Spatial distribution of pyrogenic carbon in Iberian topsoils estimated by chemometric analysis of infrared spectra

Jiménez-González, M.A., De la Rosa, J.M., Aksoy, E., Jeffery, S., Oliveira, B.R.F. and Verheijen, F.G.A. (2021) Spatial distribution of pyrogenic carbon in Iberian topsoils estimated by chemometric analysis of infrared spectra. Science of The Total Environment, 790.

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Abstract

Understanding the global carbon (C) cycle is critical to accurately model feedbacks between climate and soil. Thus, many climate change studies focused on soil organic carbon (SOC) stock changes. Pyrogenic carbon (PyC) is one of the most stable fractions of soil organic matter (SOM). Accurate maps based on measured PyC contents are required to facilitate future soil management decisions and soil-climate feedback modelling. However, consistent measurements that cover large areas are rare. Therefore, this study aimed to map the PyC content and stock of the Iberian Peninsula, which covers contrasting climatic zones and has long-term data on wildfire occurrence. A partial least square (PLS) regression using the mid-infrared spectra (1800–400 cm−1) was applied to a dataset composed of 2961 soil samples from the Iberian component of the LUCAS 2009 database. The values of PyC for LUCAS points were modelled to obtain a map of topsoil PyC by a random forest (RF) approach using 36 auxiliary variables. The results were validated through comparison with documented historical wildfire activity and anthropogenic energy production. A strong relationship was found between these sources and the distribution of PyC. Our study estimates that the accumulated PyC in Iberian Peninsula soils comprises between 3.09 and 20.39% of total organic carbon (TOC) in the topsoil. Forests have higher PyC contents than grasslands, followed by agricultural soils. The incidence of recurrent wildfires also has a notable influence on PyC contents. This study shows the potential of estimating PyC with a single, rapid, low cost, chemometric method using new or archived soil spectra, and has the ability to improve soil-climate feedback modelling. It also offers a possible tool for measuring, reporting and verifying soil C stocks, which is likely to be important moving forward if soils are used as sinks for C sequestration.

Item Type: Article
Keywords: Soil organic matter, Pyrogenic carbon, Black carbon, Carbon sequestration, Partial least squares regression, Random forest model
Divisions: Agriculture and Environment (from 1.08.20)
Depositing User: Mrs Rachael Harper
Date Deposited: 30 Jun 2021 12:53
Last Modified: 22 Jul 2021 11:30
URI: https://hau.repository.guildhe.ac.uk/id/eprint/17708

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