Optimizing the search for resources by sharing information: Mongolian gazelles as a case study

Area of Science:

• Behavioral Ecology
• Mathematical Biology
• Animal Communication

Background:

• Efficient search strategies are crucial for survival and resource acquisition in many species.
• Communication can influence collective search behavior, but its impact on efficiency is complex.
• Understanding how information exchange affects search dynamics is key in behavioral ecology.

Purpose of the Study:

• To model the relationship between communication and search efficiency in a biological context.
• To investigate how long-range pairwise interactions affect search dynamics.
• To apply the model to Mongolian gazelles searching for habitat areas using acoustic communication.

Main Methods:

• Development of a mathematical model for Brownian searchers with long-range interactions.
• Analysis of model properties using density equations.
• Monte Carlo simulations to study search efficiency and communication scales.
• Application to empirical data on Mongolian gazelles' acoustic communication.

Main Results:

• The model demonstrates that search efficiency, measured by mean first hitting time, is optimized at intermediate communication scales.
• Both excessive and insufficient communication negatively impact search performance.
• Acoustic communication in Mongolian gazelles searching for habitat areas serves as a case study.

Conclusions:

• Communication plays a critical role in optimizing collective search behavior.
• There exists an optimal range for communication signals to maximize search efficiency.
• Deviations from this optimal communication scale can lead to reduced foraging success.