Assessing trade-offs in avian behaviour using remotely collected data from a webcam.

• Published in: PLOS ONE
• Main Authors: Kevin A Wood, Rebecca Lacey, Paul E Rose
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2022
• Subjects: Medicine; R; Science; Q; Olor; Cygnus cygnus; Whooper Swan
• Online Access: https://doi.org/10.1371/journal.pone.0271257; https://doaj.org/article/b97302b75ecf4e0d8e169b1c0f2d3255

Individual animals engage in many behaviours which are mutually exclusive, and so where individuals increase the duration of time spent on one type of behavioural activity, this must be offset by a corresponding decrease in at least one other type of behaviour. To understand the variation observed in animal behaviour, researchers need to know how individuals trade-off these mutually-exclusive behaviours within their time-activity budget. In this study, we used remotely collected behavioural observations made from a live-streaming webcam to investigate trade-offs in the behaviour of two bird species, the mute swan (Cygnus olor) and whooper swan (Cygnus cygnus). For both species, we tested for correlations in the duration of time spent on key mutually exclusive behaviours: aggression, foraging, maintenance, and resting. We detected a negative association between aggression and resting behaviours in both species, indicating that increased aggression is achieved at the expense of resting behaviour. In contrast, there was no apparent trade-off between aggression and foraging, aggression and maintenance, or maintenance and resting. Foraging and resting behaviours were negatively correlated in both species, highlighting a trade-off between these distinct modes of behaviour. A trade-off between foraging and maintenance behaviours was detected for the sedentary mute swans, but not the migratory whooper swans. Our findings show how birds can trade-off their time investments in mutually exclusive behaviours within their time-activity budgets. Moreover, our study demonstrates how remotely-collected data can be used to investigate fundamental questions in behavioural research.