Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5009-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5009-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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
Xiaoying Li
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Huijun Jin
CORRESPONDING AUTHOR
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of Ecology, Northeast Forestry University, Harbin 150040, China
Ministry of Natural Resources Field Observation and Research Station of Permafrost and Cold Regions Environment in the Da Xing'anling Mountains at Mo'he, Natural Resources Survey Institute of Heilongjiang Province, Harbin 150036, China
Qi Feng
Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Qingbai Wu
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Hongwei Wang
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of Ecology, Northeast Forestry University, Harbin 150040, China
Ruixia He
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Dongliang Luo
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaoli Chang
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan, Hunan 411202, China
Raul-David Şerban
Faculty of Agricultural, Environmental and Food Sciences, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
Tao Zhan
Ministry of Natural Resources Field Observation and Research Station of Permafrost and Cold Regions Environment in the Da Xing'anling Mountains at Mo'he, Natural Resources Survey Institute of Heilongjiang Province, Harbin 150036, China
Related authors
Xiaoli Chang, Huijun Jin, Ruixia He, Yanlin Zhang, Xiaoying Li, Xiaoying Jin, and Guoyu Li
Earth Syst. Sci. Data, 14, 3947–3959, https://doi.org/10.5194/essd-14-3947-2022, https://doi.org/10.5194/essd-14-3947-2022, 2022
Short summary
Short summary
Based on 10-year observations of ground temperatures in seven deep boreholes in Gen’he, Mangui, and Yituli’he, a wide range of mean annual ground temperatures at the depth of 20 m (−2.83 to −0.49 ℃) and that of annual maximum thawing depth (about 1.1 to 7.0 m) have been revealed. This study demonstrates that most trajectories of permafrost changes in Northeast China are ground warming and permafrost degradation, except that the shallow permafrost is cooling in Yituli’he.
Niu Zhu, Jinniu Wang, Dongliang Luo, Xufeng Wang, Cheng Shen, and Ning Wu
Biogeosciences, 21, 3509–3522, https://doi.org/10.5194/bg-21-3509-2024, https://doi.org/10.5194/bg-21-3509-2024, 2024
Short summary
Short summary
Our study delves into the vital role of subalpine forests in the Qinghai–Tibet Plateau as carbon sinks in the context of climate change. Utilizing advanced eddy covariance systems, we uncover their significant carbon sequestration potential, observing distinct seasonal patterns influenced by temperature, humidity, and radiation. Notably, these forests exhibit robust carbon absorption, with potential implications for global carbon balance.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Raul-David Şerban, Huijun Jin, Mihaela Şerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang
Earth Syst. Sci. Data, 16, 1425–1446, https://doi.org/10.5194/essd-16-1425-2024, https://doi.org/10.5194/essd-16-1425-2024, 2024
Short summary
Short summary
A particular observational network for ground surface temperature (GST) has been established on the northeastern Qinghai–Tibet Plateau, covering various environmental conditions and scales. This analysis revealed the substantial influences of the land cover on the spatial variability in GST over short distances (<16 m). Improving the monitoring of GST is important for the biophysical processes at the land–atmosphere boundary and for understanding the climate change impacts on cold environments.
Guoyu Li, Wei Ma, Fei Wang, Huijun Jin, Alexander Fedorov, Dun Chen, Gang Wu, Yapeng Cao, Yu Zhou, Yanhu Mu, Yuncheng Mao, Jun Zhang, Kai Gao, Xiaoying Jin, Ruixia He, Xinyu Li, and Yan Li
Earth Syst. Sci. Data, 14, 5093–5110, https://doi.org/10.5194/essd-14-5093-2022, https://doi.org/10.5194/essd-14-5093-2022, 2022
Short summary
Short summary
A permafrost monitoring network was established along the China–Russia crude oil pipeline (CRCOP) route at the eastern flank of the northern Da Xing'anling Mountains in Northeast China. The resulting datasets fill the gaps in the spatial coverage of mid-latitude mountain permafrost databases. Results show that permafrost warming has been extensively observed along the CRCOP route, and local disturbances triggered by the CRCOPs have resulted in significant permafrost thawing.
Xiaoli Chang, Huijun Jin, Ruixia He, Yanlin Zhang, Xiaoying Li, Xiaoying Jin, and Guoyu Li
Earth Syst. Sci. Data, 14, 3947–3959, https://doi.org/10.5194/essd-14-3947-2022, https://doi.org/10.5194/essd-14-3947-2022, 2022
Short summary
Short summary
Based on 10-year observations of ground temperatures in seven deep boreholes in Gen’he, Mangui, and Yituli’he, a wide range of mean annual ground temperatures at the depth of 20 m (−2.83 to −0.49 ℃) and that of annual maximum thawing depth (about 1.1 to 7.0 m) have been revealed. This study demonstrates that most trajectories of permafrost changes in Northeast China are ground warming and permafrost degradation, except that the shallow permafrost is cooling in Yituli’he.
