Global Soil Carbon Mineralization Data with Organic Acid Effects

A global dataset integrates meta-analysis and 13C-tracer experiments to quantify organic acid-induced abiotic destabilization of soil carbon. It contains model inputs and results showing this pathway contributes 9% ± 1% of global soil organic carbon mineralization. The dataset was created by Zhenhui Jiang and published on figshare in April 2026.

Use Cases

• Calibrate process-based models like Millennial using the quantified AD_OA (organic acid-induced abiotic destabilization) contribution of 9% ± 1%.
• Analyze the relative impact of abiotic destabilization versus direct warming effects on mineral-associated organic carbon (MAOC) mineralization, which increased by 81%–110%.
• Validate hypotheses on root exudation effects by comparing organic acid data against carbohydrate stimulation data for microbial activity.
• Incorporate the global meta-analysis results on soil organic carbon (SOC) loss under warming into regional climate projections.

Strengths

• Data is derived from a global meta-analysis, providing a broad spatial scope.
• Quantifies a specific, underrecognized pathway (AD_OA) with a precise mean contribution of 9% ± 1% standard deviation.
• Integrates multiple methodologies: meta-analysis, 13C-tracer experiments, and process-based modeling.

Limitations

• Small file size (584.3 KB) indicates limited raw observational data, likely consisting of summary statistics and model parameters.
• Specific row counts, column names, and granular sample data are unavailable, limiting direct analysis.
• The dataset's future publication date (2026-04-06) suggests it is a projection or supplementary material for a forthcoming study.

Provenance

Source

Zhenhui Jiang via figshare.

Collection Method

Integration of global meta-analysis, 13C-tracer experiments, and process-based modeling.

Freshness

Last updated April 2026.

Geography

Global scope from meta-analysis.