Heterogeneous patterns of availability for detection during visual surveys: spatiotemporal variation in sea turtle dive-surfacing behaviour on a feeding ground

1. During aerial or boat-based surveys for large-bodied diving taxa (e.g. marine mammals and marine turtles), a proportion of animals present will be missed because they are submerged and out of view, leading to ‘availability bias’ in abundance indices. Information on dive–surfacing patterns can improve corrections for availability bias. However, as dive data are typically limited, availability correction factors are often based on poorly resolved dive and surface times, and diving heterogeneity is not considered. 2. We collected dive records for green turtles Chelonia mydas, Linnaeus 1758, and loggerhead turtles Caretta caretta, Linnaeus 1758, on a foraging ground in Shark Bay, Western Australia to quantify dive–surfacing patterns and assess potential correlations with easily measured environmental features: habitat depth and water temperature. Bayesian regression models were used to predict dive and surface interval durations across temperature–depth gradients and assess their uncertainty. We used these predictions to quantify variation in availability correction factors, which were multipliers designed, in this case, to adjust surface sightings data to incorporate diving animals. 3. Dive and surface interval durations for both species varied positively with depth and negatively with temperature, consistent with a priori expectations, although temperature effects were not always significant. Dive metrics were predictable, although uncertainty increased in deeper habitat with few observed dives. 4. Availability correction factors were highly heterogeneous, with larger corrections necessary in colder, deeper conditions (long-diving, infrequent surfacing behaviour) and smaller corrections required in warmer, shallower conditions (short-diving, frequent-surfacing behaviour). 5. Predictable variation in the diving behaviour of chelonid sea turtles across environmental gradients on a foraging ground reveals that site-specific knowledge of dive–surfacing patterns can be important to mitigate the effects of availability bias during population surveys. Accounting for such trends may improve the reliability of ecological inferences (e.g. spatiotemporal distribution trends) and the efficacy of applications (e.g. conservation planning) based on survey data.