Articles | Volume 11, issue 4
https://doi.org/10.5194/essd-11-1839-2019
© Author(s) 2019. 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-11-1839-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
28 Nov 2019
Data description paper |
| 28 Nov 2019
| 28 Nov 2019
Global variability in belowground autotrophic respiration in terrestrial ecosystems
Xiaolu Tang
College of Earth Science, Chengdu University of Technology, Chengdu, China
State Environmental Protection Key Laboratory of Synergetic Control
and Joint Remediation for Soil & Water Pollution, Chengdu University of
Technology, Chengdu, China
Shaohui Fan
Key Laboratory of Bamboo and Rattan, International Centre for Bamboo and Rattan, Beijing, China
Wenjie Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Resources and Environmental Information
System, Institute of Geographic Sciences and Natural Resources Research,
Beijing, China
School of Life Sciences, University of Technology Sydney, Sydney, New South Wales,
Australia
School of Life Sciences, University of Technology Sydney, Sydney, New South Wales,
Australia
Guo Chen
College of Earth Science, Chengdu University of Technology, Chengdu, China
Leilei Shi
Key Laboratory of Geospatial Technology for the Middle and Lower Yellow
River Regions, College of Environment and Planning, Henan University,
Jinming Avenue, Kaifeng, China
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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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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.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-364, https://doi.org/10.5194/essd-2022-364, 2023
Revised manuscript accepted for ESSD
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Modern and fossil pollen data contain precious information to reconstruct pas climate and environment. 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.
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.
Hannah Weiser, Jannika Schäfer, Lukas Winiwarter, Nina Krašovec, Fabian E. Fassnacht, and Bernhard Höfle
Earth Syst. Sci. Data, 14, 2989–3012, https://doi.org/10.5194/essd-14-2989-2022, https://doi.org/10.5194/essd-14-2989-2022, 2022
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3D point clouds, acquired by laser scanning, allow us to retrieve information about forest structure and individual tree properties. We conducted airborne, UAV-borne and terrestrial laser scanning in German mixed forests, resulting in overlapping point clouds with different characteristics. From these, we generated a comprehensive database of individual tree point clouds and corresponding tree metrics. Our dataset may serve as a benchmark dataset for algorithms in forestry research.
Quandi Niu, Xuecao Li, Jianxi Huang, Hai Huang, Xianda Huang, Wei Su, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2851–2864, https://doi.org/10.5194/essd-14-2851-2022, https://doi.org/10.5194/essd-14-2851-2022, 2022
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In this paper we generated the first national maize phenology product with a fine spatial resolution (30 m) and a long temporal span (1985–2020) in China, using Landsat images. The derived phenological indicators agree with in situ observations and provide more spatial details than moderate resolution phenology products. The extracted maize phenology dataset can support precise yield estimation and deepen our understanding of the response of agroecosystem to global warming in the future.
Alexandre Castagna, Luz Amadei Martínez, Margarita Bogorad, Ilse Daveloose, Renaat Dasseville, Heidi Melita Dierssen, Matthew Beck, Jonas Mortelmans, Héloïse Lavigne, Ana Dogliotti, David Doxaran, Kevin Ruddick, Wim Vyverman, and Koen Sabbe
Earth Syst. Sci. Data, 14, 2697–2719, https://doi.org/10.5194/essd-14-2697-2022, https://doi.org/10.5194/essd-14-2697-2022, 2022
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Here we describe a dataset of optical measurements paired with the concentration and composition of dissolved and particulate components of water systems in Belgium. Sampling was performed over eight lakes, a coastal lagoon, an estuary, and coastal waters, covering the period of 2017 to 2019. The data cover a broad range of conditions and can be useful for development and evaluation of hyperspectral methods in hydrology optics and remote sensing.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Esther Githumbi, Ralph Fyfe, Marie-Jose Gaillard, Anna-Kari Trondman, Florence Mazier, Anne-Birgitte Nielsen, Anneli Poska, Shinya Sugita, Jessie Woodbridge, Julien Azuara, Angelica Feurdean, Roxana Grindean, Vincent Lebreton, Laurent Marquer, Nathalie Nebout-Combourieu, Miglė Stančikaitė, Ioan Tanţău, Spassimir Tonkov, Lyudmila Shumilovskikh, and LandClimII data contributors
Earth Syst. Sci. Data, 14, 1581–1619, https://doi.org/10.5194/essd-14-1581-2022, https://doi.org/10.5194/essd-14-1581-2022, 2022
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Reconstruction of past land cover is necessary for the study of past climate–land cover interactions and the evaluation of climate models and land-use scenarios. We used 1128 available pollen records from across Europe covering the last 11 700 years in the REVEALS model to calculate percentage cover and associated standard errors for 31 taxa, 12 plant functional types and 3 land-cover types. REVEALS results are reliant on the quality of the input datasets.
