Assessing Histotaphonomy: A Pilot Study Using Image Analysis for Quantitative Scoring of Bone Diagenesis

Abstract

This pilot study focusses on improving the methodological approach of histotaphonomy by integrating image analysis software for assessing bone diagenesis in both bone histological sections and microcomputed tomography (μ-CT) scans of the same bone slice. Femurs and ribs from six individuals buried at the churchyard of St. Anne in Koekelberg (Belgium, 1833–1916) were analyzed with μ-CT and histology (light microscopy and scanning electron microscopy). Bone diagenesis was scored visually by the assessor, as well as quantitatively by image analysis. The results suggest that image analysis is an effective quantitative scoring method, eliminating subjectivity bias, specifically regarding the precision in percentage calculation of preserved areas which aids in assigning the right category of the Oxford Histological Index. However, algorithm limitations can affect the accuracy and reliability of the results, hence specialized expertise is advised. The taphonomic results show that bacterial degradation was similar within and between rib and femur of the same individual but varied between individuals depending on burial treatment (wooden versus zinc-lined coffins). Other inter-skeletal differences were caused by biological parameters such as the amount of primary lamellar bone. This study demonstrates the accuracy of quantitative scoring by advancements in technology such as image analysis, creating a basis for the incorporation of machine learning algorithms in future histotaphonomy studies. It also stresses the importance of using both histology and μ-CT as complementary methods.