ArticleMovement ecology2022
Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy.
Article in Movement ecology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- An introduction to statistical models used to characterize species-habitat associations with animal movement data.Movement ecology · 2025Review
- Salinity drives the distribution of a top-order predator, the tiger shark (Galeocerdo cuvier), in an inverse estuary.Scientific reports · 2025Article
- Hidden Markov models reveal behavioral state dynamics in depth-related locomotion in mice.PloS one · 2025Article
- Article
- Telemetry without collars: performance of fur- and ear-mounted satellite tags for evaluating the movement and behaviour of polar bears.Animal biotelemetry · 2024Article
- Flexible hidden Markov models for behaviour-dependent habitat selection.Movement ecology · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundChange in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible.
methodsWe used movement data from 14 polar bears (Ursus maritimus) in Hudson Bay, Canada, during the foraging season (January-June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior.
resultsPolar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion.
conclusionsOur observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat.
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