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
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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.
Sandy P. Harrison, Roberto Villegas-Diaz, Esmeralda Cruz-Silva, Daniel Gallagher, David Kesner, Paul Lincoln, Yicheng Shen, Luke Sweeney, Daniele Colombaroli, Adam Ali, Chéïma Barhoumi, Yves Bergeron, Tatiana Blyakharchuk, Přemysl Bobek, Richard Bradshaw, Jennifer L. Clear, Sambor Czerwiński, Anne-Laure Daniau, John Dodson, Kevin J. Edwards, Mary E. Edwards, Angelica Feurdean, David Foster, Konrad Gajewski, Mariusz Gałka, Michelle Garneau, Thomas Giesecke, Graciela Gil Romera, Martin P. Girardin, Dana Hoefer, Kangyou Huang, Jun Inoue, Eva Jamrichová, Nauris Jasiunas, Wenying Jiang, Gonzalo Jiménez-Moreno, Monika Karpińska-Kołaczek, Piotr Kołaczek, Niina Kuosmanen, Mariusz Lamentowicz, Martin Lavoie, Fang Li, Jianyong Li, Olga Lisitsyna, José Antonio López-Sáez, Reyes Luelmo-Lautenschlaeger, Gabriel Magnan, Eniko Katalin Magyari, Alekss Maksims, Katarzyna Marcisz, Elena Marinova, Jenn Marlon, Scott Mensing, Joanna Miroslaw-Grabowska, Wyatt Oswald, Sebastián Pérez-Díaz, Ramón Pérez-Obiol, Sanna Piilo, Anneli Poska, Xiaoguang Qin, Cécile C. Remy, Pierre J. H. Richard, Sakari Salonen, Naoko Sasaki, Hieke Schneider, William Shotyk, Migle Stancikaite, Dace Šteinberga, Normunds Stivrins, Hikaru Takahara, Zhihai Tan, Liva Trasune, Charles E. Umbanhowar, Minna Väliranta, Jüri Vassiljev, Xiayun Xiao, Qinghai Xu, Xin Xu, Edyta Zawisza, Yan Zhao, Zheng Zhou, and Jordan Paillard
Earth Syst. Sci. Data, 14, 1109–1124, https://doi.org/10.5194/essd-14-1109-2022, https://doi.org/10.5194/essd-14-1109-2022, 2022
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We provide a new global data set of charcoal preserved in sediments that can be used to examine how fire regimes have changed during past millennia and to investigate what caused these changes. The individual records have been standardised, and new age models have been constructed to allow better comparison across sites. The data set contains 1681 records from 1477 sites worldwide.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Jakob J. Assmann, Jesper E. Moeslund, Urs A. Treier, and Signe Normand
Earth Syst. Sci. Data, 14, 823–844, https://doi.org/10.5194/essd-14-823-2022, https://doi.org/10.5194/essd-14-823-2022, 2022
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In 2014 and 2015, the Danish government scanned the whole of Denmark using laser scanners on planes. The information can help biologists learn more about Denmark's natural environment. To make it easier to access the outputs from the scan, we divided the country into 10 m x 10 m squares and summed up the information most relevant to biologists for each square. The result is a set of 70 maps describing the three-dimensional architecture of the Danish landscape and vegetation.
