Articles | Volume 22, issue 8
https://doi.org/10.5194/bg-22-2049-2025
© Author(s) 2025. 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-22-2049-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Detection of fast-changing intra-seasonal vegetation dynamics of drylands using solar-induced chlorophyll fluorescence (SIF)
School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, NY, USA
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA
Giulia Tagliabue
Remote Sensing of Environmental Dynamics Laboratory, Department of Environmental and Earth Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
Micol Rossini
Remote Sensing of Environmental Dynamics Laboratory, Department of Environmental and Earth Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
Francesco Pietro Fava
Department of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy
Cinzia Panigada
Remote Sensing of Environmental Dynamics Laboratory, Department of Environmental and Earth Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
Lutz Merbold
Integrative Agroecology Group, Research Division Agroecology and Environment, Agroscope, Reckenholzstr. 191, 8046 Zurich, Switzerland
Sonja Leitner
International Livestock Research Institute, Mazingira Centre, P.O. Box 30709, 00100 Nairobi, Kenya
Ying Sun
CORRESPONDING AUTHOR
School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, NY, USA
Related authors
No articles found.
Alouette van Hove, Kristoffer Aalstad, Vibeke Lind, Claudia Arndt, Vincent Odongo, Rodolfo Ceriani, Francesco Fava, John Hulth, and Norbert Pirk
EGUsphere, https://doi.org/10.5194/egusphere-2024-3994, https://doi.org/10.5194/egusphere-2024-3994, 2025
Short summary
Short summary
Research on methane emissions from African livestock is limited. We used a probabilistic method fusing drone and flux tower observations with an atmospheric model to estimate emissions from various herds. This approach proved robust under non-stationary wind conditions and effective in estimating emissions as low as 100 g h-1. We also detected herd locations using spectral anomalies in satellite data. Our approach can be used to estimate diverse sources, thereby improving emission inventories.
Gerardo E. Soto, Steven W. Wilcox, Patrick E. Clark, Francesco P. Fava, Nathaniel D. Jensen, Njoki Kahiu, Chuan Liao, Benjamin Porter, Ying Sun, and Christopher B. Barrett
Earth Syst. Sci. Data, 16, 5375–5404, https://doi.org/10.5194/essd-16-5375-2024, https://doi.org/10.5194/essd-16-5375-2024, 2024
Short summary
Short summary
This paper uses machine learning and linear unmixing to produce rangeland health indicators: Landsat time series of land cover classes and vegetation fractional cover of photosynthetic vegetation, non-photosynthetic vegetation, and bare ground in arid and semi-arid Kenya, Ethiopia, and Somalia. This represents the first multi-decadal Landsat-resolution dataset specifically designed for mapping and monitoring rangeland health in the arid and semi-arid rangelands of this portion of eastern Africa.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
Short summary
Short summary
A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Russell Doughty, Thomas P. Kurosu, Nicholas Parazoo, Philipp Köhler, Yujie Wang, Ying Sun, and Christian Frankenberg
Earth Syst. Sci. Data, 14, 1513–1529, https://doi.org/10.5194/essd-14-1513-2022, https://doi.org/10.5194/essd-14-1513-2022, 2022
Short summary
Short summary
We describe and compare solar-induced chlorophyll fluorescence data produced by NASA from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 platforms.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
Short summary
Short summary
The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Yang Liu, Simon Schallhart, Ditte Taipale, Toni Tykkä, Matti Räsänen, Lutz Merbold, Heidi Hellén, and Petri Pellikka
Atmos. Chem. Phys., 21, 14761–14787, https://doi.org/10.5194/acp-21-14761-2021, https://doi.org/10.5194/acp-21-14761-2021, 2021
Short summary
Short summary
We studied the mixing ratio of biogenic volatile organic compounds (BVOCs) in a humid highland and dry lowland African ecosystem in Kenya. The mixing ratio of monoterpenoids was similar to that measured in the relevant ecosystems in western and southern Africa, while that of isoprene was lower. Modeling the emission factors (EFs) for BVOCs from the lowlands, the EFs for isoprene and β-pinene agreed well with what is assumed in the MEGAN, while those of α-pinene and limonene were higher.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
Short summary
Short summary
Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
Short summary
Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Lutz Merbold, Charlotte Decock, Werner Eugster, Kathrin Fuchs, Benjamin Wolf, Nina Buchmann, and Lukas Hörtnagl
Biogeosciences, 18, 1481–1498, https://doi.org/10.5194/bg-18-1481-2021, https://doi.org/10.5194/bg-18-1481-2021, 2021
Short summary
Short summary
Our study investigated the exchange of the three major greenhouse gases (GHGs) over a temperate grassland prior to and after restoration through tillage in central Switzerland. Our results show that irregular management events, such as tillage, have considerable effects on GHG emissions in the year of tillage while leading to enhanced carbon uptake and similar nitrogen losses via nitrous oxide in the years following tillage to those observed prior to tillage.
Sheila Wachiye, Lutz Merbold, Timo Vesala, Janne Rinne, Matti Räsänen, Sonja Leitner, and Petri Pellikka
Biogeosciences, 17, 2149–2167, https://doi.org/10.5194/bg-17-2149-2020, https://doi.org/10.5194/bg-17-2149-2020, 2020
Short summary
Short summary
Limited data on emissions in Africa translate into uncertainty during GHG budgeting. We studied annual CO2, N2O, and CH4 emissions in four land-use types in Kenyan savanna using static chambers and gas chromatography. CO2 emissions varied between seasons and land-use types. Soil moisture and vegetation explained the seasonal variation, while soil temperature was insignificant. N2O and CH4 emissions did not vary at all sites. Our results are useful in climate change mitigation interventions.
Biagio Di Mauro, Roberto Garzonio, Micol Rossini, Gianluca Filippa, Paolo Pogliotti, Marta Galvagno, Umberto Morra di Cella, Mirco Migliavacca, Giovanni Baccolo, Massimiliano Clemenza, Barbara Delmonte, Valter Maggi, Marie Dumont, François Tuzet, Matthieu Lafaysse, Samuel Morin, Edoardo Cremonese, and Roberto Colombo
The Cryosphere, 13, 1147–1165, https://doi.org/10.5194/tc-13-1147-2019, https://doi.org/10.5194/tc-13-1147-2019, 2019
Short summary
Short summary
The snow albedo reduction due to dust from arid regions alters the melting dynamics of the snowpack, resulting in earlier snowmelt. We estimate up to 38 days of anticipated snow disappearance for a season that was characterized by a strong dust deposition event. This process has a series of further impacts. For example, earlier snowmelts may alter the hydrological cycle in the Alps, induce higher sensitivity to late summer drought, and finally impact vegetation and animal phenology.
