Articles | Volume 16, issue 1
https://doi.org/10.5194/essd-16-715-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-715-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
31 Jan 2024
Data description paper |
| 31 Jan 2024
| 31 Jan 2024
Reference maps of soil phosphorus for the pan-Amazon region
João Paulo Darela-Filho
CORRESPONDING AUTHOR
Institute of Biosciences, São Paulo State University (Unesp), Rio Claro, 13506-900, Brazil
Earth System Science Laboratory (LabTerra), University of Campinas (Unicamp) Center for Meteorological and Climatic Research Applied to Agriculture (CEPAGRI), Campinas – SP, 13083-886, Brazil
School of Life Sciences, Technical University of Munich (TUM), 85354 Freising, Germany
Anja Rammig
School of Life Sciences, Technical University of Munich (TUM), 85354 Freising, Germany
Katrin Fleischer
School of Life Sciences, Technical University of Munich (TUM), 85354 Freising, Germany
Department of Biogeochemical Signals, Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
Tatiana Reichert
School of Life Sciences, Technical University of Munich (TUM), 85354 Freising, Germany
Laynara Figueiredo Lugli
School of Life Sciences, Technical University of Munich (TUM), 85354 Freising, Germany
Carlos Alberto Quesada
Coordination of Environmental Dynamics (CODAM), National Institute for Amazonian Research – INPA, Avenida André Araújo, 2236, Manaus, Amazonas, 69060-001, Brazil
Luis Carlos Colocho Hurtarte
European Synchrotron Radiation Facility, Beamline ID21, Grenoble 38100, France
Diamond Light Source Ltd., Didcot, Oxfordshire, OX11 0DE, UK
Mateus Dantas de Paula
Senckenberg Biodiversity and Climate Research Centre (SBiK-F), 60325 Frankfurt am Main, Germany
David M. Lapola
Earth System Science Laboratory (LabTerra), University of Campinas (Unicamp) Center for Meteorological and Climatic Research Applied to Agriculture (CEPAGRI), Campinas – SP, 13083-886, Brazil
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Lucia S. Layritz, Konstantin Gregor, Andreas Krause, Stefan Kruse, Ben F. Meyer, Tom A. M. Pugh, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2024-1028, https://doi.org/10.5194/egusphere-2024-1028, 2024
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Disturbances (e.g. fire) can change which species grow in a forest, affecting water, carbon, energy flows, and the climate. They are expected to increase with climate change, but it is uncertain by how much. We studied how future climate and disturbances might impact vegetation with a simulation model. Our findings highlight the importance of considering both factors, with future disturbance patterns posing significant uncertainty. More research is needed to understand their future development.
Ingrid Chanca, Ingeborg Levin, Susan Trumbore, Kita Macario, Jost Lavric, Carlos Alberto Quesada, Alessandro Carioca de Araújo, Cléo Quaresma Dias Júnior, Hella van Asperen, Samuel Hammer, and Carlos Sierra
EGUsphere, https://doi.org/10.5194/egusphere-2024-883, https://doi.org/10.5194/egusphere-2024-883, 2024
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Assessing the net carbon (C) budget of the Amazon entails considering the magnitude and timing of C absorption and losses through respiration (transit time of C). Radiocarbon-based estimates of the transit time of C in the Amazon Tall Tower Observatory (ATTO) suggest a doubling of the transit time from 6 ± 2 years and 18 ± 5 years (October 2019 and December 2021, respectively). This variability indicates that only a fraction of newly fixed C can be stored for decades or longer.
Laura M. Pereira, Ignacio Gianelli, Therezah Achieng, Diva Amon, Sally Archibald, Suchinta Arif, Azucena Castro, Tapiwa Prosper Chimbadzwa, Kaera Coetzer, Tracy-Lynn Field, Odirilwe Selomane, Nadia Sitas, Nicola Stevens, Sebastian Villasante, Mohammed Armani, Duncan M. Kimuyu, Ibukun J. Adewumi, David M. Lapola, David Obura, Patricia Pinho, Felipe Roa-Clavijo, Juan Rocha, and U. Rashid Sumaila
Earth Syst. Dynam., 15, 341–366, https://doi.org/10.5194/esd-15-341-2024, https://doi.org/10.5194/esd-15-341-2024, 2024
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Narratives around tipping points, such as the need for
positivetipping points in energy transitions to avoid
negativeEarth system tipping points, do not take into account the entire spectrum of impacts the proposed interventions could have or still rely on narratives that maintain current unsustainable behaviours and marginalize many people. We unpack these ideas in the context of what they mean for the concept of tipping points, using a critical decolonial view from the Global South.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Benjamin F. Meyer, Allan Buras, Konstantin Gregor, Lucia S. Layritz, Adriana Principe, Jürgen Kreyling, Anja Rammig, and Christian S. Zang
Biogeosciences, 21, 1355–1370, https://doi.org/10.5194/bg-21-1355-2024, https://doi.org/10.5194/bg-21-1355-2024, 2024
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Late-spring frost (LSF), critically low temperatures when trees have already flushed their leaves, results in freezing damage leaving trees with reduced ability to perform photosynthesis. Forests with a high proportion of susceptible species like European beech are particularly vulnerable. However, this process is rarely included in dynamic vegetation models (DVMs). We show that the effect on simulated productivity and biomass is substantial, warranting more widespread inclusion of LSF in DVMs.
