Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region
Permafrost soils store a large amount of nitrogen (N) which could be activated under the continuous climate warming. However, compared with carbon (C) stock, little is known about the size and spatial distribution of permafrost N stock. By combining measurements from 519 pedons with two machine lear...
Published in: | Science of The Total Environment |
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ftchiacadscibcas:oai:ir.ibcas.ac.cn:2S10CLM1/19654 2023-05-15T17:55:59+02:00 Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region Kou, Dan Ding, Jinzhi Li, Fei Wei, Ning Fang, Kai Yang, Guibiao Zhang, Beibei Liu, Li Qin, Shuqi Chen, Yongliang Xia, Jianyang Yang, Yuanhe 2019 http://ir.ibcas.ac.cn/handle/2S10CLM1/19654 https://doi.org/10.1016/j.scitotenv.2018.09.252 英语 eng ELSEVIER SCIENCE OF THE TOTAL ENVIRONMENT http://ir.ibcas.ac.cn/handle/2S10CLM1/19654 doi:10.1016/j.scitotenv.2018.09.252 cn.org.cspace.api.content.CopyrightPolicy@20b1f812 Climate warming Community Land Model Machine learning Nitrogen cycle Permafrost Tibetan Plateau Environmental Sciences ORGANIC-CARBON INORGANIC NITROGEN N2O EMISSIONS PATTERNS THAW CLIMATE STORAGE TUNDRA COVARIATION PLATEAU Environmental Sciences & Ecology Article 期刊论文 2019 ftchiacadscibcas https://doi.org/10.1016/j.scitotenv.2018.09.252 2022-06-12T18:13:52Z Permafrost soils store a large amount of nitrogen (N) which could be activated under the continuous climate warming. However, compared with carbon (C) stock, little is known about the size and spatial distribution of permafrost N stock. By combining measurements from 519 pedons with two machine learning models (supporting vector machine (SVM) and random forest (RF)), we estimated the size and spatial distribution of N stock across the Tibetan alpine permafrost region. We then compared these spatially-explicit N estimates with simulated N stocks from the Community Land Model (CLM). We found that N density (N amount per area) in the top three meters was 1.58 kg N m(-2) (interquartile range: 1.40-1.76) across the study area, constituting a total of 1802 Tg N (interquartile range: 1605-2008), decreasing from the southeast to the northwest of the plateau. N stored below 1 m accounted for 48% of the total N stock in the top three meters. CLM4.5 significantly underestimated the N stock on the Tibetan Plateau, primarily in areas with arid/semi-arid climate. The process of biological N fixation played a key role in the underestimation of N stock prediction. Overall, our study highlights that it is imperative to improve the simulation of N processes and permafrost N stocks in land models to better predict ecological consequences induced by rapid and widespread permafrost degradation. (C) 2018 Published by Elsevier B.V. Article in Journal/Newspaper permafrost Tundra Institute of Botany: IBCAS OpenIR (Chinese Academy Of Sciences) Science of The Total Environment 650 1795 1804 |
institution |
Open Polar |
collection |
Institute of Botany: IBCAS OpenIR (Chinese Academy Of Sciences) |
op_collection_id |
ftchiacadscibcas |
language |
English |
topic |
Climate warming Community Land Model Machine learning Nitrogen cycle Permafrost Tibetan Plateau Environmental Sciences ORGANIC-CARBON INORGANIC NITROGEN N2O EMISSIONS PATTERNS THAW CLIMATE STORAGE TUNDRA COVARIATION PLATEAU Environmental Sciences & Ecology |
spellingShingle |
Climate warming Community Land Model Machine learning Nitrogen cycle Permafrost Tibetan Plateau Environmental Sciences ORGANIC-CARBON INORGANIC NITROGEN N2O EMISSIONS PATTERNS THAW CLIMATE STORAGE TUNDRA COVARIATION PLATEAU Environmental Sciences & Ecology Kou, Dan Ding, Jinzhi Li, Fei Wei, Ning Fang, Kai Yang, Guibiao Zhang, Beibei Liu, Li Qin, Shuqi Chen, Yongliang Xia, Jianyang Yang, Yuanhe Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
topic_facet |
Climate warming Community Land Model Machine learning Nitrogen cycle Permafrost Tibetan Plateau Environmental Sciences ORGANIC-CARBON INORGANIC NITROGEN N2O EMISSIONS PATTERNS THAW CLIMATE STORAGE TUNDRA COVARIATION PLATEAU Environmental Sciences & Ecology |
description |
Permafrost soils store a large amount of nitrogen (N) which could be activated under the continuous climate warming. However, compared with carbon (C) stock, little is known about the size and spatial distribution of permafrost N stock. By combining measurements from 519 pedons with two machine learning models (supporting vector machine (SVM) and random forest (RF)), we estimated the size and spatial distribution of N stock across the Tibetan alpine permafrost region. We then compared these spatially-explicit N estimates with simulated N stocks from the Community Land Model (CLM). We found that N density (N amount per area) in the top three meters was 1.58 kg N m(-2) (interquartile range: 1.40-1.76) across the study area, constituting a total of 1802 Tg N (interquartile range: 1605-2008), decreasing from the southeast to the northwest of the plateau. N stored below 1 m accounted for 48% of the total N stock in the top three meters. CLM4.5 significantly underestimated the N stock on the Tibetan Plateau, primarily in areas with arid/semi-arid climate. The process of biological N fixation played a key role in the underestimation of N stock prediction. Overall, our study highlights that it is imperative to improve the simulation of N processes and permafrost N stocks in land models to better predict ecological consequences induced by rapid and widespread permafrost degradation. (C) 2018 Published by Elsevier B.V. |
format |
Article in Journal/Newspaper |
author |
Kou, Dan Ding, Jinzhi Li, Fei Wei, Ning Fang, Kai Yang, Guibiao Zhang, Beibei Liu, Li Qin, Shuqi Chen, Yongliang Xia, Jianyang Yang, Yuanhe |
author_facet |
Kou, Dan Ding, Jinzhi Li, Fei Wei, Ning Fang, Kai Yang, Guibiao Zhang, Beibei Liu, Li Qin, Shuqi Chen, Yongliang Xia, Jianyang Yang, Yuanhe |
author_sort |
Kou, Dan |
title |
Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
title_short |
Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
title_full |
Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
title_fullStr |
Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
title_full_unstemmed |
Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region |
title_sort |
spatially-explicit estimate of soil nitrogen stock and its implication for land model across tibetan alpine permafrost region |
publisher |
ELSEVIER |
publishDate |
2019 |
url |
http://ir.ibcas.ac.cn/handle/2S10CLM1/19654 https://doi.org/10.1016/j.scitotenv.2018.09.252 |
genre |
permafrost Tundra |
genre_facet |
permafrost Tundra |
op_relation |
SCIENCE OF THE TOTAL ENVIRONMENT http://ir.ibcas.ac.cn/handle/2S10CLM1/19654 doi:10.1016/j.scitotenv.2018.09.252 |
op_rights |
cn.org.cspace.api.content.CopyrightPolicy@20b1f812 |
op_doi |
https://doi.org/10.1016/j.scitotenv.2018.09.252 |
container_title |
Science of The Total Environment |
container_volume |
650 |
container_start_page |
1795 |
op_container_end_page |
1804 |
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1766164027074936832 |