Towards Robust Demographic Models: A Systematic Approach to 14C Data Aggregation and Analysis with Lessons from the Southern Levant

This study presents a robust seven-step framework for curating and analysing extensive radiocarbon (14C) datasets, optimised to construct accurate Summed Probability Distribution (SPD) models. Applied to a comprehensive dataset of 4,657 14C dates from 582 archaeological sites in the Southern Levant spanning the last 50,000 years, this framework systematically consolidates data by eliminating duplicates, refining archaeological periodisation, and integrating key environmental variables like phytogeographic zones and natural regions. Through meticulous 14C classification, outlier identification, and model assessment, the resulting dataset and models are refined, transparent, and adhere to FAIR principles for accessibility. This approach enhances the reliability of SPD models in studying ancient population trends and human-environment dynamics, offering a versatile tool adaptable to similar large-scale datasets across regions.

Publication Details

Journal
ResearchOnline at James Cook University (James Cook University)
Published
2025-01-01
Primary Topic
Archaeology and ancient environmental studies
Type
article
Field-Weighted Citation Impact
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article

Towards Robust Demographic Models: A Systematic Approach to 14C Data Aggregation and Analysis with Lessons from the Southern Levant

ResearchOnline at James Cook University (James Cook University)
Archaeology and ancient environmental studies
article

Towards Robust Demographic Models: A Systematic Approach to 14C Data Aggregation and Analysis with Lessons from the Southern Levant

article en

Abstract

This study presents a robust seven-step framework for curating and analysing extensive radiocarbon (14C) datasets, optimised to construct accurate Summed Probability Distribution (SPD) models. Applied to a comprehensive dataset of 4,657 14C dates from 582 archaeological sites in the Southern Levant spanning the last 50,000 years, this framework systematically consolidates data by eliminating duplicates, refining archaeological periodisation, and integrating key environmental variables like phytogeographic zones and natural regions. Through meticulous 14C classification, outlier identification, and model assessment, the resulting dataset and models are refined, transparent, and adhere to FAIR principles for accessibility. This approach enhances the reliability of SPD models in studying ancient population trends and human-environment dynamics, offering a versatile tool adaptable to similar large-scale datasets across regions.

ResearchOnline at James Cook University (James Cook University)
Universität Leipzig
Life in Land
Openalex Percentile: Top 39%
Archaeology and ancient environmental studies
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