Abstract
Time-since-death and time-since-burial (TSB) estimation methods have grown from research conducted within the University of Tennessee. Through decades of analyzing decomposing remains, Dr. Arpad Vass established two Postmortem Interval (PMI) equations which estimate the PMI of human remains that decomposed in aerobic and anaerobic environments respectively. Key equation variables included soil moisture, air humidity, soil temperature, ambient air temperature, adipocere development and skeletonization percentage. Similarly, other prominent PMI estimation methods, such as the Megyesi et al. (2005) and Moffat et al. (2016) accumulated-degree-days (ADD) systems also rely upon variables such as average daily temperature. It is well established in the literature that these variables are proximal influences upon decomposition rates as (1) warm temperatures increase in the rate of decomposition (per Van’t Hoff’s Law) and (2) an increase in soil moisture slows body decay rate. Soil moisture differs markedly between Knoxville (40-80%) and Fort Myers (15-40%). As such, I hypothesized that these equations would overestimate the TSB and PMI when applied to decomposing remains in southwest Florida. Furthermore, I contend that while the relationship of variables such as temperature and moisture to decomposition rates is well described, previous research has neglected to consider how the act of disturbing soil strata layers when a clandestine grave is dug without the addition of a body may influence these variables. The present research investigates these hypotheses through three experiments. First, soil temperature and moisture measurements of undisturbed soil will be statistically compared to disturbed soil of mock clandestine graves which are excavated twice a year as part of Florida Gulf Coast University’s (FGCU) forensic anthropology course. Second, the rate of decomposition of pigs (Sus scrofa) with a known interment period buried at the FGCU Buckingham Site Forensic Anthropology Facility will be statistically compared to the TSB predicted by Vass’ (2011) anaerobic decomposition equation. Finally, the rate of decomposition of a pig decomposing on surface substrate with a known PMI at the FGCU Buckingham Site Forensic Anthropology Facility was statistically compared to the PMI estimates generated by the Vass (2011) aerobic decomposition equation in addition to the Megyesi et al. (2005) and Moffat et al. (2016) ADD systems. Evidence is presented that agitating soil strata layers does not significantly influence key variables used in the Vass (2011) TSB estimation method. Further evidence is presented that current methods of PMI estimation are not applicable in the unique environment of southwest Florida as they attempt to fit linear relationships to logistic patterns of decomposition in addition to errors in the construction of the equations. Better fits for the observed data were achieved using Gompertz transformations and non-linear least squares methods. I present recommendations for future research.