COMPUTER-BASED PHOTO IDENTIFICATION AS A TOOL FOR MONITORING SOUTHERN STINGRAYS AT STINGRAY CITY, CAYMAN ISLANDS

Colby Kresge

Abstract:

The aggregation of southern stingrays (Hypanus americanus) at Stingray City, Grand Cayman comprise the world’s most famous marine wildlife interaction site, generating over $50 million annually for the local economy. Because of the economic value of these animals, and because the rays are wild and come and go from the interaction site, the aggregation has been monitored for the last 20 years by recording the presence of individuals using tag and recapture methods with passive integrated transponder (PIT) tags. Reliance on PIT tags, which are not detectable by visual inspection, limits observation of aggregation members by excluding resident rays that have shed tags, rays that have recently been recruited to Stingray City as well as individuals that are difficult to capture. Conjointly, when injured or dead rays are observed, they cannot be identified without the use of a PIT tag scanner. Hence PIT tagging methods do not enable 100% coverage of individuals comprising the aggregation. The ability to expand identification of these additional individuals would improve monitoring and the assessment of aggregation composition that occur over time. The goal of this project was to develop a method for using “natural tags” for Stingray City rays based on characteristic markings using Photo ID software analogous to facial recognition methods. I developed a photo ID library containing 78 unique individual rays based on photos extracted from videos collected during biannual censuses of all stingrays present at Stingray City. Although the methods require substantial editing of extrinsic features such as sunlight, sand, and turbidity, the use of natural tags and Photo ID methods provide a potential mechanism that will allow the monitoring program to identify nearly 100% of the stingrays that occupy Stingray City. Monitoring of the entire aggregation of rays through identification based on natural tags will improve understanding of residency patterns, turnover rates, and long-term stability of aggregation of stingrays at Stingray City and improve long-term management of the aggregation.