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Título

Effect of climatic variability in the soil organic matter composition studied by analytical pyrolysis

AutorJiménez-González, Marco A. CSIC ORCID; Rosa Arranz, José M. de la; González-Pérez, José Antonio CSIC ORCID ; Álvarez, Ana María; Carral, Pilar; Almendros Martín, Gonzalo CSIC ORCID
Fecha de publicaciónoct-2018
EditorSociedad Española de Cromatografía y Técnicas Afines
CitaciónBook of abstracts XVIII Scientific Meeting of the Spanish Society of Chromatography and Related Tecniques – SECYTA 2018: 103-104 (2018)
ResumenIn present days there is a growing concern about the progress of desertification in different areas of the world. The unsuitable management of the soils and the change of land use may increase the desertification risk. On the other hand, desertification is typically associated with the decrease of soil organic matter (SOM) levels with the consequent loss of fertility in the soil. Presumably, all these aspects are reflected in the molecular composition of SOM. Previous studies have evidenced that a correlation exists between the carbon sequestration efficiency and the relative abundance of specific SOM constituents, e.g., alkane homologous series [1] or lignin-derived methoxyphenols [2]. This study aims to identify molecular descriptors of the SOM composition, which are responsive for the impact of climate, quantified with bioclimatic indices defining a continuous gradient between wet and dry areas. A total of 33 soil samples were collected from different areas of Spain. The studied soils presented a large variability in their chemical and physical properties, and were developed under different geological substrate and vegetation type. The sampling was carried out in the topsoil (0–10 cm) where the SOM content is higher. In order to assess desertification levels we used the De Martonne aridity index. This index was calculated from the annual average rainfall and annual average temperature for each soil sampling point. The SOM was analyzed by pyrolysis - gas chromatography mass spectrometry (Py-GC/MS) of whole soil samples. A total of 193 pyrolysis compounds were identified, and used as predictor variables in Partial Least Squares (PLS) regression models forecasting the De Martonne aridity index. The results showed that a significant prediction of this index (R = 0.869) exclusively using the information provided by Py-GC/MS analysis of the corresponding soils is possible. A graphical-statistical method based in the classical van Krevelen diagram was used for displaying the pyrolysis results [3], representing difference values between the proportions of the 193 pyrolysis products, calculated between average pyrograms for soils in the uppermost quartile of the De Martonne index, and the average of those in the lower quartile. These values are shown as a scatterdiagram where the coordinates in the plane of the individual molecules correspond to their H/C and O/C atomic ratios, calculated from their empirical formulas. The difference values between relative abundances were represented as a density map where the green colour indicates compounds predominant in the SOM of soils formed in sites with high De Martonne index, and the red colour indicate compounds predominant in soils with low index (i.e., comparatively dry ecosystems). The Student’s t (p > 90%) was also used to evaluate the significant differences between the proportions of compounds, and was represented as a superimposed contour diagram in the Figure
[1] M.A. Jiménez-González, A.M. Álvarez, Z. Hernández, G. Almendros, Biology and Fertility of Soils 54 (2018) 617–629. [2] M.A. Jiménez-González, A.M. Álvarez, P. Carral, F.J. González-Vila, G. Almendros J. Chromatography A 1508 (2017) 130–137. [3] D.W. van Krevelen, Fuel 29 (1950) 269–284.
DescripciónPóster (P-EA-10) presentado en la XVIII Reunión de la Sociedad Española de Cromatografía y Técnicas Afines (SECyTA 2018), Granada, del 2 al 4 de Octubre de 2018.
URIhttp://hdl.handle.net/10261/174382
ISBN978-84-17293-61-1
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