Late Holocene climate variability in the North Atlantic based on a biomarker reconstruction. The Lake Azul (Sao Miguel Island, Azores archipelago) case.

• Main Author: Rubio de Inglés, Maria Jesús
• Other Authors: Giralt, Santiago
• Format: Doctoral or Postdoctoral Thesis
• Language: unknown
• Published: Universidad de Barcelona 2016
• Subjects: Holocene; Climate; North Atlantic; North Atlantic oscillation
• Online Access: http://hdl.handle.net/10261/149616

The principal objective of this PhD thesis is to obtain a high resolution reconstruction of the climate (temperature and precipitation) in the north Atlantic for the late Holocene. This new reconstruction is from a sedimentary lacustrine record located in Azores (Lake Azul) that has been compared and discussing with principal other climate reconstructions published on the North Atlantic region. Climate in the North Atlantic is modulated by the conjunction of atmospheric patterns and ocean dynamics. The main atmospheric pattern is the North Atlantic Oscillation (NAO) but, other climatic modes such as the Eastern Atlantic (EA) and the Atlantic Meridional Oscillation (AMO) are also present. The use of biomarkers has appeared as a cutting edge technique to reconstruct climate and their validity has been proved by previous works. The Azul lacustrine sedimentary sequence occupied the last 660 years, and on it has been applied a multiproxy study including: facies analysis, X-Ray Diffraction (XRD), X-Ray Fluorescense (XRF), Total Organic Carbon (TOC), Total Nitrogen (TN), bulk isotopes of Carbon (δ13C) and Nitrogen (δ15N) and biomarkers (GDGTs and δD leaf waxes). Facies were grouped in two main facies types according to the velocity of sedimentation and the organic matter origin: (1) “Continuous facies” accumulated by a more or less continuously sedimentation processes and dominated by lake organic matter, and (2) “rapid facies” deposited from flood events and transporting mainly terrestrial organic matter. An accurate age-depth model based on 14C and 210Pb dates and XRF data was built to figure out those sudden changes (the Dynamic Age Model, DAM). The DAM calculates the age of the samples redistributing the time along the profile according to the amount of crystalline terrestrial particulated material. DAM can acquire short and long-term sedimentation rate (SR) changes and previous models only acquire longterm fluctuations. The biomarkers (GDGTs and δD leaf waxes) were extracted and studied on the continuous ...