atmosphere. This finding strengthens the recognition that CO2 efflux from tree stems is not an accurate measure of respiration. The CO2 / O2 fluxes did not vary as expected if CO2 dissolution in the xylem sap was the main driver for the CO2 retention. We suggest the examination of refixation of respired CO2 as a possible mechanism for CO2 retention.
Cited articles
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., and Hegewisch, K. C.:
TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, Sci. Data, 5, 1–12, https://doi.org/10.1038/sdata.2017.191, 2018.
Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A., Jung, M., Reichstein, M., Canadell, J. G., Friedlingstein, P., Jain, A. K., Kato, E., Poulter, B., Sitch, S., Stocker, B. D., Viovy, N., Wang, Y. P., Wiltshire, A., Zaehle, S., and Zeng, N.:
The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink, Science, 348, 895–899, https://doi.org/10.1002/2015JA021022, 2015.
Allred, B. W., Bestelmeyer, B. T., Boyd, C. S., Brown, C., Davies, K. W., Duniway, M. C., Ellsworth, L. M., Erickson, T. A., Fuhlendorf, S. D., Griffiths, T. V., Jansen, V., Jones, M. O., Karl, J., Knight, A., Maestas, J. D., Maynard, J. J., McCord, S. E., Naugle, D. E., Starns, H. D., Twidwell, D., and Uden, D. R.:
Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty, Methods Ecol. Evol., 12, 841–849, https://doi.org/10.1111/2041-210X.13564, 2021.
Anderegg, W. R. L., Ballantyne, A. P., Smith, W. K., Majkut, J., Rabin, S., and Beaulieu, C.:
Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink, P. Natl. Acad. Sci. USA, 112, 15591–15596, https://doi.org/10.1073/pnas.1521479112, 2015.
Andersen, O. B., Seneviratne, S. I., Hinderer, J., and Viterbo, P.:
GRACE-derived terrestrial water storage depletion associated with the 2003 European heat wave, Geophys. Res. Lett., 32, L18405, https://doi.org/10.1029/2005GL023574, 2005.
Anderson-Teixeira, K. J., Delong, J. P., Fox, A. M., Brese, D. A., and Litvak, M. E.:
Differential responses of production and respiration to temperature and moisture drive the carbon balance across a climatic gradient in New Mexico, Glob. Change Biol., 17, 410–424, https://doi.org/10.1111/j.1365-2486.2010.02269.x, 2011.
Anderson, M. C., Allen, R. G., Morse, A., and Kustas, W. P.:
Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources, Remote Sens. Environ., 122, 50–65, https://doi.org/10.1016/j.rse.2011.08.025, 2012.
Atkin, O. K. and Tjoelker, M. G.:
Thermal acclimation and the dynamic response of plant respiration to temperature, Trends Plant Sci., 8, 343–351, https://doi.org/10.1016/S1360-1385(03)00136-5, 2003.
Atkinson, P. M. and Tatnall, A. R. L.:
Introduction neural networks in remote sensing, Int. J. Remote Sens., 18, 699–709, https://doi.org/10.1080/014311697218700, 1997.
Ault, T. R.:
On the essentials of drought in a changing climate, Science, 368, 256–260, 2020.
Badgley, G., Field, C. B., and Berry, J. A.:
Canopy near-infrared reflectance and terrestrial photosynthesis, Sci. Adv., 3, e1602244, https://doi.org/10.1126/sciadv.1602244, 2017.
Barnes, M. L., Farella, M. M., Scott, R. L., Moore, D. J. P., Ponce-Campos, G. E., Biederman, J. A., MacBean, N., Litvak, M. E., and Breshears, D. D.:
Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling, Commun. Earth Environ., 2, 1–9, https://doi.org/10.1038/s43247-021-00308-2, 2021.
Bateni, S. M. and Entekhabi, D.:
Relative efficiency of land surface energy balance components, Water Resour. Res., 48, 1–8, https://doi.org/10.1029/2011WR011357, 2012.
Bestelmeyer, B. T., Okin, G. S., Duniway, M. C., Archer, S. R., Sayre, N. F., Williamson, J. C., and Herrick, J. E.:
Desertification, land use, and the transformation of global drylands, Front. Ecol. Environ., 13, 28–36, https://doi.org/10.1890/140162, 2015.
Biederman, J. A., Scott, R. L., Goulden, M. L., Vargas, R., Litvak, M. E., Kolb, T. E., Yepez, E. A., Oechel, W. C., Blanken, P. D., Bell, T. W., Garatuza-Payan, J., Maurer, G. E., Dore, S., and Burns, S. P.:
Terrestrial carbon balance in a drier world: The effects of water availability in southwestern North America, Glob. Change Biol., 22, 1867–1879, https://doi.org/10.1111/gcb.13222, 2016.
