Limited latitudinal ranging of juvenile whale sharks in the Western Indian Ocean suggests the existence of regional management units

Abstract

Assessing the movements and connectivity of whale sharks Rhincodon typus through their range is difficult due to high individual mobility and limited knowledge of their behaviour following dispersal from coastal aggregation sites. Here, we use a large set of photo-identification and stable isotope data (δ 15 N and δ 13 C) to test the assumption that sharks frequenting aggregation sites in Mozambique, Tanzania, and Qatar are a mixed stock, as inferred by genetic data. Photo-identification revealed negligible connectivity among aggregation sites and none between the southern and central areas of the Western Indian Ocean (Mozambique and Tanzania) and the Arabian Gulf (Qatar). Sight−resight data indicated that shark movements at each site could be best represented by a model that included emigration, re-immigration, and some mortality or permanent emigration. Although there was high individual variation in the isotope profiles of sharks from each location, comparison with latitudinal isotope data suggests that sharks had shown site fidelity to within a few hundred kilometres of each study area over the period of isotopic integration. Given the Endangered status of whale sharks and regional differences in anthropogenic threat profiles, further studies -and conservation assessment efforts -should consider the possibility that whale shark subpopulations exist over smaller geographical scales than previously documented.

Stable Isotope Analysis of Dermis and the Foraging Behavior of Whale Sharks at Ningaloo Reef, Western Australia

“…The number of other studies of stable isotopes of whale sharks are limited, although they have yielded results similar to our work. Values of δ 13 C and δ 15 N of whale sharks at Ningaloo Reef were within ranges recorded in dermis of juvenile males in coastal waters of the western Indian Ocean (Mozambique, Tanzania and Qatar), and off the coast of Okinawa in Japan (Prebble et al, 2018;Wyatt et al, 2019). Notably, sharks sampled off the coast of Okinawa also had a diet of prey supported by regional phytoplankton.…”

“…Depletion in 13 C in muscle relative to the dermis we sampled in our study could, however, be due to differences in sample treatment before analysis. This also could be a result of physiological and metabolic factors including differences in the diet-to-tissue discrimination factors, turnover rates and/or amino acid composition between tissues, as noted for other pelagic sharks (Carlisle et al, 2012;Li et al, 2016;Prebble et al, 2018).…”

“…Stable isotope analysis (SIA) is often used to investigate the trophic ecology of sharks (e.g., Abrantes and Barnett, 2011;Albo-Puigserver et al, 2015;Ferreira et al, 2017), including whale sharks (Borrell et al, 2011;Prebble et al, 2018;Wyatt et al, 2019). This is possible because the isotopic composition of the tissues of an animal reflects assimilated diet over time (e.g., quality and composition of food), plus some variation related to the metabolism and the physiology of the species and the types of tissue analyzed (DeNiro and Epstein, 1976;Wolf et al, 2009).…”

“…Values of 13 C for fin cartilage from this study are among the largest calculated for elasmobranchs (e.g., MacNeil et al, 2006;Hussey et al, 2010;Kim et al, 2011Kim et al, , 2012, highlighting the complexity in interpreting stable isotope data in these large ectotherms. Where whale sharks are sampled in the wild, the collection of tissues for biochemical analyses from living animals generally involves skin biopsies that remove the outermost layer of dermal denticles and a portion of the collagenous connective tissue that lies beneath (hereafter "dermis") (e.g., Couturier et al, 2013;Rohner et al, 2013;Marcus et al, 2016;Prebble et al, 2018). Turnover rates and discrimination factors for this tissue type are still unknown.…”

St. Helena: An Important Reproductive Habitat for Whale Sharks (Rhincodon typus) in the Central South Atlantic

“…Further information regarding each receiver is provided in Table 3. Fox et al, 2013), yet lower than that estimated at coastal sites such as Donsol (50 days, McCoy et al, 2018) or Tanzania (31 days, Prebble et al, 2018). These estimates of residency using photo-ID data are supported by the acoustic telemetry findings, where detection peaks at various stations were 2-3 weeks apart (Figure 12).…”