Acoustic activity across a seabird colony reflects patterns of within‐colony flight rather than nest density. (27th June 2019)

• Record Type: Journal Article
• Authors: Arneill, Gavin E.; Critchley, Emma Jane; Wischnewski, Saskia; Jessopp, Mark J.; Quinn, John L.
• Is Part Of: Ibis. Volume 162:Number 2(2020)
• Page Start: 416
• Page End: 428
• Publication Date: 2019-06-27
• Subjects: acoustic indices -- burrow‐nesting seabird -- census methods -- passive acoustic monitoring -- procellariiformes -- telemetry; Birds -- Periodicals; 598
• DOI: 10.1111/ibi.12740
• Languages: English
• ISSNs: 0019-1019

Abstract

Abstract : Passive acoustic monitoring is increasingly being used as a cost‐effective way to study wildlife populations, especially those that are difficult to census using conventional methods. Burrow‐nesting seabirds are among the most threatened birds globally, but they are also one of the most challenging taxa to census, making them prime candidates for research into such automated monitoring platforms. Passive acoustic monitoring has the potential to determine presence/absence or quantify burrow‐nesting populations, but its effectiveness remains unclear. We compared passive acoustic monitoring, tape‐playbacks and GPS tracking data to investigate the ability of passive acoustic monitoring to capture unbiased estimates of within‐colony variation in nest density for the Manx Shearwater Puffinus puffinus . Variation in acoustic activity across 12 study plots on an island colony was examined in relation to burrow density and environmental factors across 2 years. As predicted fewer calls were recorded when wind speed was high, and on moon‐lit nights, but there was no correlation between acoustic activity and the density of breeding birds within the plots as determined by tape‐playback surveys. Instead, acoustic indices correlated positively with spatial variation in the in‐colony flight activity of breeding individuals detected by GPS. Although passive acoustic monitoring has enormous potential in avian conservation, our results highlight the importance of understanding behaviour when using passive acoustic monitoring to estimate density and distribution.