Biederman, J. A., Scott, R. L., Bell, T. W., Bowling, D. R., Dore, S., Garatuza-Payan, J., Kolb, T. E., Krishnan, P., Krofcheck, D. J., Litvak, M. E., Maurer, G. E., Meyers, T. P., Oechel, W. C., Papuga, S. A., Ponce-Campos, G. E., Rodriguez, J. C., Smith, W. K., Vargas, R., Watts, C. J., Yepez, E. A., and Goulden, M. L.:
CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America, Glob. Change Biol., 23, 4204–4221, https://doi.org/10.1111/gcb.13686, 2017.
Biederman, J. A., Scott, R. L., Arnone, J. A., Jasoni, R. L., Litvak, M. E., Moreo, M. T., Papuga, S. A., Ponce-Campos, G. E., Schreiner-McGraw, A. P., and Vivoni, E. R.:
Shrubland carbon sink depends upon winter water availability in the warm deserts of North America, Agr. Forest Meteorol., 249, 407–419, https://doi.org/10.1016/j.agrformet.2017.11.005, 2018.
Camps-Valls, G., Campos-Taberner, M., Moreno-Martínez, Á., Walther, S., Duveiller, G., Cescatti, A., Mahecha, M. D., Muñoz-Marí, J., García-Haro, F. J., Guanter, L., Jung, M., Gamon, J. A., Reichstein, M., and Running, S. W.:
A unified vegetation index for quantifying the terrestrial biosphere, Sci. Adv., 7, 1–11, https://doi.org/10.1126/sciadv.abc7447, 2021.
Cayan, D. R., Das, T., Pierce, D. W., Barnett, T. P., Tyree, M., and Gershunov, A.:
Future dryness in the southwest US and the hydrology of the early 21st century drought, P. Natl. Acad. Sci. USA, 107, 21271–21276, https://doi.org/10.1073/pnas.0912391107, 2010.
Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., and Grégoire, J.-M.:
Detecting vegetation leaf water content using reflectance in the optical domain, Remote Sens. Environ., 77, 22–33, https://doi.org/10.1016/S0034-4257(01)00191-2, 2001.
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, https://doi.org/10.1016/j.agrformet.2021.108350, 2021.
Cook, B. I., Ault, T. R., and Smerdon, J. E.:
Unprecedented 21st century drought risk in the American Southwest and Central Plains, Sci. Adv., 1, e1400082, https://doi.org/10.1126/sciadv.1400082, 2015.
Cook, B. I., Mankin, J. S., Marvel, K., Williams, A. P., Smerdon, J. E., and Anchukaitis, K. J.:
Twenty-first century drought projections in the CMIP6 forcing scenarios, Earths Future, 8, e2019EF001461, https://doi.org/10.1029/2019ef001461, 2020.
Curiel Yuste, J., Baldocchi, D. D., Gershenson, A., Goldstein, A., Misson, L., and Wong, S.:
Microbial soil respiration and its dependency on carbon inputs, soil temperature and moisture, Glob. Change Biol., 13, 2018–2035, https://doi.org/10.1111/j.1365-2486.2007.01415.x, 2007.
Dannenberg, M. P.: drylANNd, GitHub [code], https://github.com/mpdannenberg/drylANNd, last access: 18 January 2023.
Dannenberg, M. P., Song, C., Hwang, T., and Wise, E. K.:
Empirical evidence of El Niño-Southern Oscillation influence on land surface phenology and productivity in the western United States, Remote Sens. Environ., 159, 167–180, 2015.
Dannenberg, M., Wang, X., Yan, D., and Smith, W.:
Phenological characteristics of global ecosystems based on optical, fluorescence, and microwave remote sensing, Remote Sens.-Basel, 12, 671, https://doi.org/10.3390/rs12040671, 2020.
Dannenberg, M. P., Smith, W. K., Zhang, Y., Song, C., Huntzinger, D. N., and Moore, D. J. P.:
Large-scale reductions in terrestrial carbon uptake following central Pacific El Niño, Geophys. Res. Lett., 48, e2020GL092367, https://doi.org/10.1029/2020GL092367, 2021.
Dannenberg, M. P., Yan, D., Barnes, M. L., Smith, W. K., Johnston, M. R., Scott, R. L., Biederman, J. A., Knowles, J. F., Wang, X., Duman, T., Litvak, M. E., Kimball, J. S., Williams, A. P., and Zhang, Y.:
Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U. S. Southwest hot drought, Glob. Change Biol., 28, 4794–4806, https://doi.org/10.1111/gcb.16214, 2022a.