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
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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.
Arial J. Shogren, Jay P. Zarnetske, Benjamin W. Abbott, Samuel Bratsman, Brian Brown, Michael P. Carey, Randy Fulweber, Heather E. Greaves, Emma Haines, Frances Iannucci, Joshua C. Koch, Alexander Medvedeff, Jonathan A. O'Donnell, Leika Patch, Brett A. Poulin, Tanner J. Williamson, and William B. Bowden
Earth Syst. Sci. Data, 14, 95–116, https://doi.org/10.5194/essd-14-95-2022, https://doi.org/10.5194/essd-14-95-2022, 2022
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Rapidly sampling multiple points in an entire river network provides a high-resolution snapshot in time that can reveal where nutrients and carbon are being taken up and released. Here, we describe two such datasets of river network chemistry in six Arctic watersheds in northern Alaska. We describe how these repeated snapshots can be used as an indicator of ecosystem response to climate change and to improve predictions of future release of carbon, nutrient, and other solutes.
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.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Yingping Wang, Julian Helfenstein, Yuanyuan Huang, Kailiang Yu, Zhiqiang Wang, Yongchuan Yang, and Enqing Hou
Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, https://doi.org/10.5194/essd-13-5831-2021, 2021
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Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg−1. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
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Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Yi-Wei Zhang, Yanpei Guo, Zhiyao Tang, Yuhao Feng, Xinrong Zhu, Wenting Xu, Yongfei Bai, Guoyi Zhou, Zongqiang Xie, and Jingyun Fang
Earth Syst. Sci. Data, 13, 5337–5351, https://doi.org/10.5194/essd-13-5337-2021, https://doi.org/10.5194/essd-13-5337-2021, 2021
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Nitrogen (N) and phosphorus (P) are limiting nutrients for ecosystem productivity. For the first time, we mapped N and P densities of living plants, litter, and soil in forest, shrubland, and grassland ecosystems across China using random forest models based on a dataset of 4868 field sites. Our results depicted the spatial distribution pattern, the total pool, and the allocation among ecosystem components of N and P, which could benefit a more precise prediction of the carbon cycle.
Cited articles
Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A.,
Jung, M., Reichstein, M., Canadell, J. G., Friedlingstein, P., and Jain, A.
K.: 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.
Ballantyne, A., Smith, W., Anderegg, W., Kauppi, P., Sarmiento, J., Tans,
P., Shevliakova, E., Pan, Y., Poulter, B., Anav, A., Friedlingstein, P.,
Houghton, R., and Running, S.: Accelerating net terrestrial carbon uptake
during the warming hiatus due to reduced respiration, Nat. Clim. Change,
7, 148–152, https://doi.org/10.1038/nclimate3204, 2017.
Bodesheim, P., Jung, M., Gans, F., Mahecha, M. D., and Reichstein, M.: Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product, Earth Syst. Sci. Data, 10, 1327–1365, https://doi.org/10.5194/essd-10-1327-2018, 2018.
Bond-Lamberty, B.: New Techniques and Data for Understanding the Global Soil
Respiration Flux, Earth's Future, 6, 1176–1180, https://doi.org/10.1029/2018ef000866, 2018.
Bond-Lamberty, B. and Thomson, A.: Temperature-associated increases in the
global soil respiration record, Nature, 464, 579–582, https://doi.org/10.1038/nature08930, 2010.
Bond-Lamberty, B. P. and Thomson, A. M.: A Global Database of Soil
Respiration Data, Version 4.0. ORNL Distributed Active Archive Center,
https://doi.org/10.3334/ORNLDAAC/1578, 2018.
Bond-Lamberty, B., Wang, C., and Gower, S. T.: A global relationship between
the heterotrophic and autotrophic components of soil respiration?, Global
Chang. Biol., 10, 1756–1766, https://doi.org/10.1111/j.1365-2486.2004.00816.x, 2004.
