Articles | Volume 15, issue 1
https://doi.org/10.5194/essd-15-431-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-431-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Harmonized Soil Database of Ecuador (HESD): data from 2009 to 2015
Daphne Armas
CORRESPONDING AUTHOR
Departamento de Agronomía, Edif. CITEIIB, Universidad de
Almería, Almería, Spain
Centro Andaluz para la Evaluación y Seguimiento del Cambio Global
(CAESCG), Universidad de Almería, Almería, Spain
Mario Guevara
Centro de Geociencias, Universidad Nacional Autónoma de
México, Campus Juriquilla, Querétaro, Mexico
Fernando Bezares
Departamento de Agronomía, Edif. CITEIIB, Universidad de
Almería, Almería, Spain
Fundación Cesefor, Soria, Spain
Rodrigo Vargas
Department of Plant and Soil Science, University of Delaware, Newark,
DE, USA
Pilar Durante
Departamento de Agronomía, Edif. CITEIIB, Universidad de
Almería, Almería, Spain
Centro Andaluz para la Evaluación y Seguimiento del Cambio Global
(CAESCG), Universidad de Almería, Almería, Spain
Agresta Sociedad Cooperativa, 28012 Madrid, Spain
Víctor Osorio
Facultad de
ingeniería Marítima y Ciencias del Mar, Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador
Wilmer Jiménez
Ministerio de Agricultura y Ganadería, Dirección de
Generación de Geoinformación Agropecuaria, Quito, Ecuador
Cecilio Oyonarte
CORRESPONDING AUTHOR
Departamento de Agronomía, Edif. CITEIIB, Universidad de
Almería, Almería, Spain
Centro Andaluz para la Evaluación y Seguimiento del Cambio Global
(CAESCG), Universidad de Almería, Almería, Spain
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Sergio Díaz-Guadarrama, Viviana M. Varón-Ramírez, Iván Lizarazo, Mario Guevara, Marcos Angelini, Gustavo A. Araujo-Carrillo, Jainer Argeñal, Daphne Armas, Rafael A. Balta, Adriana Bolivar, Nelson Bustamante, Ricardo O. Dart, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Díaz, Wilmer Jiménez, Raúl S. Lavado, Jesús F. Mansilla-Baca, Maria de Lourdes Mendonça-Santos, Lucas M. Moretti, Iván D. Muñoz, Carolina Olivera, Guillermo Olmedo, Christian Omuto, Sol Ortiz, Carla Pascale, Marco Pfeiffer, Iván A. Ramos, Danny Ríos, Rafael Rivera, Lady M. Rodriguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Víctor Sevilla, Leonardo M. Tenti, Ronald Vargas, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano
Earth Syst. Sci. Data, 16, 1229–1246, https://doi.org/10.5194/essd-16-1229-2024, https://doi.org/10.5194/essd-16-1229-2024, 2024
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In this work, the Latin America and Caribbean Soil Information System (SISLAC) database (https://54.229.242.119/sislac/es) was revised to generate an improved version of the data. Rules for data enhancement were defined. In addition, other datasets available in the region were included. Subsequently, through a principal component analysis (PCA), the main soil characteristics for the region were analyzed. We hope this dataset can help mitigate problems such as food security and global warming.
Pilar Durante, Juan Miguel Requena-Mullor, Rodrigo Vargas, Mario Guevara, Domingo Alcaraz-Segura, and Cecilio Oyonarte
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-431, https://doi.org/10.5194/essd-2024-431, 2024
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Human activities have disrupted the global carbon cycle, increasing CO2 levels. Soils are the largest carbon stores on land, making it essential to understand how much carbon they hold to fight climate change. Our study improved estimates of soil carbon in peninsular Spain by integrating historical soil data and using machine-learning methods to create detailed maps of carbon content. These maps will help manage soil carbon better and support efforts to track carbon emissions globally.
