A comparative bone surface modification database for revealing the origins and evolution of human carnivory - Keevil, Trevor L.; Pelissero, Alex J.; Negash, Tewabe; Orlikoff, Emily R.; Osborne, Isabell; Tolley, April M.; Pobiner, Briana; Pante, Michael C. (Frontiers in Ecology and Evolution, 2026)
Fossilized trace marks left by our ancestors as they processed animals for food are important clues to the emergence and intensification of human carnivory and tool use. When studied in tandem with fossilized tooth marks made by carnivorous predators, butchery marks also help reconstruct the larger ecological framework and trophic dynamics of paleoecosystems. However, some taphonomic processes produce bone surface modifications that mimic the morphology of butchery marks, introducing the potential for misclassification when relying on imprecise criteria. The implementation of digital modeling techniques that allow the collection of microscopic quantitative data has begun to improve the reliability of mark identification. Although many digital taphonomy methods appear promising, their broader applications are limited by a lack of replicable methods, unpublished and closed-source databases, and statistical methodologies that violate core assumptions for accurate model inference. In this paper, we present an open-source database of experimentally generated cut, percussion, tooth, and trample marks measured and analyzed using high-resolution confocal profilometry and a replicable quantification protocol. Statistical classificatory models using our taphonomic measurement database can distinguish between experimentally generated bone surface modifications with 74% to 83% accuracy, depending on the comparative groupings. Our aim for these classification models is to facilitate accurate identification of the processes that created fossilized bone surface modifications, which is the first step to resolving long-standing debates surrounding the origins and evolution of human carnivory. Additionally, we hope that publishing our open-source data and code underscores the need for more replicable, collaborative, and transparent methods in paleoanthropological research.