Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107523
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Land Surveying and Geo-Informatics | - |
| dc.creator | Han, D | - |
| dc.creator | Hu, Z | - |
| dc.creator | Wang, X | - |
| dc.creator | Wang, T | - |
| dc.creator | Chen, A | - |
| dc.creator | Weng, Q | - |
| dc.creator | Liang, M | - |
| dc.creator | Zeng, X | - |
| dc.creator | Cao, R | - |
| dc.creator | Di, K | - |
| dc.creator | Luo, D | - |
| dc.creator | Zhang, G | - |
| dc.creator | Yang, Y | - |
| dc.creator | He, H | - |
| dc.creator | Fan, J | - |
| dc.creator | Yu, G | - |
| dc.date.accessioned | 2024-07-02T01:36:13Z | - |
| dc.date.available | 2024-07-02T01:36:13Z | - |
| dc.identifier.issn | 1748-9318 | - |
| dc.identifier.uri | http://hdl.handle.net/10397/107523 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Physics Publishing Ltd. | en_US |
| dc.rights | © 2022 The Author(s). Published by IOP Publishing Ltd | en_US |
| dc.rights | Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence (https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. | en_US |
| dc.rights | The following publication Han, D., Hu, Z., Wang, X., Wang, T., Chen, A., Weng, Q., Liang, M., Zeng, X., Cao, R., Di, K., Luo, D., Zhang, G., Yang, Y., He, H., Fan, J., & Yu, G. (2022). Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau. Environmental Research Letters, 17(7), 074016 is available at https://doi.org/10.1088/1748-9326/ac78f5. | en_US |
| dc.subject | Driving factors | en_US |
| dc.subject | Machine learning algorithms | en_US |
| dc.subject | Qinghai-Tibetan Plateau | en_US |
| dc.subject | SOC mapping | en_US |
| dc.subject | Uncertainties | en_US |
| dc.title | Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 17 | - |
| dc.identifier.issue | 7 | - |
| dc.identifier.doi | 10.1088/1748-9326/ac78f5 | - |
| dcterms.abstract | 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 32.0119.6947.9 Pg ( 11.727.217.53 kg m-2 on average), accounting for approximately 37.222.955.6 % of China's SOC stock on its <30% land area. There was 15.529.9123.52 Pg C stored in grassland soils (1 m), which played as the largest C pool on the TP, followed by shrubland ( 7.524.811.6 Pg) and forest ( 3.722.55.36 Pg). The estimated plant C pool was 2.40.955.16 Pg ( 1.030.22.7 Pg in aboveground biomass (AGB) and 1.370.752.45 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. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Environmental research letters, July 2022, v. 17, no. 7, 074016 | - |
| dcterms.isPartOf | Environmental research letters | - |
| dcterms.issued | 2022-07 | - |
| dc.identifier.eissn | 1748-9326 | - |
| dc.identifier.artn | 074016 | - |
| dc.description.validate | 202406 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | a2914a [Non PolyU] | en_US |
| dc.identifier.SubFormID | 48726 | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The Second Tibetan Plateau Scientific Expedition and Research Program (Grant No. 2019QZKK0405); China Postdoctoral Science Foundation (Grant No. 2020M672684); Key R&D Program of Hainan (Grant No. ZDYF2022SHFZ042); Start-up fund of Hainan University (Grant No. KYQD(ZR)21096) | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Han_2022_Environ._Res._Lett._17_074016.pdf | 3.54 MB | Adobe PDF | View/Open |
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