Sergio Díaz-Guadarrama, Viviana M. Varón-Ramírez, Iván Lizarazo, Mario Guevara, Marcos Angelini, Gustavo A. Araujo-Carrillo, Jainer Argeñal, Daphne Armas, Rafael A. Balta, Adriana Bolivar, Nelson Bustamante, Ricardo O. Dart, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Díaz, Wilmer Jiménez, Raúl S. Lavado, Jesús F. Mansilla-Baca, Maria de Lourdes Mendonça-Santos, Lucas M. Moretti, Iván D. Muñoz, Carolina Olivera, Guillermo Olmedo, Christian Omuto, Sol Ortiz, Carla Pascale, Marco Pfeiffer, Iván A. Ramos, Danny Ríos, Rafael Rivera, Lady M. Rodriguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Víctor Sevilla, Leonardo M. Tenti, Ronald Vargas, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano
Earth Syst. Sci. Data, 16, 1229–1246, https://doi.org/10.5194/essd-16-1229-2024, https://doi.org/10.5194/essd-16-1229-2024, 2024
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In this work, the Latin America and Caribbean Soil Information System (SISLAC) database (https://54.229.242.119/sislac/es) was revised to generate an improved version of the data. Rules for data enhancement were defined. In addition, other datasets available in the region were included. Subsequently, through a principal component analysis (PCA), the main soil characteristics for the region were analyzed. We hope this dataset can help mitigate problems such as food security and global warming.
Josué Delgado-Balbuena, Henry W. Loescher, Carlos A. Aguirre-Gutiérrez, Teresa Alfaro-Reyna, Luis F. Pineda-Martínez, Rodrigo Vargas, and Tulio Arredondo
Biogeosciences, 20, 2369–2385, https://doi.org/10.5194/bg-20-2369-2023, https://doi.org/10.5194/bg-20-2369-2023, 2023
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In the semiarid grassland, an increase in soil moisture at shallow depths instantly enhances carbon release through respiration. In contrast, deeper soil water controls plant carbon uptake but with a delay of several days. Previous soil conditions, biological activity, and the size and timing of precipitation are factors that determine the amount of carbon released into the atmosphere. Thus, future changes in precipitation patterns could convert ecosystems from carbon sinks to carbon sources.
Rodrigo Vargas and Van Huong Le
Biogeosciences, 20, 15–26, https://doi.org/10.5194/bg-20-15-2023, https://doi.org/10.5194/bg-20-15-2023, 2023
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Quantifying the role of soils in nature-based solutions requires accurate estimates of soil greenhouse gas (GHG) fluxes. We suggest that multiple GHG fluxes should not be simultaneously measured at a few fixed time intervals, but an optimized sampling approach can reduce bias and uncertainty. Our results have implications for assessing GHG fluxes from soils and a better understanding of the role of soils in nature-based solutions.
Viviana Marcela Varón-Ramírez, Gustavo Alfonso Araujo-Carrillo, and Mario Antonio Guevara Santamaría
Earth Syst. Sci. Data, 14, 4719–4741, https://doi.org/10.5194/essd-14-4719-2022, https://doi.org/10.5194/essd-14-4719-2022, 2022
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These are the first national soil texture maps obtained via digital soil mapping. We built clay, sand, and silt maps using spatial assembling with the best possible predictions at different depths. Also, we identified the better model for each pixel. This work was done to address the lack of soil texture maps in Colombia, and it can provide soil information for water-related applications, ecosystem services, and agricultural and crop modeling.
