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Over the past decades several software packages have been developed dedicated to age-modelling. For example, clam (Blaauw 2010) uses basic statistical models such as linear interpolation and smooth splines to draw age-depth curves through dated depths, taking into account dating uncertainties through random sampling of the dates. Bayesian age-models such as Bacon use more sophisticated approaches to constrain the models, including limits on accumulation rate and its variability.
If you require help constructing age-models for your site(s), Dr Maarten Blaauw, the primary author of the software clam and Bacon, can offer advice. Please contact Maarten at firstname.lastname@example.org to discuss options.
Simulation of accumulating sediment (yellow blocks with black lines). As the sediment accumulates through time, changes in accumulation rate will cause fluctuations in the age-depth curve. Often only few samples will be dated (red crosses), and on those few dates an age-depth model (red line, linear interpolation between dated points) needs to be constructed.
© 2008 Maarten Blaauw (please cite this page when using the graphs).
Archaeological Bayesian modelling
Prior knowledge of phases and stratigraphy can be included along with dating evidence in Bayesian models to help constrain the age and time span of phases, gaps, etc. The program OxCal (Bronk Ramsey 2009) was designed for this purpose and is widely used in archaeology.
If you require help constructing and running OxCal age-models for your site(s), Dr Cormac McSparron from the Centre for Archaeological Fieldwork has extensive experience in the field and can build and run the models for you. Please contact Cormac at email@example.com to discuss options.
A Bayesian way to produce age-depth models constrained by chronological/stratigraphical ordering of the dates. Material deeper down in a core will be older than material further up, so, we know that any age-model should increase monotonously, and not show any “leaps back in time”. We simulate calendar ages from each of the calibrated C14 ages (blue lines), and construct an age-depth model through these points (linear interpolation between the dated levels). We repeat this process many times. If the age-model shows any negative accumulation rates, we reject that model (red lines). If it increases monotonously, without any negative accumulation rates, we accept the model (green) and store it (grey lines). For the Bayesian model based on the prior knowledge of stratigraphically ordered dates, we will only use the accepted age-models (the growing grey blur).
Blaauw, M., 2010. Methods and code for ‘classical’ age-modelling of radiocarbon sequences. Quaternary Geochronology 5, 512-518
Blaauw, M., Christen, J.A., 2011. Flexible paleoclimate age-depth models using an autoregressive gamma process. Bayesian Analysis 6, 457-474
Bronk Ramsey C. 2009. Bayesian analysis of radiocarbon dates. Radiocarbon 55(1):337-60.
Ramped Pyroxidation/ Combustion