Using Species Distribution Modeling for Geoforensic Analyses

Abstract

Microscopic trace material such as pollen is an important category of evidentiary elements recovered during forensic investigations. As an environmentally ubiquitous material that attaches to various surfaces, pollen facilitates the ability to link objects and people in space and time. This study uses bees as representative objects that are mobile and collect spatiotemporal environmental traces that can be used to model (pollen) species distributions for predictive geoforensic location efforts, measured as search space reduction. In addition to using bees as moving objects, we also applied the same method to documented real-world forensic cases to evaluate how well the search space would have been reduced. Results demonstrate promising predictive performances of species distribution models for identifying location history of bees at both a subcontinental scale and a near-global scale. We assessed effective search space reduction for three solved criminal cases that involved sampled surface pollen, and one case that identified the long-term residence of an unidentified decedent using pollen recovered in human lung tissue. This framework can efficiently aid law enforcement in optimizing search strategies during investigations when other biotic and abiotic materials are provided as multiple lines of evidence.