Data from: Spatial patterning of prey at reproduction to reduce predation risk: what drives dispersion from groups?

• Main Authors: DeMars, Craig, Breed, Greg, Potts, Jonathan, Boutin, Stan
• Format: Dataset
• Language: unknown
• Published: Data Archiving and Networked Services (DANS) 2020
• Subjects: Life sciences; medicine and health care; Behavior: antipredator; Modeling: predator/prey; Behavior: social; Rangifer tarandus; Canis lupus; envir; info
• Online Access: https://doi.org/10.5061/dryad.vr0kc

Group-living is a widespread behaviour thought to be an evolutionary adaptation for reducing predation risk. Many group-living species, however, spend a portion of their life cycle as dispersed individuals, suggesting that the costs and benefits of these opposing behaviours vary temporally. Here, we evaluated mechanistic hypotheses for explaining individual dispersion as a tactic for reducing predation risk at reproduction (i.e. birthing) in an otherwise group-living animal. Using simulation analyses parameterized by empirical data, we assessed whether dispersion increases reproductive success by: (i) increasing predator search time, (ii) reducing predator encounter rates because individuals are inconspicuous relative to groups, or (iii) eliminating the risk of multiple kills per encounter. Simulations indicate that dispersion only becomes favourable when detectability increases with group size and there is risk of multiple kills per encounter. This latter effect, however, is likely the primary mechanism driving females to disperse at reproduction because group detectability effects are presumably constant year round. We suggest that the risk of multiple kills imposed by highly vulnerable offspring may be an important factor influencing dispersive behaviour in many species and conservation strategies for such species will require protecting sufficient space to allow dispersion to effectively reduce predation risk. Wolf GPS location data from DeMars et al.GPS location data from 15 wolves. This data was used to parameterize the simulation model contained in DeMars et al. Please read the README file for data attributes.DeMars_et_al_data.xlsx