Debsunder Dutta, David S. Schimel, Ying Sun, Christiaan van der Tol, and Christian Frankenberg
Biogeosciences, 16, 77–103, https://doi.org/10.5194/bg-16-77-2019, https://doi.org/10.5194/bg-16-77-2019, 2019
Short summary
Short summary
Canopy structural and leaf photosynthesis parameterizations are often fixed over time in Earth system models and represent large sources of uncertainty in predictions of carbon and water fluxes. We develop a moving window nonlinear optimal parameter inversion framework using constraining flux and satellite reflectance observations. The results demonstrate the applicability of the approach for error reduction and capturing the seasonal variability of key ecosystem parameters.
Kathrin Fuchs, Lukas Hörtnagl, Nina Buchmann, Werner Eugster, Val Snow, and Lutz Merbold
Biogeosciences, 15, 5519–5543, https://doi.org/10.5194/bg-15-5519-2018, https://doi.org/10.5194/bg-15-5519-2018, 2018
Short summary
Short summary
Replacing fertiliser nitrogen with biologically fixed nitrogen (BFN) through legumes has been suggested as a strategy for nitrous oxide (N2O) mitigation from intensively managed grasslands. On our site the mitigation strategy reduced N2O emissions by 54 % and 39 % in 2015 and 2016, while annual yields were similar under mitigation management. We conclude that N2O emissions can be effectively reduced without losses in yield by increasing the clover proportion and reducing fertilisation.
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
Short summary
Short summary
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.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
Short summary
Short summary
Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
Biagio Di Mauro, Giovanni Baccolo, Roberto Garzonio, Claudia Giardino, Dario Massabò, Andrea Piazzalunga, Micol Rossini, and Roberto Colombo
The Cryosphere, 11, 2393–2409, https://doi.org/10.5194/tc-11-2393-2017, https://doi.org/10.5194/tc-11-2393-2017, 2017
Short summary
Short summary
In the paper, we demonstrate the potential of field and satellite hyperspectral reflectance data in characterizing the spatial distribution of impurities on the Morteratsch Glacier. In situ reflectance spectra showed that impurities reduced ice reflectance in visible wavelengths by 80–90 %. Satellite data also showed the outcropping of dust during the melting season in the upper parts of the glacier. Laboratory measurements of cryoconite showed the presence of elemental and organic carbon.
Fanny Kittler, Ina Burjack, Chiara A. R. Corradi, Martin Heimann, Olaf Kolle, Lutz Merbold, Nikita Zimov, Sergey Zimov, and Mathias Göckede
Biogeosciences, 13, 5315–5332, https://doi.org/10.5194/bg-13-5315-2016, https://doi.org/10.5194/bg-13-5315-2016, 2016
Short summary
Short summary
We compared growing season CO2 fluxes of a wet tussock tundra ecosystem from an area affected by decadal drainage and an undisturbed area on the Kolyma floodplain in northeastern Siberia. The results show systematically reduced CO2 uptake within the drained area, caused by increased respiration, and that the local permafrost ecosystem is capable of adapting to significantly different hydrologic conditions without losing its capacity to act as a net sink for CO2.
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale
Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, https://doi.org/10.5194/bg-13-4291-2016, 2016
Short summary
Short summary
We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
O. Perez-Priego, J. Guan, M. Rossini, F. Fava, T. Wutzler, G. Moreno, N. Carvalhais, A. Carrara, O. Kolle, T. Julitta, M. Schrumpf, M. Reichstein, and M. Migliavacca
Biogeosciences, 12, 6351–6367, https://doi.org/10.5194/bg-12-6351-2015, https://doi.org/10.5194/bg-12-6351-2015, 2015
Short summary
Short summary
Sun-induced chlorophyll fluorescence and photochemical reflectance index revealed controls of climate and nutrient availability on photosynthesis (gross primary production, GPP). Meteo-driven models (MMs) were unable to describe nutrient-induced effects on GPP. Important implications can be derived from these results, and uncertainties in the prediction of global GPP still remain when MMs do not account for plant nutrient availability.
A. Porcar-Castell, A. Mac Arthur, M. Rossini, L. Eklundh, J. Pacheco-Labrador, K. Anderson, M. Balzarolo, M. P. Martín, H. Jin, E. Tomelleri, S. Cerasoli, K. Sakowska, A. Hueni, T. Julitta, C. J. Nichol, and L. Vescovo
Biogeosciences, 12, 6103–6124, https://doi.org/10.5194/bg-12-6103-2015, https://doi.org/10.5194/bg-12-6103-2015, 2015
B. Wolf, L. Merbold, C. Decock, B. Tuzson, E. Harris, J. Six, L. Emmenegger, and J. Mohn
Biogeosciences, 12, 2517–2531, https://doi.org/10.5194/bg-12-2517-2015, https://doi.org/10.5194/bg-12-2517-2015, 2015
W. Eugster and L. Merbold
SOIL, 1, 187–205, https://doi.org/10.5194/soil-1-187-2015, https://doi.org/10.5194/soil-1-187-2015, 2015
Short summary
Short summary
The eddy covariance (EC) method has become increasingly popular in soil science. The basic concept of this method and its use in different types of experimental designs in the field are given, and we indicate where progress in advancing and extending the field of applications is made. The greatest strengths of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes and (2) spatial integration over
small-scale heterogeneity in the soil.
