Articles | Volume 10, issue 2
Earth Syst. Sci. Data, 10, 969–984, 2018
https://doi.org/10.5194/essd-10-969-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 10, 969–984, 2018
https://doi.org/10.5194/essd-10-969-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
04 Jun 2018
04 Jun 2018
Historical nitrogen fertilizer use in agricultural ecosystems of the contiguous United States during 1850–2015: application rate, timing, and fertilizer types
Peiyu Cao et al.
Related authors
Peiyu Cao, Chaoqun Lu, Jien Zhang, and Avani Khadilkar
Atmos. Chem. Phys., 20, 11907–11922, https://doi.org/10.5194/acp-20-11907-2020, https://doi.org/10.5194/acp-20-11907-2020, 2020
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In this study, we estimate monthly ammonia emission from synthetic nitrogen fertilizer use across the contiguous US from 1900 to 2015. The results indicate the important role that cropland expansion and nitrogen fertilizer enrichment played in enhancing NH3 emissions. It shows such long-term human activities have dramatically changed the spatiotemporal and seasonal patterns of NH3 emission, impacting air pollution and public health in the US.
Zhen Yu, Xiaobin Jin, Lijuan Miao, and Xuhong Yang
Earth Syst. Sci. Data, 13, 3203–3218, https://doi.org/10.5194/essd-13-3203-2021, https://doi.org/10.5194/essd-13-3203-2021, 2021
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We reconstructed the annual, 5 km × 5 km resolution cropland percentage map that covers mainland China and spans from 1900 to 2016. Our results are advantageous, as they reconcile accuracy, temporal coverage, and spatial resolutions. We further examined the cropland shift pattern and its driving factors in China using the reconstructed maps. This work will greatly contribute to the field of global ecology and land surface modeling.
Peiyu Cao, Chaoqun Lu, Jien Zhang, and Avani Khadilkar
Atmos. Chem. Phys., 20, 11907–11922, https://doi.org/10.5194/acp-20-11907-2020, https://doi.org/10.5194/acp-20-11907-2020, 2020
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In this study, we estimate monthly ammonia emission from synthetic nitrogen fertilizer use across the contiguous US from 1900 to 2015. The results indicate the important role that cropland expansion and nitrogen fertilizer enrichment played in enhancing NH3 emissions. It shows such long-term human activities have dramatically changed the spatiotemporal and seasonal patterns of NH3 emission, impacting air pollution and public health in the US.
Xiaolu Tang, Shaohui Fan, Manyi Du, Wenjie Zhang, Sicong Gao, Shibin Liu, Guo Chen, Zhen Yu, and Wunian Yang
Earth Syst. Sci. Data, 12, 1037–1051, https://doi.org/10.5194/essd-12-1037-2020, https://doi.org/10.5194/essd-12-1037-2020, 2020
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Global soil heterotrophic respiration (RH) was modelled using Random Forest by linking published observations and globally gridded environmental variables. Globally, RH increased from 55.8 to 58.3 Pg C a−1 with an increasing trend of 0.036 ± 0.007 Pg C a−2 and an annual mean RH of 57.2 ± 0.6 Pg C a−1 over 1980–2016. The developed RH dataset has great potential to serve as a benchmark to constrain global vegetation models.
Xuecao Li, Yuyu Zhou, Lin Meng, Ghassem R. Asrar, Chaoqun Lu, and Qiusheng Wu
Earth Syst. Sci. Data, 11, 881–894, https://doi.org/10.5194/essd-11-881-2019, https://doi.org/10.5194/essd-11-881-2019, 2019
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We generated a long-term (1985–2015) and medium-resolution (30 m) product of phenology indicators in urban domains in the conterminous US using Landsat satellite observations. The derived phenology indicators agree well with in situ observations and provide more spatial details in complex urban areas compared to the existing coarse resolution phenology products (e.g., MODIS). The published data are of great use for urban phenology studies (e.g., pollen-induced respiratory allergies).
Xiaolu Tang, Nuno Carvalhais, Catarina Moura, Bernhard Ahrens, Sujan Koirala, Shaohui Fan, Fengying Guan, Wenjie Zhang, Sicong Gao, Vincenzo Magliulo, Pauline Buysse, Shibin Liu, Guo Chen, Wunian Yang, Zhen Yu, Jingjing Liang, Leilei Shi, Shenyan Pu, and Markus Reichstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-37, https://doi.org/10.5194/bg-2019-37, 2019
Preprint withdrawn
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Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass. This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls. Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.
Bowen Zhang, Hanqin Tian, Chaoqun Lu, Shree R. S. Dangal, Jia Yang, and Shufen Pan
Earth Syst. Sci. Data, 9, 667–678, https://doi.org/10.5194/essd-9-667-2017, https://doi.org/10.5194/essd-9-667-2017, 2017
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This work addressed how manure nitrogen (N) production and application to cropland have changed over time and space. The 5 arcmin gridded global dataset of manure nitrogen production generated from this study could be used as an input for global or regional land surface and ecosystem models to evaluate the impacts of manure nitrogen on key biogeochemical processes and water quality.
