Abstract

Topic: Movements and habitat use

What are you doing today? Hidden Markov Models give insights into moose behaviour

Bruno Esattore¹, Fredrik Stenbacka², Göran Ericsson², Wiebke Neumann²

Swedish University of Agricultural Sciences, Skogsmarksgränd, 907 36, Umeå, Sweden, Sweden
Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden

Direct observations of animals are a highly reliable way to define behavioural characteristics, although the elusive nature of some species and the complexity of their habitats often make direct observation logistically challenging, if not impossible. The rise of remote sensing technologies in the last decades has revolutionized the study of animal behaviour, enabling detailed investigations of space use, activity patterns, and even long-term, cross-context inter-individual differences, commonly referred to as animal personality. While evidence of personality exists across a broad range of taxa, the behavioural consistency and personality traits of large, long-lived, free-ranging herbivores remain largely unexplored. Moose (Alces alces), as dominant browsers in boreal ecosystems, have significant ecological impacts, particularly in human-modified landscapes. In this study, we analyse multi-year GPS and activity data from 51 free-ranging moose (39 females, 12 males) in Ljusdal, Gävleborg County, North-Central Sweden, to investigate behavioural variation and personality traits. Using a hidden Markov model framework, we characterize behavioural sequences, quantifying the probability of transitioning between different states (e.g., resting, feeding/short distance movement, and travelling), and assessing how behavioural states are influenced by subject-specific factors (e.g., sex) and time-dependent covariates (e.g., time of day). We believe that a throughout understanding of personality-driven behavioural variation in moose could provide valuable insights into their ecological impact and interactions with human-dominated landscapes, and that this new perspective may offer new opportunities for more effective personality-based management strategies.