Articles | Volume 15, issue 10
https://doi.org/10.5194/essd-15-4599-2023
© 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-15-4599-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The patterns of soil nitrogen stocks and C : N stoichiometry under impervious surfaces in China
Qian Ding
Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi, 270600, China
Hua Shao
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
Chi Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi, 270600, China
Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, 830011, China
Xia Fang
Xinjiang Institute of Engineering, Urumqi, 830091, China
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C. Zhang, H. Tian, S. Pan, G. Lockaby, and A. Chappelka
Biogeosciences, 11, 7107–7124, https://doi.org/10.5194/bg-11-7107-2014, https://doi.org/10.5194/bg-11-7107-2014, 2014
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Based on a comprehensive analysis framework including 15 factors, a factorial analysis scheme was developed to quantify a relative contribution of individual factors to carbon dynamics induced by urbanization. A case study in the southern US showed that land conversion had larger impacts than other factors, causing C loss. Urban managements & the interactive effect among factors compensated for 42% of the C loss in LC. The altered disturbance regime after urbanization enhanced the urban C sink.
H. Tian, G. Chen, C. Lu, X. Xu, W. Ren, K. Banger, B. Zhang, B. Tao, S. Pan, M. Liu, and C. Zhang
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-19811-2013, https://doi.org/10.5194/bgd-10-19811-2013, 2013
Revised manuscript has not been submitted
Related subject area
Domain: ESSD – Land | Subject: Pedology
BIS-4D: mapping soil properties and their uncertainties at 25 m resolution in the Netherlands
An integrated dataset of ground hydrothermal regimes and soil nutrients monitored during 2016–2022 in some previously burned areas in hemiboreal forests in Northeast China
European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions
Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)
Improving the Latin America and Caribbean Soil Information System (SISLAC) database enhances its usability and scalability
Mapping of peatlands in the forested landscape of Sweden using lidar-based terrain indices
Harmonized Soil Database of Ecuador (HESD): data from 2009 to 2015
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
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.
Xiaoying Li, Huijun Jin, Qi Feng, Qingbai Wu, Hongwei Wang, Ruixia He, Dongliang Luo, Xiaoli Chang, Raul-David Șerban, and Tao Zhan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-187, https://doi.org/10.5194/essd-2024-187, 2024
Preprint under review for ESSD
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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 observation system has been gradually established for ground hydrothermal regimes and soil nutrient contents 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.
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.
Niels Hindrik Batjes, Luis Calisto, and Luis Moreira de Sousa
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-14, https://doi.org/10.5194/essd-2024-14, 2024
Revised manuscript accepted for ESSD
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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.
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.
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.
Daphne Armas, Mario Guevara, Fernando Bezares, Rodrigo Vargas, Pilar Durante, Víctor Osorio, Wilmer Jiménez, and Cecilio Oyonarte
Earth Syst. Sci. Data, 15, 431–445, https://doi.org/10.5194/essd-15-431-2023, https://doi.org/10.5194/essd-15-431-2023, 2023
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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.
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.
Cited articles
Bae, J. and Ryu, Y.: High soil organic carbon stocks under impervious surfaces contributed by urban deep cultural layers, Landscape Urban Plan., 204, 103953, https://doi.org/10.1016/j.landurbplan.2020.103953, 2020.
Bloom, D. E., Canning, D., and Fink, G.: Urbanization and the wealth of nations, Science, 319, 772–775, https://doi.org/10.1126/science.1153057, 2008.
Bremner, J. M. and Mulvaney, C. S.: Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties, Nitrogen-Total, American Society of Agronomy, Soil Science Society of America, 595–624 pp., 1982.
Cambou, A., Shaw, R. K., Huot, H., Vidal-Beaudet, L., Hunault, G., Cannavo, P., Nold, F., and Schwartz, C.: Estimation of soil organic carbon stocks of two cities, New York City and Paris, Sci. Total Environ., 644, 452–464, https://doi.org/10.1016/j.scitotenv.2018.06.322, 2018.