Youhua Ran, Xin Li, Guodong Cheng, Jingxin Che, Juha Aalto, Olli Karjalainen, Jan Hjort, Miska Luoto, Huijun Jin, Jaroslav Obu, Masahiro Hori, Qihao Yu, and Xiaoli Chang
Earth Syst. Sci. Data, 14, 865–884, https://doi.org/10.5194/essd-14-865-2022, https://doi.org/10.5194/essd-14-865-2022, 2022
Short summary
Short summary
Datasets including ground temperature, active layer thickness, the probability of permafrost occurrence, and the zonation of hydrothermal condition with a 1 km resolution were released by integrating unprecedentedly large amounts of field data and multisource remote sensing data using multi-statistical\machine-learning models. It updates the understanding of the current thermal state and distribution for permafrost in the Northern Hemisphere.
Tingting Ning, Zhi Li, Qi Feng, Zongxing Li, and Yanyan Qin
Hydrol. Earth Syst. Sci., 25, 3455–3469, https://doi.org/10.5194/hess-25-3455-2021, https://doi.org/10.5194/hess-25-3455-2021, 2021
Short summary
Short summary
Previous studies decomposed ET variance in precipitation, potential ET, and total water storage changes based on Budyko equations. However, the effects of snowmelt and vegetation changes have not been incorporated in snow-dependent basins. We thus extended this method in arid alpine basins of northwest China and found that ET variance is primarily controlled by rainfall, followed by coupled rainfall and vegetation. The out-of-phase seasonality between rainfall and snowmelt weaken ET variance.
Junfeng Wang, Qingbai Wu, Ziqiang Yuan, and Hojeong Kang
The Cryosphere, 14, 2835–2848, https://doi.org/10.5194/tc-14-2835-2020, https://doi.org/10.5194/tc-14-2835-2020, 2020
Short summary
Short summary
The active layer, a buffer between permafrost and the atmosphere, is more sensitive and responds more quickly to climate change. How the freeze–thaw action at different stages regulates carbon emissions is still unclear. We conducted 2-year continuous in situ measurements in an alpine meadow permafrost ecosystem in the Qinghai–Tibet Plateau and found the freeze–thaw process modified the Rs dynamics differently in different stages. Results suggest great changes in freeze–thaw process patterns.
Bin Cao, Tingjun Zhang, Qingbai Wu, Yu Sheng, Lin Zhao, and Defu Zou
The Cryosphere, 13, 511–519, https://doi.org/10.5194/tc-13-511-2019, https://doi.org/10.5194/tc-13-511-2019, 2019
Short summary
Short summary
Many maps have been produced to estimate permafrost distribution over the Qinghai–Tibet Plateau. However the evaluation and inter-comparisons of them are poorly understood due to limited in situ measurements. We provided an in situ inventory of evidence of permafrost presence or absence, with 1475 sites over the Qinghai–Tibet Plateau. Based on the in situ measurements, our evaluation results showed a wide range of map performance, and the estimated permafrost region and area are extremely large.
Shuhua Yi, Yujie He, Xinlei Guo, Jianjun Chen, Qingbai Wu, Yu Qin, and Yongjian Ding
The Cryosphere, 12, 3067–3083, https://doi.org/10.5194/tc-12-3067-2018, https://doi.org/10.5194/tc-12-3067-2018, 2018
Short summary
Short summary
Coarse-fragment soil on the Qinghai–Tibetan Plateau has different thermal and hydrological properties to soils commonly used in modeling studies. We took soil samples and measured their physical properties in a laboratory, which were used in a model to simulate their effects on permafrost dynamics. Model errors were reduced using the measured properties, in which porosity played an dominant role.
Hanbo Yun, Qingbai Wu, Qianlai Zhuang, Anping Chen, Tong Yu, Zhou Lyu, Yuzhong Yang, Huijun Jin, Guojun Liu, Yang Qu, and Licheng Liu
The Cryosphere, 12, 2803–2819, https://doi.org/10.5194/tc-12-2803-2018, https://doi.org/10.5194/tc-12-2803-2018, 2018
Short summary
Short summary
Here we reported the QTP permafrost region was a CH4 sink of −0.86 ± 0.23 g CH4-C m−2 yr−1 over 2012–2016, soil temperature and soil water content were dominant factors controlling CH4 fluxes, and their correlations changed with soil depth due to cryoturbation dynamics. This region was a net CH4 sink in autumn, but a net source in spring, despite both seasons experiencing similar top soil thawing and freezing dynamics.
