The potential of varves in high-resolution paleolimnological studies

A novel approach to investigating annually laminated lake sediments combines micro-facies analyses on thin sections with high-resolution X-ray fluorescence scanning on impregnated sediments.It facilitates improved varve counting and interpretation of seasonal paleoclimate signals including extreme events and the dynamics of abrupt changes.Varved lake sediments are important high-resolution climate and environment archives for paleolimnological investigations because they provide independently datable evidence of environmental change in response to either climatic change or human impact (Lamoureux, 2001;Brauer, 2004;Zolitschka, 2003; 2006).Such records are not only found in present-day lakes but also in paleolake deposits and allow detailed reconstructions for time intervals without any human influence (Mangili et al., 2005;Brauer et al., 2007).Varved sediments provide both an independent dating tool (e.g., Kitagawa and van der Plicht, 1998) and high-resolution proxy data.Traditional geochemical, physical and biological analyses at discrete sample intervals commonly provide data at decadal to sub-decadal resolution.Annual resolution is revealed from varve thickness measurements.A comprehensive interpretation of the latter requires profound knowledge of the seasonal composition and structure of varves because many different varve types can form depending on the climate regime and environmental conditions.The classification of varves into three major types, i.e., clastic, organic and evaporitic (e.g., Zolitschka, 2003), however, is too broad to describe all variations in varve deposition.Further details about seasonal sub-layers can be obtained by micro-facies analyses (Brauer, 2004) and provide crucial information on the seasonal signals in varve records, thereby enabling the detection of low-amplitude and short-term climate changes (Brauer et al., 2008a; b).The main limitation of micro-facies data, however, lies in their only semi-quantitative character.This problem can be overcome by integrating microscope analyses with µ-XRF scanning, which allows detailed element profiling across individual varves.