Commentary on J-P. Michaud, G. Moreau, Predicting the Visitation of Carcasses by Carrion-Related Insects Under Different Rates of Degree-Day Accumulation

• NCJ Number: 252292
• Author(s): L. R. LaMotte, J. D. Wells
• Date Published: January 2017
• Length: 4 pages
• Agencies: NIJ-Sponsored
• Award: Statistical Methods for Combining Multivariate and Categorical Data in Postmortem Interval Estimation

Annotation

This commentary article re-analyzed and criticized one research in which a novel statistical test for predicting postmortem interval from insect succession data was proposed.

Abstract

Using simple mathematical examples, the authors demonstrate that the original research erred because the analyses were based on an erroneous interpretation of the nature of probabilities that disregards more than 300 years of scientific literature on probability combination. It is argued that the methods presented in the rebuttal more specifically the use of degree-day-based logistic regression analysis to model succession, was a positive contribution to the fields of forensic entomology and carrion ecology, which was omitted or trivialized by the original researchers. The original research found common assumptions in forensic entomology are that insects visit and colonize carcasses following a predictable sequence, and that this succession varies among seasons. However, currently available evidence for insect succession on decomposing bodies is essentially descriptive and the fine-scale predictability of insect succession with respect to seasons has never been confirmed statistically. In that study, the authors tested these assumptions through the sampling of carrion-related insects attracted to pig carcasses. Of the five species of carrion-related insects with high enough occurrence on carcasses to allow modelling, three showed predictable occurrence with respect to degree-day accumulation and seasonal effects demonstrating that the occurrence probability of some carrion-related insects on carcasses can be estimated from meteorological records even across seasons with different rates of degree-day accumulation.