Dannenberg, M. P., Barnes, M. L., Smith, W. K., Miriam R Johnston, Susan K Meerdink, Xian Wang, Russell L Scott and Joel A. Biederman: Monthly 0.05∘ gross primary production, net ecosystem exchange, and evapotranspiration estimates for western U.S. drylands, University of Iowa [data set], https://doi.org/10.25820/data.006185, 2022b.
Dietze, M. C., Fox, A., Beck-Johnson, L. M., Betancourt, J. L., Hooten, M. B., Jarnevich, C. S., Keitt, T. H., Kenney, M. A., Laney, C. M., Larsen, L. G., Loescher, H. W., Lunch, C. K., Pijanowski, B. C., Randerson, J. T., Read, E. K., Tredennick, A. T., Vargas, R., Weathers, K. C., and White, E. P.:
Iterative near-term ecological forecasting: Needs, opportunities, and challenges, P. Natl. Acad. Sci. USA, 115, 1424–1432, https://doi.org/10.1073/pnas.1710231115, 2018.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.:
A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, https://doi.org/10.1007/BF00386231, 1980.
Fisher, J. B., Melton, F., Middleton, E., Hain, C., Anderson, M., Allen, R., McCabe, M. F., Hook, S., Baldocchi, D., Townsend, P. A., Kilic, A., Tu, K., Miralles, D. D., Perret, J., Lagouarde, J.-P. P., Waliser, D., Purdy, A. J., French, A., Schimel, D., Famiglietti, J. S., Stephens, G., and Wood, E. F.:
The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, Water Resour. Res., 53, 2618–2626, https://doi.org/10.1002/2016WR020175, 2017.
Gao, B.:
NDWI–a normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sens. Environ., 58, 257–266, 1996.
Gevrey, M., Dimopoulos, I., and Lek, S.:
Review and comparison of methods to study the contribution of variables in artificial neural network models, Ecol. Modell., 160, 249–264, https://doi.org/10.1016/S0304-3800(02)00257-0, 2003.
Guan, K., Wu, J., Kimball, J. S., Anderson, M. C., Frolking, S., Li, B., Hain, C. R., and Lobell, D. B.:
The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields, Remote Sens. Environ., 199, 333–349, https://doi.org/10.1016/j.rse.2017.06.043, 2017.
Hartman, M. D., Parton, W. J., Derner, J. D., Schulte, D. K., Smith, W. K., Peck, D. E., Day, K. A., Del Grosso, S. J., Lutz, S., Fuchs, B. A., Chen, M., and Gao, W.:
Seasonal grassland productivity forecast for the U. S. Great Plains using Grass-Cast, Ecosphere, 11, e03280, https://doi.org/10.1002/ecs2.3280, 2020.
Haughton, N., Abramowitz, G., De Kauwe, M. G., and Pitman, A. J.:
Does predictability of fluxes vary between FLUXNET sites?, Biogeosciences, 15, 4495–4513, https://doi.org/10.5194/bg-15-4495-2018, 2018.
Heinsch, F. A., Zhao, M., Running, S. W., Kimball, J. S., Nemani, R. R., Davis, K. J., Bolstad, P. V., Cook, B. D., Desai, A. R., Ricciuto, D. M., Law, B. E., Oechel, W. C., Kwon, H., Luo, H., Wofsy, S. C., Dunn, A. L., Munger, J. W., Baldocchi, D. D., Xu, L., Hollinger, D. Y., Richardson, A. D., Stoy, P. C., Siqueira, M. B. S., Monson, R. K., Burns, S. P., and Flanagan, L. B.:
Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations, IEEE T. Geosci. Remote, 44, 1908–1925, https://doi.org/10.1109/TGRS.2005.853936, 2006.
Holben, B. N.:
Characteristics of maximum-value composite images from temporal AVHRR data, Int. J. Remote Sens., 7, 1417–1434, https://doi.org/10.1080/01431168608948945, 1986.
Huang, G. B.:
Learning capability and storage capacity of two-hidden-layer feedforward networks, IEEE T. Neural Netwo., 14, 274–281, https://doi.org/10.1109/TNN.2003.809401, 2003.
Huang, J., Yu, H., Guan, X., Wang, G., and Guo, R.:
Accelerated dryland expansion under climate change, Nat. Clim. Change, 6, 166–171, https://doi.org/10.1038/nclimate2837, 2016.
Huang, J., Yu, H., Dai, A., Wei, Y., and Kang, L.:
Drylands face potential threat under 2 ∘C global warming target, Nat. Clim. Change, 7, 417–422, https://doi.org/10.1038/nclimate3275, 2017.
