Soil organic carbon sequestration potential explained by mineralogical and microbiological activity using spectral...

Area of Science:

• Soil Science
• Microbiology
• Geochemistry
• Remote Sensing

Background:

• Soil carbon sequestration is vital for reducing atmospheric CO2, but its capacity is influenced by soil mineralogy and microbial interactions.
• Soil organic matter (SOM) and clay minerals possess functional groups that interact with specific light wavelengths (Vis-NIR-SWIR, Mid-IR), influencing microbial activity.
• Understanding these spectral-mineral-microbial relationships is key to assessing soil's carbon sequestration potential.

Purpose of the Study:

• To determine the relationship between mineralogical and organic compounds and their role in carbon sequestration in Brazilian soils using spectral data.
• To map microbiological activity and quantify soil properties related to carbon sequestration using spectral transfer functions and digital soil mapping.

Main Methods:

• Utilized spectral analysis in Vis-NIR-SWIR and Mid-IR ranges to identify interactions between soil minerals, organic matter, and microbial communities.
• Applied spectral transfer functions and digital soil mapping to quantify microbiological activity (R² 0.77-0.85).
• Employed recursive feature elimination (RFE) to identify specific spectral bands correlating with enzymatic activity, microbial biomass carbon (MBC), particulate organic matter (POM), and mineral-associated organic matter (MAOM) (correlations 0.64-0.98).

Main Results:

• Successfully mapped microbiological activity and quantified key soil carbon components using spectral data.
• Developed prediction models for carbon sequestration potential integrating microbiological and mineralogical variables.
• Identified soil properties like kaolinite, hematite, goethite, gibbsite, fungal abundance, and POM as significant predictors of carbon sequestration.

Conclusions:

• Spectral analysis is a powerful tool for assessing soil carbon sequestration potential by linking mineralogy and microbial activity.
• Fungal abundance emerged as a primary microbiological indicator, while enzymatic activity was less significant for predicting carbon sequestration.
• Integrating spectral data with land use history can identify areas critical for carbon sequestration, offering strategies for climate change mitigation.