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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.
Carbon sequestration, Carbon Sequestration, Climate Change, Random forest model, black carbon, Partial least squares regression, Wildfires, Black carbon, Soil, Geología, Soil organic matter, random forest model, partial least squares regression, Agriculture, carbon sequestration, pyrogenic carbon, Carbon, Pyrogenic carbon
Carbon sequestration, Carbon Sequestration, Climate Change, Random forest model, black carbon, Partial least squares regression, Wildfires, Black carbon, Soil, Geología, Soil organic matter, random forest model, partial least squares regression, Agriculture, carbon sequestration, pyrogenic carbon, Carbon, Pyrogenic carbon
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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