ESR 7:39-53 (2009)  -  DOI: https://doi.org/10.3354/esr00186

Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification

Jason Holmberg1,2,*, Bradley Norman3, Zaven Arzoumanian2,4

1ECOCEAN USA, 4836 NE 31st Avenue, Portland, Oregon 92711, USA
2Centre for Fish and Fisheries Research, Murdoch University, South Street, Murdoch, Western Australia 6150, Australia
3ECOCEAN, c/o Centre for Fish and Fisheries Research, Murdoch University, South Street, Murdoch, Western Australia 6150, Australia
4Present address: Universities Space Research Association, 10211 Wincopin Circle, Columbia, Maryland 21044, USA

ABSTRACT: Capture-mark-recapture (CMR) data from Ningaloo Marine Park (NMP) in Western Australia have recently been used to study the population dynamics of the local whale shark aggregation. Because nascent research efforts at other aggregation points look to NMP as a model, further analysis of existing modeling approaches is important. We have expanded upon previous studies of NMP whale sharks by estimating CMR survival and recruitment rates as functions of average total length (TL). Our analysis suggests a decline in reported values of TL coincident with marginally increasing abundance among sharks sighted in more than one year (‘returning’) from 1995 to 2008. We found a positive, average returning recruitment rate (λ) of 1.07 yr–1 (0.99 to 1.15, 95% CI); smaller individuals contributed in larger numbers to recruitment, allowing for population growth accompanied by a decline in median size. We subsequently explored intraseasonal population dynamics with the Open Robust Design (ORD) model structure. Our best-fit model estimated modestly increasing annual abundances between 107 (95% CI = 90 to 124) and 159 (95% CI = 127 to 190) for 2004 to 2007, suggesting a short-term increase in total annual abundance. The ORD also estimated an average residency time of 33 d (95% CI = 31 to 39) and biweekly entry profiles into the study area. Overall, our techniques demonstrate how large aggregations of the species can be modeled to better understand short- and long-term population trends. These results also show the direct scientific benefit from the development of an online, collaborative data management system to increase collection of sighting data for a rare species in conjunction with ecotourism activity.


KEY WORDS: Mark-recapture · Open Robust Design · Population biology · Rhincodon typus · Survivorship · Transience · Whale shark


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Cite this article as: Holmberg J, Norman B, Arzoumanian Z (2009) Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification. Endang Species Res 7:39-53. https://doi.org/10.3354/esr00186

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