Abstract
The Lévy walk is found from amoebas to humans and has been described as the optimal strategy for food research. Recent results, however, have generated controversy about this conclusion since animals also display alternatives to the Lévy walk such as the Brownian walk or mental maps and because movement patterns found in some species only seem to depend on food patches distribution. Here I show that movement patterns of chacma baboons do not follow a Lévy walk but a Brownian process. Moreover this Brownian walk is not the main process responsible for movement patterns of baboons. Findings about their speed and trajectories show that baboons use metal maps and memory to find resources. Thus the Brownian process found in this species appears to be more dependent on the environment or might be an alternative when known food patches are depleted and when animals have to find new resources.
Highlights
Particles suspended in a fluid, air or water move in a random way called Brownian motion [1,2,3]
This study shows that chacma baboons present evidence of random walks in their daily trajectories
This study shows, that this group of chacma baboons does not use the Levy walk but rather a Brownian process
Summary
Particles suspended in a fluid, air or water move in a random way called Brownian motion [1,2,3]. The probability distribution of step length is exponential whereas in the second case it is power-law This Levy walk was defined as an optimal strategy for a forager searching without information about its heterogeneous environment with low density food patches [3,4,8]. There has been growing interest in the Levy walk and this strategy is reported in many species such as soil amoebas [9], zooplankton [5], jackals [10], albatrosses [11] and elephants [12] This similarity between these phylogenetically distant species suggests that random walks are efficient and adaptive. Some studies cast doubt on Levy walks as an optimal strategy existing in animals, first because of methodological shortcomings in the estimation of power-law exponents and because of the impact of resource distribution and the probability of species’ cognitive abilities being sufficient to find this strategy [3,13,14,15]
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