Margaret Capooci and Rodrigo Vargas
Biogeosciences, 19, 4655–4670, https://doi.org/10.5194/bg-19-4655-2022, https://doi.org/10.5194/bg-19-4655-2022, 2022
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Katherine E. O. Todd-Brown, Rose Z. Abramoff, Jeffrey Beem-Miller, Hava K. Blair, Stevan Earl, Kristen J. Frederick, Daniel R. Fuka, Mario Guevara Santamaria, Jennifer W. Harden, Katherine Heckman, Lillian J. Heran, James R. Holmquist, Alison M. Hoyt, David H. Klinges, David S. LeBauer, Avni Malhotra, Shelby C. McClelland, Lucas E. Nave, Katherine S. Rocci, Sean M. Schaeffer, Shane Stoner, Natasja van Gestel, Sophie F. von Fromm, and Marisa L. Younger
Biogeosciences, 19, 3505–3522, https://doi.org/10.5194/bg-19-3505-2022, https://doi.org/10.5194/bg-19-3505-2022, 2022
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Research data are becoming increasingly available online with tantalizing possibilities for reanalysis. However harmonizing data from different sources remains challenging. Using the soils community as an example, we walked through the various strategies that researchers currently use to integrate datasets for reanalysis. We find that manual data transcription is still extremely common and that there is a critical need for community-supported informatics tools like vocabularies and ontologies.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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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.
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.
Flavio Lopes Ribeiro, Mario Guevara, Alma Vázquez-Lule, Ana Paula Cunha, Marcelo Zeri, and Rodrigo Vargas
Nat. Hazards Earth Syst. Sci., 21, 879–892, https://doi.org/10.5194/nhess-21-879-2021, https://doi.org/10.5194/nhess-21-879-2021, 2021
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The main objective of this paper was to analyze differences in soil moisture responses to drought for each biome of Brazil. For that we used satellite data from the European Space Agency from 2009 to 2015. We found an overall soil moisture decline of −0.5 % yr−1 at the country level and identified the most vulnerable biomes of Brazil. This information is crucial to enhance the national drought early warning system and develop strategies for drought risk reduction and soil moisture conservation.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
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Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Mario Guevara, Michela Taufer, and Rodrigo Vargas
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-191, https://doi.org/10.5194/essd-2019-191, 2019
Revised manuscript not accepted
Mario Guevara, Guillermo Federico Olmedo, Emma Stell, Yusuf Yigini, Yameli Aguilar Duarte, Carlos Arellano Hernández, Gloria E. Arévalo, Carlos Eduardo Arroyo-Cruz, Adriana Bolivar, Sally Bunning, Nelson Bustamante Cañas, Carlos Omar Cruz-Gaistardo, Fabian Davila, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo Tacona, Fernando Fontes, José Antonio Hernández Herrera, Alejandro Roberto Ibelles Navarro, Veronica Loayza, Alexandra M. Manueles, Fernando Mendoza Jara, Carolina Olivera, Rodrigo Osorio Hermosilla, Gonzalo Pereira, Pablo Prieto, Iván Alexis Ramos, Juan Carlos Rey Brina, Rafael Rivera, Javier Rodríguez-Rodríguez, Ronald Roopnarine, Albán Rosales Ibarra, Kenset Amaury Rosales Riveiro, Guillermo Andrés Schulz, Adrian Spence, Gustavo M. Vasques, Ronald R. Vargas, and Rodrigo Vargas
SOIL, 4, 173–193, https://doi.org/10.5194/soil-4-173-2018, https://doi.org/10.5194/soil-4-173-2018, 2018
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We provide a reproducible multi-modeling approach for SOC mapping across Latin America on a country-specific basis as required by the Global Soil Partnership of the United Nations. We identify key prediction factors for SOC across each country. We compare and test different methods to generate spatially explicit predictions of SOC and conclude that there is no best method on a quantifiable basis.
