Is pre-breeding prospecting behaviour affected by snow cover in the irruptive snowy owl? A test using state-space modelling and environmental data annotated via Movebank

Movement Ecology

Joël Bety¹  Keith L Bildstein²  Nicolas Lecomte⁵  Gilles Gauthier⁴  David Pinaud³  Jean-François Therrien² 

[1] Département de Biologie & Centre d’Études Nordiques, Université du Québec à Rimouski, Québec G5L 3A1, Canada;Hawk Mountain Sanctuary, Acopian Center for Conservation Learning, Orwigsburg 17961, PA, USA;CEBC, UMR7372, CNRS/Univ La Rochelle, 79360 Villiers en Bois, La Rochelle, France;Département de Biologie & Centre d’Études Nordiques, Université Laval, Québec G1V 0A6, Canada;Canada Research Chair in Polar and Boreal Ecology, Université de Moncton, Moncton E1A 3E9, Canada

关键词: State-space model;    Snowy owl;    Snow;    Pre-breeding movements;    Movebank;    Env-DATA;    Dispersal;   

Others  :  1132166
DOI  :  10.1186/s40462-015-0028-7

 received in 2014-10-15, accepted in 2015-01-05,  发布年份 2015

【 摘 要 】

Background

Tracking individual animals using satellite telemetry has improved our understanding of animal movements considerably. Nonetheless, thorough statistical treatment of Argos datasets is often jeopardized by their coarse temporal resolution. State-space modelling can circumvent some of the inherent limitations of Argos datasets, such as the limited temporal resolution of locations and the lack of information pertaining to the behavioural state of the tracked individuals at each location. We coupled state-space modelling with environmental characterisation of modelled locations on a 3-year Argos dataset of 9 breeding snowy owls to assess whether searching behaviour for breeding sites was affected by snow cover and depth in an arctic predator that shows a lack of breeding site fidelity.

Results

The state-space modelling approach allowed the discrimination of two behavioural states (searching and moving) during pre-breeding movements. Tracked snowy owls constantly switched from moving to searching behaviour during pre-breeding movements from mid-March to early June. Searching events were more likely where snow cover and depth was low. This suggests that snowy owls adapt their searching effort to environmental conditions encountered along their path.

Conclusions

This modelling technique increases our understanding of movement ecology and behavioural decisions of individual animals both locally and globally according to environmental variables.

【 授权许可】

   
2015 Therrien et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

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