R. V. Hiller, D. Bretscher, T. DelSontro, T. Diem, W. Eugster, R. Henneberger, S. Hobi, E. Hodson, D. Imer, M. Kreuzer, T. Künzle, L. Merbold, P. A. Niklaus, B. Rihm, A. Schellenberger, M. H. Schroth, C. J. Schubert, H. Siegrist, J. Stieger, N. Buchmann, and D. Brunner
Biogeosciences, 11, 1941–1959, https://doi.org/10.5194/bg-11-1941-2014, https://doi.org/10.5194/bg-11-1941-2014, 2014
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-5475-2013, https://doi.org/10.5194/gmdd-6-5475-2013, 2013
Revised manuscript not accepted
Related subject area
Remote Sensing: Terrestrial
Field heterogeneity of soil texture controls leaf water potential spatial distribution predicted from UAS-based vegetation indices in non-irrigated vineyards
Duration of vegetation green-up response to snowmelt on the Tibetan Plateau
Remote sensing reveals fire-driven enhancement of a C4 invasive alien grass on a small Mediterranean volcanic island
Divergent biophysical responses of western United States forests to wildfire driven by eco-climatic gradients
Synergistic use of Sentinel-2 and UAV-derived data for plant fractional cover distribution mapping of coastal meadows with digital elevation models
Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest
Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples
Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity
Geographically divergent trends in snow disappearance timing and fire ignitions across boreal North America
Dune belt restoration effectiveness assessed by UAV topographic surveys (northern Adriatic coast, Italy)
High-resolution data reveal a surge of biomass loss from temperate and Atlantic pine forests, contextualizing the 2022 fire season distinctiveness in France
Local environmental context drives heterogeneity of early succession dynamics in alpine glacier forefields
Louis Delval, Jordan Bates, François Jonard, and Mathieu Javaux
Biogeosciences, 22, 513–534, https://doi.org/10.5194/bg-22-513-2025, https://doi.org/10.5194/bg-22-513-2025, 2025
Short summary
Short summary
The accurate quantification of grapevine water status is crucial for winemakers as it significantly impacts wine quality. It is acknowledged that within a single vineyard, the variability of grapevine water status can be significant. The within-field spatial distribution of soil hydraulic conductance and weather conditions are the primary factors governing the leaf water potential spatial heterogeneity and extent observed in non-irrigated vineyards, and their effects are concomitant.
Jingwen Ni, Jin Chen, Yao Tang, Jingyi Xu, Jiahui Xu, Linxin Dong, Qingyu Gu, Bailang Yu, Jianping Wu, and Yan Huang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2885, https://doi.org/10.5194/egusphere-2024-2885, 2024
Short summary
Short summary
The average time differences (∆T) between green-up date and snowmelt onset date from 2001–2018 on the Tibetan Plateau were 36.7 days. With the increasing spring mean temperature, spring total precipitation and daily snowmelt, ∆T became shorter. Besides, in arid and low-vegetation areas, ∆T is primarily influenced by snowmelt, whereas in humid and high-vegetation areas, temperature plays a dominant role.
Riccardo Guarino, Daniele Cerra, Renzo Zaia, Alessandro Chiarucci, Pietro Lo Cascio, Duccio Rocchini, Piero Zannini, and Salvatore Pasta
Biogeosciences, 21, 2717–2730, https://doi.org/10.5194/bg-21-2717-2024, https://doi.org/10.5194/bg-21-2717-2024, 2024
Short summary
Short summary
The severity and the extent of a large fire event that occurred on the small volcanic island of Stromboli (Aeolian archipelago, Italy) on 25–26 May 2022 were evaluated through remotely sensed data to assess the short-term effect of fire on local plant communities. For the first time, we documented the outstanding after-fire resilience of an invasive alien species, Saccharum biflorum, which is a rhizomatous C4 perennial grass introduced on the island in the nineteenth century.
Surendra Shrestha, Christopher A. Williams, Brendan M. Rogers, John Rogan, and Dominik Kulakowski
Biogeosciences, 21, 2207–2226, https://doi.org/10.5194/bg-21-2207-2024, https://doi.org/10.5194/bg-21-2207-2024, 2024
Short summary
Short summary
Here, we generated chronosequences of leaf area index (LAI) and surface albedo as a function of time since fire to demonstrate the differences in the characteristic trajectories of post-fire biophysical changes among seven forest types and 21 level III ecoregions of the western United States (US) using satellite data from different sources. We also demonstrated how climate played the dominant role in the recovery of LAI and albedo 10 and 20 years after wildfire events in the western US.
Ricardo Martínez Prentice, Miguel Villoslada, Raymond D. Ward, Thaisa F. Bergamo, Chris B. Joyce, and Kalev Sepp
Biogeosciences, 21, 1411–1431, https://doi.org/10.5194/bg-21-1411-2024, https://doi.org/10.5194/bg-21-1411-2024, 2024
Short summary
Short summary
Despite hosting a wide range of ecosystem services, coastal wetlands face threats from global changes. This study models the plant fractional cover of plant communities in Estonian coastal meadows with a synergistic use of drone, satellite imagery and digital elevation models. This approach highlights the significant contribution of digital elevation models to multispectral data, enabling the modelling of heterogeneous plant community distributions in such wetlands.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, Abderrahmane Ounis, and Kamel Soudani
Biogeosciences, 21, 1259–1276, https://doi.org/10.5194/bg-21-1259-2024, https://doi.org/10.5194/bg-21-1259-2024, 2024
Short summary
Short summary
We show that FyieldLIF was not correlated with SIFy at the diurnal timescale, and the diurnal patterns in SIF and PAR did not match under clear-sky conditions due to canopy structure. Φk was sensitive to canopy structure. RF models show that Φk can be predicted using reflectance in different bands. RF models also show that FyieldLIF was more sensitive to reflectance and radiation than SIF and SIFy, indicating that the combined effect of reflectance bands could hide the SIF physiological trait.
Peng Li, Rong Shang, Jing M. Chen, Mingzhu Xu, Xudong Lin, Guirui Yu, Nianpeng He, and Li Xu
Biogeosciences, 21, 625–639, https://doi.org/10.5194/bg-21-625-2024, https://doi.org/10.5194/bg-21-625-2024, 2024
Short summary
Short summary
The amount of carbon that forests gain from the atmosphere, called net primary productivity (NPP), changes a lot with age. These forest NPP–age relationships could be modeled from field survey data, but we are not sure which model works best. Here we tested five different models using 3121 field survey samples in China, and the semi-empirical mathematical (SEM) function was determined as the optimal. The relationships built by SEM can improve China's forest carbon modeling and prediction.
