Geolocation analysis using Maxent and plant sample data

Abstract

A study was conducted to assess the feasibility of geolocation based on correctly identifying pollen samples found on goods or people for purposes of compliance with U.S. import laws and criminal forensics. The analysis was based on Neotropical plant data sets from the Global Biodiversity Information Facility. The data were processed through the software algorithm Maxent that calculates plant probability geographic distributions of maximum entropy, subject to constraints. Derivation of single and joint continuous probability densities of geographic points, for single and multiple taxa occurrences, were performed. Statistical metrics were calculated directly from the output of Maxent for single taxon probabilities and were mathematically derived for joint taxa probabilities. Predictions of likeliest geographic regions at a given probability percentage level were made, along with the total corresponding geographic ranges. We found that joint probability distributions greatly restrict the areas of possible provenance of pollen samples.