Microbial decomposition in experimental single and mass graves New insights on post-burial interval estimation

Open Access
Authors
  • Timothy P. Gocha
  • Daniel J. Wescott
  • Noemi Procopio
Publication date 06-2026
Journal Forensic Science International: Genetics
Article number 103517
Volume | Issue number 84
Number of pages 14
Organisations
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR) - Amsterdam School for Heritage, Memory and Material Culture (AHM)
Abstract

Soil microbiomes are increasingly recognized as valuable indicators in forensic investigations, but microbial dynamics in mass graves remain poorly understood. This study investigates differences in microbial succession between individual graves (IG) and mass graves (MG) with human body donors and evaluates the potential of soil microbiome data to predict post-burial interval (PBI). Using ASV-level assessment, we analysed soil samples collected over time from both grave types in a controlled decomposition experiment. At the final timepoint (M18), MG and IG soils exhibited significantly different microbial compositions, with specific taxa, some associated with specific decomposition stages, enriched in each context. A regression model trained on IG samples predicted PBI with a mean error of 2.68 months when adjusted for seasonal variation but performed poorly on MG samples (RMSE = 7.12 months), highlighting ecological complexity and reduced generalisability. These findings underscore the importance of studying MG-specific microbial processes and caution against applying models developed from single-body burials to mass grave contexts. As mass graves are encountered in humanitarian and criminal investigations and establishing the duration of burial can be an important component of forensic reconstruction, our findings highlight the value of further research into context-specific microbiome models and their integration alongside existing methods for detection and time estimation in complex burial environments.

Document type Article
Language English
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