Qingbai Wu, Zhongqiong Zhang, Siru Gao, and Wei Ma
The Cryosphere, 10, 1695–1706, https://doi.org/10.5194/tc-10-1695-2016, https://doi.org/10.5194/tc-10-1695-2016, 2016
Ji Chen, Yu Sheng, Qingbai Wu, Lin Zhao, Jing Li, and Jingyi Zhao
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-134, https://doi.org/10.5194/tc-2016-134, 2016
Revised manuscript not accepted
Short summary
Short summary
The extreme thin and short-time snow cover in the northeastern Qinghai-Tibet plateau is predominantly during spring and autumn. Removal of seasonal snow cover is beneficial for cooling the active layer in the first few years. Seasonal snow cover maintains the high water content of the active layer because of the inhibitory action of snow cover on the evaporation capacity in the natural site during the daytime and in summer. Snow removal can therefore lead to a rapid decrease of soil moisture.
Shengyun Chen, Wenjie Liu, Qian Zhao, Lin Zhao, Qingbai Wu, Xingjie Lu, Shichang Kang, Xiang Qin, Shilong Chen, Jiawen Ren, and Dahe Qin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-80, https://doi.org/10.5194/tc-2016-80, 2016
Revised manuscript not accepted
Short summary
Short summary
Experimental warming was manipulated using open top chambers in alpine grassland ecosystem in the permafrost regions of the Qinghai-Tibet Plateau. The results revealed variations of earlier thawing, later freezing and longer freezing-thawing periods in shallow soil. Further, the estimated permafrost table declined under the warming scenarios. The work will be helpful to evaluate the stability of Qinghai-Tibet Railway/Highway and estimate the release of carbon under the future climate warming.
C. Mu, T. Zhang, Q. Wu, X. Peng, B. Cao, X. Zhang, B. Cao, and G. Cheng
The Cryosphere, 9, 479–486, https://doi.org/10.5194/tc-9-479-2015, https://doi.org/10.5194/tc-9-479-2015, 2015
S. Yi, J. Chen, Q. Wu, and Y. Ding
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4703-2013, https://doi.org/10.5194/tcd-7-4703-2013, 2013
Revised manuscript not accepted
Related subject area
Domain: ESSD – Land | Subject: Pedology
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
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
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Biskaborn, B. K., Smith, S. L., Noetzli, J., Matthes, H., Vieira, G., Streletskiy, D. A., Schoeneich, P., Romanovsky, V. E., Lewkowicz, A. G., Abramov, A., Allard, M., Boike, J., Cable, W. L., Christiansen, H. H., Delaloye, R., Diekmann, B., Drozdov, D., Etzelmuller, B., Grosse, G., Guglielmin, M., Ingeman-Nielsen, T., Isaksen, K., Ishikawa, M., Johansson, M., Johannsson, H., Joo, A., Kaverin, D., Kholodov, A., Konstantinov, P., Kroger, T., Lambiel, C., Lanckman, J. P., Luo, D., Malkova, G., Meiklejohn, I., Moskalenko, N., Oliva, M., Phillips, M., Ramos, M., Sannel, A. B. K., Sergeev, D., Seybold, C., Skryabin, P., Vasiliev, A., Wu, Q., Yoshikawa, K., Zheleznyak, M., and Lantuit, H.: Permafrost is warming at a global scale, Nat. Commun., 10, 264, https://doi.org/10.1038/s41467-018-08240-4, 2019.
Boyd, M. A., Walker, X. J., Barnes, J., Celis, G., Goetz, S. J., Johnstone, J. F., Link, N. T., Melvin, A. M., Saperstein, L., Schuur, E. A. G., and Mack, M. C.: Decadal impacts of wildfire fuel reduction treatments on ecosystem characteristics and fire behavior in Alaskan boreal forests, Forest Ecol. Manage., 546, 121347, https://doi.org/10.1016/j.foreco.2023.121347, 2023.
Brown, D. R. N., Jorgenson, M. T., Douglas, T. A., Romanovsky, V. E., Kielland, K., Hiemstra, C., Euskirchen, E. S., and Ruess, R. W.: Interactive effects of wildfire and climate on permafrost degradation in Alaskan lowland forests, J. Geophys. Res.-Biogeo., 120, 1619–1637, https://doi.org/10.1002/2015jg003033, 2015.
