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https://hdl.handle.net/1959.11/55711
Title: | Using referential alarm signals to remotely quantify 'landscapes of fear' in fragmented woodland |
Contributor(s): | McDonald, Paul G (author) ; Doohan, Samantha J (author); Eveleigh, Kyia J (author) |
Publication Date: | 2022 |
Early Online Version: | 2021-12-20 |
DOI: | 10.1080/09524622.2021.2013319 |
Handle Link: | https://hdl.handle.net/1959.11/55711 |
Abstract: | | Land-use changes have greatly impacted biodiversity and led to new conservation challenges, including greater predation pressure, although this can be difficult to quantify. Here we directly monitor predator encounters in fragmented woodlands by using passive acoustic monitoring (PAM) and a semiautomated assessment protocol to detect functionally referential alarm vocalisations of the noisy miner Manorina melanocephala. We demonstrate that measuring changes in perceived predation pressure, the so-called 'landscape of fear', in a prey species across temporal (dawn, midday, dusk across multiple seasons) and spatial scales (small/large fragments and edge/ centre locations within fragments) is achievable. Vocalisations linked with ground predator presence were rarer during midday recordings, but more commonly detected from the edge rather than centre of smaller fragments. While the probability of detecting aerial alarm calls directed at flying raptors also increased in edge habitat, aerial alarm detections declined from a dawn peak to a minimum during dusk recordings. These patterns did not simply reflect noisy miner occupancy or different sections of monitored patches, but highlighted higher perceived predation risk along edges, particularly for small patches, demonstrating the nuanced insights that PAM can offer when quantifying animal behaviour
Publication Type: | Journal Article |
Source of Publication: | Bioacoustics, 31(6), p. 629-645 |
Publisher: | Taylor & Francis |
Place of Publication: | United Kingdom |
ISSN: | 2165-0586 0952-4622 |
Fields of Research (FoR) 2020: | 310901 Animal behaviour 310301 Behavioural ecology 310405 Evolutionary ecology |
Socio-Economic Objective (SEO) 2020: | 280102 Expanding knowledge in the biological sciences |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Environmental and Rural Science
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