Bond-Lamberty, B., Bailey, V. L., Chen, M., Gough, C. M., and Vargas, R.:
Globally rising soil heterotrophic respiration over recent decades, Nature,
560, 80-83, https://doi.org/10.1038/s41586-018-0358-x, 2018.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Chen, G. S., Yang, Y. S., and Robinson, D.: Allometric constraints on, and
trade-offs in, belowground carbon allocation and their control of soil
respiration across global forest ecosystems, Global Chang. Biol., 20,
1674–1684, https://doi.org/10.1111/gcb.12494, 2014.
Feng, H. H. and Liu, Y. B.: Combined effects of precipitation and air
temperature on soil moisture in different land covers in a humid basin, J.
Hydrol., 531, 1129–1140, https://doi.org/10.1016/j.jhydrol.2015.11.016, 2015.
Forkel, M., Carvalhais, N., Rödenbeck, C., Keeling, R., Heimann, M.,
Thonicke, K., Zaehle, S., and Reichstein, M.: Enhanced seasonal CO2
exchange caused by amplified plant productivity in northern ecosystems,
Science, 351, 696–699, https://doi.org/10.1126/science.aac4971, 2016.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm
refinements and characterization of new datasets, Remote Sens. Environ.,
114, 168–182, https://doi.org/10.1016/j.rse.2009.08.016, 2010.
Gaucherel, C., Alleaume, S., and Hely, C.: The comparison map profile
method: a strategy for multiscale comparison of quantitative and qualitative
images, IEEE Trans. Geosci. Remote Sens., 46, 2708–2719, https://doi.org/10.1109/TGRS.2008.919379, 2008.
Global Soil Data, T.: Global Gridded Surfaces of Selected Soil
Characteristics (IGBP-DIS), ORNL Distributed Active Archive Center,
https://doi.org/10.3334/ornldaac/569, 2000.
Gomez-Casanovas, N., Matamala, R., Cook, D. R., and Gonzalez-Meler, M. A.:
Net ecosystem exchange modifies the relationship between the autotrophic and
heterotrophic components of soil respiration with abiotic factors in prairie
grasslands, Global Chang. Biol., 18, 2532–2545, https://doi.org/10.1111/j.1365-2486.2012.02721.x, 2012.
Gray, S. B., Dermody, O., Klein, S. P., Locke, A. M., McGrath, J. M., Paul,
R. E., Rosenthal, D. M., Ruiz-Vera, U. M., Siebers, M. H., Strellner, R.,
Ainsworth, E. A., Bernacchi, C. J., Long, S. P., Ort, D. R., and Leakey, A.
D. B.: Intensifying drought eliminates the expected benefits of elevated
carbon dioxide for soybean, Nat. Plants, 2, 16132, https://doi.org/10.1038/nplants.2016.132, 2016.
Högberg, P., Nordgren, A., Buchmann, N., Taylor, A. F. S., Ekblad, A.,
Hogberg, M. N., Nyberg, G., Ottosson-Lofvenius, M., and Read, D. J.:
Large-scale forest girdling shows that current photosynthesis drives soil
respiration, Nature, 411, 789–792, https://doi.org/10.1038/35081058, 2001.
Högberg, P., Nordgren, A., and Ågren, G.: Carbon allocation between
tree root growth and root respiration in boreal pine forest, Oecologia, 132,
579–581, https://doi.org/10.1007/s00442-002-0983-8, 2002.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A.,
Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R.,
Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townshend, J. R.
G.: High-Resolution Global Maps of 21st-Century Forest Cover Change,
Science, 342, 850–853, https://doi.org/10.1126/science.1244693, 2013.
Hanson, P. J., Edwards, N. T., Garten, C. T., and Andrews, J. A.: Separating
root and soil microbial contributions to soil respiration: A review of
methods and observations, Biogeochemistry, 48, 115–146, https://doi.org/10.1023/a:1006244819642, 2000.