Ana López-Ballesteros, Cecilio Oyonarte, Andrew S. Kowalski, Penélope Serrano-Ortiz, Enrique P. Sánchez-Cañete, M. Rosario Moya, and Francisco Domingo
Biogeosciences, 15, 263–278, https://doi.org/10.5194/bg-15-263-2018, https://doi.org/10.5194/bg-15-263-2018, 2018
A. W. King, R. J. Andres, K. J. Davis, M. Hafer, D. J. Hayes, D. N. Huntzinger, B. de Jong, W. A. Kurz, A. D. McGuire, R. Vargas, Y. Wei, T. O. West, and C. W. Woodall
Biogeosciences, 12, 399–414, https://doi.org/10.5194/bg-12-399-2015, https://doi.org/10.5194/bg-12-399-2015, 2015
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Pedology
An integrated dataset of ground hydrothermal regimes and soil nutrients monitored in some previously burned areas in hemiboreal forests in Northeast China during 2016–2022
Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)
BIS-4D: mapping soil properties and their uncertainties at 25 m resolution in the Netherlands
European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions
Improving the Latin America and Caribbean Soil Information System (SISLAC) database enhances its usability and scalability
The patterns of soil nitrogen stocks and C : N stoichiometry under impervious surfaces in China
Mapping of peatlands in the forested landscape of Sweden using lidar-based terrain indices
ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993–2018
Colombian soil texture: building a spatial ensemble model
SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022
A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling
A repository of measured soil freezing characteristic curves: 1921 to 2021
A compiled soil respiration dataset at different time scales for forest ecosystems across China from 2000 to 2018
Xiaoying Li, Huijun Jin, Qi Feng, Qingbai Wu, Hongwei Wang, Ruixia He, Dongliang Luo, Xiaoli Chang, Raul-David Şerban, and Tao Zhan
Earth Syst. Sci. Data, 16, 5009–5026, https://doi.org/10.5194/essd-16-5009-2024, https://doi.org/10.5194/essd-16-5009-2024, 2024
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In Northeast China, the permafrost is more sensitive to climate warming and fire disturbances than the boreal and Arctic permafrost. Since 2016, a continuous ground hydrothermal regime and soil nutrient content observation system has been gradually established in Northeast China. The integrated dataset includes soil moisture content, soil organic carbon, total nitrogen, total phosphorus, total potassium, ground temperatures at depths of 0–20 m, and active layer thickness from 2016 to 2022.
Niels H. Batjes, Luis Calisto, and Luis M. de Sousa
Earth Syst. Sci. Data, 16, 4735–4765, https://doi.org/10.5194/essd-16-4735-2024, https://doi.org/10.5194/essd-16-4735-2024, 2024
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Soils are an important provider of ecosystem services. This dataset provides quality-assessed and standardised soil data to support digital soil mapping and environmental applications at a broad scale. 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 three measures to assess "fitness for intended use" of the standardised data.
Anatol Helfenstein, Vera L. Mulder, Mirjam J. D. Hack-ten Broeke, Maarten van Doorn, Kees Teuling, Dennis J. J. Walvoort, and Gerard B. M. Heuvelink
Earth Syst. Sci. Data, 16, 2941–2970, https://doi.org/10.5194/essd-16-2941-2024, https://doi.org/10.5194/essd-16-2941-2024, 2024
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Earth system models and decision support systems greatly benefit from high-resolution soil information with quantified accuracy. Here we introduce BIS-4D, a statistical modeling platform that predicts nine essential soil properties and their uncertainties at 25 m resolution in surface 2 m across the Netherlands. Using machine learning informed by up to 856 000 soil observations coupled with 366 spatially explicit environmental variables, prediction accuracy was the highest for clay, sand and pH.
Songchao Chen, Zhongxing Chen, Xianglin Zhang, Zhongkui Luo, Calogero Schillaci, Dominique Arrouays, Anne Christine Richer-de-Forges, and Zhou Shi
Earth Syst. Sci. Data, 16, 2367–2383, https://doi.org/10.5194/essd-16-2367-2024, https://doi.org/10.5194/essd-16-2367-2024, 2024
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A new dataset for topsoil bulk density (BD) and soil organic carbon (SOC) stock (0–20 cm) across Europe using machine learning was generated. The proposed approach performed better in BD prediction and slightly better in SOC stock prediction than earlier-published PTFs. The outcomes present a meaningful advancement in enhancing the accuracy of BD, and the resultant topsoil BD and SOC stock datasets across Europe enable more precise soil hydrological and biological modeling.