Rongting Xu, Hanqin Tian, Chaoqun Lu, Shufen Pan, Jian Chen, Jia Yang, and Bowen Zhang
Clim. Past, 13, 977–990, https://doi.org/10.5194/cp-13-977-2017, https://doi.org/10.5194/cp-13-977-2017, 2017
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As N2O emissions were present in preindustrial times, only the difference between current and preindustrial emissions represents net human-induced climate change. Large uncertainty exists in previous estimates of preindustrial N2O emissions from the land biosphere. Our estimate using process-based model was the first study that provided the preindustrial N2O emission at the biome, sector or country, and global level, which could be a useful reference for future climate mitigation.
Chaoqun Lu and Hanqin Tian
Earth Syst. Sci. Data, 9, 181–192, https://doi.org/10.5194/essd-9-181-2017, https://doi.org/10.5194/essd-9-181-2017, 2017
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This work has addressed how agricultural nitrogen and phosphorous fertilizer use has changed over time and space. The final product covers global agricultural land, spanning from 1961 to 2013 at a spatial resolution of 0.5° × 0.5° latitude by longitude. It can serve as an important input driver for regional and global assessment and Earth system modeling of agricultural productivity, crop yield, greenhouse gas balance, global nutrient budget, and ecosystem feedback to climate.
Related subject area
Biosphere – Biogeosciences
Global transpiration data from sap flow measurements: the SAPFLUXNET database
MOSAIC (Modern Ocean Sediment Archive and Inventory of Carbon): a (radio)carbon-centric database for seafloor surficial sediments
Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M)
MOSEV: a global burn severity database from MODIS (2000–2020)
SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0
Gap-free global annual soil moisture: 15 km grids for 1991–2018
Carbon emissions and removals from forests: new estimates, 1990–2020
Standardized flux seasonality metrics: a companion dataset for FLUXNET annual product
LUCAS Copernicus 2018: Earth-observation-relevant in situ data on land cover and use throughout the European Union
A distributed time-lapse camera network to track vegetation phenology with high temporal detail and at varying scales
The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience
Seabed video and still images from the northern Weddell Sea and the western flanks of the Powell Basin
Production and application of manure nitrogen and phosphorus in the United States since 1860
Synchronized high-resolution bed-level change and biophysical data from 10 marsh–mudflat sites in northwestern Europe
Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020)
A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States
FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
A satellite-derived database for stand-replacing windthrow events in boreal forests of European Russia in 1986–2017
Drainage of organic soils and GHG emissions: validation with country data
Element and radionuclide concentrations in soils and wildlife from forests in north-eastern England with a focus on species representative of the ICRP's Reference Animals and Plants
Apparent ecosystem carbon turnover time: uncertainties and robust features
A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany
The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations
Decomposability of soil organic matter over time: the Soil Incubation Database (SIDb, version 1.0) and guidance for incubation procedures
The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
A spatially downscaled sun-induced fluorescence global product for enhanced monitoring of vegetation productivity
Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems
Observations of late-winter marine microbial activity in an ice-covered fjord, west Greenland
Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale
A spatially explicit database of wind disturbances in European forests over the period 2000–2018
Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019)
The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA)
A taxonomically harmonized and temporally standardized fossil pollen dataset from Siberia covering the last 40 kyr
A review of biomass equations for China's tree species
Global variability in belowground autotrophic respiration in terrestrial ecosystems
Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
A leaf area index data set acquired in Sahelian rangelands of Gourma in Mali over the 2005–2017 period
The Global Fire Atlas of individual fire size, duration, speed and direction
Increased nitrogen enrichment and shifted patterns in the world's grassland: 1860–2016
Global Carbon Budget 2018
Mapping the vegetation of the Lake Tana basin, Ethiopia, using Google Earth images
Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies
Radiocarbon measurements of ecosystem respiration and soil pore-space CO2 in Utqiaġvik (Barrow), Alaska
A global compilation of coccolithophore calcification rates
A weekly, continually updated dataset of the probability of large wildfires across western US forests and woodlands
Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations
Global radiation, photosynthetically active radiation, and the diffuse component dataset of China, 1981–2010
Seasonal evolution of soil and plant parameters on the agricultural Gebesee test site: a database for the set-up and validation of EO-LDAS and satellite-aided retrieval models
Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015)
Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Tessa Sophia van der Voort, Thomas Michael Blattmann, Muhammed Usman, Daniel Montluçon, Thomas Loeffler, Maria Luisa Tavagna, Nicolas Gruber, and Timothy Ian Eglinton
Earth Syst. Sci. Data, 13, 2135–2146, https://doi.org/10.5194/essd-13-2135-2021, https://doi.org/10.5194/essd-13-2135-2021, 2021
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Ocean sediments form the largest and longest-term storage of organic carbon. Despite their global importance, information on these sediments is often scattered, incomplete or inaccessible. Here we present MOSAIC (Modern Ocean Sediment Archive and Inventory of Carbon, mosaic.ethz.ch), a (radio)carbon-centric database that addresses this information gap. This database provides a platform for assessing the transport, deposition and storage of carbon in ocean surface sediments.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Esteban Alonso-González and Víctor Fernández-García
Earth Syst. Sci. Data, 13, 1925–1938, https://doi.org/10.5194/essd-13-1925-2021, https://doi.org/10.5194/essd-13-1925-2021, 2021
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We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution from November 2000 onwards. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
William R. Wieder, Derek Pierson, Stevan Earl, Kate Lajtha, Sara G. Baer, Ford Ballantyne, Asmeret Asefaw Berhe, Sharon A. Billings, Laurel M. Brigham, Stephany S. Chacon, Jennifer Fraterrigo, Serita D. Frey, Katerina Georgiou, Marie-Anne de Graaff, A. Stuart Grandy, Melannie D. Hartman, Sarah E. Hobbie, Chris Johnson, Jason Kaye, Emily Kyker-Snowman, Marcy E. Litvak, Michelle C. Mack, Avni Malhotra, Jessica A. M. Moore, Knute Nadelhoffer, Craig Rasmussen, Whendee L. Silver, Benjamin N. Sulman, Xanthe Walker, and Samantha Weintraub
Earth Syst. Sci. Data, 13, 1843–1854, https://doi.org/10.5194/essd-13-1843-2021, https://doi.org/10.5194/essd-13-1843-2021, 2021
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Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Here we present the SOils DAta Harmonization database (SoDaH), a flexible database designed to harmonize diverse SOM datasets from multiple research networks.
Mario Guevara, Michela Taufer, and Rodrigo Vargas
Earth Syst. Sci. Data, 13, 1711–1735, https://doi.org/10.5194/essd-13-1711-2021, https://doi.org/10.5194/essd-13-1711-2021, 2021
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Soil moisture is key for understanding soil–plant–atmosphere interactions. We provide a machine learning approach to increase the spatial resolution of satellite-derived soil moisture information. The outcome is a dataset of gap-free global mean annual soil moisture predictions and associated uncertainty for 28 years (1991–2018) across 15 km grids. This dataset has higher agreement with in situ soil moisture and precipitation measurements. Results show a decline of global annual soil moisture.
Francesco N. Tubiello, Giulia Conchedda, Nathan Wanner, Sandro Federici, Simone Rossi, and Giacomo Grassi
Earth Syst. Sci. Data, 13, 1681–1691, https://doi.org/10.5194/essd-13-1681-2021, https://doi.org/10.5194/essd-13-1681-2021, 2021
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This paper presents the first estimates of forest carbon fluxes (1990–2020) based on the new Global Forest Resources Assessment (FRA) 2020. We document for the first time in the literature forest carbon fluxes for the last decade 2011–2020. Results show that carbon losses from net forest conversion (3.1 billion tonnes of CO2) were counterbalanced by carbon gains on forest land (−3.3 billion tonnes of CO2), resulting in the world's forests acting overall as a small carbon sink in the past decade.
Linqing Yang and Asko Noormets
Earth Syst. Sci. Data, 13, 1461–1475, https://doi.org/10.5194/essd-13-1461-2021, https://doi.org/10.5194/essd-13-1461-2021, 2021
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We present a flux seasonality metrics database (FSMD) depicting a set of standardized metrics of ecosystem biogeochemical fluxes of CO2, water, and energy, including transition dates, phase lengths, and rates of change with uncertainty estimates. FSMD allows assessment of spatial and temporal patterns in developmental dynamics, validation of novel aspects of phenology product, and process models. It is calculated from FLUXNET2015 data product and will be updated with new FLUXNET data releases.
Raphaël d'Andrimont, Astrid Verhegghen, Michele Meroni, Guido Lemoine, Peter Strobl, Beatrice Eiselt, Momchil Yordanov, Laura Martinez-Sanchez, and Marijn van der Velde
Earth Syst. Sci. Data, 13, 1119–1133, https://doi.org/10.5194/essd-13-1119-2021, https://doi.org/10.5194/essd-13-1119-2021, 2021
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The Land Use/Cover Area frame Survey (LUCAS) is a regular in situ land cover and land use ground survey exercise that extends over the whole of the European Union. A new LUCAS module specifically tailored to Earth observation was introduced in 2018: the LUCAS Copernicus module. This paper summarizes the LUCAS Copernicus survey and provides the unique resulting data: 58 426 polygons with level-3 land cover (66 specific classes including crop type) and land use (38 classes).
