Hotspots of soil organic carbon storage revealed by laboratory hyperspectral imaging

Eleanor Hobley,Markus Steffens,Sara L Bauke,Ingrid Kögel-Knabner

doi:10.1038/s41598-018-31776-w

Abstract

Subsoil organic carbon (OC) is generally lower in content and more heterogeneous than topsoil OC, rendering it difficult to detect significant differences in subsoil OC storage. We tested the application of laboratory hyperspectral imaging with a variety of machine learning approaches to predict OC distribution in undisturbed soil cores. Using a bias-corrected random forest we were able to reproduce the OC distribution in the soil cores with very good to excellent model goodness-of-fit, enabling us to map the spatial distribution of OC in the soil cores at very high resolution (~53 × 53 µm). Despite a large increase in variance and reduction in OC content with increasing depth, the high resolution of the images enabled statistically powerful analysis in spatial distribution of OC in the soil cores. In contrast to the relatively homogeneous distribution of OC in the plough horizon, the subsoil was characterized by distinct regions of OC enrichment and depletion, including biopores which contained ~2–10 times higher SOC contents than the soil matrix in close proximity. Laboratory hyperspectral imaging enables powerful, fine-scale investigations of the vertical distribution of soil OC as well as hotspots of OC storage in undisturbed samples, overcoming limitations of traditional soil sampling campaigns.

Highlights

Storing around 1500 Pg of organic carbon (OC) in the upper 1 m of soil[1], soils comprise the largest stock of the terrestrial C pools
OC storage decreases with increasing soil depth, and subsoils - i.e. the soil located below the ‘topsoil’ horizon have been frequently excluded from investigations into soil organic carbon (SOC) storage and dynamics
In this study we investigate the application of laboratory hyperspectral imaging to predict SOC contents down the soil profile on cores sampled down to 1 m from an agricultural site near Bonn, western Germany

Summary

Introduction

Storing around 1500 Pg of organic carbon (OC) in the upper 1 m of soil[1], soils comprise the largest stock of the terrestrial C pools. Subsoils are often characterised by pronounced heterogeneity[12,13,14], with distinct regions of enhanced or depleted SOC storage[15] Such hotspots are potentially important for SOC storage, but against the backdrop of generally low OC contents in deeper soil horizons, this greater variance of subsoil OC storage renders it more difficult to detect significant differences in SOC storage between sites of interest. Classical sampling methods for SOC investigations involve sampling discrete depth intervals or horizons and subsequent mixing of the samples This homogenisation is important to overcome the microscale variability of soil[3], enabling analysis of representative subsamples which reflect the SOC contents across field sites or landscapes. To overcome this low statistical power, a greater number of samples is required, which implies greater analysis cost and effort

Objectives

Methods

Results