Huete, A. R.:
A soil-adjusted vegetation index (SAVI), Remote Sens. Environ., 25, 295–309, https://doi.org/10.1016/0034-4257(88)90106-X, 1988.
Huete, A. R. and Jackson, R. D.:
Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands, Remote Sens. Environ., 23, 213–232, https://doi.org/10.1016/0034-4257(87)90038-1, 1987.
Huete, A. R., Justice, C., and Liu, H.:
Development of vegetation and soil indices for MODIS-EOS, Remote Sens. Environ., 49, 224–234, https://doi.org/10.1016/0034-4257(94)90018-3, 1994.
Huete, A. R., Liu, H. Q., Batchily, K., and van Leeuwen, W.:
A comparison of vegetation indices over a global set of TM images for EOS-MODIS, Remote Sens. Environ., 59, 440–451, 1997.
Huete, A. R., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L. G.:
Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195–213, https://doi.org/10.1016/S0034-4257(02)00096-2, 2002.
Humphrey, V., Zscheischler, J., Ciais, P., Gudmundsson, L., Sitch, S., and Seneviratne, S. I.:
Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage, Nature, 560, 628–631, https://doi.org/10.1038/s41586-018-0424-4, 2018.
Huxman, T. E., Snyder, K. A., Tissue, D., Leffler, A. J., Ogle, K., Pockman, W. T., Sandquist, D. R., Potts, D. L., and Schwinning, S.:
Precipitation pulses and carbon fluxes in semiarid and arid ecosystems, Oecologia, 141, 254–268, https://doi.org/10.1007/s00442-004-1682-4, 2004.
Javadian, M., Smith, W. K., Lee, K., Knowles, J. F., Scott, R. L., Fisher, J. B., Moore, D. J. P., van Leeuwen, W. J. D., Barron-Gafford, G., and Behrangi, A.:
Canopy temperature Is regulated by ecosystem structural traits and captures the ecohydrologic dynamics of a semiarid mixed conifer forest site, J. Geophys. Res.-Biogeo., 127, 1–15, https://doi.org/10.1029/2021JG006617, 2022.
Jensen, R. R., Hardin, P. J., and Yu, G.:
Artificial neural networks and remote sensing, Geogr. Compass, 3, 630–646, https://doi.org/10.1111/j.1749-8198.2008.00215.x, 2009.
Joiner, J., Guanter, L., Lindstrot, R., Voigt, M., Vasilkov, A. P., Middleton, E. M., Huemmrich, K. F., Yoshida, Y., and Frankenberg, C.:
Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2, Atmos. Meas. Tech., 6, 2803–2823, https://doi.org/10.5194/amt-6-2803-2013, 2013.
Jones, L. A., Kimball, J. S., Reichle, R. H., Madani, N., Glassy, J., Ardizzone, J. V., Colliander, A., Cleverly, J., Desai, A. R., Eamus, D., Euskirchen, E. S., Hutley, L., Macfarlane, C., and Scott, R. L.:
The SMAP Level 4 Carbon product for monitoring ecosystem land-atmosphere CO2 exchange, IEEE T. Geosci. Remote, 55, 6517–6532, https://doi.org/10.1109/TGRS.2017.2729343, 2017.
Jones, M. O., Allred, B. W., Naugle, D. E., Maestas, J. D., Donnelly, P., Metz, L. J., Karl, J., Smith, R., Bestelmeyer, B., Boyd, C., Kerby, J. D., and McIver, J. D.:
Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U. S. rangelands, 1984–2017, Ecosphere, 9, e02430, https://doi.org/10.1002/ecs2.2430, 2018.
Kannenberg, S. A., Bowling, D. R., and Anderegg, W. R. L.:
Hot moments in ecosystem fluxes: High GPP anomalies exert outsized influence on the carbon cycle and are differentially driven by moisture availability across biomes, Environ. Res. Lett., 15, 054004, https://doi.org/10.1088/1748-9326/ab7b97, 2020.
Köhler, P., Frankenberg, C., Magney, T. S., Guanter, L., Joiner, J., and Landgraf, J.:
Global retrievals of solar-induced chlorophyll fluorescence with TROPOMI: first results and intersensor comparison to OCO-2, Geophys. Res. Lett., 45, 10456–10463, https://doi.org/10.1029/2018GL079031, 2018.
