New approaches to dating intermittently varved sediment, Columbine lake, Colorado, USA

Abstract

Abstract. Annually laminated lake sediment can track paleoenvironmental change at high-resolution where alternative archives are often not available. However, information about both paleoenvironmental change and chronology are often affected by indistinct and intermittent varves. We present an approach that overcomes these and other obstacles by using a quantitative varve quality index combined with a multi-core, multi-observer Bayesian varve sedimentation model that quantifies realistic under- and over-counting uncertainties while integrating information from radiometric measurements (210Pb, 137Cs, and 14C) into the chronology. We demonstrate this approach on thin sections of indistinct and intermittently varved sequences from alpine Columbine Lake, Colorado. The integrated model indicates 3137 (95 percentile highest density probability range: 2753–3375) varve years with a cumulative posterior distribution of counting uncertainties of −13/+7\u2009% indicative of systematic observer undercounting. The sedimentary features of the thin and complex varves shift through time, from normally graded couplets to couplets interrupted with coarser sub-laminae, to inversely graded couplets. We interpret the normal grading couplets as spring nival discharge followed by winter settling, the coarser sub-laminae as high rainfall events, and the inverse grading as hyperpycnal flows and/or pulses of dust related to human impact changing the varve formation mechanism. Our novel approach provides a realistic constraint on sedimentation rates and quantifies uncertainty in varve counts by quantifying over- and under-counting uncertainties related to observer bias and the quality and variability of the sediment appearance. The approach permits the construction of a varve chronology and sedimentation rates for sites with intermittent or indistinct varves, which are likely more prevalent than sequences with distinct varves, and thus, expands the possibilities of reconstructing past environmental change with high resolution.\n