Certini, G.; Effects of fire on properties of forest soils: A review, Oecologia, 143, 1–10, 2005.
Chang, X., Jin, H., He, R., Zhang, Y., Li, X., Jin, X., and Li, G.: Permafrost changes in the northwestern Da Xing'anling Mountains, Northeast China, in the past decade, Earth Syst. Sci. Data, 14, 3947–3959, https://doi.org/10.5194/essd-14-3947-2022, 2022.
Chang, X., Jin, H., Zhang, Y., Li, X., He, R., Li, Y., Lü, L., and Wang, H.: Permafrost thermal dynamics at a local scale in northern Da Xing'anling Mountains, Environ. Res. Lett., 19, 064014, https://doi.org/10.1088/1748-9326/ad42b6, 2024.
Chen, X., Kang, S., Hu, Y., and Yang, J.: Temporal and spatial analysis of vegetation fire activity in the circum-Arctic during 2001–2020, Res. Cold Arid Reg., 15, 48–56, https://doi.org/10.1016/j.rcar.2023.03.002, 2023.
Chen, Y., Kelly, R., Genet, H., Lara, M. J., Chipman, M. L., McGuire, A. D., and Hu, F. S.: Resilience and sensitivity of ecosystem carbon stocks to fire-regime change in Alaskan tundra, Sci. Total Environ., 806, 151482, https://doi.org/10.1016/j.scitotenv.2021.151482, 2022.
Cocke, A. E., Fulé, P. Z., and Crouse, J. E.: Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data, Int. J. Wildland Fire, 14, 189–198, 2005.
Cunningham, C. X., Williamson, G. J., and Bowman, D. M.: Increasing frequency and intensity of the most extreme wildfires on Earth, Nat. Ecol. Evol., 8, 1420–1425, https://doi.org/10.1038/s41559-024-02452-2, 2024.
Dieleman, C. M., Day, N. J., Holloway, J. E., Baltzer, J., Douglas, T. A., and Turetsky, M. R.: Carbon and nitrogen cycling dynamics following permafrost thaw in the Northwest Territories, Canada, Sci. Total Environ., 845, 157288, https://doi.org/10.1016/j.scitotenv.2022.157288, 2022.
Escuin, S., Navarro, R., and Fernandez, P.: Fire severity assessment by using NBR (normalized Burn ratio) and NDVI (normalized difference vegetation index) derived from Landsat TM/ETM images, Int. J. Remote Sens., 29, 1053–1073, 2008.
Fultz, L. M., Moore-Kucera, J., Dathe, J., Davinic, M., Perry, G., Wester, D., Schwilk, D. W., and Rideout-Hanzak, S.: Forest wildfire and grassland prescribed fire effects on soil biogeochemical processes and microbial communities: Two case studies in the semi-arid Southwest, Appl. Soil Ecol., 99, 118–128, https://doi.org/10.1016/j.apsoil.2015.10.023, 2016.
Genet, H., McGuire, A. D., Barrett, K., Breen, A., Euskirchen, E. S., Johnstone, J. F., Kasischke, E. S., Melvin, A. M., Bennett, A., Mack, M. C., Rupp, T. S., Schuur, A. E. G., Turetsky, M. R., and Yuan, F.: Modeling the effects of fire severity and climate warming on active layer thickness and soil carbon storage of black spruce forests across the landscape in interior Alaska, Environ. Res. Lett., 8, 045016, https://doi.org/10.1088/1748-9326/8/4/045016, 2013.
Gu, H., Jin, J., Cheng, X., Wang, E., Zhou, Y., and Chai, Y.: The long-term impacts on chemical properties of Larix gmelini forest on the northern slope of greater Hinggan Mountains from a forest fire of varying fire intensity, J. Nat. Resour., 25, 1114–1121, 2010 (in Chinese).
Holloway, J. E., Lewkowicz, A. G., Douglas, T. A., Li, X., Turetsky, M. R., Baltzer, J. L., and Jin, H.: Impact of wildfire on permafrost landscapes: a review of recent advances and future prospects, Permafrost Periglac., 31, 371–382, 2020.
Hugelius, G., Strauss, J., Zubrzycki, S., Harden, J. W., Schuur, E. A. G., Ping, C.-L., Schirrmeister, L., Grosse, G., Michaelson, G. J., Koven, C. D., O'Donnell, J. A., Elberling, B., Mishra, U., Camill, P., Yu, Z., Palmtag, J., and Kuhry, P.: Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps, Biogeosciences, 11, 6573–6593, https://doi.org/10.5194/bg-11-6573-2014, 2014.
