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Title: Using Referential Alarm Signals to Remotely Quantify 'Landscapes of Fear' in Fragmented Woodland
Contributor(s): McDonald, Paul  (creator)orcid ; Doohan, Samantha (creator); Eveleigh, Kyia (creator)
Publication Date: 2021-12-15
DOI: 10.25952/bthq-5q25
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Abstract/Context: 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.
Publication Type: Dataset
Fields of Research (FoR) 2020: 310901 Animal behaviour
310301 Behavioural ecology
310308 Terrestrial ecology
Socio-Economic Objective (SEO) 2020: 280102 Expanding knowledge in the biological sciences
Keywords: Bioacoustics
Noisy Miner
Ecology of Feare
Location: Armidale, New South Wales, Australia
HERDC Category Description: X Dataset
Project: Using Referential Alarm Signals to Remotely Quantify 'Landscapes of Fear' in Fragmented Woodland
Dataset Managed By: Paul McDonald
Rights Holder: Paul McDonald
Dataset Stored at: University of New England
Primary Contact Details: Paul McDonald -
Dataset Custodian Details: Paul McDonald -
Appears in Collections:Dataset
School of Environmental and Rural Science

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