MacBean, N., Scott, R. L., Biederman, J. A., Peylin, P., Kolb, T., Litvak, M. E., Krishnan, P., Meyers, T. P., Arora, V. K., Bastrikov, V., Goll, D., Lombardozzi, D. L., Nabel, J. E. M. S., Pongratz, J., Sitch, S., Walker, A. P., Zaehle, S., and Moore, D. J. P.:
Dynamic global vegetation models underestimate net CO2 flux mean and inter-annual variability in dryland ecosystems, Environ. Res. Lett., 16, 094023, https://doi.org/10.1088/1748-9326/ac1a38, 2021.
Magney, T. S., Bowling, D. R., Logan, B. A., Grossmann, K., Stutz, J., Blanken, P. D., Burns, S. P., Cheng, R., Garcia, M. A., Köhler, P., Lopez, S., Parazoo, N. C., Raczka, B., Schimel, D., and Frankenberg, C.:
Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence, P. Natl. Acad. Sci. USA, 116, 11640–11645, https://doi.org/10.1073/pnas.1900278116, 2019.
Mas, J. F. and Flores, J. J.:
The application of artificial neural networks to the analysis of remotely sensed data, Int. J. Remote Sens., 29, 617–663, https://doi.org/10.1080/01431160701352154, 2008.
McCormick, E. L., Dralle, D. N., Hahm, W. J., Tune, A. K., Schmidt, L. M., Chadwick, K. D., and Rempe, D. M.:
Widespread woody plant use of water stored in bedrock, Nature, 597, 225–229, https://doi.org/10.1038/s41586-021-03761-3, 2021.
McDowell, N. G., Sapes, G., Pivovaroff, A., Adams, H. D., Allen, C. D., Anderegg, W. R. L., Arend, M., Breshears, D. D., Brodribb, T., Choat, B., Cochard, H., De Cáceres, M., De Kauwe, M. G., Grossiord, C., Hammond, W. M., Hartmann, H., Hoch, G., Kahmen, A., Klein, T., Mackay, D. S., Mantova, M., Martínez-Vilalta, J., Medlyn, B. E., Mencuccini, M., Nardini, A., Oliveira, R. S., Sala, A., Tissue, D. T., Torres-Ruiz, J. M., Trowbridge, A. M., Trugman, A. T., Wiley, E., and Xu, C.:
Mechanisms of woody-plant mortality under rising drought, CO2 and vapour pressure deficit, Nat. Rev. Earth Environ., 3, 294–308, https://doi.org/10.1038/s43017-022-00272-1, 2022.
Moyano, F. E., Manzoni, S., and Chenu, C.:
Responses of soil heterotrophic respiration to moisture availability: An exploration of processes and models, Soil Biol. Biochem., 59, 72–85, https://doi.org/10.1016/j.soilbio.2013.01.002, 2013.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.:
Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2006.07.007, 2007.
Mu, Q., Zhao, M., and Running, S. W.:
Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, https://doi.org/10.1016/j.rse.2011.02.019, 2011.
Nguyen, D. and Widrow, B.:
Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights, in: 1990 IJCNN International Joint Conference on Neural Networks, 21–26, 1990.
Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., Oishi, A. C., Papuga, S. A., Blanken, P. D., Noormets, A., Sulman, B. N., Scott, R. L., Wang, L., and Phillips, R. P.:
The increasing importance of atmospheric demand for ecosystem water and carbon fluxes, Nat. Clim. Change, 6, 1023–1027, https://doi.org/10.1038/nclimate3114, 2016.
Olden, J. D., Lawler, J. J., and Poff, N. L.:
Machine learning methods without tears: a primer for ecologists, Q. Rev. Biol., 83, 171–93, 2008.
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.:
Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Poulter, B., Frank, D., Ciais, P., Myneni, R. B., Andela, N., Bi, J., Broquet, G., Canadell, J. G., Chevallier, F., Liu, Y. Y., Running, S. W., Sitch, S., and van der Werf, G. R.:
Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle, Nature, 509, 600–603, https://doi.org/10.1038/nature13376, 2014.
R Core Team:
R: A Language and Environment for Statistical Computing, http://www.r-project.org (last access: 18 January 2023), 2021.
Rao, K., Williams, A. P., Diffenbaugh, N. S., Yebra, M., and Konings, A. G.:
Plant-water sensitivity regulates wildfire vulnerability, Nat. Ecol. Evol., 6, 332–339, https://doi.org/10.1038/s41559-021-01654-2, 2022.
