2 research outputs found

    Undersea constellations: The global biology of an endangered marine megavertebrate further informed through citizen science

    Full text link
    The whale shark is an ideal flagship species for citizen science projects because of its charismatic nature, its size, and the associated ecotourism ventures focusing on the species at numerous coastal aggregation sites. An online database of whale shark encounters, identifying individuals on the basis of their unique skin patterning, captured almost 30,000 whale shark encounter reports from 1992 to 2014, with more than 6000 individuals identified from 54 countries. During this time, the number of known whale shark aggregation sites (hotspots) increased from 13 to 20. Examination of photo-identification data at a global scale revealed a skewed sex-ratio bias toward males (overall, more than 66%) and high site fidelity among individuals, with limited movements of sharks between neighboring countries but no records confirming large, ocean basin-scale migrations. Citizen science has been vital in amassing large spatial and temporal data sets to elucidate key aspects of whale shark life history and demographics and will continue to provide substantial long-term value

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

    Full text link
    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
    corecore