2026/06/10 by Abel Ruiz-Giralt, Stefano Biagetti, Carla Lancelotti +5 · 1 voice
Computer Science · Earth and Planetary Sciences · Social Sciences · #Archaeology and ancient environmental studies #Geochemistry and Geologic Mapping #Pleistocene-Era Hominins and Archaeology
paper · pdf · doi:10.1007/s10816-026-09799-9
openalex created_date 2026/06/10 · openalex publication_date 2026/06/10 · openalex updated_date 2026/07/29
Abstract Anthropic Activity Markers (AAMs) were formalized over 10 years ago as a toolkit to infer human activities from biological and geochemical signatures preserved in sediments. This paper presents AAMs 2.0, a revised analytical framework that integrates compositional data analysis (CoDA) and geostatistics, as the appropriate statistical foundations for this approach. We first outline the theoretical motivation of this framework, demonstrating that treating geochemical concentrations as absolute values generates statistical artefacts that limit analytical reliability. Using the ethnoarchaeological dataset of Rondelli et al . (2014) as a test case, we illustrate how CoDA principles can be applied to revisit established interpretations. With this approach, we can identify meaningful compositional relationships without relying exclusively on heuristic element combinations, yielding results that are more statistically robust. Ultimately, AAMs 2.0 reframes activity markers as relational, ratio-based signals in space, providing a more rigorous foundation for archaeological inference.