Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau
The Qinghai-Tibetan Plateau (TP) accumulated a large amount of organic carbon, while its size and response to environmental factors for the whole area remain uncertain. Here, we synthesized a dataset to date with the largest data volume and broadest geographic coverage over the TP, composing of 7196...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2022-01-01
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| Series: | Environmental Research Letters |
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| Online Access: | https://doi.org/10.1088/1748-9326/ac78f5 |
| _version_ | 1827869838972813312 |
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| author | Daorui Han Zhongmin Hu Xuhui Wang Tao Wang Anping Chen Qihao Weng Minqi Liang Xiang Zeng Ruochen Cao Kai Di Dengnan Luo Guangru Zhang Yuanhe Yang Honglin He Jiangwen Fan Guirui Yu |
| author_facet | Daorui Han Zhongmin Hu Xuhui Wang Tao Wang Anping Chen Qihao Weng Minqi Liang Xiang Zeng Ruochen Cao Kai Di Dengnan Luo Guangru Zhang Yuanhe Yang Honglin He Jiangwen Fan Guirui Yu |
| author_sort | Daorui Han |
| collection | DOAJ |
| description | The Qinghai-Tibetan Plateau (TP) accumulated a large amount of organic carbon, while its size and response to environmental factors for the whole area remain uncertain. Here, we synthesized a dataset to date with the largest data volume and broadest geographic coverage over the TP, composing of 7196 observations from multiple field campaigns since the 1980s, and provided a comprehensive assessment of the size and spatial distribution of carbon pools for both plant and soils on the TP using machine learning algorithms. The estimated soil organic carbon (SOC) storage to 1 m depth was ${\text{32}}{\text{.01}}_{{\text{19}}{\text{.69}}}^{{\text{47}}{\text{.9}}}$ Pg ( ${\text{11}}{\text{.72}}_{{\text{7}}{\text{.2}}}^{{\text{17}}{\text{.53}}}$ kg m ^−2 on average), accounting for approximately ${\text{37}}{\text{.2}}_{{\text{22}}{\text{.9}}}^{{\text{55}}{\text{.6}}}$ % of China’s SOC stock on its <30% land area. There was ${\text{15}}{\text{.52}}_{{\text{9}}{\text{.91}}}^{{\text{23}}{\text{.52}}}{ }$ Pg C stored in grassland soils (1 m), which played as the largest C pool on the TP, followed by shrubland ( ${\text{7}}{\text{.52}}_{{\text{4}}{\text{.8}}}^{11.6}$ Pg) and forest ( ${\text{3}}{\text{.72}}_{{\text{2}}{\text{.5}}}^{{\text{5}}{\text{.36}}}$ Pg). The estimated plant C pool was ${\text{2}}{\text{.4}}_{{\text{0}}{\text{.95}}}^{{\text{5}}{\text{.16}}}$ Pg ( ${\text{1}}{\text{.03}}_{{\text{0}}{\text{.2}}}^{{\text{2}}{\text{.7}}}$ Pg in aboveground biomass (AGB) and ${\text{1}}{\text{.37}}_{{\text{0}}{\text{.75}}}^{{\text{2}}{\text{.45}}}$ Pg in belowground biomass). Soil and biomass C density presented a similar spatial pattern, which generally decreased from the east and southeast parts to the central and western parts. We found both vegetation and soil C (1 m depth) were primarily regulated by climatic variables and C input across the entire TP. However, main driving factors of the C stocks varied among vegetation types and depth intervals. Though AGB played as an important role in SOC variation for both topsoil (0–30 cm) and subsoil (30–100 cm), the strength of the correlation weakened with depth and was gradually attenuated from grassland to shrubland, and forest. The outcomes of this study provided an updated geospatial estimate of SOC stocks for the entire TP and their relationships with environmental factors, which are essential to carbon model benchmarking and better understanding the feedbacks of C stocks to global change. |
| first_indexed | 2024-03-12T15:50:45Z |
| format | Article |
| id | doaj.art-43a92b289efc49f7ae7470e2296003ce |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:50:45Z |
| publishDate | 2022-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-43a92b289efc49f7ae7470e2296003ce2023-08-09T15:13:16ZengIOP PublishingEnvironmental Research Letters1748-93262022-01-0117707401610.1088/1748-9326/ac78f5Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan PlateauDaorui Han0Zhongmin Hu1Xuhui Wang2Tao Wang3Anping Chen4Qihao Weng5Minqi Liang6Xiang Zeng7Ruochen Cao8Kai Di9Dengnan Luo10Guangru Zhang11Yuanhe Yang12https://orcid.org/0000-0002-5399-4606Honglin He13Jiangwen Fan14Guirui Yu15School of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of China; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, Hainan University , Haikou 570228, People’s Republic of ChinaSino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University , Beijing 100091, People’s