Improving sightings-derived residency estimation for whale shark aggregations: A novel metric applied to a global data set

Gonzalo Araujo, Ariana Agustines, Steffen S. Bach, Jesse Cochran, Emilio de la Parra-Galván, Rafael de la Parra-Venegas, Stella Diamant, Alistair Dove, Steve Fox, Rachel T. Graham, Sofia M. Green, Jonathan R. Green, Royale Hardenstine, Alex Hearn, Mahardika R. Himawan, Rhys Hobbs, Jason Holmberg, Ibrahim Shameel, Mohammed Y. Jaidah, Jessica LabajaSavi Leblond, Christine G. Legaspi, Rossana Maguiño, Kirsty Magson, Stacia D. Marcoux, Travis M. Marcoux, Sarah Anne Marley, Meynard Matalobos, Alejandra Mendoza, Joni A. Miranda, Brad M. Norman, Cameron T. Perry, Simon J. Pierce, Alessandro Ponzo, Clare E.M. Prebble, Dení Ramírez-Macías, Richard Rees, Katie E. Reeve-Arnold, Samantha D. Reynolds, David P. Robinson, Christoph A. Rohner, David Rowat, Sally Snow, Abraham Vázquez-Haikin, Alex M. Watts

Research output: Contribution to journalArticlepeer-review

Abstract

The world’s largest extant fish, the whale shark Rhincodon typus, is one of the most-studied species of sharks globally. The discovery of predictable aggregation sites where these animals gather seasonally or are sighted year-round – most of which are coastal and juvenile-dominated – has allowed for a rapid expansion of research on this species. The most common method for studying whale sharks at these sites is photographic identification (photo-ID). This technique allows for long-term individual-based data to be collected which can, in turn, be used to evaluate population structure, build population models, identify long-distance movements, and assess philopatry and other population dynamics. Lagged identification rate (LIR) models have fewer underlying assumptions than more traditional capture mark recapture approaches, making them more broadly applicable to marine taxa, especially far-ranging megafauna species like whale sharks. However, the increased flexibility comes at a cost. Parameter estimations based on LIR can be difficult to interpret and may not be comparable between areas with different sampling regimes. Using a unique data-set from the Philippines with ~8 years of nearly continuous survey effort, we were able to derive a metric for converting LIR residency estimates into more intuitive days-per-year units. We applied this metric to 25 different sites allowing for the first quantitatively-meaningful comparison of sightings-derived residence among the world’s whale shark aggregations. We validated these results against the only three published acoustic residence metrics (falling within the ranges established by these earlier works in all cases). The results were then used to understand residency behaviours exhibited by the sharks at each site. The adjusted residency metric is an improvement to LIR-based population modelling, already one of the most widely used tools for describing whale shark aggregations. The standardised methods presented here can serve as a valuable tool for assessing residency patterns of whale sharks, which is crucial for tailored conservation action, and can cautiously be tested in other taxa.
Original languageEnglish (US)
JournalFrontiers in Marine Science
Volume9
DOIs
StatePublished - Jul 28 2022

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