Frans-Jan W. Parmentier, Lennart Nilsen, Hans Tømmervik, and Elisabeth J. Cooper
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-56, https://doi.org/10.5194/essd-2021-56, 2021
Revised manuscript accepted for ESSD
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Satellites provide a global overview of Earth's ecosystems, but they have coarse resolutions and low revisit times. Small scale vegetation patterns and sudden shifts in plant growth can therefore be missed. In this paper, we show how to fill these gaps with vegetation indices obtained with ordinary time-lapse cameras – deployed across a valley on Svalbard. We show how to adjust for unwanted camera movement, and that vegetation indices from ordinary cameras compare well to those from satellites.
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
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The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
Autun Purser, Simon Dreutter, Huw Griffiths, Laura Hehemann, Kerstin Jerosch, Axel Nordhausen, Dieter Piepenburg, Claudio Richter, Henning Schröder, and Boris Dorschel
Earth Syst. Sci. Data, 13, 609–615, https://doi.org/10.5194/essd-13-609-2021, https://doi.org/10.5194/essd-13-609-2021, 2021
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This dataset comprises 26-megapixel seafloor images collected from below ice and steeply sloped regions of the Southern Ocean (the western Weddell Sea; the Powell Basin; and the rapidly shallowing, iceberg-scoured Nachtigaller Shoal). These data were collected with the Ocean Floor Observation and Bathymetry System (OFOBS), an advanced towed camera platform incorporating various sonar devices to aid in hazard avoidance and seafloor mapping, for use in challenging, high-relief seafloor areas.
Zihao Bian, Hanqin Tian, Qichun Yang, Rongting Xu, Shufen Pan, and Bowen Zhang
Earth Syst. Sci. Data, 13, 515–527, https://doi.org/10.5194/essd-13-515-2021, https://doi.org/10.5194/essd-13-515-2021, 2021
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The estimation of manure nutrient production and application is critical for the efficient use of manure nutrients. This study developed four manure nitrogen and phosphorus datasets with high spatial resolution and a long time period (1860–2017) in the US. The datasets can provide useful information for stakeholders and scientists who focus on agriculture, nutrient budget, and biogeochemical cycle.
Zhan Hu, Pim W. J. M. Willemsen, Bas W. Borsje, Chen Wang, Heng Wang, Daphne van der Wal, Zhenchang Zhu, Bas Oteman, Vincent Vuik, Ben Evans, Iris Möller, Jean-Philippe Belliard, Alexander Van Braeckel, Stijn Temmerman, and Tjeerd J. Bouma
Earth Syst. Sci. Data, 13, 405–416, https://doi.org/10.5194/essd-13-405-2021, https://doi.org/10.5194/essd-13-405-2021, 2021
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Erosion and accretion processes govern the ecogeomorphic evolution of intertidal (salt marsh and tidal flat) ecosystems and hence substantially affect their valuable ecosystem services. By applying a novel sensor, we obtained unique high-resolution daily bed-level change datasets from 10 marsh–mudflat sites in northwestern Europe. This dataset has revealed diverse spatial bed-level change patterns over daily to seasonal scales, which are valuable to theoretical and model development.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Chongya Jiang, Kaiyu Guan, Genghong Wu, Bin Peng, and Sheng Wang
Earth Syst. Sci. Data, 13, 281–298, https://doi.org/10.5194/essd-13-281-2021, https://doi.org/10.5194/essd-13-281-2021, 2021
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Photosynthesis, quantified by gross primary production (GPP), is a key Earth system process. To date, there is a lack of a high-spatiotemporal-resolution, real-time and observation-based GPP dataset. This work addresses this gap by developing a SatelLite Only Photosynthesis Estimation (SLOPE) model and generating a new GPP product, which is advanced in spatial and temporal resolutions, instantaneity, and quantitative uncertainty. The dataset will benefit a range of research and applications.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, M. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Thomas Friborg, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Joachim Jansen, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Ivan Mammarella, Giovanni Manca, Luca Belelli Marchesini, Jaclyn Hatala Matthes, Trofim Maximon, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-307, https://doi.org/10.5194/essd-2020-307, 2021
Revised manuscript accepted for ESSD
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Andrey N. Shikhov, Alexander V. Chernokulsky, Igor O. Azhigov, and Anastasia V. Semakina
Earth Syst. Sci. Data, 12, 3489–3513, https://doi.org/10.5194/essd-12-3489-2020, https://doi.org/10.5194/essd-12-3489-2020, 2020
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Severe winds are among the main causes of forest disturbances in Russia. However, compared to other European countries, windthrows in Russian forests remain substantially understudied. In this study, we compiled a new spatial database of stand-replacing (total) windthrows in the forest zone of European Russia for 1986–2017. Windthrows were delineated mainly with Landsat images. The total area of windthrows was estimated to be 2966 km2 (0.19 % of the total forest-covered area).
