Assessing uncertainty in sighting records: an example of the Barbary lion

• Published in: PeerJ (San Francisco, CA) Vol. 3; p. e1224
• Main Authors: Lee, Tamsin E, Black, Simon A, Fellous, Amina, Yamaguchi, Nobuyuki, Angelici, Francesco M, Al Hikmani, Hadi, Reed, J Michael, Elphick, Chris S, Roberts, David L
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 01.09.2015; PeerJ, Inc; PeerJ Inc
• Subjects: Analysis; Bayesian analysis; Campephilus principalis; Conservation biology; Critically endangered; Data quality; Ecology; Endangered & extinct species; Endangered species; Estimates; Experts; Extinction; IUCN red list; Lion; Mathematical Biology; Methods; New records; Possibly extinct; Rare species; Sighting record; Sighting uncertainty; Simon, David E; Species extinction; Morocco; Algeria; Extinct; Sighting record; IUCN red list; Panthera leo; Sighting uncertainty; Critically endangered; Data quality; Possibly extinct
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.1224

As species become rare and approach extinction, purported sightings can be controversial, especially when scarce management resources are at stake. We consider the probability that each individual sighting of a series is valid. Obtaining these probabilities requires a strict framework to ensure that they are as accurately representative as possible. We used a process, which has proven to provide accurate estimates from a group of experts, to obtain probabilities for the validation of 32 sightings of the Barbary lion. We consider the scenario where experts are simply asked whether a sighting was valid, as well as asking them to score the sighting based on distinguishablity, observer competence, and verifiability. We find that asking experts to provide scores for these three aspects resulted in each sighting being considered more individually, meaning that this new questioning method provides very different estimated probabilities that a sighting is valid, which greatly affects the outcome from an extinction model. We consider linear opinion pooling and logarithm opinion pooling to combine the three scores, and also to combine opinions on each sighting. We find the two methods produce similar outcomes, allowing the user to focus on chosen features of each method, such as satisfying the marginalisation property or being externally Bayesian.