The evolutionary origins of Lévy walk foraging
Fig 10
Output distribution of step lengths for a μ = 2.0 Lévy searcher in a low-dense landscape (lt = 100).
In the sparse regime, the number of truncated moves due to targets encounters is relatively low and long steps are much more frequent, if compared to the super-dense limit (see inset). Statistical data inference (MLE and AIC methods) indicates that the output distribution of step lengths in the low-dense regime is actually a power-law (Lévy-like), with best-fit exponent μ = 2.19 close to the original one.