Jin, H., Li, S., Cheng, G., Wang, S., and Li, X.: Permafrost and climatic change in China, Global Planet. Change, 26, 387–404, https://doi.org/10.1016/S0921-8181(00)00051-5, 2000.
Jin, H., Yu, Q., Lü, L., Guo, D., He, R., Yu, S., Sun, G., and Li, Y.: Degradation of permafrost in the Xing'anling Mountains, northeastern China, Permafrost Periglac., 18, 245–258, https://doi.org/10.1002/ppp.589, 2007.
Jin, H., Wu, Q., and Romanovsky, V. E.: Editorial: Impacts from degrading permafrost, Adv. Clim. Change Res., 12, 1–5, https://doi.org/10.1016/j.accre.2021.01.007, 2021.
Jin, H., Huang, Y., Bense, V. F., Ma, Q., Marchenko, S. S., Shepelev, V. V., Hu, Y., Liang, S., Spektor, V. V., Jin, X., Li, X., and Li X.: Permafrost degradation and its hydrogeological impacts, Water, 14, 372, https://doi.org/10.3390/w14030372, 2022.
Jin, H., Yang, D., Makarieva, O., and Tang, L.: Changes in permafrost and snow cover in the Boreal and Arctic zones (BAZ) and their impacts, Adv. Clim. Change Res., 14, 157–163, https://doi.org/10.1016/j.accre.2023.04.002, 2023.
Johnstone, J. F., Chapin Iii, F. S., Foote, J., Kemmett, S., Price, K., and Viereck, L.: Decadal observations of tree regeneration following fire in boreal forests, Can. J. Forest Res., 34, 267–273, https://doi.org/10.1139/x03-183, 2004.
Johnstone, J. F., Hollingsworth, T. N., Chapin Iii, F. S., and Mack, M. C.: Changes in fire regime break the legacy lock on successional trajectories in Alaskan boreal forest, Glob. Change Biol., 16, 1281–1295, https://doi.org/10.1111/j.1365-2486.2009.02051.x, 2010.
Jones, B. M., Grosse, G., Arp, C. D., Miller, E., Liu, L., Hayes, D. J., and Larsen, C. F.: Recent Arctic tundra fire initiates widespread thermokarst development, Sci. Rep., 5, 15865, https://doi.org/10.1038/srep15865, 2015.
Jorgenson, M. T., Harden, J., Kanevskiy, M., O'Donnell, J., Wickland, K., Ewing, S., Manies, K., Zhuang, Q. L., Shur, Y., Striegl, R., and Koch, J.: Reorganization of vegetation, hydrology and soil carbon after permafrost degradation across heterogeneous boreal landscapes, Environ. Res. Lett., 8, 035017, https://doi.org/10.1088/1748-9326/8/3/035017, 2013.
Key, C. H. and Benson, N. C.: Landscape assessment (LA), Sampling and analysis methods, edited by: Lutes, D. C., Keane, R. E., Caratti, J. F., Key, C. H., Benson, N. C., Sutherland, S., and Gangi, L. J., FIREMON: Fire effects monitoring and inventory system. Integration of standardized field data collection techniques and sampling design with remote sensing to assess fire effects, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO, LA1–LA51, Gen. Tech. Rep. RMRS-GTR-164-CD, 2006.
Kirdyanov, A. V., Saurer, M., Siegwolf, R., Knorre, A. A., Prokushkin, A. S., Churakova, O. V., Fonti, M. V., and Büntgen, U.: Long-term ecological consequences of forest fires in the continuous permafrost zone of Siberia, Environ. Res. Lett., 15, 034061, https://doi.org/10.1088/1748-9326/ab7469, 2020.
Knicker, H.: How does fire affect the nature and stability of soil organic nitrogen and carbon? A review, Biogeochemistry, 85, 91–118, 2007.
Knorr, W., Arneth, A., and Jiang, L.: Demographic controls of future global fire risk, Nat. Clim. Change, 6, 781–785, https://doi.org/10.1038/nclimate2999, 2016.
Kolka, R. K., Sturtevant, B. R., Miesel, J. R., Singh, A., Wolter, P. T., Fraver, S., DeSutter, T. M., and Townsend, P. A.: Emissions of forest floor and mineral soil carbon, nitrogen and mercury pools and relationships with fire severity for the Pagami Creek Fire in the Boreal Forest of northern Minnesota, Int. J. Wildland Fire., 26, 296–305, 2017.
