Graph Coloring Techniques for Mapping Animal Social Networks and Ineractions

Abstract

Animal social networks are complex systems of interactions that influence various aspects of their lives, from mating and foraging to disease transmission and survival. This paper explores the application of graph coloring techniques as a powerful tool for analyzing these intricate networks. We examine various graph coloring algorithms, including greedy coloring, Welsh-Powell algorithm, DSATUR algorithm, and constraint satisfaction algorithms, discussing their strengths and limitations in the context of animal social network analysis. Through a case study on dolphin social networks and examples from primate troops, bird flocks, insect colonies, and fish schools, we illustrate how graph coloring can reveal hidden social structures, hierarchies, and individual roles. We also address challenges in data collection and network dynamics, and propose future directions for research, such as integrating multiple data sources, developing dynamic graph coloring algorithms, and incorporating behavioral data. This paper highlights the significant potential of graph coloring techniques in advancing our understanding of animal behavior, ecology, and evolution.