Prof Christopher Ramsey

Abstract:

The ¹³C/¹²C ratio of C₃ plant matter is thought to be controlled by the isotopic composition of atmospheric CO₂ and stomatal response to environmental conditions, particularly mean annual precipitation (MAP). The effect of CO₂ concentration on ¹³C/¹²C ratios is currently debated, yet crucial to reconstructing ancient environments and quantifying the carbon cycle. Here we compare high-resolution ice core measurements of atmospheric CO₂ with fossil plant and faunal isotope records. We show the effect of pCO₂ during the last deglaciation is stronger for gymnosperms (-1.4 ± 1.2‰) than angiosperms/fauna (-0.5 ± 1.5‰), while the contributions from changing MAP are -0.3 ± 0.6‰ and -0.4 ± 0.4‰, respectively. Previous studies have assumed that plant ¹³C/¹²C ratios are mostly determined by MAP, an assumption which is sometimes incorrect in geological time. Atmospheric effects must be taken into account when interpreting terrestrial stable carbon isotopes, with important implications for past environments and climates, and understanding plant responses to climate change.

Abstract:

The melting of perennial ice patches globally is uncovering a fragile record of alpine activity, especially hunting and the use of mountain passes. When rescued by systematic fieldwork (glacial archaeology), this evidence opens an unprecedented window on the chronology of high-elevation activity. Recent research in Jotunheimen and surrounding mountain areas of Norway has recovered over 2000 finds—many associated with reindeer hunting (e.g. arrows). We report the radiocarbon dates of 153 objects and use a kernel density estimation (KDE) method to determine the distribution of dated events fromca4000 BCE to the present. Interpreted in light of shifting environmental, preservation and socio-economic factors, these new data show counterintuitive trends in the intensity of reindeer hunting and other high-elevation activity. Cold temperatures may sometimes have kept humans from Norway's highest elevations, as expected based on accessibility, exposure and reindeer distributions. In times of increasing demand for mountain resources, however, activity probably continued in the face of adverse or variable climatic conditions. The use of KDE modelling makes it possible to observe this patterning without the spurious effects of noise introduced by the discrete nature of the finds and the radiocarbon calibration process.

Abstract:

Rationale

For radiocarbon results to be accurate, samples must be free of contaminating carbon. Sample pre-treatment using an HPLC approach has been developed at the Oxford Radiocarbon Accelerator Unit (ORAU) as an alternative to conventional methods for dating heavily contaminated bones. This approach isolates hydroxyproline from bone collagen, enabling a purified bone-specific fraction to then be radiocarbon dated by accelerator mass spectrometry (AMS).

Methods

Using semi-preparative chromatography and non-carbon based eluents, this technique enables the separation of underivatised amino acids liberated by hydrolysis of extracted bone collagen. A particular focus has been the isolation of hydroxyproline for single compound AMS dating since this amino acid is one of the main contributors to the total amount of carbon in mammalian collagen. Our previous approach, involving a carbon-free aqueous mobile phase, required a 2-step separation using two different chromatographic columns.2

Results

This paper reports significant improvements that have been recently made to the method to enable faster semi-preparative separation of hydroxyproline from bone collagen, making the method more suitable for routine radiocarbon dating of contaminated and/or poorly preserved bone samples by AMS. All steps of the procedure, from the collagen extraction to the correction of the AMS data, are described.

Conclusions

The modifications to the hardware and to the method itself have reduced significantly the time required for the preparation of each sample. This makes it easier for other radiocarbon facilities to implement and use this approach as a routine method for preparing contaminated bone samples.

Abstract:

AbstractBayesian models have proved very powerful in analyzing large datasets of radiocarbon (14C) measurements from specific sites and in regional cultural or political models. These models require the prior for the underlying processes that are being described to be defined, including the distribution of underlying events. Chronological information is also incorporated into Bayesian models used in DNA research, with the use of Skyline plots to show demographic trends. Despite these advances, there remain difficulties in assessing whether data conform to the assumed underlying models, and in dealing with the type of artifacts seen in Sum plots. In addition, existing methods are not applicable for situations where it is not possible to quantify the underlying process, or where sample selection is thought to have filtered the data in a way that masks the original event distribution. In this paper three different approaches are compared: “Sum” distributions, postulated undated events, and kernel density approaches. Their implementation in the OxCal program is described and their suitability for visualizing the results from chronological and geographic analyses considered for cases with and without useful prior information. The conclusion is that kernel density analysis is a powerful method that could be much more widely applied in a wide range of dating applications.