Luiz A. T. Machado, Jürgen Kesselmeier, Santiago Botia, Hella Van Asperen, Alessandro C. de Araújo, Paulo Artaxo, Achim Edtbauer, Rosa Ferreira, Hartwig Harder, Sam Jones, Cléo Q. Dias-Júnior, Guido G. Haytzmann, Carlos A. Quesada, Shujiro Komiya, Jost Lavric, Jos Lelieveld, Ingeborg Levin, Anke Nölscher, Eva Pfannerstill, Mira Pöhlker, Ulrich Pöschl, Akima Ringsdorf, Luciana Rizzo, Ana M. Yáñez-Serrano, Susan Trumbore, Wanda I. D. Valenti, Jordi Vila-Guerau de Arellano, David Walter, Jonathan Williams, Stefan Wolff, and Christopher Pöhlker
EGUsphere, https://doi.org/10.5194/egusphere-2023-2901, https://doi.org/10.5194/egusphere-2023-2901, 2024
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Composite analysis of the gas concentration before and after rainfall, during the day and night, gives insight into the complex relationship between trace gas variability and precipitation. This analysis helps to understand the sources and sinks of trace gases within a forest ecosystem. It elucidates processes that are not discernible under undisturbed conditions and contributes to a deeper understanding of the trace gas life cycle and its intricate interactions with cloud dynamics in the Amazon
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Phillip Papastefanou, Christian S. Zang, Zlatan Angelov, Aline Anderson de Castro, Juan Carlos Jimenez, Luiz Felipe Campos De Rezende, Romina C. Ruscica, Boris Sakschewski, Anna A. Sörensson, Kirsten Thonicke, Carolina Vera, Nicolas Viovy, Celso Von Randow, and Anja Rammig
Biogeosciences, 19, 3843–3861, https://doi.org/10.5194/bg-19-3843-2022, https://doi.org/10.5194/bg-19-3843-2022, 2022
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The Amazon rainforest has been hit by multiple severe drought events. In this study, we assess the severity and spatial extent of the extreme drought years 2005, 2010 and 2015/16 in the Amazon. Using nine different precipitation datasets and three drought indicators we find large differences in drought stress across the Amazon region. We conclude that future studies should use multiple rainfall datasets and drought indicators when estimating the impact of drought stress in the Amazon region.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Lore T. Verryckt, Sara Vicca, Leandro Van Langenhove, Clément Stahl, Dolores Asensio, Ifigenia Urbina, Romà Ogaya, Joan Llusià, Oriol Grau, Guille Peguero, Albert Gargallo-Garriga, Elodie A. Courtois, Olga Margalef, Miguel Portillo-Estrada, Philippe Ciais, Michael Obersteiner, Lucia Fuchslueger, Laynara F. Lugli, Pere-Roc Fernandez-Garberí, Helena Vallicrosa, Melanie Verlinden, Christian Ranits, Pieter Vermeir, Sabrina Coste, Erik Verbruggen, Laëtitia Bréchet, Jordi Sardans, Jérôme Chave, Josep Peñuelas, and Ivan A. Janssens
Earth Syst. Sci. Data, 14, 5–18, https://doi.org/10.5194/essd-14-5-2022, https://doi.org/10.5194/essd-14-5-2022, 2022
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We provide a comprehensive dataset of vertical profiles of photosynthesis and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N and P, and other leaf nutrients, in photosynthesis in tropical forests.
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021, https://doi.org/10.5194/gmd-14-6071-2021, 2021
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Forests play an important role in the global carbon cycle and for carbon storage. In Europe, forests are intensively managed. To understand how management influences carbon storage in European forests, we implement detailed forest management into the dynamic vegetation model LPJ-GUESS. We test the model by comparing model output to typical forestry measures, such as growing stock and harvest data, for different countries in Europe.
Thomas Janssen, Ype van der Velde, Florian Hofhansl, Sebastiaan Luyssaert, Kim Naudts, Bart Driessen, Katrin Fleischer, and Han Dolman
Biogeosciences, 18, 4445–4472, https://doi.org/10.5194/bg-18-4445-2021, https://doi.org/10.5194/bg-18-4445-2021, 2021
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Satellite images show that the Amazon forest has greened up during past droughts. Measurements of tree stem growth and leaf litterfall upscaled using machine-learning algorithms show that leaf flushing at the onset of a drought results in canopy rejuvenation and green-up during drought while simultaneously trees excessively shed older leaves and tree stem growth declines. Canopy green-up during drought therefore does not necessarily point to enhanced tree growth and improved forest health.
Gilvan Sampaio, Marília H. Shimizu, Carlos A. Guimarães-Júnior, Felipe Alexandre, Marcelo Guatura, Manoel Cardoso, Tomas F. Domingues, Anja Rammig, Celso von Randow, Luiz F. C. Rezende, and David M. Lapola
Biogeosciences, 18, 2511–2525, https://doi.org/10.5194/bg-18-2511-2021, https://doi.org/10.5194/bg-18-2511-2021, 2021
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The impact of large-scale deforestation and the physiological effects of elevated atmospheric CO2 on Amazon rainfall are systematically compared in this study. Our results are remarkable in showing that the two disturbances cause equivalent rainfall decrease, though through different causal mechanisms. These results highlight the importance of not only curbing regional deforestation but also reducing global CO2 emissions to avoid climatic changes in the Amazon.