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution
grids of monthly climatic observations–the CRU TS3. 10 Dataset, Int. J.
Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711,
2014.
Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V.,
Brönnimann, S., and Charabi, Y. A. R.: Observations: Atmosphere and
Surface, in: Climate Change 2013 – The Physical Science Basis: Working
Group I Contribution to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, Intergovernmental Panel on Climate, edited by: Stocker, T., Qin, D., Plattner, G., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.,
Cambridge University Press, Cambridge, 2014.
Hashimoto, S., Carvalhais, N., Ito, A., Migliavacca, M., Nishina, K., and Reichstein, M.: Global spatiotemporal distribution of soil respiration modeled using a global database, Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, 2015.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M.,
Kilibarda, M., Blagotic, A., Shangguan, W., Wright, M. N., Geng, X.,
Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A.,
Batjes, N. H., Leenaars, J. G., Ribeiro, E., Wheeler, I., Mantel, S., and
Kempen, B.: SoilGrids250m: Global gridded soil information based on machine
learning, PLoS One, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Huang, J., Guan, X., and Ji, F.: Enhanced cold-season warming in semi-arid regions, Atmos. Chem. Phys., 12, 5391–5398, https://doi.org/10.5194/acp-12-5391-2012, 2012.
Hursh, A., Ballantyne, A., Cooper, L., Maneta, M., Kimball, J., and Watts,
J.: The sensitivity of soil respiration to soil temperature, moisture, and
carbon supply at the global scale, Global Chang. Biol., 23, 2090–2103,
https://doi.org/10.1111/gcb.13489, 2017.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, 2013.
Jian, J., Steele, M. K., Day, S. D., and Thomas, R. Q.: Future global soil
respiration rates will swell despite regional decreases in temperature
sensitivity caused by rising temperature, Earth's Fut., 6, 1539–1554,
https://doi.org/10.1029/2018EF000937, 2018a.
Jian, J., Steele, M. K., Thomas, R. Q., Day, S. D., and Hodges, S. C.:
Constraining estimates of global soil respiration by quantifying sources of
variability, Global Chang. Biol., 24, 4143–4159, https://doi.org/10.1111/gcb.14301, 2018b.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlstrom, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P.,
Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B., Raduly,
B., Rodenbeck, C., Tramontana, G., Viovy, N., Wang, Y. P., Weber, U.,
Zaehle, S., and Zeng, N.: Compensatory water effects link yearly global land
CO2 sink changes to temperature, Nature, 541, 516–520, https://doi.org/10.1038/nature20780, 2017.
Kabacoff, R. I.: R in action: data analysis and graphics with R, Manning
Publications Co., Shelter Island, New York, 2015.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:Tnyrp>2.0.Co;2, 1996.
Klein Goldewijk, K., Beusen, A., Van Drecht, G., and De Vos, M.: The HYDE
3.1 spatially explicit database of human-induced global land-use change over
the past 12,000 years, Global Ecol. Biogeogr., 20, 73–86, https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2011.
Kuzyakov, Y. and Gavrichkova, O.: Time lag between photosynthesis and carbon
dioxide efflux from soil: a review of mechanisms and controls, Global Chang.
Biol., 16, 3386–3406, https://doi.org/10.1111/j.1365-2486.2010.02179.x, 2010.
Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R., Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G., Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell, D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M., Dahl-Jensen, D., Das, S., Fritzsche, D., and Nolan, M.: Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes, Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, 2013.
Liu, Y., Liu, S., Wan, S., Wang, J., Luan, J., and Wang, H.: Differential
responses of soil respiration to soil warming and experimental throughfall
reduction in a transitional oak forest in central China, Agr. Forest
Meteorol., 226, 186–198, https://doi.org/10.1016/j.agrformet.2016.06.003, 2016.
Long, S. J. and Freese, J. (Eds.): Regression models for categorical dependent variables using Stata, College Station, TX: Stata Press, Texas, 2006.