Chan, K. Y.: Soil particulate organic carbon under different land use and management, Soil Use Managem., 17, 217–221, https://doi.org/10.1079/sum200180, 2001.
Chapin, F. S., Matson, P. A., and Vitousek, P. M.: Principles of Terrestrial Ecosystem Ecology, Springer, New York, https://doi.org/10.1007/978-1-4419-9504-9, 2011.
Delgado-Baquerizo, M., Eldridge, D. J., Liu, Y. R., Sokoya, B., Wang, J. T., Hu, H. W., He, J. Z., Bastida, F., Moreno, J. L., Bamigboye, A. R., Blanco-Pastor, J. L., Cano-Diaz, C., Illan, J. G., Makhalanyane, T. P., Siebe, C., Trivedi, P., Zaady, E., Verma, J. P., Wang, L., Wang, J., Grebenc, T., Penaloza-Bojaca, G. F., Nahberger, T. U., Teixido, A. L., Zhou, X., Berdugo, M., Duran, J., Rodriguez, A., Zhou, X., Alfaro, F., Abades, S., Plaza, C., Rey, A., Singh, B. K., Tedersoo, L., and Fierer, N.: Global homogenization of the structure and function in the soil microbiome of urban greenspaces, Sci. Adv., 7, eabg5809, https://doi.org/10.1126/sciadv.abg5809, 2021.
Ding, Q., Shao, H., Chen, X., and Zhang, C.: Urban Land Conversion Reduces Soil Organic Carbon Density Under Impervious Surfaces, Global Biogeochem. Cycles, 36, e2021GB007293, https://doi.org/10.1029/2021GB007293, 2022.
Ding, Q., Shao, H., Zhang, C., and Fang, X.: Observations of soil nitrogen and soil organic carbon to soil nitrogen stoichiometry under the impervious surfaces areas (ISA) of China, National Cryosphere Desert Data Center [data set], https://doi.org/10.12072/ncdc.socn.db2851.2023, 2023.
Edmondson, J. L., Davies, Z. G., McHugh, N., Gaston, K. J., and Leake, J. R.: Organic carbon hidden in urban ecosystems, Sci. Rep., 2, 963, https://doi.org/10.1038/srep00963, 2012.
Fleischer, K., Rammig, A., De Kauwe, M. G., Walker, A. P., Domingues, T. F., Fuchslueger, L., Garcia, S., Goll, D. S., Grandis, A., Jiang, M., Haverd, V., Hofhansl, F., Holm, J. A., Kruijt, B., Leung, F., Medlyn, B. E., Mercado, L. M., Norby, R. J., Pak, B., von Randow, C., Quesada, C. A., Schaap, K., Valverde-Barrantes, O. J., Wang, Y. P., Yang, X., Zaehle, S., Zhu, Q., and Lapola, D. M.: Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition, Nat. Geosci., 12, 736–741, https://doi.org/10.1038/s41561-019-0404-9, 2019.
Fowler, D., Coyle, M., Skiba, U., Sutton, M. A., Cape, J. N., Reis, S., Sheppard, L. J., Jenkins, A., Grizzetti, B., Galloway, J. N., Vitousek, P., Leach, A., Bouwman, A. F., Butterbach-Bahl, K., Dentener, F., Stevenson, D., Amann, M., and Voss, M.: The global nitrogen cycle in the twenty-first century, Philos. T. Roy. Soc. B, 368, 20130164, https://doi.org/10.1098/rstb.2013.0164, 2013.
Gong, P., Li, X., Wang, J., Bai, Y., Chen, B., Hu, T., Liu, X., Xu, B., Yang, J., Zhang, W., and Zhou, Y.: Annual maps of global artificial impervious area (GAIA) between 1985 and 2018, Remote Sens. Environ., 236, 111510, https://doi.org/10.1016/j.rse.2019.111510, 2020.
He, Y. and Zhang, G. L.: Historical record of black carbon in urban soils and its environmental implications, Environ. Pollut., 157, 2684–2688, https://doi.org/10.1016/j.envpol.2009.05.019, 2009.