Reichle, R. H., De Lannoy, G. J. M., Liu, Q., Ardizzone, J. V., Colliander, A., Conaty, A., Crow, W., Jackson, T. J., Jones, L. A., Kimball, J. S., Koster, R. D., Mahanama, S. P., Smith, E. B., Berg, A., Bircher, S., Bosch, D., Caldwell, T. G., Cosh, M., González-Zamora, Á., Collins, C. D. H., Jensen, K. H., Livingston, S., Lopez-Baeza, E., Martínez-Fernández, J., McNairn, H., Moghaddam, M., Pacheco, A., Pellarin, T., Prueger, J., Rowlandson, T., Seyfried, M., Starks, P., Su, Z., Thibeault, M., van der Velde, R., Walker, J., Wu, X., and Zeng, Y.:
Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements, J. Hydrometeorol., 18, 2621–2645, https://doi.org/10.1175/JHM-D-17-0063.1, 2017.
Reichle, R. H., Liu, Q., Koster, R. D., Crow, W. T., De Lannoy, G. J. M., Kimball, J. S., Ardizzone, J. V., Bosch, D., Colliander, A., Cosh, M., Kolassa, J., Mahanama, S. P., Prueger, J., Starks, P., and Walker, J. P.:
Version 4 of the SMAP Level-4 Soil Moisture algorithm and data product, J. Adv. Model. Earth Sy., 11, 3106–3130, https://doi.org/10.1029/2019MS001729, 2019.
Reichle, R. H., De Lannoy, G., Koster, R. D., Crow, W. T., Kimball, J. S., Liu, Q., and Bechtold, M.:
SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update, Version 7, National Snow and Ice Data Center [data set], https://doi.org/10.5067/LWJ6TF5SZRG3, 2022.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J. M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.:
On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm, Glob. Change Biol., 11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Rempe, D. M. and Dietrich, W. E.:
Direct observations of rock moisture, a hidden component of the hydrologic cycle, P. Natl. Acad. Sci. USA, 115, 2664–2669, https://doi.org/10.1073/pnas.1800141115, 2018.
Reynolds, J. F., Smith, D. M. S., Lambin, E. F., Turner, B. L., Mortimore, M., Batterbury, S. P. J., Downing, T. E., Dowlatabadi, H., Fernández, R. J., Herrick, J. E., Huber-Sannwald, E., Jiang, H., Leemans, R., Lynam, T., Maestre, F. T., Ayarza, M., and Walker, B.:
Global Desertification: Building a Science for Dryland Development, Science, 316, 847–851, https://doi.org/10.1126/science.1131634, 2007.
Roby, M. C., Scott, R. L., and Moore, D. J. P.:
High vapor pressure deficit decreases the productivity and water use efficiency of rain-induced pulses in semiarid ecosystems, J. Geophys. Res.-Biogeo., 125, e2020JG005665, https://doi.org/10.1029/2020JG005665, 2020.
Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W., and Harlan, J. C.:
Monitoring the vernal advancement and retrogradation (greenwave effect) of natural vegetation, NASA/GSFC Type III Final Report, Greenbelt, MD, 371 pp., 1974.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and Hashimoto, H.:
A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production, BioScience, 54, 547–560, https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2, 2004.
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., Strugnell, N. C., Zhang, X., Jin, Y., Muller, J.-P., Lewis, P., Barnsley, M., Hobson, P., Disney, M., Roberts, G., Dunderdale, M., Doll, C., D'Entremont, R. P., Hu, B., Liang, S., Privette, J. L., and Roy, D.:
First operational BRDF, albedo nadir reflectance products from MODIS, Remote Sens. Environ., 83, 135–148, https://doi.org/10.1016/S0034-4257(02)00091-3, 2002.
Scott, R. L., Jenerette, G. D., Potts, D. L., and Huxman, T. E.:
Effects of seasonal drought on net carbon dioxide exchange from a woody-plant-encroached semiarid grassland, J. Geophys. Res., 114, G04004, https://doi.org/10.1029/2008JG000900, 2009.
Scott, R. L., Hamerlynck, E. P., Jenerette, G. D., Moran, M. S., and Barron-Gafford, G. A.:
Carbon dioxide exchange in a semidesert grassland through drought-induced vegetation change, J. Geophys. Res., 115, G03026, https://doi.org/10.1029/2010JG001348, 2010.
Scott, R. L., Biederman, J. A., Hamerlynck, E. P., and Barron-Gafford, G. A.:
The carbon balance pivot point of southwestern U. S. semiarid ecosystems: Insights from the 21st century drought, J. Geophys. Res.-Biogeo., 120, 2612–2624, https://doi.org/10.1002/2015JG003181, 2015.
Sims, D. A., Rahman, A. F., Cordova, V. D., El-Masri, B. Z., Baldocchi, D. D., Bolstad, P. V., Flanagan, L. B., Goldstein, A. H., Hollinger, D. Y., Misson, L., Monson, R. K., Oechel, W. C., Schmid, H. P., Wofsy, S. C., and Xu, L.:
A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS, Remote Sens. Environ., 112, 1633–1646, https://doi.org/10.1016/j.rse.2007.08.004, 2008.