Moyano, F. E., Vasilyeva, N., Bouckaert, L., Cook, F., Craine, J., Curiel Yuste, J., Don, A., Epron, D., Formanek, P., Franzluebbers, A., Ilstedt, U., Kätterer, T., Orchard, V., Reichstein, M., Rey, A., Ruamps, L., Subke, J.-A., Thomsen, I. K., and Chenu, C.: The moisture response of soil heterotrophic respiration: interaction with soil properties, Biogeosciences, 9, 1173–1182, https://doi.org/10.5194/bg-9-1173-2012, 2012.
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007.
Piñeiro, J., Ochoa-Hueso, R., Delgado-Baquerizo, M., Dobrick, S., Reich,
P. B., Pendall, E., and Power, S. A.: Effects of elevated CO2 on fine
root biomass are reduced by aridity but enhanced by soil nitrogen: A global
assessment, Sci. Rep., 7, 15355, https://doi.org/10.1038/s41598-017-15728-4, 2017.
Pumpanen, J., Kolari, P., Ilvesniemi, H., Minkkinen, K., Vesala, T.,
Niinist, S., Lohila, A., Larmola, T., Morero, M., Pihlatie, M., Janssens,
I., Yuste, J. C., Grünzweig, J. M., Reth, S., Subke, J.-A., Savage, K.,
Kutsch, W., Østreng, G., Ziegler, W., Anthoni, P., Lindroth, A., and
Hari, P.: Comparison of different chamber techniques for measuring soil
CO2 efflux, Agr. Forest Meteorol., 123, 159–176, https://doi.org/10.1016/j.agrformet.2003.12.001, 2004.
Raich, J. W. and Schlesinger, W. H.: The global carbon dioxide flux in soil
respiration and its relationship to vegetation and climate, Tellus B, 44,
81–99, https://doi.org/10.1034/j.1600-0889.1992.t01-1-00001.x, 1992.
Raich, J. W., Potter, C. S., and Bhagawati, D.: Interannual variability in
global soil respiration, 1980–94, Global Chang. Biol., 8, 800–812,
https://doi.org/10.1046/j.1365-2486.2002.00511.x, 2002.
Reichstein, M., Papale, D., Valentini, R., Aubinet, M., Bernhofer, C.,
Knohl, A., Laurila, T., Lindroth, A., Moors, E., Pilegaard, K., and Seufert,
G.: Determinants of terrestrial ecosystem carbon balance inferred from
European eddy covariance flux sites, Geophys. Res. Lett., 34, L01402,
https://doi.org/10.1029/2006GL027880, 2007.
Schaefer, D. A., Feng, W., and Zou, X.: Plant carbon inputs and
environmental factors strongly affect soil respiration in a subtropical
forest of southwestern China, Soil Biol. Biochem., 41, 1000–1007, https://doi.org/10.1016/j.soilbio.2008.11.015, 2009.
Subke, J.-A., Voke, N. R., Leronni, V., Garnett, M. H., and Ineson, P.:
Dynamics and pathways of autotrophic and heterotrophic soil CO2 efflux
revealed by forest girdling, J. Ecol., 99, 186–193, https://doi.org/10.1111/j.1365-2745.2010.01740.x, 2011.
Tang, X., Fan, S., Qi, L., Guan, F., Du, M., and Zhang, H.: Soil respiration
and net ecosystem production in relation to intensive management in Moso
bamboo forests, Catena, 137, 219–228, https://doi.org/10.1016/j.catena.2015.09.008, 2016.
Tang, X., Fan, S., Zhang, W., Gao, S., Chen, G., and Shi, L.: A gridded
dataset of belowground autotrophic respiration from 1980 to 2012 in global
terrestrial ecosystems upscaling of field observations, in: Figshare,
https://doi.org/10.6084/m9.figshare.7636193, 2019.
