Percorrer por autor "Garcia, Susana"
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- Changes in dental wear magnitude in the last ∼8000 years in southwestern IberiaPublication . Godinho, Ricardo Miguel; Umbelino, Cláudia; Garcia, Susana; Gonçalves, CéliaObjective: This study examines changes in dental wear magnitude in the past -8000 years, i.e., since Mesolithic until the 19th century, in southwestern Iberia. Thus, it encompasses the transition from hunting-gathering to agro-pastoralism, and then to the industrialization of food production and pre-processing. Design: Dental wear magnitude was scored in a total of 191 individuals and 1557 teeth from Mesolithic (individuals=56; teeth=643), Neolithic (individuals=35; teeth=169), Chalcolithic (individuals =35; teeth=221), Modern Age (individuals=17; teeth=209), and Late Modern Age (individuals=48; teeth=315) samples originating in southwestern Iberia (i.e., present central and southern Portugal) and according to the 8 levels ordinal scale of Smith (1984). Results: Results show a general trend for decreased wear magnitude in these two major transitions and during this timespan (although the hunting-gathering - agro-pastoralism transition had larger impact). The only meaningful differences in wear rate were found between the Late Modern Age and all remaining samples. Conclusion: Dental wear generally decreased during this timespan (although wear magnitude was less impacted by the industrialization of food production and pre-processing). Our results are consistent with studies documenting skull morphological gracilization associated with reduced masticatory demands due to the adoption of softer diets.
- Coupling geometric morphometrics and machine learning for mandibular sex estimation in late pleistocene and late modern populationsPublication . Godinho, Ricardo Miguel; Crevecoeur, Isabelle; Garcia, Susana; Whiting, Rebecca; Aramendi, JuliaAccurate sex estimation is crucial for studying both modern and ancient human populations, yet methods are often limited to well-preserved skeletons. Here, we combine Geometric Morphometrics (GM) and Machine Learning (ML) to assess mandibular sexual dimorphism and classify sex across a wide chronological and geographic range to bracket the potential of this approach. Sixty-seven individuals from the modern, identified Luis Lopes collection (Portugal) and 18 Late Pleistocene individuals from Jebel Sahaba (Sudan) were surface scanned. Anatomical landmark coordinates were extracted and analyzed with GM, and ML models were trained on a subset of the modern sample to predict sex in both the remaining modern individuals and the Late Pleistocene specimens. GM revealed significant sexual dimorphism in all samples, and ML achieved high intrapopulation classification accuracy. However, predictions were less reliable when applied across the temporally and geographically distant Jebel Sahaba population, reflecting interpopulation differences in mandibular size and shape. These results demonstrate that while GM-ML approaches are powerful tools for sex estimation within populations, caution is required when extending models to other populations.