Hu, Y., Dou, X., Li, J., and Li, F.: Impervious Surfaces Alter Soil Bacterial Communities in Urban Areas: A Case Study in Beijing, China, Front. Microbiol., 9, 226, https://doi.org/10.3389/fmicb.2018.00226, 2018.
Jobbágy, E. G. and Jackson, R. B.: The distribution of soil nutrients with depth: Global patterns and the imprint of plants, Biogeochemistry, 53, 51–77, https://doi.org/10.1023/A:1010760720215, 2001.
Kuang, W.: Mapping global impervious surface area and green space within urban environments, Sci. China-Earth Sci., 62, 1591–1606, https://doi.org/10.1007/s11430-018-9342-3, 2019.
Kuang, W., Liu, J., Tian, H., Shi, H., Dong, J., Song, C., Li, X., Du, G., Hou, Y., Lu, D., Chi, W., Pan, T., Zhang, S., Hamdi, R., Yin, Z., Yan, H., Yan, C., Wu, S., Li, R., Yang, J., Dou, Y., Wu, W., Liang, L., Xiang, B., and Yang, S.: Cropland redistribution to marginal lands undermines environmental sustainability, Natl. Sci. Rev., 9, nwab091–nwab091, https://doi.org/10.1093/nsr/nwab091, 2021.
Li, S., Liu, X., Yue, F., Yan, Z., Wang, T., Li, S., and Liu, C.: Nitrogen dynamics in the Critical Zones of China, Prog. Phys. Geogr.-Earth Environ., 46, 869–888, https://doi.org/10.1177/03091333221114732, 2022.
Lorenz, K. and Lal, R.: Biogeochemical C and N cycles in urban soils, Environment International, 35, 1–8, https://doi.org/10.1016/j.envint.2008.05.006, 2009.
Lu, M., Zeng, F., Lv, S., Zhang, H., Zeng, Z., Peng, W., Song, T., Wang, K., and Du, H.: Soil stoichiometry and its influencing factors in forest ecosystems in southern China, Front. Forests Global Change, 6, 1142933, https://doi.org/10.3389/ffgc.2023.1142933, 2023.
Lu, T., Zhang, W., Niu, J., Lin, Y., and Wu, M.: Study on Spatial Variability and Driving Factors of Stoichiometry of Nitrogen and Phosphorus in Soils of Typical Natural Zones of China, Acta Pedologica Sinica, 54, 682–692, 2017.
Majidzadeh, H., Lockaby, B. G., and Governo, R.: Effect of home construction on soil carbon storage-A chronosequence case study, Environ. Pollut., 226, 317–323, https://doi.org/10.1016/j.envpol.2017.04.005, 2017.
Majidzadeh, H., Graeme Lockaby, B., Price, R., and Governo, R.: Soil carbon and nitrogen dynamics beneath impervious surfaces, Soil Sci. Soc. Am. J., 82, 663–670, https://doi.org/10.2136/sssaj2017.11.0381, 2018.
O'Riordan, R., Davies, J., Stevens, C., and Quinton, J. N.: The effects of sealing on urban soil carbon and nutrients, SOIL, 7, 661–675, https://doi.org/10.5194/soil-7-661-2021, 2021.
Pan, T., Kuang, W., Shao, H., Zhang, C., Wang, X., and Wang, X.: Urban expansion and intra-urban land evolution as well as their natural environmental constraints in arid/semiarid regions of China from 2000–2018, J. Geogr. Sci., 33, 1419–1441, https://doi.org/10.1007/s11442-023-2136-4, 2023.
Pereira, M. C., O'Riordan, R., and Stevens, C.: Urban soil microbial community and microbial-related carbon storage are severely limited by sealing, J. Soils Sed., 21, 1455–1465, https://doi.org/10.1007/s11368-021-02881-7, 2021.
Piotrowska-Długosz, A. and Charzyński, P.: The impact of the soil sealing degree on microbial biomass, enzymatic activity, and physicochemical properties in the Ekranic Technosols of Toruń (Poland), J. Soils Sed., 15, 47–59, https://doi.org/10.1007/s11368-014-0963-8, 2015.