Thomas A. M. Pugh, Tim Rademacher, Sarah L. Shafer, Jörg Steinkamp, Jonathan Barichivich, Brian Beckage, Vanessa Haverd, Anna Harper, Jens Heinke, Kazuya Nishina, Anja Rammig, Hisashi Sato, Almut Arneth, Stijn Hantson, Thomas Hickler, Markus Kautz, Benjamin Quesada, Benjamin Smith, and Kirsten Thonicke
Biogeosciences, 17, 3961–3989, https://doi.org/10.5194/bg-17-3961-2020, https://doi.org/10.5194/bg-17-3961-2020, 2020
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The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle. Estimates from six contemporary models found this time to range from 12.2 to 23.5 years for the global mean for 1985–2014. Future projections do not give consistent results, but 13 model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce large current uncertainty.
Thomas Janssen, Katrin Fleischer, Sebastiaan Luyssaert, Kim Naudts, and Han Dolman
Biogeosciences, 17, 2621–2645, https://doi.org/10.5194/bg-17-2621-2020, https://doi.org/10.5194/bg-17-2621-2020, 2020
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The frequency and severity of droughts are expected to increase in the tropics, impacting the functioning of tropical forests. Here, we synthesized observed responses to drought in Neotropical forests. We find that, during drought, trees generally close their leaf stomata, resulting in reductions in photosynthesis, growth and transpiration. However, on the ecosystem scale, these responses are not visible. This indicates that resistance to drought increases from the leaf to ecosystem scale.
Allan Buras, Anja Rammig, and Christian S. Zang
Biogeosciences, 17, 1655–1672, https://doi.org/10.5194/bg-17-1655-2020, https://doi.org/10.5194/bg-17-1655-2020, 2020
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This study compares the climatic conditions and ecosystem response of the extreme European drought of 2018 with the previous extreme drought of 2003. Using gridded climate data and satellite-based remote sensing information, our analyses qualify 2018 as the new European record drought with wide-ranging negative impacts on European ecosystems. Given the observation of forest-legacy effects in 2019 we call for Europe-wide forest monitoring to assess forest vulnerability to climate change.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Carlos Alberto Quesada, Claudia Paz, Erick Oblitas Mendoza, Oliver Lawrence Phillips, Gustavo Saiz, and Jon Lloyd
SOIL, 6, 53–88, https://doi.org/10.5194/soil-6-53-2020, https://doi.org/10.5194/soil-6-53-2020, 2020
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Amazon soils hold as much carbon (C) as is contained in the vegetation. In this work we sampled soils across 8 different Amazonian countries to try to understand which soil properties control current Amazonian soil C concentrations. We confirm previous knowledge that highly developed soils hold C through clay content interactions but also show a previously unreported mechanism of soil C stabilization in the younger Amazonian soil types which hold C through aluminium organic matter interactions.
Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Philippe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig
Geosci. Model Dev., 11, 5203–5215, https://doi.org/10.5194/gmd-11-5203-2018, https://doi.org/10.5194/gmd-11-5203-2018, 2018
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We propose a generic approach for a pixel-to-point comparison applicable for evaluation of models and remote-sensing products. We provide statistical measures accounting for the uncertainty in ecosystem variables. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest.
Sibyll Schaphoff, Werner von Bloh, Anja Rammig, Kirsten Thonicke, Hester Biemans, Matthias Forkel, Dieter Gerten, Jens Heinke, Jonas Jägermeyr, Jürgen Knauer, Fanny Langerwisch, Wolfgang Lucht, Christoph Müller, Susanne Rolinski, and Katharina Waha
Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, https://doi.org/10.5194/gmd-11-1343-2018, 2018
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Here we provide a comprehensive model description of a global terrestrial biosphere model, named LPJmL4, incorporating the carbon and water cycle and the quantification of agricultural production. The model allows for the consistent and joint quantification of climate and land use change impacts on the biosphere. The model represents the key ecosystem functions, but also the influence of humans on the biosphere. It comes with an evaluation paper to demonstrate the credibility of LPJmL4.
Sibyll Schaphoff, Matthias Forkel, Christoph Müller, Jürgen Knauer, Werner von Bloh, Dieter Gerten, Jonas Jägermeyr, Wolfgang Lucht, Anja Rammig, Kirsten Thonicke, and Katharina Waha
Geosci. Model Dev., 11, 1377–1403, https://doi.org/10.5194/gmd-11-1377-2018, https://doi.org/10.5194/gmd-11-1377-2018, 2018
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Here we provide a comprehensive evaluation of the now launched version 4.0 of the LPJmL biosphere, water, and agricultural model. The article is the second part to a comprehensive description of the LPJmL4 model. We have evaluated the model against various datasets of satellite observations, agricultural statistics, and in situ measurements by applying a range of metrics. We are able to show that the LPJmL4 model simulates many parameters and relations reasonably.