Republic of ChinaKey Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaDepartment of Biology, Colorado State University , Fort Collins, CO 80523, United States of AmericaCenter for Urban and Environmental Change, Department of Earth and Environmental Systems, Indiana State University , Terre Haute, IN 47809, United States of AmericaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaSchool of Geography, South China Normal University , Guangzhou 510631, People’s Republic of ChinaState Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences , Beijing 100093, People’s Republic of ChinaSynthesis Research Center of China’s Ecosystem Research Network and Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaSynthesis Research Center of China’s Ecosystem Research Network and Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaSynthesis Research Center of China’s Ecosystem Research Network and Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaThe Qinghai-Tibetan Plateau (TP) accumulated a large amount of organic carbon, while its size and response to environmental factors for the whole area remain uncertain. Here, we synthesized a dataset to date with the largest data volume and broadest geographic coverage over the TP, composing of 7196 observations from multiple field campaigns since the 1980s, and provided a comprehensive assessment of the size and spatial distribution of carbon pools for both plant and soils on the TP using machine learning algorithms. The estimated soil organic carbon (SOC) storage to 1 m depth was ${\text{32}}{\text{.01}}_{{\text{19}}{\text{.69}}}^{{\text{47}}{\text{.9}}}$ Pg ( ${\text{11}}{\text{.72}}_{{\text{7}}{\text{.2}}}^{{\text{17}}{\text{.53}}}$ kg m ^−2 on average), accounting for approximately ${\text{37}}{\text{.2}}_{{\text{22}}{\text{.9}}}^{{\text{55}}{\text{.6}}}$ % of China’s SOC stock on its <30% land area. There was ${\text{15}}{\text{.52}}_{{\text{9}}{\text{.91}}}^{{\text{23}}{\text{.52}}}{ }$ Pg C stored in grassland soils (1 m), which played as the largest C pool on the TP, followed by shrubland ( ${\text{7}}{\text{.52}}_{{\text{4}}{\text{.8}}}^{11.6}$ Pg) and forest ( ${\text{3}}{\text{.72}}_{{\text{2}}{\text{.5}}}^{{\text{5}}{\text{.36}}}$ Pg). The estimated plant C pool was ${\text{2}}{\text{.4}}_{{\text{0}}{\text{.95}}}^{{\text{5}}{\text{.16}}}$ Pg ( ${\text{1}}{\text{.03}}_{{\text{0}}{\text{.2}}}^{{\text{2}}{\text{.7}}}$ Pg in aboveground biomass (AGB) and ${\text{1}}{\text{.37}}_{{\text{0}}{\text{.75}}}^{{\text{2}}{\text{.45}}}$ Pg in belowground biomass). Soil and biomass C density presented a similar spatial pattern, which generally decreased from the east and southeast parts to the central and western parts. We found both vegetation and soil C (1 m depth) were primarily regulated by climatic variables and C input across the entire TP. However, main driving factors of the C stocks varied among vegetation types and depth intervals. Though AGB played as an important role in SOC variation for both topsoil (0–30 cm) and subsoil (30–100 cm), the strength of the correlation weakened with depth and was gradually attenuated from grassland to shrubland, and forest. The outcomes of this study provided an updated geospatial estimate of SOC stocks for the entire TP and their relationships with environmental factors, which are essential to carbon model benchmarking and better understanding the feedbacks of C stocks to global change.https://doi.org/10.1088/1748-9326/ac78f5Qinghai-Tibetan PlateauSOC mappingmachine learning algorithmsdriving factorsuncertainties |
| spellingShingle | Daorui Han Zhongmin Hu Xuhui Wang Tao Wang Anping Chen Qihao Weng Minqi Liang Xiang Zeng Ruochen Cao Kai Di Dengnan Luo Guangru Zhang Yuanhe Yang Honglin He Jiangwen Fan Guirui Yu Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau Environmental Research Letters Qinghai-Tibetan Plateau SOC mapping machine learning algorithms driving factors uncertainties |
| title | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau |
| title_full | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau |
| title_fullStr | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau |
| title_full_unstemmed | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau |
| title_short | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau |
| title_sort | shift in controlling factors of carbon stocks across biomes on the qinghai tibetan plateau |
| topic | Qinghai-Tibetan Plateau SOC mapping machine learning algorithms driving factors uncertainties |
| url | https://doi.org/10.1088/1748-9326/ac78f5 |
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