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Published online by Cambridge University Press:  27 April 2022

Haidee Cadd*
ARC Centre of Excellence in Australian Biodiversity and Heritage (CABAH), University of Wollongong, Australia Chronos 14Carbon-Cycle Facility, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW 2052, Australia GeoQuest Research Centre, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia
Bryce Sherborne-Higgins
GeoQuest Research Centre, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia
Lorena Becerra-Valdivia
Chronos 14Carbon-Cycle Facility, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW 2052, Australia Oxford Radiocarbon Accelerator Unit, Research Laboratory for Archaeology and the History of Art, University of Oxford, OxfordOX13QY, United Kingdom
John Tibby
Geography, Environment and Population, and Sprigg Geobiology Centre, University of Adelaide, Australia
Cameron Barr
Geography, Environment and Population, and Sprigg Geobiology Centre, University of Adelaide, Australia
Matt Forbes
ARC Centre of Excellence in Australian Biodiversity and Heritage (CABAH), University of Wollongong, Australia GeoQuest Research Centre, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia KCB Australasia Pty ltd, Brisbane, Australia
Tim J Cohen
ARC Centre of Excellence in Australian Biodiversity and Heritage (CABAH), University of Wollongong, Australia GeoQuest Research Centre, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia
Jonathan Tyler
Department of Earth Sciences, School of Physical Sciences, University of Adelaide, Australia
Marcus Vandergoes
GNS Science, Lower Hutt, 5040, New Zealand
Alexander Francke
GeoQuest Research Centre, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Australia Department of Earth Sciences, School of Physical Sciences, University of Adelaide, Australia
Richard Lewis
Department of Earth Sciences, School of Physical Sciences, University of Adelaide, Australia
Lee J Arnold
Department of Earth Sciences, School of Physical Sciences, University of Adelaide, Australia
Geraldine Jacobsen
Centre for Accelerator Science, Australian Nuclear Science and Technology Organisation (ANSTO), New Illawarra Road, Lucas Heights, NSW 2234, Australia
Chris Marjo
Chronos 14Carbon-Cycle Facility, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW 2052, Australia
Chris Turney
Chronos 14Carbon-Cycle Facility, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW 2052, Australia ARC Centre of Excellence in Australian Biodiversity and Heritage (CABAH), University of New South Wales, Australia Division of Research, University of Technology Sydney, Ultimo, NSW 2007, Australia
*Corresponding author. Email:


Wetland sediments are valuable archives of environmental change but can be challenging to date. Terrestrial macrofossils are often sparse, resulting in radiocarbon (14C) dating of less desirable organic fractions. An alternative approach for capturing changes in atmospheric 14C is the use of terrestrial microfossils. We 14C date pollen microfossils from two Australian wetland sediment sequences and compare these to ages from other sediment fractions (n = 56). For the Holocene Lake Werri Berri record, pollen 14C ages are consistent with 14C ages on bulk sediment and humic acids (n = 14), whilst Stable Polycyclic Aromatic Carbon (SPAC) 14C ages (n = 4) are significantly younger. For Welsby Lagoon, pollen concentrate 14C ages (n = 21) provide a stratigraphically coherent sequence back to 50 ka BP. 14C ages from humic acid and >100 µm fractions (n = 13) are inconsistent, and often substantially younger than pollen ages. Our comparison of Bayesian age-depth models, developed in Oxcal, Bacon and Undatable, highlight the strengths and weaknesses of the different programs for straightforward and more complex chrono-stratigraphic records. All models display broad similarities but differences in modeled age-uncertainty, particularly when age constraints are sparse. Intensive dating of wetland sequences improves the identification of outliers and generation of robust age models, regardless of program used.

Research Article
© The Author(s), 2022. Published by Cambridge University Press for the Arizona Board of Regents on behalf of the University of Arizona

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