Sergio Díaz-Guadarrama, Viviana M. Varón-Ramírez, Iván Lizarazo, Mario Guevara, Marcos Angelini, Gustavo A. Araujo-Carrillo, Jainer Argeñal, Daphne Armas, Rafael A. Balta, Adriana Bolivar, Nelson Bustamante, Ricardo O. Dart, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Díaz, Wilmer Jiménez, Raúl S. Lavado, Jesús F. Mansilla-Baca, Maria de Lourdes Mendonça-Santos, Lucas M. Moretti, Iván D. Muñoz, Carolina Olivera, Guillermo Olmedo, Christian Omuto, Sol Ortiz, Carla Pascale, Marco Pfeiffer, Iván A. Ramos, Danny Ríos, Rafael Rivera, Lady M. Rodriguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Víctor Sevilla, Leonardo M. Tenti, Ronald Vargas, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano
Earth Syst. Sci. Data, 16, 1229–1246, https://doi.org/10.5194/essd-16-1229-2024, https://doi.org/10.5194/essd-16-1229-2024, 2024
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In this work, the Latin America and Caribbean Soil Information System (SISLAC) database (https://54.229.242.119/sislac/es) was revised to generate an improved version of the data. Rules for data enhancement were defined. In addition, other datasets available in the region were included. Subsequently, through a principal component analysis (PCA), the main soil characteristics for the region were analyzed. We hope this dataset can help mitigate problems such as food security and global warming.
Qian Ding, Hua Shao, Chi Zhang, and Xia Fang
Earth Syst. Sci. Data, 15, 4599–4612, https://doi.org/10.5194/essd-15-4599-2023, https://doi.org/10.5194/essd-15-4599-2023, 2023
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A soil survey in 41 Chinese cities showed the soil nitrogen (N) in impervious surface areas (ISA; NISA) was 0.59±0.35 kg m−2, lower than in pervious soils. Eastern China had the highest NISA but the lowest natural soil N in China. Soil N decreased linearly with depth in ISA but nonlinearly in natural ecosystems. Temperature was negatively correlated with C : NISA but positively correlated with natural soil C : N. The unique NISA patterns imply intensive disturbance in N cycle by soil sealing.
Lukas Rimondini, Thomas Gumbricht, Anders Ahlström, and Gustaf Hugelius
Earth Syst. Sci. Data, 15, 3473–3482, https://doi.org/10.5194/essd-15-3473-2023, https://doi.org/10.5194/essd-15-3473-2023, 2023
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Peatlands have historically sequestrated large amounts of carbon and contributed to atmospheric cooling. However, human activities and climate change may instead turn them into considerable carbon emitters. In this study, we produced high-quality maps showing the extent of peatlands in the forests of Sweden, one of the most peatland-dense countries in the world. The maps are publicly available and may be used to support work promoting sustainable peatland management and combat their degradation.
Fei Cheng, Zhao Zhang, Huimin Zhuang, Jichong Han, Yuchuan Luo, Juan Cao, Liangliang Zhang, Jing Zhang, Jialu Xu, and Fulu Tao
Earth Syst. Sci. Data, 15, 395–409, https://doi.org/10.5194/essd-15-395-2023, https://doi.org/10.5194/essd-15-395-2023, 2023
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We generated a 1 km daily soil moisture dataset for dryland wheat and maize across China (ChinaCropSM1 km) over 1993–2018 through random forest regression, based on in situ observations. Our improved products have a remarkably better quality compared with the public global products in terms of both spatial and time dimensions by integrating an irrigation module (crop type, phenology, soil depth). The dataset may be useful for agriculture drought monitoring and crop yield forecasting studies.
