PubAg

Main content area

North American red squirrels mitigate costs of territory defence through social plasticity

Author:
Siracusa, Erin R., Wilson, David R., Studd, Emily K., Boutin, Stan, Humphries, Murray M., Dantzer, Ben, Lane, Jeffrey E., McAdam, Andrew G.
Source:
Animal behaviour 2019 v.151 pp. 29-42
ISSN:
0003-3472
Subject:
Tamiasciurus hudsonicus, cross-sectional studies, nests, social environment, squirrels, territoriality, vocalization
Abstract:
For territorial species, the ability to be behaviourally plastic in response to changes in their social environment may be beneficial by allowing individuals to mitigate conflict with conspecifics and reduce the costs of territoriality. Here we investigated whether North American red squirrels, Tamiasciurus hudsonicus, are able to minimize costs of territory defence by adjusting behaviour in response to the familiarity of neighbouring conspecifics. Since red squirrels living in familiar neighbourhoods face reduced intrusion risk, we predicted that increasing familiarity among territorial neighbours would allow squirrels to spend less time on territorial defence and more time in the nest. Longitudinal behavioural data (1995–2004) collected from the same squirrels across several different social environments indicated that red squirrels reduced rates of territorial vocalizations and increased nest use in response to increasing familiarity with neighbours. In contrast, cross-sectional data (2015–2016), which provided observations from each individual in a single social environment, did not provide evidence of this plasticity. Post hoc analyses revealed that evidence of social plasticity in this system is primarily due to within-individual changes in behaviour, which we were unable to estimate in the cross-sectional data. Our results demonstrate that red squirrels respond to changes in their social environment by adjusting their behaviour in a manner that reduces the costs of territoriality. However, our results also suggest that estimating plasticity by comparing behaviour among individuals (i.e. cross-sectional analyses) may not always be reliable. Our ability to detect these effects may therefore depend on having data with multiple observations from the same individuals across different social environments.
Agid:
6316019