Lammert Kooistra, Katja Berger, Benjamin Brede, Lukas Valentin Graf, Helge Aasen, Jean-Louis Roujean, Miriam Machwitz, Martin Schlerf, Clement Atzberger, Egor Prikaziuk, Dessislava Ganeva, Enrico Tomelleri, Holly Croft, Pablo Reyes Muñoz, Virginia Garcia Millan, Roshanak Darvishzadeh, Gerbrand Koren, Ittai Herrmann, Offer Rozenstein, Santiago Belda, Miina Rautiainen, Stein Rune Karlsen, Cláudio Figueira Silva, Sofia Cerasoli, Jon Pierre, Emine Tanır Kayıkçı, Andrej Halabuk, Esra Tunc Gormus, Frank Fluit, Zhanzhang Cai, Marlena Kycko, Thomas Udelhoven, and Jochem Verrelst
Biogeosciences, 21, 473–511, https://doi.org/10.5194/bg-21-473-2024, https://doi.org/10.5194/bg-21-473-2024, 2024
Short summary
Short summary
We reviewed optical remote sensing time series (TS) studies for monitoring vegetation productivity across ecosystems. Methods were categorized into trend analysis, land surface phenology, and assimilation into statistical or dynamic vegetation models. Due to progress in machine learning, TS processing methods will diversify, while modelling strategies will advance towards holistic processing. We propose integrating methods into a digital twin to improve the understanding of vegetation dynamics.
Thomas D. Hessilt, Brendan M. Rogers, Rebecca C. Scholten, Stefano Potter, Thomas A. J. Janssen, and Sander Veraverbeke
Biogeosciences, 21, 109–129, https://doi.org/10.5194/bg-21-109-2024, https://doi.org/10.5194/bg-21-109-2024, 2024
Short summary
Short summary
In boreal North America, snow and frozen ground prevail in winter, while fires occur in summer. Over the last 20 years, the northwestern parts have experienced earlier snow disappearance and more ignitions. This is opposite to the southeastern parts. However, earlier ignitions following earlier snow disappearance timing led to larger fires across the region. Snow disappearance timing may be a good proxy for ignition timing and may also influence important atmospheric conditions related to fires.
Regine Anne Faelga, Luigi Cantelli, Sonia Silvestri, and Beatrice Maria Sole Giambastiani
Biogeosciences, 20, 4841–4855, https://doi.org/10.5194/bg-20-4841-2023, https://doi.org/10.5194/bg-20-4841-2023, 2023
Short summary
Short summary
A dune restoration project on the northern Adriatic coast (Ravenna, Italy) was assessed using UAV monitoring. Structure-from-motion photogrammetry, elevation differencing, and statistical analysis were used to quantify dune development in terms of sand volume and vegetation cover change. Results show that the installed fence has been effective as there was significant sand accumulation, embryo dune development, and a decrease in blowout features due to increased vegetation colonization.
Lilian Vallet, Martin Schwartz, Philippe Ciais, Dave van Wees, Aurelien de Truchis, and Florent Mouillot
Biogeosciences, 20, 3803–3825, https://doi.org/10.5194/bg-20-3803-2023, https://doi.org/10.5194/bg-20-3803-2023, 2023
Short summary
Short summary
This study analyzes the ecological impact of the 2022 summer fire season in France by using high-resolution satellite data. The total biomass loss was 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests. While Mediterranean forests had a lower biomass loss, there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. This result revisits the distinctiveness of the 2022 fire season.
Arthur Bayle, Bradley Z. Carlson, Anaïs Zimmer, Sophie Vallée, Antoine Rabatel, Edoardo Cremonese, Gianluca Filippa, Cédric Dentant, Christophe Randin, Andrea Mainetti, Erwan Roussel, Simon Gascoin, Dov Corenblit, and Philippe Choler
Biogeosciences, 20, 1649–1669, https://doi.org/10.5194/bg-20-1649-2023, https://doi.org/10.5194/bg-20-1649-2023, 2023
Short summary
Short summary
Glacier forefields have long provided ecologists with a model to study patterns of plant succession following glacier retreat. We used remote sensing approaches to study early succession dynamics as it allows to analyze the deglaciation, colonization, and vegetation growth within a single framework. We found that the heterogeneity of early succession dynamics is deterministic and can be explained well by local environmental context. This work has been done by an international consortium.
Cited articles
Adams, E. C., Parache, H. B., Cherrington, E., Ellenburg, W. L., Mishra, V., Lucey, R., and Nakalembe, C.: Limitations of Remote Sensing in Assessing Vegetation Damage Due to the 2019–2021 Desert Locust Upsurge, Frontiers in Climate, 3, 112, https://doi.org/10.3389/FCLIM.2021.714273, 2021.
Ageet, S., Fink, A. H., Maranan, M., Diem, J. E., Hartter, J., Ssali, A. L., and Ayabagabo, P.: Validation of Satellite Rainfall Estimates over Equatorial East Africa, J. Hydrometeorol., 23, 129–151, https://doi.org/10.1175/JHM-D-21-0145.1, 2022.
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/10.1126/science.aaa1668, 2015.
Alonso, L., Gómez-Chova, L., Vila-Francés, J., Amorós-López, J., Guanter, L., Calpe, J., and Moreno, J.: Improved fraunhofer line discrimination method for vegetation fluorescence quantification, IEEE Geosci. Remote S., 5, 620–624, https://doi.org/10.1109/LGRS.2008.2001180, 2008.
Ayehu, G. T., Tadesse, T., Gessesse, B., and Dinku, T.: Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia, Atmos. Meas. Tech., 11, 1921–1936, https://doi.org/10.5194/amt-11-1921-2018, 2018.
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.
Beal, T., Gardner, C. D., Herrero, M., Iannotti, L. L., Merbold, L., Nordhagen, S., and Mottet, A.: Friend or Foe? The Role of Animal-Source Foods in Healthy and Environmentally Sustainable Diets, J. Nutr., 153, 409–425, https://doi.org/10.1016/J.TJNUT.2022.10.016, 2023.
Carbonell, V., Merbold, L., Díaz-Pinés, E., Dowling, T. P. F., and Butterbach-Bahl, K.: Nitrogen cycling in pastoral livestock systems in Sub-Saharan Africa: knowns and unknowns, Ecol. Appl., 31, e02368, https://doi.org/10.1002/EAP.2368, 2021.
Chang, C. Y., Guanter, L., Frankenberg, C., Köhler, P., Gu, L., Magney, T. S., Grossmann, K., and Sun, Y.: Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy, J. Geophys. Res.-Biogeo., 125, e2019JG005533, https://doi.org/10.1029/2019JG005533, 2020.
Chen, X.: RTSIF dataset, Figshare [data set], https://doi.org/10.6084/m9.figshare.19336346.v2, 2022.
