Optimizing the Search for Resources by Sharing Information: Mongolian Gazelles as a Case Study

Abstract

We investigate the relationship between communication and search efficiency in a biological context by proposing a model of Brownian searchers with long-range pairwise interactions. After a general study of the properties of the model, we show an application to the particular case of acoustic communication among Mongolian gazelles, for which data are available, searching for good habitat areas. Using Monte Carlo simulations and density equations, our results point out that the search is optimal (i.e., the mean first hitting time among searchers is minimum) at intermediate scales of communication, showing that both an excess and a lack of information may worsen it.