Anthropic Activity Markers 2.0: A Shift Towards Compositional Data Analysis

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.