Despite the fact that nonlinearities are present in the calls of a number of different species, their adaptive function has received little empirical investigation. Previous studies have demonstrated that playbacks of nonlinear calls evoke a more extreme behavioural response and lead to an increase in responsiveness compared with control playbacks without nonlinearities. Consequently, it has been suggested that nonlinearities might prevent receivers from habituating, by increasing the unpredictability of the call (‘unpredictability hypothesis’). In this study, we tested the unpredictability hypothesis, specifically whether nonlinearities prevent receivers from habituating, by means of a playback experiment using meerkat (Suricata suricatta) alarm calls. We found that in meerkats, playbacks of naturally occurring nonlinear alarm calls take longer to habituate to than alarm calls without any nonlinear intrusions. These data provide important empirical support for the hypothesis that nonlinearities are not just an irrelevant by‐product of the vocal production system, but indeed function adaptively.

Small and cryptic species are challenging to detect and study in their natural habitat. Many of these species are of conservation concern, and conservation efforts may be hampered by the lack of basic information on their ecological needs. Brown hare (Lepus europaeus) leverets - one example of such a small, cryptic and endangered animal - are notoriously difficult to detect, and therefore data on wild leverets are virtually non-existent. Novel technologies and methods such as thermal imaging and the use of wildlife detection dogs represent suitable means for the detection of such species by overcoming the problem of camouflage, using heat or scent emission respectively. Our study on brown hare leverets provides information on how to apply these new techniques successfully for the detection of small and cryptic species, thus enabling the collection of data that was previously inaccessible (e.g. behavioural observation, radio tagging). We found that the choice of method should be made according to vegetative structure. While the handheld thermal imaging camera is best used in areas with no or low vegetative cover, the thermal drone can be used up to medium vegetative cover, whereas the detection dog method is best applied where vegetation is very dense and not suitable to be searched using thermography. Being able to search all sort of different vegetation types, our combined approach enables the collection of a balanced and unbiased dataset regarding habitat type and hence selection of study specimen. We hope that the use of these new techniques will encourage research on many cryptic species that formerly have been neglected because they could not be detected using conventional methodologies.

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