Giulia Conchedda and Francesco N. Tubiello
Earth Syst. Sci. Data, 12, 3113–3137, https://doi.org/10.5194/essd-12-3113-2020, https://doi.org/10.5194/essd-12-3113-2020, 2020
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This paper describes the FAO methodology used to globally assess areas of drained organic soils and peatlands due to agriculture over the period 1990–2019. We overlay geospatial information of soil type, land cover, agro-climatic zones, livestock distribution and IPCC coefficients, then aggregate it at national level for over 200 countries and territories. Results are compared to inventory data reported to UNFCCC, showing good agreement between the FAO estimates and country data.
Catherine L. Barnett, Nicholas A. Beresford, Michael D. Wood, Maria Izquierdo, Lee A. Walker, and Ross Fawkes
Earth Syst. Sci. Data, 12, 3021–3038, https://doi.org/10.5194/essd-12-3021-2020, https://doi.org/10.5194/essd-12-3021-2020, 2020
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This paper describes data from a study conducted in 2015–2016 to sample terrestrial wildlife, soil and water from two forests in north-eastern England. Sampling was targeted towards species representative of the International Commission on Radiological Protection’s (ICRP) terrestrial Reference Animals and Plants (RAPs): Wild Grass, Pine Tree, Earthworm, Bee, Rat, Deer and Frog. The dataset comprises stable-element and radionuclide activity concentrations.
Naixin Fan, Sujan Koirala, Markus Reichstein, Martin Thurner, Valerio Avitabile, Maurizio Santoro, Bernhard Ahrens, Ulrich Weber, and Nuno Carvalhais
Earth Syst. Sci. Data, 12, 2517–2536, https://doi.org/10.5194/essd-12-2517-2020, https://doi.org/10.5194/essd-12-2517-2020, 2020
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The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback. In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback.
Tim G. Reichenau, Wolfgang Korres, Marius Schmidt, Alexander Graf, Gerhard Welp, Nele Meyer, Anja Stadler, Cosimo Brogi, and Karl Schneider
Earth Syst. Sci. Data, 12, 2333–2364, https://doi.org/10.5194/essd-12-2333-2020, https://doi.org/10.5194/essd-12-2333-2020, 2020
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë Rozendaal, Valerio Avitabilie, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-148, https://doi.org/10.5194/essd-2020-148, 2020
Revised manuscript accepted for ESSD
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Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest aboveground biomass, i.e., carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests although for dense forests in the tropics values are somewhat underestimated. This dataset will have considerable impact on climate, carbon and socio-economic modelling schemes.
Christina Schädel, Jeffrey Beem-Miller, Mina Aziz Rad, Susan E. Crow, Caitlin E. Hicks Pries, Jessica Ernakovich, Alison M. Hoyt, Alain Plante, Shane Stoner, Claire C. Treat, and Carlos A. Sierra
Earth Syst. Sci. Data, 12, 1511–1524, https://doi.org/10.5194/essd-12-1511-2020, https://doi.org/10.5194/essd-12-1511-2020, 2020
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Carbon loss to the atmosphere via microbial decomposition is often assessed by laboratory soil incubation studies that measure greenhouse gases released from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available, open-access database of carbon dioxide and methane flux. We also provide guidance for database entry and the required variables.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Gregory Duveiller, Federico Filipponi, Sophia Walther, Philipp Köhler, Christian Frankenberg, Luis Guanter, and Alessandro Cescatti
Earth Syst. Sci. Data, 12, 1101–1116, https://doi.org/10.5194/essd-12-1101-2020, https://doi.org/10.5194/essd-12-1101-2020, 2020
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Sun-induced chlorophyll fluorescence is a valuable indicator of vegetation productivity, but our capacity to measure it from space using satellite remote techniques has been hampered by a lack of spatial detail. Based on prior knowledge of how ecosystems should respond to growing conditions in some modelling along with ancillary satellite observations, we provide here a new enhanced dataset with higher spatial resolution that better represents the spatial patterns of vegetation growth over land.
Xiaolu Tang, Shaohui Fan, Manyi Du, Wenjie Zhang, Sicong Gao, Shibin Liu, Guo Chen, Zhen Yu, and Wunian Yang
Earth Syst. Sci. Data, 12, 1037–1051, https://doi.org/10.5194/essd-12-1037-2020, https://doi.org/10.5194/essd-12-1037-2020, 2020
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Global soil heterotrophic respiration (RH) was modelled using Random Forest by linking published observations and globally gridded environmental variables. Globally, RH increased from 55.8 to 58.3 Pg C a−1 with an increasing trend of 0.036 ± 0.007 Pg C a−2 and an annual mean RH of 57.2 ± 0.6 Pg C a−1 over 1980–2016. The developed RH dataset has great potential to serve as a benchmark to constrain global vegetation models.
