Data from: From randomness to traplining: a framework for the study of routine movement behavior
Cite this dataset
Riotte-Lambert, Louise; Benhamou, Simon; Chamaillé-Jammes, Simon (2016). Data from: From randomness to traplining: a framework for the study of routine movement behavior [Dataset]. Dryad. https://doi.org/10.5061/dryad.8sj5g
Memory allows many animals to benefit from the spatial predictability of their environment by revisiting known profitable places. Travel route optimization or resource acquisition constraints usually lead to repeated sequences of visits, which may have major evolutionary and ecological implications. However, the study of this behavior has been impaired by a lack of concepts and methodologies. We here formally define routine movement behavior, provide an index that quantifies the degree of repetitiveness in movement sequences in terms of minimal conditional entropy, and design a flexible procedure that detects the specific subsequences that are repeated. We demonstrate our framework using computer simulations and real-world movement data of black-tailed deer (Odocoileus hemionus) introduced into a novel environment. The simulation example showed that our methods can suitably reveal the increase in the level of routine movement behavior during home range (HR) establishment. Black-tailed deer did not show such an increase, suggesting that HR establishment occurred very fast. In both examples, our procedure determining the subsequences that are repeated provides a precise visualization of routine movements. Our approach solves limitations in the study of routine movement behavior and thus opens promising perspectives for the study of the linkages between cognition, foraging strategies, and environments. Although we developed it to study routine movement behavior, it can be applied to any type of behavioral sequence and should thus be of interest to a broad range of behavioral ecologists.