Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores

Jinzhi Ding, Fei Li, Guibiao Yang, Leiyi Chen, Beibei Zhang, Li Liu, Kai Fang, Shuqi Qin, Yongliang Chen, Yunfeng Peng, Chengjun Ji, Honglin He, Pete Smith, Yuanhe Yang

Global Change Biology · 2016

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Summary

This study provides a comprehensive reassessment of permafrost organic carbon stocks on the Tibetan Plateau by combining systematic field measurements from 342 deep cores and 177 shallow pits with support vector machine modelling. The work reveals a substantial carbon pool of 15.31 Pg C in the top 3 m, with 44% occurring in deep layers, and identifies significant spatial heterogeneity driven by landscape type. The findings highlight both the magnitude of this frozen carbon reservoir and the climate feedback risks associated with permafrost thawing in alpine regions.

UK applicability

This research has limited direct applicability to UK farming systems, as the Tibetan Plateau's alpine permafrost environment differs fundamentally from UK soil and climate conditions. However, the methodological approach combining systematic soil sampling with machine learning for spatial upscaling may inform UK soil carbon monitoring and sequestration assessment frameworks.

Key measures

Organic carbon density (OCD) per unit area; organic carbon pool size (Pg C); spatial distribution patterns; proportion of carbon in deep layers (100–300 cm); uncertainty ranges (interquartile ranges)

Outcomes reported

The study quantified permafrost organic carbon stocks to 3 m depth across the Tibetan Plateau using deep sediment cores and machine learning modelling. The median organic carbon pool size was estimated at 15.31 Pg C, with spatial variations documented and uncertainties quantified through Monte Carlo simulations.

Theme
Climate & resilience
Subject
Climate & greenhouse gas mitigation
Study type
Research
Study design
Field survey with spatial modelling
Source type
Peer-reviewed study
Status
Published
Geography
China
System type
Other
DOI
10.1111/gcb.13257
Catalogue ID
BFmor3g9dh-6bxcdk

Topic tags

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