Extraction of climatic signals from fossil organic compounds in marine sediments up to 11.7Ma old (IODP-U1318)

This study focuses on the extraction of climate signals and processes using a combined approach which includes the analysis of a high number of lipid molecules in marine sediments, and the chemometric analysis of the acquired data. Neutral and acidic fractions of marine sediments from site IODP-U1318 (south-west of the UK, Porcupine Seabight) were quantified by GC-MS. The alkenone unsaturation index, Uk'37, was estimated from the composition of C37 alkenones and it was then used for the estimation of sea surface temperatures (SST) for reference. Principal component analysis (PCA), explained 77.45% of the total data variance, and differentiated neutral fraction GC-MS total ion current (TIC) profiles according to SST values of the different sediment sections. GC-MS TIC chromatograms were correlated to sea surface temperatures (SST) by partial least squares regression (PLSR). The compounds more robustly in line with SST values at each sediment section explained 93% of the SST variance and they were identified using the variable importance in projection (VIP) scores method. The proposed approach enables an objective identification of organic compounds sensitive to SST variability throughout complete chromatographic profiles. As a result of this multivariate unbiased approach, lipid composition of sediments was differentiated between compounds of marine (long chain n-alkanes, long chain n-alkan-1-ols) and terrestrial (short chain n-alkan1-ols, alkenols, cholesterol, squalene) origin, whose concentrations were directly and inversely correlated to SST, respectively. © 2015 Elsevier B.V.

Bibliographic Details

Main Authors:	Farrés, Mireia, Martrat, Belen, De Mol, Ben, Grimalt, Joan O., Tauler, Romà
Other Authors:	Ministerio de Economía y Competitividad (España)
Format:	artículo biblioteca
Language:	English
Published:	Elsevier 2015-06-16
Subjects:	Chromatographic profiles, Climate marker, Early-middle Miocene, Partial least squares regression, Sea surface temperature, Variable importance in projection,
Online Access:	http://hdl.handle.net/10261/134522 http://dx.doi.org/10.13039/501100003329
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