Assessing the viability of airborne environmental DNA detection for identifying trafficked lion pelts (Panthera leo) in a containerised environment - Moloney, Georgia Kate; Brien, Gabrielle Grace; Shute, Nellie May; Khabiri, Aliakbar; Moloney, John; Delcheva, Iliana; MacGregor, Melanie; Chaber, Anne-Lise (Frontiers in Conservation Science, 2025)
Accurate and rapid detection methodologies for monitoring the illicit trafficking of threatened species through highly exploited maritime routes are crucial to support law enforcement and conservation efforts. One of the most prominent trafficked species is the lion (Panthera leo), prized for their pelts, bones, and other derivatives, with the intensity of the trade contributing to their current vulnerable International Union for Conservation of Nature (IUCN) conservation status. The trade in such wildlife products is facilitated by the limited availability of detection technologies at seaports and border crossings to identify and intercept trafficking efforts. Thus, we explored the feasibility of airborne environmental DNA (eDNA) analysis as a novel method to detect lion pelts concealed in shipping containers. Air samples were collected within close proximity of the pelts, as well as from the external air vents of a sealed container using a custom air extraction device. To enhance trace eDNA capture and attempt to overcome the combined challenges of degraded DNA (common in wildlife trade samples) and a confined environment, samples were collected on plasma polymer-coated HEPA F7 filters. All filter samples captured eDNA from the air, with no significant difference in overall yield across filter types (p > 0.05). However, only three surface-modified filters captured amplifiable P. leo mitochondrial DNA using species-specific primers, and only when sampling occurred in close proximity to pelts. Although the adaptation of eDNA-based detection methods shows potential, our findings demonstrate that the current protocol may be unsuitable for law enforcement applications without significant optimisation and validation.