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.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
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We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
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Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
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In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
K. E. Clark, A. J. West, R. G. Hilton, G. P. Asner, C. A. Quesada, M. R. Silman, S. S. Saatchi, W. Farfan-Rios, R. E. Martin, A. B. Horwath, K. Halladay, M. New, and Y. Malhi
Earth Surf. Dynam., 4, 47–70, https://doi.org/10.5194/esurf-4-47-2016, https://doi.org/10.5194/esurf-4-47-2016, 2016
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The key findings of this paper are that landslides in the eastern Andes of Peru in the Kosñipata Valley rapidly turn over the landscape in ~1320 years, with a rate of 0.076% yr-1. Additionally, landslides were concentrated at lower elevations, due to an intense storm in 2010 accounting for ~1/4 of the total landslide area over the 25-year remote sensing study. Valley-wide carbon stocks were determined, and we estimate that 26 tC km-2 yr-1 of soil and biomass are stripped by landslides.
J. Lloyd, T. F. Domingues, F. Schrodt, F. Y. Ishida, T. R. Feldpausch, G. Saiz, C. A. Quesada, M. Schwarz, M. Torello-Raventos, M. Gilpin, B. S. Marimon, B. H. Marimon-Junior, J. A. Ratter, J. Grace, G. B. Nardoto, E. Veenendaal, L. Arroyo, D. Villarroel, T. J. Killeen, M. Steininger, and O. L. Phillips
Biogeosciences, 12, 6529–6571, https://doi.org/10.5194/bg-12-6529-2015, https://doi.org/10.5194/bg-12-6529-2015, 2015
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Across tropical South America, forest soils are typically of a higher cation status than their savanna equivalents with soil exchangeable potassium a key soil nutrient differentiating these two vegetation types. Differences in soil water storage capacity are also important – interacting with both potassium availability and precipitation regimes in a relatively complex manner.
M. O. Andreae, O. C. Acevedo, A. Araùjo, P. Artaxo, C. G. G. Barbosa, H. M. J. Barbosa, J. Brito, S. Carbone, X. Chi, B. B. L. Cintra, N. F. da Silva, N. L. Dias, C. Q. Dias-Júnior, F. Ditas, R. Ditz, A. F. L. Godoi, R. H. M. Godoi, M. Heimann, T. Hoffmann, J. Kesselmeier, T. Könemann, M. L. Krüger, J. V. Lavric, A. O. Manzi, A. P. Lopes, D. L. Martins, E. F. Mikhailov, D. Moran-Zuloaga, B. W. Nelson, A. C. Nölscher, D. Santos Nogueira, M. T. F. Piedade, C. Pöhlker, U. Pöschl, C. A. Quesada, L. V. Rizzo, C.-U. Ro, N. Ruckteschler, L. D. A. Sá, M. de Oliveira Sá, C. B. Sales, R. M. N. dos Santos, J. Saturno, J. Schöngart, M. Sörgel, C. M. de Souza, R. A. F. de Souza, H. Su, N. Targhetta, J. Tóta, I. Trebs, S. Trumbore, A. van Eijck, D. Walter, Z. Wang, B. Weber, J. Williams, J. Winderlich, F. Wittmann, S. Wolff, and A. M. Yáñez-Serrano
Atmos. Chem. Phys., 15, 10723–10776, https://doi.org/10.5194/acp-15-10723-2015, https://doi.org/10.5194/acp-15-10723-2015, 2015
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This paper describes the Amazon Tall Tower Observatory (ATTO), a new atmosphere-biosphere observatory located in the remote Amazon Basin. It presents results from ecosystem ecology, meteorology, trace gas, and aerosol measurements collected at the ATTO site during the first 3 years of operation.
G. Saiz, M. Bird, C. Wurster, C. A. Quesada, P. Ascough, T. Domingues, F. Schrodt, M. Schwarz, T. R. Feldpausch, E. Veenendaal, G. Djagbletey, G. Jacobsen, F. Hien, H. Compaore, A. Diallo, and J. Lloyd
Biogeosciences, 12, 5041–5059, https://doi.org/10.5194/bg-12-5041-2015, https://doi.org/10.5194/bg-12-5041-2015, 2015
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We demonstrate and explain differential patterns in SOM dynamics in C3/C4 mixed ecosystems at various spatial scales across contrasting climate and soils. This study shows that the interdependence between biotic and abiotic factors ultimately determines whether SOM dynamics of C3- and C4-derived vegetation are at variance in ecosystems where both vegetation types coexist. The results also highlight the far-reaching implications that vegetation thickening may have for the stability of deep SOM.
E. M. Veenendaal, M. Torello-Raventos, T. R. Feldpausch, T. F. Domingues, F. Gerard, F. Schrodt, G. Saiz, C. A. Quesada, G. Djagbletey, A. Ford, J. Kemp, B. S. Marimon, B. H. Marimon-Junior, E. Lenza, J. A. Ratter, L. Maracahipes, D. Sasaki, B. Sonké, L. Zapfack, D. Villarroel, M. Schwarz, F. Yoko Ishida, M. Gilpin, G. B. Nardoto, K. Affum-Baffoe, L. Arroyo, K. Bloomfield, G. Ceca, H. Compaore, K. Davies, A. Diallo, N. M. Fyllas, J. Gignoux, F. Hien, M. Johnson, E. Mougin, P. Hiernaux, T. Killeen, D. Metcalfe, H. S. Miranda, M. Steininger, K. Sykora, M. I. Bird, J. Grace, S. Lewis, O. L. Phillips, and J. Lloyd
Biogeosciences, 12, 2927–2951, https://doi.org/10.5194/bg-12-2927-2015, https://doi.org/10.5194/bg-12-2927-2015, 2015
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When nearby forest and savanna stands are compared, they are not as structurally different as first seems. Moreover, savanna-forest transition zones typically occur at higher rainfall for South America than for Africa but with coexistence confined to a well-defined edaphic-climate envelope. With interacting soil cation-soil water storage–precipitations effects on canopy cover also observed we argue that both soils and climate influence the location of the two major tropical vegetation types.