David Chandler and Shona Mackie
Earth Syst. Sci. Data, 12, 897–906, https://doi.org/10.5194/essd-12-897-2020, https://doi.org/10.5194/essd-12-897-2020, 2020
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The activity of microorganisms at the bottom of the marine food chain has rarely been measured under sea ice in winter. We present the first observations of Arctic winter microbial activity under sea ice in a west Greenland fjord. By measuring changes in the oxygen concentration of seawater under the ice, we found low but significant levels of activity, suggesting these microbial communities may constitute an important part of the winter marine ecosystem.
Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu
Earth Syst. Sci. Data, 12, 789–804, https://doi.org/10.5194/essd-12-789-2020, https://doi.org/10.5194/essd-12-789-2020, 2020
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We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.
Giovanni Forzieri, Matteo Pecchi, Marco Girardello, Achille Mauri, Marcus Klaus, Christo Nikolov, Marius Rüetschi, Barry Gardiner, Julián Tomaštík, David Small, Constantin Nistor, Donatas Jonikavicius, Jonathan Spinoni, Luc Feyen, Francesca Giannetti, Rinaldo Comino, Alessandro Wolynski, Francesco Pirotti, Fabio Maistrelli, Ionut Savulescu, Stéphanie Wurpillot-Lucas, Stefan Karlsson, Karolina Zieba-Kulawik, Paulina Strejczek-Jazwinska, Martin Mokroš, Stefan Franz, Lukas Krejci, Ionel Haidu, Mats Nilsson, Piotr Wezyk, Filippo Catani, Yi-Ying Chen, Sebastiaan Luyssaert, Gherardo Chirici, Alessandro Cescatti, and Pieter S. A. Beck
Earth Syst. Sci. Data, 12, 257–276, https://doi.org/10.5194/essd-12-257-2020, https://doi.org/10.5194/essd-12-257-2020, 2020
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Strong winds may uproot and break trees and represent a risk for forests. Despite the importance of this natural disturbance and possible intensification in view of climate change, spatial information about wind-related impacts is currently missing on a pan-European scale. We present a new database of wind disturbances in European forests comprised of more than 80 000 records over the period 2000–2018. Our database is a unique spatial source for the study of forest disturbances at large scales.
Niels H. Batjes, Eloi Ribeiro, and Ad van Oostrum
Earth Syst. Sci. Data, 12, 299–320, https://doi.org/10.5194/essd-12-299-2020, https://doi.org/10.5194/essd-12-299-2020, 2020
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This dataset provides quality-assessed and standardised soil data to support digital soil mapping and environmental applications at broadscale levels. The underpinning soil profiles were shared by a wide range of data providers. Special attention was paid to the standardisation of soil property definitions, analytical method descriptions and property values. We present measures for geographic accuracy and a first approximation for the uncertainty associated with the various analytical methods.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
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Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Xianyong Cao, Fang Tian, Andrei Andreev, Patricia M. Anderson, Anatoly V. Lozhkin, Elena Bezrukova, Jian Ni, Natalia Rudaya, Astrid Stobbe, Mareike Wieczorek, and Ulrike Herzschuh
Earth Syst. Sci. Data, 12, 119–135, https://doi.org/10.5194/essd-12-119-2020, https://doi.org/10.5194/essd-12-119-2020, 2020
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Pollen percentages in spectra cannot be utilized to indicate past plant abundance directly because of the different pollen productivities among plants. In this paper, we applied relative pollen productivity estimates (PPEs) to calibrate plant abundances during the last 40 kyr using pollen counts from 203 pollen spectra in northern Asia. Results indicate the vegetation are generally stable during the Holocene and that climate change is the primary factor.
Yunjian Luo, Xiaoke Wang, Zhiyun Ouyang, Fei Lu, Liguo Feng, and Jun Tao
Earth Syst. Sci. Data, 12, 21–40, https://doi.org/10.5194/essd-12-21-2020, https://doi.org/10.5194/essd-12-21-2020, 2020
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How to accurately estimate tree and forest biomass a concern worldwide. Biomass equations are the most commonly used method. China is one of the most important ecoregions of the world. Here, we develop a tree biomass equation dataset for China via literature retrieval. This dataset consists of 5924 equations for nearly 200 tree species, showing sound geographical, climatic and forest coverage across China. Furthermore, multiple potential avenues for future research are identified.
