McDonald, Paul

Doohan, Samantha

Eveleigh, Kyia

2021-12-15

These data are derived from both automated and manual screening of passive acoustic monitoring data collected using SM2+ recorders placed in woodland fragments in and around the Armidale region. The focal species of interest was the Noisy Miner (Manorina melanocephala), and three different call types were quantified using the species functionally referential signals: chip (social calls), chur (ground predator) and aerial (aerial predator) vocalisations. These data were then used to assess encounters with perceived predators in both different sized fragments and also locations within or on the edge of these habitats. Together, these were then used to infer the landscape of fear remotely in this system.

https://hdl.handle.net/1959.11/33596

en

University of New England

Using Referential Alarm Signals to Remotely Quantify 'Landscapes of Fear' in Fragmented Woodland

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