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

Modeling of soil organic carbon stock and sequestration potential in grassland and cropland in Qinghai-Tibet Plateau: prediction and carbon management strategies based on different climate scenarios

Haoran Gao, Jian Gong, Jiakang Liu, Xin Wen, Liping Huang, Martin Maier

CATENA · 2025

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Summary

This spatially explicit modelling study estimates soil organic carbon stocks and sequestration potential across grassland and cropland systems in the Qinghai-Tibet Plateau under current and projected future climate scenarios. The authors evaluate carbon management strategies to identify approaches for enhancing soil carbon sequestration capacity in this climatically sensitive region. The work is intended to support evidence-based climate mitigation policy and soil carbon management in an area of considerable ecological and hydrological significance.

UK applicability

Direct applicability to UK systems is limited, given the Qinghai-Tibet Plateau's distinct high-altitude climate, permafrost dynamics, and grassland-dominated land use. However, the modelling framework and approach to projecting soil carbon trajectories under climate scenarios may inform UK climate mitigation strategy and inform comparative assessment of carbon sequestration potential across contrasting agroecological zones.

Key measures

Soil organic carbon stocks (tonnes per hectare or similar); sequestration potential under current and future climate scenarios; effectiveness of carbon management strategies

Outcomes reported

The study modelled soil organic carbon stocks and sequestration potential across grassland and cropland systems in the Qinghai-Tibet Plateau under current and projected future climate scenarios. Carbon management strategies were evaluated to identify approaches for enhancing soil carbon sequestration capacity in this climatically sensitive region.

Theme
Climate & resilience
Subject
Soil carbon & organic matter
Study type
Research
Study design
Spatially explicit modelling study
Source type
Peer-reviewed study
Status
Published
Geography
China
System type
Mixed farming
DOI
10.1016/j.catena.2025.109545
Catalogue ID
SNmov0g4z1-6qtypl

Topic tags

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