Xiaolu Tang, Shaohui Fan, Wenjie Zhang, Sicong Gao, Guo Chen, and Leilei Shi
Earth Syst. Sci. Data, 11, 1839–1852, https://doi.org/10.5194/essd-11-1839-2019, https://doi.org/10.5194/essd-11-1839-2019, 2019
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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.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
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Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Eric Mougin, Mamadou Oumar Diawara, Nogmana Soumaguel, Ali Amadou Maïga, Valérie Demarez, Pierre Hiernaux, Manuela Grippa, Véronique Chaffard, and Abdramane Ba
Earth Syst. Sci. Data, 11, 675–686, https://doi.org/10.5194/essd-11-675-2019, https://doi.org/10.5194/essd-11-675-2019, 2019
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The leaf area index of Sahelian rangelands was measured between 2005 and 2017 in northern Mali. These observations collected over more than a decade, in a remote and not very accessible region, provide a relevant and unique data set that can be used for a better understanding of the Sahelian vegetation response to the current rainfall changes. The collected data can also be used for satellite product evaluation and land surface model validation.
Niels Andela, Douglas C. Morton, Louis Giglio, Ronan Paugam, Yang Chen, Stijn Hantson, Guido R. van der Werf, and James T. Randerson
Earth Syst. Sci. Data, 11, 529–552, https://doi.org/10.5194/essd-11-529-2019, https://doi.org/10.5194/essd-11-529-2019, 2019
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Natural and human-ignited fires affect all major biomes, and satellite observations provide evidence for rapid changes in global fire activity. The Global Fire Atlas of individual fire size, duration, speed, and direction is the first global data product on individual fire behavior. Moving towards a global understanding of individual fire behavior is a critical next step in fire research, required to understand how global fire regimes are changing in response to land management and climate.
Rongting Xu, Hanqin Tian, Shufen Pan, Shree R. S. Dangal, Jian Chen, Jinfeng Chang, Yonglong Lu, Ute Maria Skiba, Francesco N. Tubiello, and Bowen Zhang
Earth Syst. Sci. Data, 11, 175–187, https://doi.org/10.5194/essd-11-175-2019, https://doi.org/10.5194/essd-11-175-2019, 2019
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We provide three gridded datasets of synthetic nitrogen (N) fertilizer and manure N inputs in global pastures and rangelands at a resolution of 0.5° × 0.5° for the period 1860–2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer use rate and manure N application rate). These three datasets could fill data gaps of N inputs in global and regional grasslands and serve as input drivers for earth system models.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Chuangye Song, Lisanework Nigatu, Yibrah Beneye, Abdurezak Abdulahi, Lin Zhang, and Dongxiu Wu
Earth Syst. Sci. Data, 10, 2033–2041, https://doi.org/10.5194/essd-10-2033-2018, https://doi.org/10.5194/essd-10-2033-2018, 2018
Emilio Chuvieco, Joshua Lizundia-Loiola, Maria Lucrecia Pettinari, Ruben Ramo, Marc Padilla, Kevin Tansey, Florent Mouillot, Pierre Laurent, Thomas Storm, Angelika Heil, and Stephen Plummer
Earth Syst. Sci. Data, 10, 2015–2031, https://doi.org/10.5194/essd-10-2015-2018, https://doi.org/10.5194/essd-10-2015-2018, 2018
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We present a new global burned area product, generated from MODIS information and thermal anomalies data, providing the highest spatial resolution (approx. 250 m) global product to date. The dataset comprises the 2001–2016 time series of the MODIS archive, and includes two types of BA products: monthly full-resolution continental tiles and biweekly global grid files at a degraded resolution of 0.25 °, supplemented with several auxiliary variables useful for different applications.
Lydia J. S. Vaughn and Margaret S. Torn
Earth Syst. Sci. Data, 10, 1943–1957, https://doi.org/10.5194/essd-10-1943-2018, https://doi.org/10.5194/essd-10-1943-2018, 2018
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This paper discusses radiocarbon in CO2 and soil organic carbon from Arctic Alaska. From soil chamber measurements, we observed strong seasonal and spatial patterns in 14C of ecosystem respiration, which declined throughout the summer and differed among permafrost features. Radiocarbon in pore-space CO2 indicated decomposition of carbon as old as 3000 years near the permafrost table. Together, these data reveal different rates of old carbon decomposition from distinct permafrost features.
Chris J. Daniels, Alex J. Poulton, William M. Balch, Emilio Marañón, Tim Adey, Bruce C. Bowler, Pedro Cermeño, Anastasia Charalampopoulou, David W. Crawford, Dave Drapeau, Yuanyuan Feng, Ana Fernández, Emilio Fernández, Glaucia M. Fragoso, Natalia González, Lisa M. Graziano, Rachel Heslop, Patrick M. Holligan, Jason Hopkins, María Huete-Ortega, David A. Hutchins, Phoebe J. Lam, Michael S. Lipsen, Daffne C. López-Sandoval, Socratis Loucaides, Adrian Marchetti, Kyle M. J. Mayers, Andrew P. Rees, Cristina Sobrino, Eithne Tynan, and Toby Tyrrell
Earth Syst. Sci. Data, 10, 1859–1876, https://doi.org/10.5194/essd-10-1859-2018, https://doi.org/10.5194/essd-10-1859-2018, 2018
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Calcifying marine algae (coccolithophores) are key to oceanic biogeochemical processes, such as calcium carbonate production and export. We compile a global database of calcium carbonate production from field samples (n = 2756), alongside primary production rates and coccolithophore abundance. Basic statistical analysis highlights global distribution, average surface and integrated rates, patterns with depth and the importance of considering cell-normalised rates as a simple physiological index.
