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An application of upscaled optimal foraging theory using hidden Markov modelling: year-round behavioural variation in a large arctic herbivore.

Larissa T BeumerJennifer PohleNiels Martin SchmidtMarianna ChimientiJean-Pierre DesforgesLars H HansenRoland LangrockStine Højlund PedersenMikkel StelvigFloris M van Beest
Published in: Movement ecology (2020)
Our results clearly indicate that female muskoxen follow an energy intake maximisation strategy during the arctic summer. During winter, our results were not easily reconcilable with just one dominant foraging strategy. The overall reduction in activity likely reflects higher time requirements for rumination in response to the reduction of forage quality (supporting an energy intake maximisation strategy). However, deep snow and low temperatures were apparent constraints to winter foraging, hence also suggesting attempts to conserve energy (net energy maximisation strategy). Our approach provides new insights into the year-round behavioural strategies of the largest Arctic herbivore and outlines a practical example of how to approximate qualitative predictions of upscaled optimal foraging theory using multi-year GPS tracking data.
Keyphrases
  • climate change
  • systematic review
  • big data
  • weight gain
  • machine learning
  • physical activity
  • electronic health record
  • body mass index
  • quality improvement
  • artificial intelligence
  • heat stress