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Multivariate geostatistical analysis of compound-specific isotope ratios obtained by direct pyrolysis of a xerophytic species from a volcanic valley in Tenerife Island.

AuthorsGonzález-Pérez, José Antonio CSIC ORCID ; Jiménez Morillo, N. T. CSIC ORCID; González-Vila, Francisco Javier CSIC ORCID ; Almendros Martín, Gonzalo CSIC ORCID
Issue Date3-Oct-2017
PublisherSociedad Española de Cromatografía y Técnicas Afines
Citation15 Jornadas de Análisis Instrumental 2017 3-5 Oct. (2017) Barcelona (Spain)
AbstractCompound-specific isotope analysis (CSIA) and particularly of plant lipids due to its high chemical stability and sensibility to climate variations, is used for tracing environmental and geographic variables [1]. The technique requires sample pre-treatments (e.g. extraction, derivatization, purification). Analytical pyrolysis (Py-GC) when combined with CSIA (Py-CSIA) allows the simultaneous, time-saving, analysis of different chemical families minimizing sample manipulation [2]. Here, Py-CSIA is used as tool for tracing the influence of geographic variables in the isotope composition of plant biomass, and to identify the extent to which the isotopic ratios of different compound families correlate with these variables. Specimens of Aeonium canariense Webb & Berthel (Crassulaceae) [3] were collected in δBarranco de Ruízδ (Tenerife, Spain), a protected site of scientific interest and highly-controlled anthropogenic perturbation. The sampling was done at different altitude (m a.s.l.), longitude and oceanic influence (latitude). Bulk isotope compositions (δ13C, δ15N, δ18O and δD) were obtained by EA-IRMS. Also compound-specific isotope ratios were recorded for C and H using Py-CSIA and the results grouped into 4 main biogenic families; fatty acids (FA), n-alkanes (ALK), carbohydrates (S) and aromatic compounds (A), i.e., δ13CFA, δ13CALK, δ13CS, δ13CA, δ13CFA, δDALK, δDS and δDA. Linear correlation showed significant models between oceanic influence and δ13C and δD values (bulk and specific compounds). Multiple linear regression (MLR) and partial least squares regression (PLS) indicated that δDALK values can be explained by geographic variables mainly longitude and altitude (m a.s.l.). This was confirmed by multidimensional scaling (MDS), that indicated that δD and δ13CALK were the ratios most responsive to spatial information. Discriminant analysis confirmed that the pattern of compound-specific isotope ratios (12 variables) includes sufficient information to predict sample origin amongst discrete areas (100% correctly classified) either in terms of the progressive marine influence or in terms of the slope in the valley. Concerning δ15N, significant correlations with altitude (-) and latitude (+) were found only in samples collected over 460 m a.s.l., which could be explained as the effect of a natural phenomenon caused by the trade winds (i.e., sea of clouds). References [1] SJ. Feakins, LP. Bentley, N. Salinas, et al. Geochimica et Cosmochimica Acta 182 (2016) 155-172. [2] NT. Jiménez-Morillo, FJ. González-Vila, G. Almendros, JM. de la Rosa, JA. González-Pérez. Geophysical Research Abstracts 17 (2015) 14123. [3] PB. Webb, S. Berthelot. Histoire Naturelle des Îles Canaries (1840) Béthune, Paris 28-35.
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