Integrating Archaeological, Palaeoenvironmental, and Computational Data
The ESTER Project employs a multi-disciplinary approach to reconstruct prehistoric population estimates with unprecedented accuracy. By integrating diverse data sources and leveraging advanced statistical modeling, we refine demographic reconstructions across Europe and Western Asia from 12,000 to 2,000 BP.
Bayesian Hierarchical State-Space Modeling
At the core of our methodology is a Bayesian Hierarchical State-Space Model (HSSM), which allows us to:
✔ Combine multiple independent datasets while accounting for missing or uncertain data.
✔ Estimate population densities at high temporal resolution (50-year intervals).
✔ Incorporate spatial and environmental variability into demographic reconstructions.
✔ Quantify uncertainty, ensuring robust and reproducible estimates.
This framework enables us to move beyond previous approaches that relied on simplified models, expert assumptions, or limited datasets.
Key Data Sources
We integrate a wide range of archaeological, palaeoenvironmental, and computational datasets, including:
- Radiocarbon Dates (14C): A primary proxy for human activity, calibrated and analyzed in a Bayesian framework.
- Settlement Patterns: Spatial distributions of known sites, categorized by occupation phases and intensity.
- Palaeoenvironmental Indicators: Data from pollen cores, isotopic records, and other proxies to reconstruct environmental contexts.
- Land-Use and Subsistence Models: Evidence of agricultural expansion, domestication patterns, and economic shifts.
- Mobility and Interaction Networks: Patterns of exchange, migration, and cultural diffusion inferred from material culture and isotopic studies.
Data Harmonization & Standardization
A major challenge in prehistoric demographic studies is the heterogeneous nature of data sources. ESTER addresses this by:
✔ Developing a unified data framework for integrating diverse datasets.
✔ Applying probabilistic models to handle gaps and uncertainties.
✔ Using spatial interpolation techniques to refine regional estimates.
Model Calibration & Validation
To ensure accuracy and reliability, the ESTER model undergoes:
- Cross-validation with known historical population benchmarks where available.
- Sensitivity analysis to assess the impact of different variables.
- Comparisons with independent paleoenvironmental and archaeological datasets to verify consistency.
Interdisciplinary Collaboration & Open Science
ESTER is built on an open science philosophy, ensuring all models, datasets, and results are:
✔ Reproducible and transparent.
✔ Available to researchers, policymakers, and the public.
✔ Continuously refined through interdisciplinary collaboration.
By integrating big data, computational modeling, and archaeological expertise, ESTER sets a new standard for prehistoric demographic research.
Header Image: Photo by ThisisEngineering at Unsplash