Chen, X., Huang, Y., Nie, C., Zhang, S., Wang, G., Chen, S., and Chen, Z.: A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms, Scientific Data, 9, 427, https://doi.org/10.1038/s41597-022-01520-1, 2022.
Cheng, Y., Vrieling, A., Fava, F., Meroni, M., Marshall, M., and Gachoki, S.: Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2, Remote Sens. Environ., 248, 112004, https://doi.org/10.1016/j.rse.2020.112004, 2020.
Cogliati, S., Verhoef, W., Kraft, S., Sabater, N., Alonso, L., Vicent, J., Moreno, J., Drusch, M., and Colombo, R.: Retrieval of sun-induced fluorescence using advanced spectral fitting methods, Remote Sens. Environ., 169, 344–357, https://doi.org/10.1016/j.rse.2015.08.022, 2015.
Constenla-Villoslada, S., Liu, Y., Wen, J., Sun, Y., and Chonabayashi, S.: Large-scale land restoration improved drought resilience in Ethiopia's degraded watersheds, Nat. Sustain., 5, 488–497, https://doi.org/10.1038/s41893-022-00861-4, 2022.
Daumard, F., Champagne, S., Fournier, A., Goulas, Y., Ounis, A., Hanocq, J. F., and Moya, I.: A field platform for continuous measurement of canopy fluorescence, IEEE T. Geosci. Remote, 48, 3358–3368, https://doi.org/10.1109/TGRS.2010.2046420, 2010.
Dechant, B., Ryu, Y., Badgley, G., Zeng, Y., Berry, J. A., Zhang, Y., Goulas, Y., Li, Z., Zhang, Q., Kang, M., Li, J., and Moya, I.: Canopy structure explains the relationship between photosynthesis and sun-induced chlorophyll fluorescence in crops, Remote Sens. Environ., 241, 111733, https://doi.org/10.1016/j.rse.2020.111733, 2020.
Dechant, B., Ryu, Y., Badgley, G., Köhler, P., Rascher, U., Migliavacca, M., Zhang, Y., Tagliabue, G., Guan, K., Rossini, M., Goulas, Y., Zeng, Y., Frankenberg, C., and Berry, J. A.: NIRVP: A robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales, Remote Sens. Environ., 268, 112763, https://doi.org/10.1016/J.RSE.2021.112763, 2022.
Dinku, T., Funk, C., Peterson, P., Maidment, R., Tadesse, T., Gadain, H., and Ceccato, P.: Validation of the CHIRPS satellite rainfall estimates over eastern Africa, Q. J. Roy. Meteor. Soc., 144, 292–312, https://doi.org/10.1002/qj.3244, 2018.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., De Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., Van Der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Biogeochemistry Remote Sensing of Environment, 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017.
Dorigo, W., Preimesberger, W., Moesinger, L., Pasik, A., Scanlon, T., Hahn, S., Van der Schalie, R., Van der Vliet, M., De Jeu, R., Kidd, R., Rodriguez-Fernandez, N., and Hirschi, M.: ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 06.1, NERC EDS Centre for Environmental Data Analysis [data set] https://catalogue.ceda.ac.uk/uuid/43d73291472444e6b9c2d2420dbad7d6/ (last access: 21 March 2022), 2021.
Dowling, T. P. F., Langsdale, M. F., Ermida, S. L., Wooster, M. J., Merbold, L., Leitner, S., Trigo, I. F., Gluecks, I., Main, B., O'Shea, F., Hook, S., Rivera, G., De Jong, M. C., Nguyen, H., and Hyll, K.: A new East African satellite data validation station: Performance of the LSA-SAF all-weather land surface temperature product over a savannah biome, ISPRS J. Photogramm., 187, 240–258, https://doi.org/10.1016/J.ISPRSJPRS.2022.03.003, 2022.
Duveiller, G. and Cescatti, A.: Spatially downscaling sun-induced chlorophyll fluorescence leads to an improved temporal correlation with gross primary productivity, Remote Sens. Environ., 182, 72–89, https://doi.org/10.1016/j.rse.2016.04.027, 2016.
Fava, F., Vrieling, A., Fu, B., Smith, M. S., and Fu, C.: Earth observation for drought risk financing in pastoral systems of sub-Saharan Africa, Curr. Opin. Environ. Sustain., 48, 44–52, https://doi.org/10.1016/J.COSUST.2020.09.006, 2021.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Friedl, M. and Sulla-Menashe, D.: MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V061, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD12C1.061, 2022.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Scientific Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015.
Funk, C. C., Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., Romero, B. E., Husak, G. J., Michaelsen, J. C., and Verdin, A. P.: A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 pp., ftp://ftp.chc.ucsb/pub/org/chg/products/CHIRPS-2.0/docs/USGS-DS832.CHIRPS.pdf (last access: 18 September 2022), 2014 (data available at: https://data.chc.ucsb.edu/products/CHIRPS-2.0/, last access: 18 September 2022).
Gerhards, M., Schlerf, M., Mallick, K., and Udelhoven, T.: Challenges and Future Perspectives of Multi-/Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review, Remote Sensing, 11, 1240, https://doi.org/10.3390/RS11101240, 2019.
Global Modeling and Assimilation Office (GMAO): MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/VJAFPLI1CSIV, 2015a.
Global Modeling and Assimilation Office (GMAO): MERRA-2 tavg1_2d_lfo_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Forcings V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/L0T5GEG1NYFA, 2015b.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019.
Gu, L., Han, J., Wood, J. D., Chang, C. Y. Y., and Sun, Y.: Sun-induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions, New Phytol., 223, 1179–1191, https://doi.org/10.1111/NPH.15796, 2019.
Guanter, L., Bacour, C., Schneider, A., Aben, I., van Kempen, T. A., Maignan, F., Retscher, C., Köhler, P., Frankenberg, C., Joiner, J., and Zhang, Y.: The TROPOSIF global sun-induced fluorescence dataset from the Sentinel-5P TROPOMI mission, Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, 2021.
Han, J., Chang, C. Y. Y., Gu, L., Zhang, Y., Meeker, E. W., Magney, T. S., Walker, A. P., Wen, J., Kira, O., McNaull, S., and Sun, Y.: The physiological basis for estimating photosynthesis from Chla fluorescence, New Phytol., 234, 1206–1219, https://doi.org/10.1111/NPH.18045, 2022.
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, 2015.