Pouyat, R. V., Russell-Anelli, J., Yesilonis, I. D., and Groffman, P. M.: Soil carbon in urban forest ecosystems, in: Potential of U.S. Forest Soils to Sequester Carbon and Mitigate the Greenhouse Effect, edited by: Kimble, J. M., Heath, L. S., Birdsey, R. A., Lal, R., CRC Press, 347–362 pp., 2003.
Raciti, S. M., Hutyra, L. R., and Finzi, A. C.: Depleted soil carbon and nitrogen pools beneath impervious surfaces, Environ. Pollut., 164, 248–251, https://doi.org/10.1016/j.envpol.2012.01.046, 2012.
Schroeder, J., Peplau, T., Pennekamp, F., Gregorich, E., Tebbe, C. C., and Poeplau, C.: Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils, Biol. Fert. Soils, https://doi.org/10.1007/s00374-022-01669-2, 2022.
Sheng, H., Yin, Z., Zhou, P., and Thompson, M. L.: Soil ratio in subtropical paddy fields: variation and correlation with environmental controls, J. Soils Sed., 22, 21–31, https://doi.org/10.1007/s11368-021-03046-2, 2022.
Shi, X., Yu, D., Warner, E., Pan, X., Petersen, G., Gong, Z., and Weindorf, D.: Soil database of 1:1 000 000 digital soil survey and reference system of the Chinese genetic soil classification system, Soil Surv. Horizons, 45, 129–136, https://doi.org/10.2136/sh2004.4.0129, 2004.
Short, J. R., Fanning, D. S., Foss, J. E., and Patterson, J. C.: Soils of the Mall in Washington, DC: II. Genesis, Classification, and Mapping, Soil Sci. Soc. Am. J., 50, 705–710, https://doi.org/10.2136/sssaj1986.03615995005000030031x, 1986.
Tang, X., Zhao, X., Bai, Y., Tang, Z., Wang, W., Zhao, Y., Wan, H., Xie, Z., Shi, X., Wu, B., Wang, G., Yan, J., Ma, K., Du, S., Li, S., Han, S., Ma, Y., Hu, H., He, N., Yang, Y., Han, W., He, H., Yu, G., Fang, J., and Zhou, G.: Carbon pools in China's terrestrial ecosystems: New estimates based on an intensive field survey, P. Natl. Acad. Sci. USA, 115, 4021–4026, https://doi.org/10.1073/pnas.1700291115, 2018.
Tian, H., Wang, S., Liu, J., Pan, S., Chen, H., Zhang, C., and Shi, X.: Patterns of soil nitrogen storage in China, Global Biogeochem. Cycles, 20, GB1001, https://doi.org/10.1029/2005GB002464, 2006.
Tian, H., Chen, G., Zhang, C., Melillo, J. M., and Hall, C. A. S.: Pattern and variation of ratios in China's soils: a synthesis of observational data, Biogeochemistry, 98, 139–151, https://doi.org/10.1007/s10533-009-9382-0, 2010.
Vitousek, P. M. and Howarth, R. W.: Nitrogen limitation on land and in the sea: How can it occur?, Biogeochemistry, 13, 87–115, https://doi.org/10.1007/BF00002772, 1991.
Wei, Z., Wu, S., Zhou, S., and Lin, C.: Installation of impervious surface in urban areas affects microbial biomass, activity (potential C mineralisation), and functional diversity of the fine earth, Soil Res., 51, 59–67, https://doi.org/10.1071/sr12089, 2013.
Wei, Z., Wu, S., Yan, X., and Zhou, S.: Density and Stability of Soil Organic Carbon beneath Impervious Surfaces in Urban Areas, Plos One, 9, e109380, https://doi.org/10.1371/journal.pone.0109380, 2014a.
Wei, Z., Wu, S., Zhou, S., Li, J., and Zhao, Q.: Soil Organic Carbon Transformation and Related Properties in Urban Soil Under Impervious Surfaces, Pedosphere, 24, 56–64, https://doi.org/10.1016/s1002-0160(13)60080-6, 2014b.