Tian, X., Yan, M., van der Tol, C., Li, Z., Su, Z., Chen, E., Li, X., Li,
L., Wang, X., Pan, X., Gao, L., and Han, Z.: Modeling forest above-ground
biomass dynamics using multi-source data and incorporated models: A case
study over the qilian mountains, Agr. Forest Meteorol., 246, 1–14,
https://doi.org/10.1016/j.agrformet.2017.05.026, 2017.
van den Dool, H., Huang, J., and Fan, Y.: Performance and analysis of the
constructed analogue method applied to U.S. soil moisture over 1981–2001,
J. Geophys. Res.-Atmos., 108, 8617, https://doi.org/10.1029/2002jd003114, 2003.
van der Schrier, G., Barichivich, J., Briffa, K. R., and Jones, P. D.: A
scPDSI-based global data set of dry and wet spells for 1901–2009, J.
Geophys. Res.-Atmos., 118, 4025–4048, https://doi.org/10.1002/jgrd.50355, 2013.
Wang, C. and Yang, J.: Rhizospheric and heterotrophic components of soil
respiration in six Chinese temperate forests, Global Chang. Biol., 13,
123–131, https://doi.org/10.1111/j.1365-2486.2006.01291.x,
2007.
Wang, X., Liu, L., Piao, S., Janssens, I. A., Tang, J., Liu, W., Chi, Y.,
Wang, J., and Xu, S.: Soil respiration under climate warming: differential
response of heterotrophic and autotrophic respiration, Global Chang. Biol.,
20, 3229–3237, https://doi.org/10.1111/gcb.12620, 2014.
Yan, M. F., Zhou, G. S., and Zhang, X. S.: Effects of irrigation on the soil
CO2 efflux from different poplar clone plantations in arid northwest
China, Plant Soil, 375, 89–97, https://doi.org/10.1007/s11104-013-1944-1, 2014.
Yang, J., Gong, P., Fu, R., Zhang, M., Chen, J., Liang, S., Xu, B., Shi, J., and Dickinson, R.: The role of satellite remote sensing in climate change studies, Nat. Clim. Chang., 3, 875–883, https://doi.org/10.1038/nclimate1908, 2013.
Yao, Y., Wang, X., Li, Y., Wang, T., Shen, M., Du, M., He, H., Li, Y., Luo,
W., Ma, M., Ma, Y., Tang, Y., Wang, H., Zhang, X., Zhang, Y., Zhao, L.,
Zhou, G., and Piao, S.: Spatiotemporal pattern of gross primary productivity
and its covariation with climate in China over the last thirty years, Global
Chang. Biol., 24, 184–196, https://doi.org/10.1111/gcb.13830,
2018.
Zhang, Y., Xiao, X., Wu, X., Zhou, S., Zhang, G., Qin, Y., and Dong, J.: A
global moderate resolution dataset of gross primary production of vegetation
for 2000–2016, Sci. Data, 4, 170165, https://doi.org/10.1038/sdata.2017.165, 2017.
Zhao, Z., Peng, C., Yang, Q., Meng, F.-R., Song, X., Chen, S., Epule, T. E.,
Li, P., and Zhu, Q.: Model prediction of biome-specific global soil
respiration from 1960 to 2012, Earth's Future, 5, 715–729, https://doi.org/10.1002/2016EF000480, 2017.
Zhou, L., Zhou, X., Shao, J., Nie, Y., He, Y., Jiang, L., Wu, Z., and
Hosseini Bai, S.: Interactive effects of global change factors on soil
respiration and its components: a meta-analysis, Global Chang. Biol., 22,
3157–3169, https://doi.org/10.1111/gcb.13253, 2016.
Short summary
We estimated the missing global carbon flux component – global belowground autotrophic respiration (RA), using global published observations with the linkage of global variables with random forest. Globally, annual mean RA was 43.8 ± 0.4 Pg C yr-1, with a temporally increasing trend of 0.025 ± 0.006 Pg C yr-2 in 1980–2012. Precipitation dominated 56 % of global areas of the spatial pattern of RA. The RA database also has great potential to serve as a benchmark for future data–model comparisons.
We estimated the missing global carbon flux component – global belowground autotrophic...
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