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

Authors :
Gonzalo Araujo
Ariana Agustines
Steffen S. Bach
Jesse E. M. 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 S. Hardenstine
Alex Hearn
Mahardika R. Himawan
Rhys Hobbs
Jason Holmberg
Ibrahim Shameel
Mohammed Y. Jaidah
Jessica Labaja
Savi 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
Source :
Frontiers in Marine Science, Vol 9 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

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.

Details

Language :
English
ISSN :
22967745
Volume :
9
Database :
Directory of Open Access Journals
Journal :
Frontiers in Marine Science
Publication Type :
Academic Journal
Accession number :
edsdoj.319d24b3dce425aab4804b4d61a8ef6
Document Type :
article
Full Text :
https://doi.org/10.3389/fmars.2022.775691