S. Rolinski, A. Rammig, A. Walz, W. von Bloh, M. van Oijen, and K. Thonicke
Biogeosciences, 12, 1813–1831, https://doi.org/10.5194/bg-12-1813-2015, https://doi.org/10.5194/bg-12-1813-2015, 2015
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Extreme weather events can but do not have to cause extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions.
We use a simple probabilistic risk assessment and apply it to terrestrial ecosystems, defining a hazard as negative net biome productivity. In Europe, ecosystems are vulnerable to drought in the Mediterranean and temperate region, whereas vulnerability in Scandinavia is not caused by water shortages.
A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
D. C. Zemp, C.-F. Schleussner, H. M. J. Barbosa, R. J. van der Ent, J. F. Donges, J. Heinke, G. Sampaio, and A. Rammig
Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, https://doi.org/10.5194/acp-14-13337-2014, 2014
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
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We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
B. B. L. Cintra, J. Schietti, T. Emillio, D. Martins, G. Moulatlet, P. Souza, C. Levis, C. A. Quesada, and J. Schöngart
Biogeosciences, 10, 7759–7774, https://doi.org/10.5194/bg-10-7759-2013, https://doi.org/10.5194/bg-10-7759-2013, 2013
A. D. A. Castanho, M. T. Coe, M. H. Costa, Y. Malhi, D. Galbraith, and C. A. Quesada
Biogeosciences, 10, 2255–2272, https://doi.org/10.5194/bg-10-2255-2013, https://doi.org/10.5194/bg-10-2255-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Biogeosciences and biodiversity
TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Spatial mapping of key plant functional traits in terrestrial ecosystems across China
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020
Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022
Investigating limnological processes and modern sedimentation at Lake Żabińskie, northeast Poland: a decade-long multi-variable dataset, 2012–2021
Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020
Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada
Quantifying exchangeable base cations in permafrost: a reserve of nutrients about to thaw
Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
The Portuguese Large Wildfire Spread database (PT-FireSprd)
Thirty-meter map of young forest age in China
GRiMeDB: the Global River Methane Database of concentrations and fluxes
A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests
Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT
A global database on holdover time of lightning-ignited wildfires
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
Mammals in the Chornobyl Exclusion Zone's Red Forest: a motion-activated camera trap study
Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years
AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America
TiP-Leaf: a dataset of leaf traits across vegetation types on the Tibetan Plateau
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
Global climate-related predictors at kilometer resolution for the past and future
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020
Global land surface 250 m 8 d fraction of absorbed photosynthetically active radiation (FAPAR) product from 2000 to 2021
Rates and timing of chlorophyll-a increases and related environmental variables in global temperate and cold-temperate lakes
Harmonized gap-filled datasets from 20 urban flux tower sites
Holocene spatiotemporal millet agricultural patterns in northern China: a dataset of archaeobotanical macroremains
The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil
Airborne SnowSAR data at X and Ku bands over boreal forest, alpine and tundra snow cover
The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile
Aridec: an open database of litter mass loss from aridlands worldwide with recommendations on suitable model applications
LegacyPollen 1.0: a taxonomically harmonized global late Quaternary pollen dataset of 2831 records with standardized chronologies
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu
Earth Syst. Sci. Data, 16, 2789–2809, https://doi.org/10.5194/essd-16-2789-2024, https://doi.org/10.5194/essd-16-2789-2024, 2024
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To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
Daju Wang, Peiyang Ren, Xiaosheng Xia, Lei Fan, Zhangcai Qin, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 16, 2465–2481, https://doi.org/10.5194/essd-16-2465-2024, https://doi.org/10.5194/essd-16-2465-2024, 2024
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This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
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Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
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Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge
Earth Syst. Sci. Data, 16, 277–293, https://doi.org/10.5194/essd-16-277-2024, https://doi.org/10.5194/essd-16-277-2024, 2024
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This study utilized 24,552 in situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020. These phenology maps are the first gridded, independent and reliable phenology data sources for China, offering a high spatial resolution of 0.1° and an average deviation of about 10 days. It contributes to more comprehensive research on plant phenology and climate change.
Jiabin Pu, Kai Yan, Samapriya Roy, Zaichun Zhu, Miina Rautiainen, Yuri Knyazikhin, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 15–34, https://doi.org/10.5194/essd-16-15-2024, https://doi.org/10.5194/essd-16-15-2024, 2024
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Long-term global LAI/FPAR products provide the fundamental dataset for accessing vegetation dynamics and studying climate change. This study develops a sensor-independent LAI/FPAR climate data record based on the integration of Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products and applies advanced gap-filling techniques. The SI LAI/FPAR CDR provides a valuable resource for researchers studying vegetation dynamics and their relationship to climate change in the 21st century.
