Meta-modeling soil organic carbon sequestration potential and its application at regional scale

Area of Science:

• Agricultural Science
• Environmental Science
• Soil Science

Background:

• Upscaling process-based soil-plant models for regional soil organic carbon (SOC) assessment is hindered by limited spatial data, especially soil properties.
• Meta-modeling offers a solution by simplifying complex models and reducing data demands for large-scale applications.

Purpose of the Study:

• To develop and validate a meta-model for predicting SOC change and sequestration potential across Australia's cereal-growing regions.
• To assess the influence of climate, soil properties, and management on SOC dynamics.
• To quantify the uncertainty in SOC sequestration estimates due to soil variability.

Main Methods:

• Utilized the Agricultural Production Systems sIMulator (APSIM) to simulate SOC changes at 613 reference sites under continuous wheat.
• Developed a meta-model linking APSIM-simulated SOC change to drivers: recalcitrant SOC, plant available water capacity, pH, solar radiation, temperature, and rainfall.
• Applied the meta-model using high-resolution soil texture and climate data across Australia's cereal-growing regions.

Main Results:

• The meta-model explained 74% of the variation in final SOC content simulated by APSIM.
• Regional analysis revealed higher SOC stocks in cooler, wetter areas.
• Mean SOC sequestration potential was estimated at 8.17 Mg/ha, with potential SOC stocks ranging from 21.14 to 152.71 Mg/ha.

Conclusions:

• Soils in Australia's cereal-growing regions under continuous wheat act as a sink for atmospheric carbon dioxide.
• The meta-model provides a scalable approach to assess regional SOC sequestration potential and associated uncertainties.
• Soil property variations introduce significant uncertainty (12%–117%) in SOC estimates, particularly in warmer, wetter regions.