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

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