ArticleMovement ecology2020
Understanding decision making in a food-caching predator using hidden Markov models.
Article in Movement ecology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Understanding Sex-Specific Behavioral States of Bobcats in Response to Highway Proximity in South Texas.Ecology and evolution · 2026Article
- Anthropogenic Infrastructures Shape Brown Bear Movements in Human-Modified Landscapes.Ecology and evolution · 2026Article
- Movement phases make a difference in habitat selection: Iberian lynx diversity of responses to human-modified landscapes.The Journal of animal ecology · 2025Article
- Effects of urbanisation on the movements of an arboreal specialist using hidden Markov models.Movement ecology · 2025Article
- Rest to roam: behavioural adaptations of tigers in anthropogenically altered landscapes.Movement ecology · 2025Article
- Hidden Markov Model-Based Behavioral Classification Reveals Visual Function Recovery After Retinal Organoid Transplantation in Mice.Journal of neuroscience research · 2025Article
- Tracking the Ghosts of the Himalayas: Snow Leopard Conservation Insights From Satellite Collar Data.Ecology and evolution · 2025Article
- Hidden Markov models reveal behavioral state dynamics in depth-related locomotion in mice.PloS one · 2025Article
- Movement behavior in a dominant ungulate underlies successful adjustment to a rapidly changing landscape following megafire.Movement ecology · 2024Article
- Multiphasic movement and step-selection patterns of dispersed tigers in the central Indian landscape.PloS one · 2024Article
- Intraspecific interactions in a high-density leopard population.Ecology and evolution · 2021Article
- Digging into the behaviour of an active hunting predator: arctic fox prey caching events revealed by accelerometry.Movement ecology · 2021Article
- The effect of competing carnivores on the feeding behaviour of leopards (Ecology and evolution · 2021Article
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5 authors.
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Abstract
backgroundTackling behavioural questions often requires identifying points in space and time where animals make decisions and linking these to environmental variables. State-space modeling is useful for analysing movement trajectories, particularly with hidden Markov models (HMM). Yet importantly, the ontogeny of underlying (unobservable) behavioural states revealed by the HMMs has rarely been verified in the field.
methodsUsing hidden Markov models of individual movement from animal location, biotelemetry, and environmental data, we explored multistate behaviour and the effect of associated intrinsic and extrinsic drivers across life stages. We also decomposed the activity budgets of different movement states at two general and caching phases. The latter - defined as the period following a kill which likely involves the caching of uneaten prey - was subsequently confirmed by field inspections. We applied this method to GPS relocation data of a caching predator, Persian leopard
resultsMultistate modeling provided strong evidence for an effect of life stage on the behavioural states and their associated time budget. Although environmental covariates (ambient temperature and diel period) and ecological outcomes (predation) affected behavioural states in non-resident leopards, the response in resident leopards was not clear, except that temporal patterns were consistent with a crepuscular and nocturnal movement pattern. Resident leopards adopt an energetically more costly mobile behaviour for most of their time while non-residents shift their behavioural states from high energetic expenditure states to energetically less costly encamped behaviour for most of their time, which is likely to be a risk avoidance strategy against conspecifics or humans.
conclusionsThis study demonstrates that plasticity in predator behaviour depending on life stage may tackle a trade-off between successful predation and avoiding the risks associated with conspecifics, human presence and maintaining home range. Range residency in territorial predators is energetically demanding and can outweigh the predator's response to intrinsic and extrinsic variables such as thermoregulation or foraging needs. Our approach provides an insight into spatial behavior and decision making of leopards, and other large felids in rugged landscapes through the application of the HMMs in movement ecology.
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