A statistical framework for inferring the influence of conspecifics on movement behaviour
Article first published online: 24 JAN 2014
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
Methods in Ecology and Evolution
Volume 5, Issue 2, pages 183–189, February 2014
How to Cite
Delgado, M. d. M., Penteriani, V., Morales, J. M., Gurarie, E., Ovaskainen, O. (2014), A statistical framework for inferring the influence of conspecifics on movement behaviour. Methods in Ecology and Evolution, 5: 183–189. doi: 10.1111/2041-210X.12154
- Issue published online: 13 FEB 2014
- Article first published online: 24 JAN 2014
- Accepted manuscript online: 19 DEC 2013 10:44AM EST
- Manuscript Accepted: 11 DEC 2013
- Manuscript Received: 18 OCT 2013
- Spanish Ministry of Economy and Competitiveness. Grant Number: CGL2012-33240
- Junta de Andalucía. Grant Number: RNM-5090
- Academy of Finland
- European Research Council. Grant Number: ERC StG 205905
- CONICET. Grant Number: PIP 114 – 200801 – 00276
- behavioural rules;
- condition-dependent dispersal;
- mixed-effect model;
- social information;
- statistical inference
- The movements of individuals – at almost any scale – are likely to depend on the behaviour of conspecifics. As an example, the movements of dispersing juveniles and their settling decisions may depend on the availability of mates and free territories, that is, both the presence and absence of other individuals. As another example, individuals can use the presence of conspecifics during foraging movements as an indicator of habitat quality.
- We develop a general statistical framework for identifying and characterizing conspecific influence on movements from tracking data acquired simultaneously from a set of potentially interacting individuals.
- We model conspecific attraction/repulsion through a functional response in which social behaviour is assumed to depend on proximity to other individuals. The model partitions variation in the functional response into a population component (common to all individuals), variation among individuals (modelled as random intercept-slope) and variation within an individual's trajectory (modelled through temporal autocorrelation).
- We present a Bayesian approach for the estimation of the model and illustrate its use with simulated movement data generated from a number of contrasting scenarios. We then apply the method to a case study on eagle owl Bubo bubo juvenile dispersal, demonstrating that individual movements are generally influenced by the presence of conspecifics, with the level of attraction decreasing with increasing proximity to other individuals. We further show that female eagle owls are more attracted to conspecifics than males, and both males and females are more attracted to females than to males.