Smerdon, J. E., Kaplan, A., Zorita, E., González-Rouco, J. F., and Evans, M. N.:
Spatial performance of four climate field reconstruction methods targeting the Common Era, Geophys. Res. Lett., 38, L11705, https://doi.org/10.1029/2011GL047372, 2011.
Smith, W. K., Biederman, J. A., Scott, R. L., Moore, D. J. P., He, M., Kimball, J. S., Yan, D., Hudson, A., Barnes, M. L., MacBean, N., Fox, A. M., and Litvak, M. E.:
Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America, Geophys. Res. Lett., 45, 748–757, https://doi.org/10.1002/2017GL075922, 2018.
Smith, W. K., Dannenberg, M. P., Yan, D., Herrmann, S., Barnes, M. L., Barron-Gafford, G. A., Biederman, J. A., Ferrenberg, S., Fox, A. M., Hudson, A., Knowles, J. F., MacBean, N., Moore, D. J. P., Nagler, P. L., Reed, S. C., Rutherford, W. A., Scott, R. L., Wang, X., and Yang, J.:
Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities, Remote Sens. Environ., 233, 111401, https://doi.org/10.1016/j.rse.2019.111401, 2019.
Song, C., Dannenberg, M. P., and Hwang, T.:
Optical remote sensing of terrestrial ecosystem primary productivity, Prog. Phys. Geog., 37, 834–854, https://doi.org/10.1177/0309133313507944, 2013.
Stavros, E. N., Schimel, D., Pavlick, R., Serbin, S., Swann, A., Duncanson, L., Fisher, J. B., Fassnacht, F., Ustin, S., Dubayah, R., Schweiger, A., and Wennberg, P.:
ISS observations offer insights into plant function, Nat. Ecol. Evol., 1, 1–4, https://doi.org/10.1038/s41559-017-0194, 2017.
Still, C. J., Rastogi, B., Page, G. F. M., Griffith, D. M., Sibley, A., Schulze, M., Hawkins, L., Pau, S., Detto, M., and Helliker, B. R.:
Imaging canopy temperature: shedding (thermal) light on ecosystem processes, New Phytol., 230, 1746–1753, https://doi.org/10.1111/nph.17321, 2021.
Stocker, B. D., Zscheischler, J., Keenan, T. F., Prentice, I. C., Peñuelas, J., and Seneviratne, S. I.:
Quantifying soil moisture impacts on light use efficiency across biomes, New Phytol., 218, 1430–1449, https://doi.org/10.1111/nph.15123, 2018.
Stocker, B. D., Zscheischler, J., Keenan, T. F., Prentice, I. C., Seneviratne, S. I., and Peñuelas, J.:
Drought impacts on terrestrial primary production underestimated by satellite monitoring, Nat. Geosci., 12, 264–270, https://doi.org/10.1038/s41561-019-0318-6, 2019.
Sun, Y., Frankenberg, C., Jung, M., Joiner, J., Guanter, L., Köhler, P., and Magney, T.:
Overview of Solar-Induced chlorophyll Fluorescence (SIF) from the Orbiting Carbon Observatory-2: Retrieval, cross-mission comparison, and global monitoring for GPP, Remote Sens. Environ., 209, 808–823, https://doi.org/10.1016/j.rse.2018.02.016, 2018.
Tucker, C. J.:
Red and photographic infrared linear combinations for monitoring vegetation, Remote Sens. Environ., 8, 127–150, 1979.
Turner, D. P., Gower, S. T., Cohen, W. B., Gregory, M., and Maiersperger, T. K.:
Effects of spatial variability in light use efficiency on satellite-based NPP monitoring, Remote Sens. Environ., 80, 397–405, https://doi.org/10.1016/S0034-4257(01)00319-4, 2002.
Turner, D. P., Ritts, W. D., Cohen, W. B., Maeirsperger, T. K., Gower, S. T., Kirschbaum, A. A., Running, S. W., Zhao, M., Wofsy, S. C., Dunn, A. L., Law, B. E., Campbell, J. L., Oechel, W. C., Kwon, H. J., Meyers, T. P., Small, E. E., Kurc, S. A., and Gamon, J. A.:
Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring, Glob. Change Biol., 11, 666–684, https://doi.org/10.1111/j.1365-2486.2005.00936.x, 2005.
Turner, D. P., Ritts, W. D., Zhao, M., Kurc, S. A., Dunn, A. L., Wofsy, S. C., Small, E. E., and Running, S. W.:
Assessing interannual variation in MODIS-based estimates of gross primary production, IEEE T. Geosci. Remote, 44, 1899–1907, 2006a.
