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Animal group dynamics have often been studied by biologists through the use of mathematical models and statistical analyses. Wildebeest herds (Connochaetes taurinus) occur in large numbers and follow certain migration patterns throughout the year. However, it is not known whether the aggregation patterns of migrating wildebeest herds follow predictable statistical distributions. In this work, we investigated whether social interactions between individual wildebeest can generate the observed distribution patterns of herds based on empirical data of wildebeest in the Serengeti, Tanzania. We quantified the distribution of real herds by analyzing the frequency distribution of wildebeest counts in aerial survey images collected in 2015. We then used a Lagrangian model of animal interactions to simulate individual movement and herd aggregation patterns. We equipped the model with parameter values that matched empirical distributions. Our results from the empirical data analysis reveal that wildebeest herds follow a truncated power law in their aggregation patterns. We claim that this behaviour can be explained by social interactions between individual wildebeest.

An investigation of power law distribution in wildebeest (Connochaetes taurinus) herds in Serengeti National Park, Tanzania