Miranda E. Gray, Luke J. Zachmann, and Brett G. Dickson
Earth Syst. Sci. Data, 10, 1715–1727, https://doi.org/10.5194/essd-10-1715-2018, https://doi.org/10.5194/essd-10-1715-2018, 2018
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There is broad consensus that wildfire activity is likely to increase in western US forests and woodlands over the next century. Therefore, spatial predictions of the potential for large wildfires have immediate and growing relevance to near and long-term research, planning, and management objectives. The dataset described here is a weekly time series of images (250 m resolution) from 2005 to 2017 that depicts the probability of large fire across western US forests and woodlands.
Gregory Duveiller, Giovanni Forzieri, Eddy Robertson, Wei Li, Goran Georgievski, Peter Lawrence, Andy Wiltshire, Philippe Ciais, Julia Pongratz, Stephen Sitch, Almut Arneth, and Alessandro Cescatti
Earth Syst. Sci. Data, 10, 1265–1279, https://doi.org/10.5194/essd-10-1265-2018, https://doi.org/10.5194/essd-10-1265-2018, 2018
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Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate. While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.
Xiaoli Ren, Honglin He, Li Zhang, and Guirui Yu
Earth Syst. Sci. Data, 10, 1217–1226, https://doi.org/10.5194/essd-10-1217-2018, https://doi.org/10.5194/essd-10-1217-2018, 2018
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A spatial radiation dataset of China from 1981 to 2010, including global radiation, diffuse radiation, photosynthetically active radiation (PAR), and diffuse PAR, is generated and shared based on several estimation models and observations of the China Meteorology Administration and the Chinese Ecosystem Research Network. This is an integral and consistent radiation dataset for ecological modeling and the analysis of the effects of diffuse radiation on terrestrial ecosystem productivity.
Sina C. Truckenbrodt and Christiane C. Schmullius
Earth Syst. Sci. Data, 10, 525–548, https://doi.org/10.5194/essd-10-525-2018, https://doi.org/10.5194/essd-10-525-2018, 2018
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A comprehensive ground reference database for the set-up and validation of models for the satellite-aided retrieval of crop characteristics is presented. Data on the evolution of biophysical and biochemical plant parameters were collected for seven crop types on the Gebesee test site (central Germany) in 2013 and 2014. Field work was carried out on a weekly basis and close to satellite acquisitions. The data reflects spatial heterogeneity and interannual phenological variability.
Wei Li, Natasha MacBean, Philippe Ciais, Pierre Defourny, Céline Lamarche, Sophie Bontemps, Richard A. Houghton, and Shushi Peng
Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018, https://doi.org/10.5194/essd-10-219-2018, 2018
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We evaluated the land cover changes based on plant functional types (PFTs) derived from the newly released annual ESA land cover maps. We addressed the geographical distributions and temporal trends of the translated PFT maps and compared with other datasets commonly used by the land surface model community. Different choices of these datasets for the applications in land surface models are proposed depending on the research purposes.
Mikko Peltoniemi, Mika Aurela, Kristin Böttcher, Pasi Kolari, John Loehr, Jouni Karhu, Maiju Linkosalmi, Cemal Melih Tanis, Juha-Pekka Tuovinen, and Ali Nadir Arslan
Earth Syst. Sci. Data, 10, 173–184, https://doi.org/10.5194/essd-10-173-2018, https://doi.org/10.5194/essd-10-173-2018, 2018
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Monitoring ecosystems using low-cost time lapse cameras has gained wide interest among researchers worldwide. Quantitative information stored in image pixels can be analysed automatically to track time-dependent phenomena, e.g. seasonal course of leaves in the canopies or snow on ground. As such, cameras can provide valuable ground references to earth observation. Here we document the ecosystem camera network we established to Finland and publish time series of images recorded between 2014–2016.
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Short summary
A long-term N fertilizer use history is important for both field investigators and modeling community to examine the cumulative impacts of N fertilizer uses. We developed a spatially explicit time-series data set of nitrogen fertilizer use in agricultural land of the continental US during 1850–2015 at a resolution of 5 km × 5 km based on multiple data sources and historical cropland maps. It contains nitrogen fertilizer use rate, application timing, and ammonium and nitrate form fertilizer use.
A long-term N fertilizer use history is important for both field investigators and modeling...
