Summary
This paper quantifies the substantial uncertainty arising from the choice of allometric equation when estimating soil carbon inputs from crop residues in agricultural systems. Using 28 years of data from a Swiss long-term cropping experiment with multiple fertiliser treatments, the authors demonstrate that equation selection alone drives considerable variation in modelled soil organic carbon stocks—ranging from simulated decreases to no change. The study identifies the evaluation and selection of allometric equations as a critical but underappreciated source of uncertainty in model-based soil carbon inventories for agriculture.
UK applicability
The findings highlight a methodological challenge applicable to UK soil carbon monitoring and greenhouse gas inventory protocols, where allometric equations may similarly introduce substantial uncertainty. However, the paper's calibration is specific to Swiss conditions, so UK practitioners would need to validate equation choice against local yield data and cropping systems.
Key measures
Annual soil carbon inputs (Mg C ha⁻¹ year⁻¹) from five allometric equations; simulated soil organic carbon stocks using the C-TOOL model; variation in estimates across crop types and yield levels
Outcomes reported
The study compared five allometric equations for estimating soil carbon inputs from crop residues and tested their effects on modelled soil organic carbon stocks using long-term experimental yield data. Estimated annual soil carbon inputs varied widely (2.1–5.3 Mg C ha⁻¹ year⁻¹) depending on the equation chosen, resulting in substantially different SOC stock projections.
Topic tags
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.