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Abstract. Annually laminated lake sediment can track paleoenvironmental change at high resolution where alternative archives are often not available. However,information about the chronology is often affected by indistinct and intermittent laminations. Traditional chronology building struggles with thesekinds of laminations, typically failing to adequately estimate uncertainty or discarding the information recorded in the laminations entirely,despite their potential to improve chronologies. We present an approach that overcomes the challenge of indistinct or intermediate laminations andother obstacles by using a quantitative lamination quality index combined with a multi-core, multi-observer Bayesian lamination sedimentation modelthat 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 sediment of indistinct and intermittently laminatedsequences from alpine Columbine Lake, Colorado. The integrated model indicates 3137 (95 % highest probability density range: 2753–3375) varveyears with a cumulative posterior distribution of counting uncertainties of −13 % to +7 %, indicative of systematic observerunder-counting. Our novel approach provides a realistic constraint on sedimentation rates and quantifies uncertainty in the varve chronology byquantifying over- and under-counting uncertainties related to observer bias as well as the quality and variability of the sediment appearance. The approachpermits the construction of a chronology and sedimentation rates for sites with intermittent or indistinct laminations, which are likely moreprevalent than sequences with distinct laminations, especially when considering non-lacustrine sequences, and thus expands the possibilities ofreconstructing past environmental change with high resolution.
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Semi-automated counting of complex varves through image autocorrelation
Annual resolution sediment layers, known as varves, can provide continuous and high-resolution chronologies of sedimentary sequences. In addition, varve counting is not burdened with the high laboratory costs of geochronological analyses. Despite a more than 100-year history of use, many existing varve counting techniques are time consuming and difficult to reproduce. We present countMYvarves, a varve counting toolbox which uses sliding-window autocorrelation to count the number of repeated patterns in core scans or outcrop photos. The toolbox is used to build an annually-resolved record of sedimentation rates, which are depth-integrated to provide ages. We validate the model with repeated manual counts of a high sedimentation rate lake with biogenic varves (Herd Lake, USA) and a low sedimentation rate glacial lake (Lago Argentino, Argentina). In both cases, countMYvarves is consistent with manual counts and provides additional sedimentation rate data. The toolbox performs multiple simultaneous varve counts, enabling uncertainty to be quantified and propagated into the resulting age-depth model. The toolbox also includes modules to automatically exclude non-varved portions of sediment and interpolate over missing or disrupted sediment. CountMYvarves is open source, runs through a graphical user interface, and is available online for download for use on Windows, macOS or Linux at https://doi.org/10.5281/zenodo.4031811 .
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- Award ID(s):
- 1714614
- PAR ID:
- 10296953
- Date Published:
- Journal Name:
- Quaternary Research
- ISSN:
- 0033-5894
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/qua.2021.10