Kopp, B. J., Minderlein, S., and Menzel, L.: Soil moisture dynamics in a mountainous headwater area in the discontinuous permafrost zone of northern Mongolia, Arct. Antarct. Alp. Res., 46, 459–470, 2014.
Koven, C. D., Schuur, E. A. G., Schädel, C., Bohn, T. J., Burke, E. J., Chen, G., Chen, X., Ciais, P., Grosse, G., Harden, J. W., Hayes, D. J., Hugelius, G., Jafarov, E. E., Krinner, G., Kuhry, P., Lawrence, D. M., MacDougall, A. H., Marchenko, S. S., McGuire, A. D., Natali, S. M., Nicolsky, D. J., Olefeldt, D., Peng, S., Romanovsky, V. E., Schaefer, K. M., Strauss, J., Treat, C. C., and Turetsky, M.: A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback, Philos. T. R. Soc. Lond. Ser. A-Math., 373, 20140423, https://doi.org/10.1098/rsta.2014.0423, 2015.
Li, G., Ma, W., Wang, F., Jin, H., Fedorov, A., Chen, D., Wu, G., Cao, Y., Zhou, Y., Mu, Y., Mao, Y., Zhang, J., Gao, K., Jin, X., He, R., Li, X., and Li, Y.: A newly integrated ground temperature dataset of permafrost along the China–Russia crude oil pipeline route in Northeast China, Earth Syst. Sci. Data, 14, 5093–5110, https://doi.org/10.5194/essd-14-5093-2022, 2022.
Li, X. and Jin, H.: An integrated dataset of ground hydrothermal regimes and soil nutrients monitored during 2016-2022 in burned areas in Northeast China, National Tibetan Plateau/Third Pole Environment Data Center [data set], https://doi.org/10.11888/Cryos.tpdc.300933, 2024.
Li, X., Jin, H., He, R., Huang, Y., Wang, H., Luo, D., Jin, X., Lu, L., Wang, L., Li, W., Wei, C., Chang, X., Yang, S., and Yu, S.: Effects of forest fires on the permafrost environment in the northern Da Xing'anling (Hinggan) mountains, Northeast China, Permafrost Periglac., 30, 163–177, 2019.
Li, X., Jin, H., Wang, H., Marchenko, S. S., Shan, W., Luo, D., He, R., Spektor, V., Huang, Y., Li, X., and Jia, N.: Influences of forest fires on the permafrost environment: A review, Adv. Clim. Change Res., 12, 48–65, 2021.
Li, X., Jin, H., Wang, H., Jin, X., Bense, V. F., Marchenko, S. S., He, R., Huang, Y., and Luo, D.: Effects of fire history on thermal regimes of permafrost in the northern Da Xing'anling Mountains, NE China, Geoderma, 410, 115670, https://doi.org/10.1016/j.geoderma.2021.115670, 2022a.
Li, X., Jin, H., Sun, L., Wang, H., Huang, Y., He, R., Chang, X., Yu, S. and Zang, S.: TTOP-model-based maps of permafrost distribution in Northeast China for 1961–2020, Permafrost Periglac., 33, 425–435, https://doi.org/10.1002/ppp.2157, 2022b.
Li, X., Jin, H., He, R., Wang, H., Sun, L., Luo, D., Huang, Y., Li, Y., Chang, X., Wang, L., and Wei, C.: Impact of wildfire on soil carbon and nitrogen storage and vegetation succession in the Nanweng'he National Natural Wetlands Reserve, Northeast China, Catena, 221, 106797, https://doi.org/10.1016/j.catena.2022.106797, 2023.
Liang, L., Zhou, Y., Wang, J., and Gao, X.: Changes of the permafrost environment in Great Xian Ridge after disastrous forest fire, Taking Gulian mining area as an example (in Chinese), J. Glaciol. Geocryol., 13, 17–25, https://doi.org/10.7522/j.issn.1000-0240.1991.0003, 1991.
Mack, M. C., Bret-Harte, M. S., Hollingsworth, T. N., Jandt, R. R., Schuur, E. A., Shaver, G. R., and Verbyla, D. L.: Carbon loss from an unprecedented Arctic tundra wildfire, Nature, 475, 489–492, 2011.
Mack, M. C., Walker, X. J., Johnstone, J. F., Alexander, H. D., Melvin, A. M., Jean, M., and Miller, S. N.: Carbon loss from boreal forest wildfires offset by increased dominance of deciduous trees, Science, 372, 280–283, https://doi.org/10.1126/science.abf3903, 2021.