Huang, J., Li, Y., Fu, C., Chen, F., Fu, Q., Dai, A., Shinoda, M., Ma, Z., Guo, W., Li, Z., Zhang, L., Liu, Y., Yu, H., He, Y., Xie, Y., Guan, X., Ji, M., Lin, L., Wang, S., Yan, H., and Wang, G.: Dryland climate change: Recent progress and challenges, Rev. Geophys., 55, 719–778, https://doi.org/10.1002/2016RG000550, 2017.
Huete, A., 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.
Köhler, P.: TROPOMI SIF, ftp://fluo.gps.caltech.edu, last access: 25 May 2023.
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.
Lawal, S., Hewitson, B., Egbebiyi, T. S., and Adesuyi, A.: On the suitability of using vegetation indices to monitor the response of Africa's terrestrial ecoregions to drought, Sci. Total Environ., 792, 148282, https://doi.org/10.1016/J.SCITOTENV.2021.148282, 2021.
Li, X. and Xiao, J.: Global OCO-2 SIF data set (GOSIF), Global Ecology Data Repository [data set], http://data.globalecology.unh.edu/data/GOSIF_v2, last access: 29 April 2022.
Li, W., Duveiller, G., Wieneke, S., Forkel, M., Gentine, P., Reichstein, M., Niu, S., Migliavacca, M., and Orth, R.: Regulation of the global carbon and water cycles through vegetation structural and physiological dynamics, Environ. Res. Lett., 19, 073008, https://doi.org/10.1088/1748-9326/AD5858, 2024.
Li, X. and Xiao, J.: A global, 0.05-degree product of solar-induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data, Remote Sens., 11, 517, https://doi.org/10.3390/rs11050517, 2019.
Lian, X., Piao, S., Chen, A., Huntingford, C., Fu, B., Li, L. Z. X., Huang, J., Sheffield, J., Berg, A. M., Keenan, T. F., McVicar, T. R., Wada, Y., Wang, X., Wang, T., Yang, Y., and Roderick, M. L.: Multifaceted characteristics of dryland aridity changes in a warming world, Nature Reviews Earth & Environment, 2, 232–250, https://doi.org/10.1038/s43017-021-00144-0, 2021.
Lyon, B. and Dewitt, D. G.: A recent and abrupt decline in the East African long rains, Geophys. Res. Lett, 39, L02702, https://doi.org/10.1029/2011GL050337, 2012.
Ma, Y., Liu, L., Chen, R., Du, S., and Liu, X.: Generation of a global spatially continuous tansat solar-induced chlorophyll fluorescence product by considering the impact of the solar radiation intensity, Remote Sens., 12, 2167, https://doi.org/10.3390/rs12132167, 2020.
Ma, Y., Liu, L., Liu, X., and Chen, J.: An improved downscaled sun-induced chlorophyll fluorescence (DSIF) product of GOME-2 dataset, Eur. J. Remote Sens., 55, 168–180, https://doi.org/10.1080/22797254.2022.2028579, 2022.
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.
Martini, D., Sakowska, K., Wohlfahrt, G., Pacheco-Labrador, J., van der Tol, C., Porcar-Castell, A., Magney, T. S., Carrara, A., Colombo, R., El-Madany, T. S., Gonzalez-Cascon, R., Martín, M. P., Julitta, T., Moreno, G., Rascher, U., Reichstein, M., Rossini, M., and Migliavacca, M.: Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production, New Phytol., 233, 2415–2428, https://doi.org/10.1111/NPH.17920, 2022.
Matanó, A., de Ruiter, M. C., Koehler, J., Ward, P. J., and Van Loon, A. F.: Caught Between Extremes: Understanding Human-Water Interactions During Drought-To-Flood Events in the Horn of Africa, Earth's Future, 10, e2022EF002747, https://doi.org/10.1029/2022EF002747, 2022.
Mengistu, A. G., Mengistu Tsidu, G., Koren, G., Kooreman, M. L., Boersma, K. F., Tagesson, T., Ardö, J., Nouvellon, Y., and Peters, W.: Sun-induced fluorescence and near-infrared reflectance of vegetation track the seasonal dynamics of gross primary production over Africa, Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, 2021.
Merbold, L., Scholes, R. J., Acosta, M., Beck, J., Bombelli, A., Fiedler, B., Grieco, E., Helmschrot, J., Hugo, W., Kasurinen, V., Kim, D. G., Körtzinger, A., Leitner, S., López-Ballesteros, A., Ndisi, M., Nickless, A., Salmon, E., Saunders, M., Skjelvan, I., Vermeulen, A. T., and Kutsch, W. L.: Opportunities for an African greenhouse gas observation system, Reg. Environ. Change, 21, 104, https://doi.org/10.1007/S10113-021-01823-W, 2021.
Miao, G., Guan, K., Yang, X., Bernacchi, C. J., Berry, J. A., DeLucia, E. H., Wu, J., Moore, C. E., Meacham, K., and Cai, Y.: Sun-Induced Chlorophyll Fluorescence, Photosynthesis, and Light Use Efficiency of a Soybean Field from Seasonally Continuous Measurements, J. Geophys. Res.-Biogeo., 123, 610–623, 2018.
Muthoka, J. M., Antonarakis, A. S., Vrieling, A., Fava, F., Salakpi, E. E., and Rowhani, P.: Assessing drivers of intra-seasonal grassland dynamics in a Kenyan savannah using digital repeat photography, Ecol. Indic., 142, 109223, https://doi.org/10.1016/J.ECOLIND.2022.109223, 2022.
Ngoma, H., Wen, W., Ojara, M., and Ayugi, B.: Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets, Meteorol. Atmos. Phys., 133, 823–843, https://doi.org/10.1007/S00703-021-00784-3, 2021.
NOVELTIS, UPV, SRON, LSCE, and ESA: The TROPOSIF global sun-induced fluorescence dataset from the TROPOMI mission, ESA [data set], https://doi.org/10.5270/esa-s5p_innovation-sif-20180501_20210320-v2.1-202104, 2021.
Otkin, J. A., Svoboda, M., Hunt, E. D., Ford, T. W., Anderson, M. C., Hain, C., and Basara, J. B.: Flash Droughts: A Review and Assessment of the Challenges Imposed by Rapid-Onset Droughts in the United States, B. Am. Meteorol. Soc., 99, 911–919, https://doi.org/10.1175/BAMS-D-17-0149.1, 2018.