Turner, D. P., Ritts, W. D., Cohen, W. B., Gower, S. T., Running, S. W., Zhao, M., Costa, M. H., Kirschbaum, A. A., Ham, J. M., Saleska, S. R., and Ahl, D. E.:
Evaluation of MODIS NPP and GPP products across multiple biomes, Remote Sens. Environ., 102, 282–292, https://doi.org/10.1016/j.rse.2006.02.017, 2006b.
Viovy, N., Arino, O., and Belward, A. S.:
The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series, Int. J. Remote Sens., 13, 1585–1590, 1992.
Wan, Z.:
New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product, Remote Sens. Environ., 140, 36–45, https://doi.org/10.1016/j.rse.2013.08.027, 2014.
Wan, Z. and Dozier, J.:
A generalized split-window algorithm for retrieving land-surface temperature from space, IEEE T. Geosci. Remote, 34, 892–905, https://doi.org/10.1109/36.508406, 1996.
Wang, X., Biederman, J. A., Knowles, J. F., Scott, R. L., Turner, A. J., Dannenberg, M. P., Köhler, P., Frankenberg, C., Litvak, M. E., Flerchinger, G. N., Law, B. E., Kwon, H., Reed, S. C., Parton, W. J., Barron-Gafford, G. A., and Smith, W. K.:
Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics, Remote Sens. Environ., 270, 112858, https://doi.org/10.1016/j.rse.2021.112858, 2022.
Williams, A. P., Cook, E. R., Smerdon, J. E., Cook, B. I., Abatzoglou, J. T., Bolles, K., Baek, S. H., Badger, A. M., and Livneh, B.:
Large contribution from anthropogenic warming to an emerging North American megadrought, Science, 368, 314–318, 2020.
Williams, A. P., Cook, B. I., and Smerdon, J. E.:
Rapid intensification of the emerging southwestern North American megadrought in 2020–2021, Nat. Clim. Change, 12, 232–234, https://doi.org/10.1038/s41558-022-01290-z, 2022.
Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., and Reichstein, M.:
Basic and extensible post-processing of eddy covariance flux data with REddyProc, Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, 2018.
Wutzler, T., Reichstein, M., Moffat, A. M., Menzer, O., Migliavacca, M., Sickel, K., and Šigut, L.:
REddyProc: Post processing of (half-)hourly eddy-covariance measurements, https://cran.r-project.org/web/packages/REddyProc (last access: 18 January 2023), 2020.
Xiao, J., Chevallier, F., Gomez, C., Guanter, L., Hicke, J. A., Huete, A. R., Ichii, K., Ni, W., Pang, Y., Rahman, A. F., Sun, G., Yuan, W., Zhang, L., and Zhang, X.:
Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years, Remote Sens. Environ., 233, 111383, https://doi.org/10.1016/j.rse.2019.111383, 2019.
Xiao, X., Zhang, Q., Braswell, B., Urbanski, S., Boles, S., Wofsky, S., Moore III, B., and Ojima, D.:
Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data, Remote Sens. Environ., 91, 256–270, https://doi.org/10.1016/j.rse.2004.03.010, 2004.
Yan, D., Scott, R. L., Moore, D. J. P., Biederman, J. A., and Smith, W. K.:
Understanding the relationship between vegetation greenness and productivity across dryland ecosystems through the integration of PhenoCam, satellite, and eddy covariance data, Remote Sens. Environ., 223, 50–62, https://doi.org/10.1016/j.rse.2018.12.029, 2019.
Zhang, Y., Song, C., Sun, G., Band, L. E., McNulty, S., Noormets, A., Zhang, Q., and Zhang, Z.:
Development of a coupled carbon and water model for estimating global gross primary productivity and evapotranspiration based on eddy flux and remote sensing data, Agr. Forest Meteorol., 223, 116–131, https://doi.org/10.1016/j.agrformet.2016.04.003, 2016.
Zhang, Y., Joiner, J., Alemohammad, S. H., Zhou, S., and Gentine, P.:
A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks, Biogeosciences, 15, 5779–5800, https://doi.org/10.5194/bg-15-5779-2018, 2018.
Zhang, Y., Gentine, P., Luo, X., Lian, X., Liu, Y., Zhou, S., Michalak, A. M., Sun, W., Fisher, J. B., Piao, S., and Keenan, T. F.:
Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2, Nat. Commun., 13, 4875, https://doi.org/10.1038/s41467-022-32631-3, 2022.
Short summary
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.
Earth's drylands provide ecosystem services to many people and will likely be strongly affected...
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