Wojciech Tylmann, Alicja Bonk, Dariusz Borowiak, Paulina Głowacka, Kamil Nowiński, Joanna Piłczyńska, Agnieszka Szczerba, and Maurycy Żarczyński
Earth Syst. Sci. Data, 15, 5093–5103, https://doi.org/10.5194/essd-15-5093-2023, https://doi.org/10.5194/essd-15-5093-2023, 2023
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We present a dataset from the decade-long monitoring of Lake Żabińskie, a hardwater and eutrophic lake in northeast Poland. The lake contains varved sediments, which form a unique archive of past environmental variability. The monitoring program was designed to capture a pattern of relationships between meteorological conditions, limnological processes, and modern sedimentation and to verify if meteorological and limnological phenomena can be precisely tracked with varves.
Sen Cao, Muyi Li, Zaichun Zhu, Zhe Wang, Junjun Zha, Weiqing Zhao, Zeyu Duanmu, Jiana Chen, Yaoyao Zheng, Yue Chen, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, https://doi.org/10.5194/essd-15-4877-2023, 2023
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The long-term global leaf area index (LAI) products are critical for characterizing vegetation dynamics under environmental changes. This study presents an updated GIMMS LAI product (GIMMS LAI4g; 1982−2020) based on PKU GIMMS NDVI and massive Landsat LAI samples. With higher accuracy than other LAI products, GIMMS LAI4g removes the effects of orbital drift and sensor degradation in AVHRR data. It has better temporal consistency before and after 2000 and a more reasonable global vegetation trend.
Muyi Li, Sen Cao, Zaichun Zhu, Zhe Wang, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, https://doi.org/10.5194/essd-15-4181-2023, 2023
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Long-term global Normalized Difference Vegetation Index (NDVI) products support the understanding of changes in vegetation under environmental changes. This study generates a consistent global NDVI product (PKU GIMMS NDVI) from 1982–2022 that eliminates the issue of orbital drift and sensor degradation in Advanced Very High Resolution Radiometer (AVHRR) data. More accurate than its predecessor (GIMMS NDVI3g), it shows high temporal consistency with MODIS NDVI in describing vegetation trends.
Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, and Natalia De Leon Gatti
Earth Syst. Sci. Data, 15, 3963–3990, https://doi.org/10.5194/essd-15-3963-2023, https://doi.org/10.5194/essd-15-3963-2023, 2023
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A genomic, phenomic, and climate database for maize phenotype predictability in the US and Canada is introduced. The database encompasses climate from multiple sources and OMICS from the Genomes to Fields initiative (G2F) data from 2014 to 2021, including codes for input data quality and consistency controls. Earth system modelers and breeders can use CLIM4OMICS since it interconnects the climate and biological system sciences. CLIM4OMICS is designed to foster phenotype predictability.
Elisabeth Mauclet, Maëlle Villani, Arthur Monhonval, Catherine Hirst, Edward A. G. Schuur, and Sophie Opfergelt
Earth Syst. Sci. Data, 15, 3891–3904, https://doi.org/10.5194/essd-15-3891-2023, https://doi.org/10.5194/essd-15-3891-2023, 2023
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Permafrost ecosystems are limited in nutrients for vegetation development and constrain the biological activity to the active layer. Upon Arctic warming, permafrost degradation exposes organic and mineral soil material that may directly influence the capacity of the soil to retain key nutrients for vegetation growth and development. Here, we demonstrate that the average total exchangeable nutrient density (Ca, K, Mg, and Na) is more than 2 times higher in the permafrost than in the active layer.
Anna G. Boegehold, Ashley M. Burtner, Andrew C. Camilleri, Glenn Carter, Paul DenUyl, David Fanslow, Deanna Fyffe Semenyuk, Casey M. Godwin, Duane Gossiaux, Thomas H. Johengen, Holly Kelchner, Christine Kitchens, Lacey A. Mason, Kelly McCabe, Danna Palladino, Dack Stuart, Henry Vanderploeg, and Reagan Errera
Earth Syst. Sci. Data, 15, 3853–3868, https://doi.org/10.5194/essd-15-3853-2023, https://doi.org/10.5194/essd-15-3853-2023, 2023
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Western Lake Erie suffers from cyanobacterial harmful algal blooms (HABs) despite decades of international management efforts. In response, the US National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs. Here we describe the data collected from this monitoring program from 2012 to 2021.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
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We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
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Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros
Earth Syst. Sci. Data, 15, 2879–2926, https://doi.org/10.5194/essd-15-2879-2023, https://doi.org/10.5194/essd-15-2879-2023, 2023
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The Global River Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters and concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
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We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
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We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Beatriz P. Cazorla, Javier Cabello, Andrés Reyes, Emilio Guirado, Julio Peñas, Antonio J. Pérez-Luque, and Domingo Alcaraz-Segura
Earth Syst. Sci. Data, 15, 1871–1887, https://doi.org/10.5194/essd-15-1871-2023, https://doi.org/10.5194/essd-15-1871-2023, 2023
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This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada (Spain), a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTSER) network.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
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We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
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This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
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Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Yili Jin, Haoyan Wang, Jie Xia, Jian Ni, Kai Li, Ying Hou, Jing Hu, Linfeng Wei, Kai Wu, Haojun Xia, and Borui Zhou
Earth Syst. Sci. Data, 15, 25–39, https://doi.org/10.5194/essd-15-25-2023, https://doi.org/10.5194/essd-15-25-2023, 2023
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The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits from 468 species of 1692 individuals, covering a great proportion of species and vegetation types on the highest plateau in the world. This work is the first plant trait dataset that represents all of the alpine vegetation on the TP, which is not only an update of the Chinese plant trait database, but also a great contribution to the global trait database.
