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

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.

Figure 1

Search time using Eq. (3) for the density of individuals (left) with $B_g=0.50$, $B_c=50$, $D=0.75$ and the individual based description (right) with $B_g=0.50$, $B_c=0.75$, $D=0.05$. $\kappa =0.85g_{\max }$ in both panels.

Figure 2

Mean arrival time for 500 gazelles (averaged over 50 realizations with different initial conditions). Parameter values: $D=74{\mathrm{km}}^2{\mathrm{day}}^{-1}$, $B_g=2.6\times {10}^{-3}{\mathrm{km}}^3{\mathrm{day}}^{-1}$, $B_c=13{\mathrm{km}}^2{\mathrm{day}}^{-1}$, $\kappa =0.70g_{\max }$.

Figure 3

Spatial distribution of 500 gazelles after 1 month (reflecting boundary conditions). $\nu =0.1\mathrm{kHz}$ (top), $\nu =1\mathrm{kHz}$ (bottom left), $\nu =15.8\mathrm{kHz}$ (bottom right). The size of the star is related to the size of the group at a position. Real data resources landscape.