Ouma, J. O., Wakjira, D., Amdihun, A., Nyaga, E., Opijah, F., Muthama, J., Otieno, V., Kayijamahe, E., Munywa, S., and Artan, G.: Forage Monitoring and Prediction Model for Early Warning Application over the East of Africa Region, Journal of Atmospheric Science Research, 5, 1–9, https://doi.org/10.30564/jasr.v5i4.4809, 2022.
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais, P., Friedlingstein, P., and Sitch, S.: Interannual variation of terrestrial carbon cycle: Issues and perspectives, Glob. Change Biol., 26, 300–318, https://doi.org/10.1111/GCB.14884, 2020.
Pierrat, Z., Magney, T., Parazoo, N. C., Grossmann, K., Bowling, D. R., Seibt, U., Johnson, B., Helgason, W., Barr, A., Bortnik, J., Norton, A., Maguire, A., Frankenberg, C., and Stutz, J.: Diurnal and Seasonal Dynamics of Solar-Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest, J. Geophys. Res.-Biogeo., 127, e2021JG006588, https://doi.org/10.1029/2021JG006588, 2022.
Porcar-Castell, A., Tyystjärvi, E., Atherton, J., Van Der Tol, C., Flexas, J., Pfündel, E. E., Moreno, J., Frankenberg, C., and Berry, J. A.: Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: Mechanisms and challenges, J. Exp. Bot., 65, 4065–4095, https://doi.org/10.1093/jxb/eru191, 2014.
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.
Prăvălie, R.: Drylands extent and environmental issues. A global approach, Earth Sci. Rev., 161, 259–278, https://doi.org/10.1016/j.earscirev.2016.08.003, 2016.
Preimesberger, W., Scanlon, T., Su, C. H., Gruber, A., and Dorigo, W.: Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record, IEEE T. Geosci. Remote, 59, 2845–2862, https://doi.org/10.1109/TGRS.2020.3012896, 2021.
Pricope, N. G., Husak, G., Lopez-Carr, D., Funk, C., and Michaelsen, J.: The climate-population nexus in the East African Horn: Emerging degradation trends in rangeland and pastoral livelihood zones, Global Environmental Change, 23, 1525–1541, https://doi.org/10.1016/j.gloenvcha.2013.10.002, 2013.
Qing, Y., Wang, S., Ancell, B. C., and Yang, Z.-L.: Accelerating flash droughts induced by the joint influence of soil moisture depletion and atmospheric aridity, Nat. Commun., 13, 1139, https://doi.org/10.1038/s41467-022-28752-4, 2022.
Qu, C., Hao, X., and Qu, J. J.: Monitoring Extreme Agricultural Drought over the Horn of Africa (HOA) Using Remote Sensing Measurements, Remote Sens., 11, 902, https://doi.org/10.3390/rs11080902, 2019.
R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 17 April 2025), 2022.
Reyer, C. P. O., Leuzinger, S., Rammig, A., Wolf, A., Bartholomeus, R. P., Bonfante, A., de Lorenzi, F., Dury, M., Gloning, P., Abou Jaoudé, R., Klein, T., Kuster, T. M., Martins, M., Niedrist, G., Riccardi, M., Wohlfahrt, G., de Angelis, P., de Dato, G., François, L., Menzel, A., and Pereira, M.: A plant's perspective of extremes: Terrestrial plant responses to changing climatic variability, Glob. Change Biol., 19, 75–89, https://doi.org/10.1111/GCB.12023, 2013.
Robinson, E. S., Yang, X., and Lee, J.-E.: Ecosystem Productivity and Water Stress in Tropical East Africa: A Case Study of the 2010–2011 Drought, Land, 8, 52, https://doi.org/10.3390/land8030052, 2019.
Schaaf, C. and Wang, Z.: MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF Adjusted Ref Daily L3 Global – 500m V061, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD43A4.061, 2021.
Shaw, E. A., White, C. T., Silver, W. L., Suding, K. N., and Hallett, L. M.: Intra-annual precipitation effects on annual grassland productivity and phenology are moderated by community responses, J. Ecol., 110, 162–172, https://doi.org/10.1111/1365-2745.13792, 2022.
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.
Sorensen, L.: A spatial analysis approach to the global delineation of dryland areas of relevance to the CBD Programme of Work on Dry and Subhumid Lands, UNEP-WCMC, Cambridge, https://resources.unep-wcmc.org/products/789fcac8959943ab9ed7a225e5316f08 (last access: 7 December 2022), 2007.
Sun, Y., Fu, R., Dickinson, R., Joiner, J., Frankenberg, C., Gu, L., Xia, Y., and Fernando, N.: Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events, J. Geophys. Res.-Biogeo., 120, 2427–2440, https://doi.org/10.1002/2015JG003150, 2015.
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.
Sun, Y., Gu, L., Wen, J., van der Tol, C., Porcar-Castell, A., Joiner, J., Chang, C. Y., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From Remotely-Sensed SIF to Ecosystem Structure, Function, and Service: Part I – Harnessing Theory, Glob. Change Biol., 29, 2926–2952, https://doi.org/10.1111/gcb.16634, 2023a.
Sun, Y., Wen, J., Gu, L., Joiner, J., Chang, C. Y., van der Tol, C., Porcar-Castell, A., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II – Harnessing data, Glob. Change Biol., 29, 2893–2925, https://doi.org/10.1111/gcb.16646, 2023b.
Tejera-Nieves, M., Abraha, M., Chen, J., Hamilton, S. K., Robertson, G. P., and Walker James, B.: Seasonal decline in leaf photosynthesis in perennial switchgrass explained by sink limitations and water deficit, Front. Plant Sci., 13, 1023571, https://doi.org/10.3389/FPLS.2022.1023571, 2023.
Trisos, C. H., Adelekan, I.O., Totin, E., Ayanlade, A., Efitre, J., Gemeda, A., Kalaba, K., Lennard, C., Masao, C., Mgaya, Y., Ngaruiya, G., Olago, D., Simpson, N. P., and Zakieldeen, S.: Africa, in: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1285–1455, https://doi.org/10.1017/9781009325844.011, 2022.
Tucker, C. J.: Red and photographic infrared linear combinations for monitoring vegetation, Remote Sens. Environ., 8, 127–150, https://doi.org/10.1016/0034-4257(79)90013-0, 1979.