Viviana Marcela Varón-Ramírez, Gustavo Alfonso Araujo-Carrillo, and Mario Antonio Guevara Santamaría
Earth Syst. Sci. Data, 14, 4719–4741, https://doi.org/10.5194/essd-14-4719-2022, https://doi.org/10.5194/essd-14-4719-2022, 2022
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These are the first national soil texture maps obtained via digital soil mapping. We built clay, sand, and silt maps using spatial assembling with the best possible predictions at different depths. Also, we identified the better model for each pixel. This work was done to address the lack of soil texture maps in Colombia, and it can provide soil information for water-related applications, ecosystem services, and agricultural and crop modeling.
Qiang Zhang, Qiangqiang Yuan, Taoyong Jin, Meiping Song, and Fujun Sun
Earth Syst. Sci. Data, 14, 4473–4488, https://doi.org/10.5194/essd-14-4473-2022, https://doi.org/10.5194/essd-14-4473-2022, 2022
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Compared to previous seamless global daily soil moisture (SGD-SM 1.0) products, SGD-SM 2.0 enlarges the temporal scope from 2002 to 2022. By fusing auxiliary precipitation information with the long short-term memory convolutional neural network (LSTM-CNN) model, SGD-SM 2.0 can consider sudden extreme weather conditions for 1 d in global daily soil moisture products and is significant for full-coverage global daily hydrologic monitoring, rather than averaging monthly–quarterly–yearly results.
Juri Palmtag, Jaroslav Obu, Peter Kuhry, Andreas Richter, Matthias B. Siewert, Niels Weiss, Sebastian Westermann, and Gustaf Hugelius
Earth Syst. Sci. Data, 14, 4095–4110, https://doi.org/10.5194/essd-14-4095-2022, https://doi.org/10.5194/essd-14-4095-2022, 2022
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The northern permafrost region covers 22 % of the Northern Hemisphere and holds almost twice as much carbon as the atmosphere. This paper presents data from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. We use this dataset together with ESA's global land cover dataset to estimate soil organic carbon and total nitrogen storage up to 300 cm soil depth, with estimated values of 813 Pg for carbon and 55 Pg for nitrogen.
Élise G. Devoie, Stephan Gruber, and Jeffrey M. McKenzie
Earth Syst. Sci. Data, 14, 3365–3377, https://doi.org/10.5194/essd-14-3365-2022, https://doi.org/10.5194/essd-14-3365-2022, 2022
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Soil freezing characteristic curves (SFCCs) relate the temperature of a soil to its ice content. SFCCs are needed in all physically based numerical models representing freezing and thawing soils, and they affect the movement of water in the subsurface, biogeochemical processes, soil mechanics, and ecology. Over a century of SFCC data exist, showing high variability in SFCCs based on soil texture, water content, and other factors. This repository summarizes all available SFCC data and metadata.
Hongru Sun, Zhenzhu Xu, and Bingrui Jia
Earth Syst. Sci. Data, 14, 2951–2961, https://doi.org/10.5194/essd-14-2951-2022, https://doi.org/10.5194/essd-14-2951-2022, 2022
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We compiled a new soil respiration (Rs) database of China's forests from 568 studies published up to 2018. The hourly, monthly, and annual samples were 8317, 5003, and 634, respectively. Most of the Rs data are shown in figures but were seldom exploited. For the first time, these data were digitized, accounting for 82 % of samples. Rs measured with common methods was selected (Li-6400, Li-8100, Li-8150, gas chromatography) and showed small differences of ~10 %. Bamboo had the highest Rs.
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Short summary
The global need for updated soil datasets has increased. Our main objective was to synthesize and harmonize soil profile information collected by two different projects in Ecuador between 2009 and 2015.The main result was the development of the Harmonized Soil Database of Ecuador (HESD) that includes information from 13 542 soil profiles with over 51 713 measured soil horizons, including 92 different edaphic variables, and follows international standards for archiving and sharing soil data.
The global need for updated soil datasets has increased. Our main objective was to synthesize...
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