Timon Miesner, Ulrike Herzschuh, Luidmila A. Pestryakova, Mareike Wieczorek, Evgenii S. Zakharov, Alexei I. Kolmogorov, Paraskovya V. Davydova, and Stefan Kruse
Earth Syst. Sci. Data, 14, 5695–5716, https://doi.org/10.5194/essd-14-5695-2022, https://doi.org/10.5194/essd-14-5695-2022, 2022
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We present data which were collected on expeditions to the northeast of the Russian Federation. One table describes the 226 locations we visited during those expeditions, and the other describes 40 289 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements or use data (as presented here).
Philipp Brun, Niklaus E. Zimmermann, Chantal Hari, Loïc Pellissier, and Dirk Nikolaus Karger
Earth Syst. Sci. Data, 14, 5573–5603, https://doi.org/10.5194/essd-14-5573-2022, https://doi.org/10.5194/essd-14-5573-2022, 2022
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Using mechanistic downscaling, we developed CHELSA-BIOCLIM+, a set of 15 biologically relevant, climate-related variables at unprecedented resolution, as a basis for environmental analyses. It includes monthly time series for 38+ years and 30-year averages for three future periods and three emission scenarios. Estimates matched well with station measurements, but few biases existed. The data allow for detailed assessments of climate-change impact on ecosystems and their services to societies.
Shaoyang He, Yongqiang Zhang, Ning Ma, Jing Tian, Dongdong Kong, and Changming Liu
Earth Syst. Sci. Data, 14, 5463–5488, https://doi.org/10.5194/essd-14-5463-2022, https://doi.org/10.5194/essd-14-5463-2022, 2022
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This study developed a daily, 500 m evapotranspiration and gross primary production product (PML-V2(China)) using a locally calibrated water–carbon coupled model, PML-V2, which was well calibrated against observations at 26 flux sites across nine land cover types. PML-V2 (China) performs satisfactorily in the plot- and basin-scale evaluations compared with other mainstream products. It improved intra-annual ET and GPP dynamics, particularly in the cropland ecosystem.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
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The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
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Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
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We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Keyang He, Houyuan Lu, Jianping Zhang, and Can Wang
Earth Syst. Sci. Data, 14, 4777–4791, https://doi.org/10.5194/essd-14-4777-2022, https://doi.org/10.5194/essd-14-4777-2022, 2022
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Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic and Bronze ages in northern China. Temporally, millet agriculture underwent a dramatic transition from low-yield broomcorn to high-yield foxtail millet around 6000 cal. a BP under the influence of climate and population. Spatially, millet agriculture spread westward and northward from the mid-lower Yellow River (MLY) to the agro-pastoral ecotone (APE) around 6000 cal. a BP and diversified afterwards.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
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We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Alejandro Miranda, Rayén Mentler, Ítalo Moletto-Lobos, Gabriela Alfaro, Leonardo Aliaga, Dana Balbontín, Maximiliano Barraza, Susanne Baumbach, Patricio Calderón, Fernando Cárdenas, Iván Castillo, Gonzalo Contreras, Felipe de la Barra, Mauricio Galleguillos, Mauro E. González, Carlos Hormazábal, Antonio Lara, Ian Mancilla, Francisca Muñoz, Cristian Oyarce, Francisca Pantoja, Rocío Ramírez, and Vicente Urrutia
Earth Syst. Sci. Data, 14, 3599–3613, https://doi.org/10.5194/essd-14-3599-2022, https://doi.org/10.5194/essd-14-3599-2022, 2022
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Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic data. High-quality information can help to transform evidence into decision-making. Taking advantage of big-data and remote sensing technics we developed a flexible workflow to reconstruct burned area and fire severity data for more than 8000 individual fires in Chile. The framework developed for the database can be applied anywhere in the world with minimal adaptation.
Agustín Sarquis, Ignacio Andrés Siebenhart, Amy Theresa Austin, and Carlos A. Sierra
Earth Syst. Sci. Data, 14, 3471–3488, https://doi.org/10.5194/essd-14-3471-2022, https://doi.org/10.5194/essd-14-3471-2022, 2022
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Plant litter breakdown in aridlands is driven by processes different from those in more humid ecosystems. A better understanding of these processes will allow us to make better predictions of future carbon cycling. We have compiled aridec, a database of plant litter decomposition studies in aridlands and tested some modeling applications for potential users. Aridec is open for use and collaboration, and we hope it will help answer newer and more important questions as the database develops.
Ulrike Herzschuh, Chenzhi Li, Thomas Böhmer, Alexander K. Postl, Birgit Heim, Andrei A. Andreev, Xianyong Cao, Mareike Wieczorek, and Jian Ni
Earth Syst. Sci. Data, 14, 3213–3227, https://doi.org/10.5194/essd-14-3213-2022, https://doi.org/10.5194/essd-14-3213-2022, 2022
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Pollen preserved in environmental archives such as lake sediments and bogs are extensively used for reconstructions of past vegetation and climate. Here we present LegacyPollen 1.0, a dataset of 2831 fossil pollen records from all over the globe that were collected from publicly available databases. We harmonized the names of the pollen taxa so that all datasets can be jointly investigated. LegacyPollen 1.0 is available as an open-access dataset.