Turner, A. J., Köhler, P., Magney, T. S., Frankenberg, C., Fung, I., and Cohen, R. C.: A double peak in the seasonality of California's photosynthesis as observed from space, Biogeosciences, 17, 405–422, https://doi.org/10.5194/bg-17-405-2020, 2020.
Wang, C., Beringer, J., Hutley, L. B., Cleverly, J., Li, J., Liu, Q., and Sun, Y.: Phenology Dynamics of Dryland Ecosystems Along the North Australian Tropical Transect Revealed by Satellite Solar-Induced Chlorophyll Fluorescence, Geophys. Res. Lett, 46, 5294–5302, https://doi.org/10.1029/2019GL082716, 2019.
Wang, L., Jiao, W., MacBean, N., Rulli, M. C., Manzoni, S., Vico, G., and D'Odorico, P.: Dryland productivity under a changing climate, Nat. Clim. Change, 12, 981–994, https://doi.org/10.1038/s41558-022-01499-y, 2022a.
Wang, S., Zhang, Y., Ju, W., Wu, M., Liu, L., He, W., and Peñuelas, J.: Temporally corrected long-term satellite solar-induced fluorescence leads to improved estimation of global trends in vegetation photosynthesis during 1995–2018, ISPRS J. Photogramm., 194, 222–234, https://doi.org/10.1016/j.isprsjprs.2022.10.018, 2022b.
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, 2022c.
Wang, Z., Schaaf, C. B., Sun, Q., Shuai, Y., and Román, M. O.: Capturing rapid land surface dynamics with Collection V006 MODIS BRDF/NBAR/Albedo (MCD43) products, Remote Sens. Environ., 207, 50–64, https://doi.org/10.1016/J.RSE.2018.02.001, 2018.
Wen, J.: JiamingWen/Kapiti_intraseasonal: Code for Detecting Intra-Seasonal Dryland Vegetation Dynamics Using SIF (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.15200357, 2025.
Wen, J., Köhler, P., Duveiller, G., Parazoo, N. C., Magney, T. S., Hooker, G., Yu, L., Chang, C. Y., and Sun, Y.: A framework for harmonizing multiple satellite instruments to generate a long-term global high spatial-resolution solar-induced chlorophyll fluorescence (SIF), Remote Sens. Environ., 239, 111644, https://doi.org/10.1016/j.rse.2020.111644, 2020.
Williams, A. P., Funk, C., Michaelsen, J., Rauscher, S. A., Robertson, I., Wils, T. H. G., Koprowski, M., Eshetu, Z., and Loader, N. J.: Recent summer precipitation trends in the Greater Horn of Africa and the emerging role of Indian Ocean sea surface temperature, Clim. Dynam., 39, 2307–2328, https://doi.org/10.1007/s00382-011-1222-y, 2012.
Yang, X., Tang, J., Mustard, J. F., Lee, J.-E., Rossini, M., Joiner, J., Munger, J. W., Kornfeld, A., and Richardson, A. D.: Solar-induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest, Geophys. Res. Lett., 42, 2977–2987, https://doi.org/10.1002/2015GL063201, 2015.
Yao, J., Liu, H., Huang, J., Gao, Z., Wang, G., Li, D., Yu, H., and Chen, X.: Accelerated dryland expansion regulates future variability in dryland gross primary production, Nat. Commun., 11, 1665, https://doi.org/10.1038/s41467-020-15515-2, 2020.
Yoshida, Y., Joiner, J., Tucker, C., Berry, J., Lee, J. E., Walker, G., Reichle, R., Koster, R., Lyapustin, A., and Wang, Y.: The 2010 Russian drought impact on satellite measurements of solar-induced chlorophyll fluorescence: Insights from modeling and comparisons with parameters derived from satellite reflectances, Remote Sens. Environ., 166, 163–177, https://doi.org/10.1016/j.rse.2015.06.008, 2015.
Yu, L., Wen, J., Chang, C. Y., Frankenberg, C., and Sun, Y.: High-Resolution Global Contiguous SIF of OCO-2, Geophys. Res. Lett, 46, 1449–1458, https://doi.org/10.1029/2018GL081109, 2019.
Yu, L., Wen, J., Chang, C. Y., Frankenberg, C., and Sun, Y.: High Resolution Global Contiguous SIF Estimates from OCO-2 SIF and MODIS, Version 2, ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1863, 2021.
Zeppel, M. J. B., Wilks, J. V., and Lewis, J. D.: Impacts of extreme precipitation and seasonal changes in precipitation on plants, Biogeosciences, 11, 3083–3093, https://doi.org/10.5194/bg-11-3083-2014, 2014.
Zhang, L., Xiao, J., Zheng, Y., Li, S., and Zhou, Y.: Increased carbon uptake and water use efficiency in global semi-arid ecosystems, Environ. Res. Lett., 15, 034022, https://doi.org/10.1088/1748-9326/AB68EC, 2020a.
Zhang, Y.: Contiguous solar induced chlorophyll fluorescence (CSIF), Zenodo [data set], https://doi.org/10.17605/OSF.IO/8XQY6, 2022.
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.
Zhang, Z., Zhang, Y., Porcar-Castell, A., Joiner, J., Guanter, L., Yang, X., Migliavacca, M., Ju, W., Sun, Z., Chen, S., Martini, D., Zhang, Q., Li, Z., Cleverly, J., Wang, H., and Goulas, Y.: Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence, Remote Sens. Environ., 240, 111722, https://doi.org/10.1016/j.rse.2020.111722, 2020b.
Zhang, Z., Zhang, Z., Hautier, Y., Qing, H., Yang, J., Bao, T., Hajek, O. L., and Knapp, A. K.: Effects of intra-annual precipitation patterns on grassland productivity moderated by the dominant species phenology, Front. Plant Sci., 14, 1142786, https://doi.org/10.3389/FPLS.2023.1142786, 2023.
Short summary
Solar-induced chlorophyll fluorescence (SIF), a tiny optical signal emitted from the core photosynthetic machinery, has emerged as a promising tool to evaluate vegetation growth from satellites. We find satellite SIF can capture intra-seasonal (i.e., from days to weeks) vegetation dynamics of dryland ecosystems, while greenness-based vegetation indices cannot. This study generates novel insights for developing effective real-time vegetation monitoring systems to inform climate risk management.
Solar-induced chlorophyll fluorescence (SIF), a tiny optical signal emitted from the core...
Altmetrics
Final-revised paper
Preprint