Michaelides, R. J., Schaefer, K., Zebker, H. A., Parsekian, A., Liu, L., Chen, J. Y., Natali, S., Ludwig, S., and Schaefer, S. R.: Inference of the impact of wildfire on permafrost and active layer thickness in a discontinuous permafrost region using the remotely sensed active layer thickness (ReSALT) algorithm, Environ. Res. Lett., 14, 035007, https://doi.org/10.1088/1748-9326/aaf932, 2019.
Munkhjargal, M., Yadamsuren, G., Yamkhin, J., and Menzel, L.: The combination of wildfire and changing climate triggers permafrost degradation in the Khentii Mountains, northern Mongolia, Atmosphere, 11, 155, https://doi.org/10.3390/atmos11020155, 2020.
Neff, J. C., Harden, J. W., and Gleixner, G.: Fire effects on soil organic matter content, composition, and nutrients in boreal interior Alaska, Can. J. Forest Res., 35, 2178–2187, 2005.
Nelson, D. W., Sommers, L., Page, A. L., Miller, R. H., and Keeney, D. R.: Total carbon, organic carbon, and organic matter, in: Methods of Soil Analysis, Part 3, edited by: Sparks, D. L., Page, A. L., Helmke, P. A., and Loeppert, R. H., Soil Science Society of America, Madison, WI, USA, 539–552, https://doi.org/10.2134/agronmonogr9.2.2ed.c29, 1982.
Nossov, D. R., Jorgenson, M. T., Kielland, K., and Kanevskiy, M. Z.: Edaphic and microclimatic controls over permafrost response to fire in interior Alaska, Environ. Res. Lett., 8, 035013, https://doi.org/10.1088/1748-9326/8/3/035013, 2013.
O'Donnell, J. A., Harden, J. W., McGuire, A. D., Kanevskiy, M. Z., Jorgenson, M. T., and Xu, X.: The effect of fire and permafrost interactions on soil carbon accumulation in an upland black spruce ecosystem of interior Alaska: Implications for post-thaw carbon loss, Glob. Change Biol., 17, 1461–1474, 2011a.
O'Donnell, J. A., Harden, J. W., McGuire, A. D., and Romanovsky, V. E.: Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem, Biogeosciences, 8, 1367–1382, https://doi.org/10.5194/bg-8-1367-2011, 2011b.
Petrov, M. I., Fedorov, A. N., Konstantinov, P. Y., and Argunov, R. N.: Variability of permafrost and landscape conditions following forest fires in the Central Yakutian Taiga Zone, Land, 11, 496, https://doi.org/10.3390/land11040496, 2022.
Ping, C. L., Michaelson, G. J., Kane, E. S., Packee, E. C., Stiles, C. A., Swanson, D. K., and Zaman, N. D.: Carbon stores and biogeochemical properties of soils under black spruce forest, Alaska, Soil Sci. Soc. Am. J., 74, 969–978, https://doi.org/10.2136/sssaj2009.0152, 2010.
Potter, C. and Hugny, C.: Wildfire effects on permafrost and soil moisture in spruce forests of interior Alaska, J. Forest Res., 31, 553–563, 2020.
Ramm, E., Ambus, P. L., Gschwendtner, S., Liu, C., Schloter, M., and Dannenmann, M.: Fire intensity regulates the short-term postfire response of the microbiome in Arctic tundra soil, Geoderma, 438, 116627, https://doi.org/10.1016/j.geoderma.2023.116627, 2023.
Rocha, A. V., Loranty, M. M., Higuera, P. E., Mack, M. C., Hu, F., Jones, B. M., Breen, A. L., Rastetter, E. B., Goetz, S. J., and Shaver, G. R.: The footprint of Alaskan tundra fires during the past half-century: implications for surface properties and radiative forcing. Environ. Res. Lett., 7, 044039, https://doi.org/10.1088/1748-9326/7/4/044039, 2012.
Roy, D. P., Boschetti, L., and Trigg, S. N.: Remote sensing of fire severity: assessing the performance of the normalized burn ratio, IEEE Geosci. Remote Sens. Lett., 3, 112–116, 2006.
Şerban, R. D., Şerban, M., He, R., Jin, H., Li, Y., Li, X., Wang, X., and Li, G.: 46-Year (1973–2019) permafrost landscape changes in the Hola Basin, Northeast China using machine learning and object-based classification, Remote Sens., 13, 1910, https://doi.org/10.3390/rs13101910, 2021.
Shur, Y. L. and Jorgenson, M. T.: Patterns of permafrost formation and degradation in relation to climate and ecosystems, Permafrost Periglac., 18, 7–19, 2007.
