Toward improved model structures for analyzing priming: potential pitfalls of using bulk turnover time.

Area of Science:

• Soil Science
• Ecology
• Climate Change Research

Background:

• Elevated atmospheric CO2 increases plant carbon input to soils.
• This can accelerate native soil organic matter decomposition, a phenomenon termed priming.
• Understanding priming is crucial for predicting carbon-climate feedbacks.

Purpose of the Study:

• To investigate the limitations of simple models in quantifying the priming effect under elevated CO2.
• To determine the adequacy of one-pool and two-pool models for representing soil carbon dynamics.
• To identify necessary methods for accurately assessing the fate of new plant inputs in soil.

Main Methods:

• Utilized a multi-pool soil carbon model to simulate soil responses to elevated CO2.
• Compared model outputs with calculations from a one-pool approach using bulk turnover time, respiration, and carbon stocks.
• Evaluated the necessity of isotopic tracers and microbial measurements.

Main Results:

• A multi-pool model can replicate bulk turnover time changes at elevated CO2 without invoking a priming effect.
• One-pool models alone are insufficient for quantifying the true priming effect.
• Even two-pool models may be inadequate depending on soil organic carbon distribution and turnover times.

Conclusions:

• The priming effect is complex and cannot be reliably quantified with simple, one-pool soil carbon models.
• Accurate assessment requires advanced modeling approaches (multi-pool) and complementary techniques like isotopic tracing.
• Standard measurements of carbon stocks and CO2 fluxes are insufficient to fully understand the fate of new plant carbon inputs.