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Showing posts from August, 2020

Random Returns Are Not Random

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The statistical-mechanical universality class Multi-scaled random walk (MRW) is a relatively recent addition to the menagerie of various types of random walk (RW). It seeks to capture some key aspects of animal space use, in particular the combined effects of spatio-temporal memory and scale-free movement. In this post I put focus on the statistical property of return events to previously visited positions (memory-dependent site fidelity). How can such events feasibly and realistically be treated as random, knowing that the animal by targeted returns will tend to revisit more profitable patches with a higher probability than other locations? In particular, one specific aspect of the answer, revealed here in detail for the first time, will probably surprise you. Complexity turned into simplicity!What regards the the transition from deterministic behaviour to a RW process in general terms, search my blog for "Markov", or you may for example look into Gautestad (2013). To place…

Roe Deer Comply With the MRW Model

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Animal space use expresses a balance between exploring new localities and returning to the known. However, as stated by Ranc et al. (2020), the link between spatio-temporal resource patterns and animal movement has so far found limited experimental support. In their paper they found that following the loss of the individuals' preferred resource, roe deer Capreolus capreolus actively tracked resource dynamics leading to more exploratory movements, and larger, spatially-shifted home ranges. They also demonstrated the return of individuals to their familiar, preferred resource patches after local resource restoration. On the background of this interesting and dynamic habitat manipulation, I have allowed myself to drill into the raw GPS data as provided by their paper's Supplementary material. How does space use by roe deer fit the Multi-scaled random walk (MRW) property of scale-free, memory-utilizing space use?

Choosing a biophysical universality class of movement that best compl…