A Bayesian approach to linking archaeological, paleoenvironmental and documentary datasets relating to the settlement of Iceland (Landnám)
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KeywordsBayesian outlier models; Harris matrix; Icelandic sagas; Island colonisation; Late Holocene; Palaeoecology; Radiocarbon dating; Tephrochronology; Viking Age
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Icelandic settlement (Landnám) period farmsteads offer opportunities to explore the nature and timing of anthropogenic activities and environmental impacts of the first Holocene farming communities. We employ Bayesian statistical modelling of archaeological, paleoenvironmental and documentary datasets to present a framework for improving chronological robustness of archaeological events. Specifically, we discuss events relevant to the farm Hrísbrú, an initial and complex settlement site in southwest Iceland. We demonstrate that tephra layers are key in constraining reliable chronologies, especially when combined with related datasets and treated in a Bayesian framework. The work presented here confirms earlier interpretations of the chronology of the site while providing increased confidence in the robustness of the chronology. Most importantly, integrated modelling of AMS radiocarbon dates on Hordeum vulgare grains, palynological data, documented evidence from textual records and typologically diagnostic artefacts yield increased dating reliability. The analysis has also shown that AMS radiocarbon dates on bone collagen need further scrutiny. Specifically for the Hrísbrú farm, first anthropogenic footprint palynomorph taxa are estimated to around AD 830–881 (at 95.4% confidence level), most likely before the tephra fall out of AD 877 ± 1 (the Landnám tephra layer), demonstrating the use of arable fields before the first known structures were built at Hrísbrú (AD 874–951) and prior to the conventionally accepted date of the settlement of Iceland. Finally, we highlight the importance of considering multidisciplinary factors for other archaeological and paleoecological studies of early farming communities of previously uninhabited island areas.