Blind dates: Exploring uncertainty in the radiocarbon evidence on the emergence of animal husbandry in the Dutch wetlands. (October 2022)

• Record Type: Journal Article
• Authors: Dreshaj, Merita; Dee, Michael; Peeters, Hans; Raemaekers, Daan
• Is Part Of: Journal of archaeological science. Volume 45(2022)
• Publication Date: 2022-10
• Subjects: Radiocarbon chronology -- Legacy datasets -- Animal husbandry -- Dutch wetlands -- Bayesian modelling -- Chronometric hygiene; Archaeology -- Periodicals; Archaeology -- Research -- Periodicals; 930.1
• DOI: 10.1016/j.jasrep.2022.103589
• Languages: English
• ISSNs: 2352-409X

Abstract

Highlights: This is the first in-depth chronological study of the legacy datasets from the context of early animal husbandry in the Netherlands. We scrutinise the established chronological narrative on the commencement of domestication in the Netherlands by means of Bayesian modelling and chronometric hygiene, methods novel in Dutch archaeology. We demonstrate that the chronostratigraphy of Hardinxveld-Giessendam de Bruin, Mesolithic site featuring the oldest remains of domesticated species and crucial to the debate on the start of Neolithisation in the Netherlands, is inconclusive and requires further research. Current results suggest that the context of the oldest domesticated animals is likely several centuries younger than previously thought. Abstract: The emergence of animal husbandry in the Netherlands remains the subject of much speculation. Challenges in identifying domesticated animals among the faunal remains, inconsistent excavation documentation, and flawed radiocarbon analysis have resulted in questionable chronologies. This paper examines the available radiocarbon evidence from selected sites which are the mainstay of early examples of domesticated animals in the Netherlands, between 5000 and 4000 BCE. 1 We approach the legacy data in two ways: by employing principles of chronometric hygiene to reassess the radiocarbon datasets of selected sites and by exploring the use of such data for future studies in chronology by means of Bayesian chronological modelling. The latter is demonstrated with a case study, whereby we employ legacy data from Hardinxveld-Giessendam De Bruin in Bayesian models to demonstrate that, despite their shortcomings, such dates remain a valuable resource for much needed future chronological analysis.