Climate indices as predictors of global soil organic carbon stocks

Publication date

2024-09

Authors

Zhang, Qin
Yi, Chuixiang
Wohlfahrt, Georg
Chen, Deliang
Rietkerk, MaxORCID 0000-0002-2698-3848ISNI 0000000047385244
Tian, Zhenkun
Wu, Mousong
Kutter, Eric
Han, Jianxu
Hendrey, George

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

taverne

Abstract

Global soils store more carbon than the atmosphere and terrestrial vegetation combined, with a significant proportion located in colder regions. Earth system models incorporating climate-carbon feedback suggest that a warming climate can potentially destabilize soil carbon storage, leading to carbon release into the atmosphere. However, existing models are based on limited measurements of soil organic carbon (SOC) loss and a comprehensive global-scale climate indices that effectively characterizes climate-SOC relationships is currently lacking. In this study, we present a synthetic analysis that evaluates the effectiveness of different climate indices in estimating SOC stocks using a global compilation of SOC data and the Boltzmann Sigmoidal Model (BSM). Our findings reveal that a climate index, defined as (Formula presented.), where T and D are mean century temperature (MCT) and dryness respectively, serves as the most reliable predictor for SOC stocks. Furthermore, we observed temperature tipping points for SOC, ranging from −4.5 to −3°C for different soil layers. As the temperature transitions from being below to above the tipping point, the SOC shifts from a stable, high state to a rapid decline. An analysis of the projected temperatures for SOC under various future greenhouse gas emissions scenarios showed a northward shift in the northern hemisphere, potentially opening up vast areas of arctic territory to increased SOC loss from the soils, with corresponding emissions of the stored carbon into the atmosphere. Our findings open up new avenues for research on and management strategies for climate-related SOC dynamics.

Keywords

Boltzmann Sigmoidal Model, carbon-temperature patterns, climate indices, future projections, Soil organic carbon, Taverne, Geography, Planning and Development, Geology, SDG 13 - Climate Action, SDG 15 - Life on Land

Citation

Zhang, Q, Yi, C, Wohlfahrt, G, Chen, D, Rietkerk, M, Tian, Z, Wu, M, Kutter, E, Han, J, Hendrey, G & Xu, S 2024, 'Climate indices as predictors of global soil organic carbon stocks', Geografiska Annaler, Series A: Physical Geography, vol. 105, no. 2-3, pp. 179-196. https://doi.org/10.1080/04353676.2024.2335000