High-Altitude Agro-Pastoralism in the Kyrgyz Tien Shan: New Excavations of the Chap Farmstead (1065–825 cal b.c.)

Bones of recent mammals in the Amboseli Basin, southern Kenya, exhibit distinctive weathering characteristics that can be related to the time since death and to the local conditions of temperature, humidity and soil chemistry. A categorization of weathering characteristics into six stages, recognizable on descriptive criteria, provides a basis for investigation of weathering rates and processes. The time necessary to achieve each successive weathering stage has been calibrated using known-age carcasses. Most bones decompose beyond recognition in 10 to 15 yr. Bones of animals under 100 kg and juveniles appear to weather more rapidly than bones of large animals or adults. Small-scale rather than widespread environmental factors seem to have greatest influence on weathering characteristics and rates. Bone weathering is potentially valuable as evidence for the period of time represented in recent or fossil bone assemblages, including those on archeological sites, and may also be an important tool in censusing populations of animals in modern ecosystems. Show more

Bayesian models have proved very powerful in analyzing large datasets of radiocarbon ( 14 C) 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. Show more