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Anthropic Activity Markers 2.0: A Shift Towards Compositional Data Analysis.

Abel Ruiz-Giralt1, Stefano Biagetti1,2,3, Carla Lancelotti1,2

  • 1Culture, Archaeology and Socio-Ecological Dynamics Research Group, Universitat Pompeu Fabra, C. Ramon Trias Fargas 25-27, 08005 Barcelona, Spain.

Journal of Archaeological Method and Theory
|June 12, 2026
PubMed
Summary

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This summary is machine-generated.

Anthropic Activity Markers (AAMs) 2.0 offers a new statistical framework for analyzing human activities in sediments. This revised approach uses compositional data analysis and geostatistics for more reliable archaeological inference.

Area of Science:

  • Archaeological science
  • Geochemistry
  • Data analysis

Background:

  • Anthropic Activity Markers (AAMs) were developed to infer human activities from sediment signatures.
  • Previous methods using absolute geochemical values introduced statistical limitations.
  • A need existed for a more robust analytical framework for archaeological inference.

Purpose of the Study:

  • To introduce AAMs 2.0, a revised analytical framework for inferring human activities.
  • To integrate compositional data analysis (CoDA) and geostatistics for improved statistical rigor.
  • To demonstrate the application of CoDA principles to archaeological datasets.

Main Methods:

  • Theoretical framework development for CoDA and geostatistics in AAMs.
  • Application of CoDA principles to analyze geochemical signatures in sediments.
Keywords:
Anthropic Activity MarkersCompositional Data AnalysisEthnoarchaeologyGeostatisticsSoil Geochemistry

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  • Revisiting an ethnoarchaeological dataset (Rondelli et al., 2014) as a test case.

    • Main Results:

    • Demonstration that treating geochemical concentrations as absolute values creates statistical artifacts.
    • Identification of meaningful compositional relationships using CoDA, independent of heuristic combinations.
    • Statistically robust results obtained through the revised framework.

    Conclusions:

    • AAMs 2.0 provides a more rigorous foundation for archaeological inference.
    • Activity markers are reframed as relational, ratio-based spatial signals.
    • The integrated CoDA and geostatistics approach enhances analytical reliability.