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de Myttenaere, A., Golden, B., Le Grand, B., and Rossi, F.: Mean Absolute Percentage Error for Regression Models, Neurocomputing, 192, 38–48, https://doi.org/10.1016/j.neucom.2015.12.114, 2016.
Dijkshoorn, J. A., Huting, J. R. M., and P., T.: Update of the 1:5 Million Soil and Terrain Database for Latin America and the Caribbean (Soterlac; Version 2.0), ISRIC – World Soil Information, Wageningen, https://isric.org/sites/default/files/isric_report_2005_01.pdf (last access: 20 October 2023), 2005.
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Gama-Rodrigues, A. C., Sales, M. V. S., Silva, P. S. D., Comerford, N. B., Cropper, W. P., and Gama-Rodrigues, E. F.: An Exploratory Analysis of Phosphorus Transformations in Tropical Soils Using Structural Equation Modeling, Biogeochemistry, 118, 453–469, https://doi.org/10.1007/s10533-013-9946-x, 2014.
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Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P. B., van Bodegom, P. M., and Niinemets, Ü.: Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling, Biogeosciences, 9, 3547–3569, https://doi.org/10.5194/bg-9-3547-2012, 2012.
Gu, C. H. and Margenot, A. J.: Navigating Limitations and Opportunities of Soil Phosphorus Fractionation, Plant Soil, 459, 13–17, https://doi.org/10.1007/s11104-020-04552-x, 2021.
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He, X., Augusto, L., Goll, D. S., Ringeval, B., Wang, Y., Helfenstein, J., Huang, Y., Yu, K., Wang, Z., Yang, Y., and Hou, E.: Global patterns and drivers of soil total phosphorus concentration, Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, 2021.
He, X., Augusto, L., Goll, D. S., Ringeval, B., Wang, Y.-P., Helfenstein, J., Huang, Y., and Hou, E.: Global patterns and drivers of phosphorus fractions in natural soils, Biogeosciences, 20, 4147–4163, https://doi.org/10.5194/bg-20-4147-2023, 2023.
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Hedley, M. J., Stewart, J. W. B., and Chauhan, B. S.: Changes in Inorganic and Organic Soil-Phosphorus Fractions Induced by Cultivation Practices and by Laboratory Incubations, Soil Sci. Soc. Am. J., 46, 970–976, https://doi.org/10.2136/sssaj1982.03615995004600050017x, 1982.
Helfenstein, J., Tamburini, F., von Sperber, C., Massey, M. S., Pistocchi, C., Chadwick, O. A., Vitousek, P. M., Kretzschmar, R., and Frossard, E.: Combining Spectroscopic and Isotopic Techniques Gives a Dynamic View of Phosphorus Cycling in Soil, Nat. Commun., 9, 3226, https://doi.org/10.1038/s41467-018-05731-2, 2018.
Helfenstein, J., Pistocchi, C., Oberson, A., Tamburini, F., Goll, D. S., and Frossard, E.: Estimates of mean residence times of phosphorus in commonly considered inorganic soil phosphorus pools, Biogeosciences, 17, 441–454, https://doi.org/10.5194/bg-17-441-2020, 2020.
Hou, E., Tan, X., Heenan, M., and Wen, D.: A Global Dataset of Plant Available and Unavailable Phosphorus in Natural Soils Derived by Hedley Method, Sci. Data, 5, 180166, https://doi.org/10.1038/sdata.2018.166, 2018.
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Lloyd, J., Domingues, T. F., Schrodt, F., Ishida, F. Y., Feldpausch, T. R., Saiz, G., Quesada, C. A., Schwarz, M., Torello-Raventos, M., Gilpin, M., Marimon, B. S., Marimon-Junior, B. H., Ratter, J. A., Grace, J., Nardoto, G. B., Veenendaal, E., Arroyo, L., Villarroel, D., Killeen, T. J., Steininger, M., and Phillips, O. L.: Edaphic, structural and physiological contrasts across Amazon Basin forest–savanna ecotones suggest a role for potassium as a key modulator of tropical woody vegetation structure and function, Biogeosciences, 12, 6529–6571, https://doi.org/10.5194/bg-12-6529-2015, 2015.
Lucas, T. C. D.: A Translucent Box: Interpretable Machine Learning in Ecology, Ecol. Monogr., 90, e01422, https://doi.org/10.1002/ecm.1422, 2020.
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Meyer, H. and Pebesma, E.: Predicting into Unknown Space? Estimating the Area of Applicability of Spatial Prediction Models, Methods Ecol. Evol., 12, 1620–1633, https://doi.org/10.1111/2041-210x.13650, 2021.
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Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-Learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011.
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Short summary
Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it interacts with carbon cycle in ecosystems. To apply these models, it is important to know the distribution of phosphorus in soil. In this study we estimated the distribution of phosphorus in the Amazon region. The results showed a clear gradient of soil development and P content. These maps can help improve ecosystem models and generate new hypotheses about phosphorus availability in the Amazon.
Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it...
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