Integrating chronological uncertainties for annually laminated lake sediments using layer counting, independent chronologies and Bayesian age modelling (Lake Ohau, South Island, New Zealand). (15th May 2018)
- Record Type:
- Journal Article
- Title:
- Integrating chronological uncertainties for annually laminated lake sediments using layer counting, independent chronologies and Bayesian age modelling (Lake Ohau, South Island, New Zealand). (15th May 2018)
- Main Title:
- Integrating chronological uncertainties for annually laminated lake sediments using layer counting, independent chronologies and Bayesian age modelling (Lake Ohau, South Island, New Zealand)
- Authors:
- Vandergoes, Marcus J.
Howarth, Jamie D.
Dunbar, Gavin B.
Turnbull, Jocelyn C.
Roop, Heidi A.
Levy, Richard H.
Li, Xun
Prior, Christine
Norris, Margaret
Keller, Liz D.
Baisden, W. Troy
Ditchburn, Robert
Fitzsimons, Sean J.
Bronk Ramsey, Christopher - Abstract:
- Abstract: Annually resolved (varved) lake sequences are important palaeoenvironmental archives as they offer a direct incremental dating technique for high-frequency reconstruction of environmental and climate change. Despite the importance of these records, establishing a robust chronology and quantifying its precision and accuracy (estimations of error) remains an essential but challenging component of their development. We outline an approach for building reliable independent chronologies, testing the accuracy of layer counts and integrating all chronological uncertainties to provide quantitative age and error estimates for varved lake sequences. The approach incorporates (1) layer counts and estimates of counting precision; (2) radiometric and biostratigrapic dating techniques to derive independent chronology; and (3) the application of Bayesian age modelling to produce an integrated age model. This approach is applied to a case study of an annually resolved sediment record from Lake Ohau, New Zealand. The most robust age model provides an average error of 72 years across the whole depth range. This represents a fractional uncertainty of ∼5%, higher than the <3% quoted for most published varve records. However, the age model and reported uncertainty represent the best fit between layer counts and independent chronology and the uncertainties account for both layer counting precision and the chronological accuracy of the layer counts. This integrated approach provides aAbstract: Annually resolved (varved) lake sequences are important palaeoenvironmental archives as they offer a direct incremental dating technique for high-frequency reconstruction of environmental and climate change. Despite the importance of these records, establishing a robust chronology and quantifying its precision and accuracy (estimations of error) remains an essential but challenging component of their development. We outline an approach for building reliable independent chronologies, testing the accuracy of layer counts and integrating all chronological uncertainties to provide quantitative age and error estimates for varved lake sequences. The approach incorporates (1) layer counts and estimates of counting precision; (2) radiometric and biostratigrapic dating techniques to derive independent chronology; and (3) the application of Bayesian age modelling to produce an integrated age model. This approach is applied to a case study of an annually resolved sediment record from Lake Ohau, New Zealand. The most robust age model provides an average error of 72 years across the whole depth range. This represents a fractional uncertainty of ∼5%, higher than the <3% quoted for most published varve records. However, the age model and reported uncertainty represent the best fit between layer counts and independent chronology and the uncertainties account for both layer counting precision and the chronological accuracy of the layer counts. This integrated approach provides a more representative estimate of age uncertainty and therefore represents a statistically more robust chronology. Highlights: Bayesian age models integrate layer counts, radiometric and biostratigrapic dating. Integrated age model offers quantitative age/error estimates for varved records. Quantified age uncertainty provides a statistically more robust chronology. … (more)
- Is Part Of:
- Quaternary science reviews. Volume 188(2018)
- Journal:
- Quaternary science reviews
- Issue:
- Volume 188(2018)
- Issue Display:
- Volume 188, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 188
- Issue:
- 2018
- Issue Sort Value:
- 2018-0188-2018-0000
- Page Start:
- 104
- Page End:
- 120
- Publication Date:
- 2018-05-15
- Subjects:
- Geochronology -- Bayesian age modelling -- Varve chronologies -- 14C dating -- Integrated age model
Geology, Stratigraphic -- Quaternary -- Periodicals
Stratigraphie -- Quaternaire -- Périodiques
551.79 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02773791 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/quaternary-science-reviews/ ↗ - DOI:
- 10.1016/j.quascirev.2018.03.015 ↗
- Languages:
- English
- ISSNs:
- 0277-3791
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7210.220000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11482.xml