Smith, S. L., Riseborough, D. W., and Bonnaventure, P. P.: Eighteen year record of forest fire effects on ground thermal regimes and permafrost in the Central Mackenzie Valley, NWT, Canada, Permafrost Periglac., 26, 289–303, 2015.
Smith, S. L., O'Neill, H. B., Isaksen, K., Noetzli, J., and Romanovsky, V. E.: The changing thermal state of permafrost, Nat. Rev. Earth Environ., 3, 10–23, 2022.
Soil Survey Staff: Keys to Soil Taxonomy, 12th Edn., Natural Resources Conservation Service, United States Department of Agriculture, Washington D.C., ISBN 9780160923210, 2014.
Sun, L., Zhao, J., and Hu, H.: Effect of moderate fire disturbance on soil physical and chemical properties of Betula platyphylla-Larix gmelinii mixed forest, Sci. Silvae Sinicae, 47, 103–110, 2011 (in Chinese).
Taş, N., Prestat, E., McFarland, J. W., Wickland, K. P., Knight, R., Berhe, A. A., Jorgenson, T., Waldrop, M. P., and Jansson, J. K.: Impact of fire on active layer and permafrost microbial communities and metagenomes in an upland Alaskan boreal forest, ISME J., 8, 1904–1919, 2014.
Turetsky, M. R., Abbott, B. W., Jones, M. C., Anthony, K. W., Olefeldt, D., Schuur, E. A. G., Koven, C., McGuire, A. D., Grosse, G., Kuhry, P., Hugelius, G., Lawrence, D. M., Gibson, C., and Sannel, A. B. K.: Permafrost collapse is accelerating carbon release, Nature, 569, 32–34, 2019.
Viereck, L. A., Werdin-Pfisterer, N. R., Adams, P. C., and Yoshikawa, K.: Effect of wildfire and fireline construction on the annual depth of thaw in a black spruce permafrost forest in interior alaska: a 36-year record of recovery, in: Proceedings of the Ninth International Conference on Permafrost, edited by: Kane, D. L. and Hinkel, K. M., Fairbanks, Alaska, USA, 29 June to 3 July, Vol. 2, 1845–1850, 2008.
Wang, H., Jin, H., Che, T., Li, X., Dai, L., Qi, Y., Huang, C., He, R., Zhang, J., Yang, R., Luo, D., and Jin, X.: Influences of snow cover on the thermal regimes of Xing'an permafrost in Northeast China in 1960s–2010s, Permafrost Periglac., 35, 188–201, https://doi.org/10.1002/ppp.2223, 2024.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., and Swetnam, T. W.: Warming and earlier spring increase Western U.S. forest wildfire activity, Science, 313, 940–943, https://doi.org/10.1126/science.1128834, 2006.
Xu, W., Elberling, B., and Ambus, P. L.: Long-term summer warming reduces post-fire carbon dioxide losses in an arctic heath tundra, Agr. Forest Meteorol., 344, 109823, https://doi.org/10.1016/j.agrformet.2023.109823, 2024.
Yoshikawa, K., Bolton, W. R., Romanovsky, V. E., Fukuda, M., and Hinzman, L. D.: Impacts of wildfire on the permafrost in the boreal forests of Interior Alaska, J. Geophys. Res., 108, 8148, https://doi.org/10.1029/2001JD000438, 2003.
Zhao, K., Zhang, W., Zhou, Y., and Yang, Y.: The influence and countermeasure of forest fire on environment in Da Xing 'anling Mountains, Beijing, Science Press, ISBN 9787544518161, 1994 (in Chinese).
Zhao, L., Zou, D., Hu, G., Wu, T., Du, E., Liu, G., Xiao, Y., Li, R., Pang, Q., Qiao, Y., Wu, X., Sun, Z., Xing, Z., Sheng, Y., Zhao, Y., Shi, J., Xie, C., Wang, L., Wang, C., and Cheng, G.: A synthesis dataset of permafrost thermal state for the Qinghai–Tibet (Xizang) Plateau, China, Earth Syst. Sci. Data, 13, 4207–4218, https://doi.org/10.5194/essd-13-4207-2021, 2021.
Zhou, Y., Liang, L., and Gu, Z.: Effects of forest fire on hydro-thermal regime of frozen ground, the northern part of the Da Hinggan Ling (in Chinese), J. Glaciol. Geocryol., 15, 17–26, 1993.
Short summary
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.
In Northeast China, the permafrost is more sensitive to climate warming and fire disturbances...
Altmetrics
Final-revised paper
Preprint