Wiesmeier, M., Urbanski, L., Hobley, E., Lang, B., von Luetzow, M., Marin-Spiotta, E., van Wesemael, B., Rabot, E., Liess, M., Garcia-Franco, N., Wollschlaeger, U., Vogel, H.-J., and Koegel-Knabner, I.: Soil organic carbon storage as a key function of soils – A review of drivers and indicators at various scales, Geoderma, 333, 149–162, https://doi.org/10.1016/j.geoderma.2018.07.026, 2019.
Xu, L., He, N., and Yu, G.: Nitrogen storage in China's terrestrial ecosystems, Sci. Total Environ., 709, 136201, https://doi.org/10.1016/j.scitotenv.2019.136201, 2020.
Yan, Y., Kuang, W., Zhang, C., and Chen, C.: Impacts of impervious surface expansion on soil organic carbon – a spatially explicit study, Sci. Rep., 5, 17905, https://doi.org/10.1038/srep17905, 2015.
Yang, J., Yuan, D., Zhao, Y., He, Y., and Zhang, G.: Stoichiometric relations of C, N, and P in urban top soils in Nanjing, China, and their biogeochemical implications, J. Soils Sed., 21, 2154–2164, https://doi.org/10.1007/s11368-020-02826-6, 2021.
Yang, Y., Ma, W., Mohammat, A., and Fang, J.: Storage, Patterns and Controls of Soil Nitrogen in China, Pedosphere, 17, 776–785, https://doi.org/10.1016/S1002-0160(07)60093-9, 2007.
Yu, W. W., Hu, Y. H., Cui, B. W., Chen, Y. Y., and Wang, X. K.: The Effects of Pavement Types on Soil Bacterial Communities across Different Depths, Int. J. Environ. Res. Publ. He., 16, 11, https://doi.org/10.3390/ijerph16101805, 2019.
Zhang, X., Liu, L., Wu, C., Chen, X., Gao, Y., Xie, S., and Zhang, B.: Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform, Earth Syst. Sci. Data, 12, 1625–1648, https://doi.org/10.5194/essd-12-1625-2020, 2020.
Zhang, Y.-W., Guo, Y., Tang, Z., Feng, Y., Zhu, X., Xu, W., Bai, Y., Zhou, G., Xie, Z., and Fang, J.: Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China, Earth Syst. Sci. Data, 13, 5337–5351, https://doi.org/10.5194/essd-13-5337-2021, 2021.
Zhao, D., Li, F., Wang, R., Yang, Q., and Ni, H.: Effect of soil sealing on the microbial biomass, N transformation and related enzyme activities at various depths of soils in urban area of Beijing, China, J. Soils Sed., 12, 519–530, https://doi.org/10.1007/s11368-012-0472-6, 2012.
Zhao, H., Wu, S., Xu, X., Zhou, S., and Li, X.: Spatial Distribution of Soil Inorganic Carbon in Urban Soil and Its Relationship with Urbanization History of the City, Acta Pedologica Sinica, 54, 1540–1546, https://doi.org/10.11766/trxb201703300075, 2017.
Zhu, G., Zhou, L., He, X., Wei, P., Lin, D., Qian, S., Zhao, L., Luo, M., Yin, X., Zeng, L., Long, Y., Hu, S., Ouyang, X., and Yang, Y.: Effects of Elevation Gradient on Soil Carbon and Nitrogen in a Typical Karst Region of Chongqing, Southwest China, J. Geophys. Res.-Biogeo., 127, e2021JG006742, https://doi.org/10.1029/2021JG006742, 2022.
Zhu, M., Li, M., Wei, S., Song, J., Hu, J., Jia, W., and Peng, P. A.: Evaluation of a dichromate oxidation method for the isolation and quantification of black carbon in ancient geological samples, Org. Geochem., 133, 20–31, https://doi.org/10.1016/j.orggeochem.2019.03.009, 2019.
Short summary
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.
A soil survey in 41 Chinese cities showed the soil nitrogen (N) in impervious surface areas (ISA;...
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