From Top to Bottom: Using Pedotransfer Functions to Predict Subsoil Organic Carbon and Nitrogen Contents

Stockholm

2024

1326

Bandaufführung

40005311

Most monitoring systems on soil organic carbon (C) and total nitrogen (N) sequestration are restricted to the top soil, primarily caused by ressource restrictions. Accurate estimations of C and N contents at subsurface depths are challenging due to limited data availability and the high cost and time required for direct measurements. Therefore, pedotransfer functions (PTFs) have gained prominence in soil science as a reliable tool for estimating soil properties, including the prediction of C and N concentration and stocks at various locations and depths, as a cost-effective and practical solution. C and N concentrations and stocks play a crucial role in understanding soil health and its potential as a C and N sink. This abstract focuses on the development and application of PTFs to predict C and N concentrations and stocks in the depth range of 50 to 80 cm based on topsoil C and N analyses and soil assessments from more than 800 soil profiles in Austria. This study employs a dataset encompassing soil samples of forests from diverse geographic regions in Austria, with measured topsoil organic C and N, and corresponding C and N content data obtained from 50 to 80 cm depths. Various soil properties from soil assessments, such as soil texture, bulk density or root density, geological and topographic indices, tree species composition and climate data are considered as potential predictors in the PTF development. The PTFs were developed using statistical modeling techniques, including multiple linear regression, general additive models and machine learning algorithms, such as random forests or artificial neural networks. Models were assessed by cross-validation to ensure robustness and generalizability and associated quality measures such as root mean square error and coefficient of determination. The resulting PTFs exhibit significant predictive capabilities, enabling accurate estimations of C and N concentrations and stocks at 50 to 80 cm depths based on C and N measurements at the topsoil. Therefore, they can help in identifying forest areas with high C and N stocks at 50 to 80 cm depths, estimating C and N sequestration potentials and optimizing forestry practices to enhance soil fertility, C and N storage.