Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater.

Understanding the behaviour of animals in the wild is fundamental to conservation efforts. Advances in bio-logging technologies have offered insights into the behaviour of animals during foraging, migration and social interaction. However, broader application of these systems has been limited by device mass, cost and longevity.

Modelling the prey detection performance of Rhinonicteris aurantia (Chiroptera: Hipposideridae) in different atmospheric conditions discounts the notional role of relative humidity in adaptive evolution.

We examined a recent notion that differences in echolocation call frequency amongst geographic groups of constant frequency (CF)-emitting bats is the result of a trade-off between maximising prey detection range at lower frequencies and enhancing small-prey resolution at higher frequencies in different atmospheric (relative humidity; RH) environments. Isolated populations of the endemic Australian orange leaf-nosed bat Rhinonicteris aurantia were used as an example since geographic isolation in different environments has been a precursor to differences in their characteristic echolocation call frequencies (mean difference c. 6 kHz; means of 114.