The estimation of postmortem interval (PMI) is a critical component of medicolegal death investigation. An accurate PMI estimate has the potential to influence the allocation of investigative resources, establish the probative value of associated biological and material evidence, shape the analytical framework applied to skeletal analysis, and inform cause and manner of death. Forensic anthropologists are often tasked with PMI estimation throughout all stages of decomposition and typically rely on categorical phases of soft tissue and skeletal change purported to correspond to broad estimates of elapsed time. In an attempt to improve precision, Megyesi et al. (2005) developed the Total Body Score model (TBS). This quantitative method relies on qualitative assessment of value-assigned categories of tissue change within three anatomical regions to estimate accumulated degree days (ADD), and subsequently, PMI. However, the TBS model has failed to prove reliable in a diversity of region-specific validation studies, emphasizing the need for environment-specific research in taphonomy study. Toward that end, the rate, pattern, and trajectory of decomposition was assessed among a cohort of 12 human donors in the high-altitude Rocky Mountain region of Colorado. This research was performed at Colorado Mesa University’s Forensic Investigation Research Station high-altitude satellite facility, FIRS-TB40. The site lies at an elevation of 3000 meters/9840 feet above mean sea level (AMSL), in the Dfc (snow, fully humid, cool summer) climate region. With both significantly higher elevation and an unrepresented climate classification, FIRS-TB40 introduces a novel environment for the controlled study of human decomposition. This quadripartite study sought to (1) test the qualitative and quantitative aspects of the TBS model in a high-altitude environment to assess suitability of application in the estimation of local PMI; (2) test seven atmospheric variables to assess the utility of integrating atmospheric data beyond ADD into PMI estimation; (3) establish the rate and pattern of human decomposition, isolate and describe phasic patterns of soft tissue change throughout the trajectory of decomposition, and (4) develop a region specific bioecological profile with an emphasis on the integration of human behavior.Results: (1) Neither the qualitative or quantitative aspects of the TBS model tested well at high-altitude and are therefore not recommended for application within the study environment. The qualitative changes presented in the TBS model were not observed among the high-altitude cohort. While Megyesi et al. report that time and temperature - as measured by ADD - accounts for 84% of the variance observed throughout decomposition, ADD accounted for only 42% of the variance observed in decomposition within the high-altitude cohort. (2) Seven atmospheric variables were assessed using locally estimated scatterplot smoothing (LOESS) and multivariate regression. Two of these variables - accumulated solar radiation days (r2 = 0.67) and accumulated windspeed days (r2 = 0.65) – explained more variance in decomposition than ADD (r2 = 64). (3) Five categories of phasic, macroscopic soft tissue change, the suite of which is inferred unique to high-altitude, were identified. These include adipocere formation, trajectory of soft tissue color change, fluid bloat, tissue island formation, and skin sloughing. Patterns of slope roll and slope wash were also described to inform the local taphonomic profile. (4) A forensic bioecological profile was developed using empirically derived patterns of scavenger behavior, census and land use data, extant ethnographic data, and forensic case study. Analysis demonstrated that the data sources were cyclically informative and sufficient to develop an early phase foundational model that will benefit from future interdisciplinary research.Summarily, the high-altitude region of Colorado is culturally and environmentally distinct. The observed disparity in rate and pattern of human decomposition between the high-altitude cohort and the TBS model, and the inadequacy of ADD alone to predict PMI are demonstrative of the need for environment-specific model building in human taphonomy research.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:dissertations-3202 |
| Date | 01 May 2024 |
| Creators | Baigent, Christiane Irene |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations |
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