Static and dynamic methods in social network analysis reveal the association patterns of desert-dwelling giraffe


Patterns of association in animal societies vary through space and time. Understanding such variation is key to predicting inter- and intra-population variation across factors as diverse as gene flow, disease transmission, and resilience to climate change. Here, we use 3.5 years of observational data, coupled with static and dynamic methods in social network analysis, to investigate patterns of social association in wild giraffe in the northern Namib Desert, Namibia (a habitat of extreme aridity for the species). Our static analyses reveal similar robust nested social communities, but less distinct community structures, than those found in giraffe populations inhabiting less arid environments. Furthermore, results of our dynamic social network analyses show increased social connectivity in this population during the morning and hot-dry season. These temporal patterns align with patterns of thermoregulatory and sociosexual behaviour in this population. However, they differ from temporal patterns of connectivity revealed in populations in less arid environments. Combined, results of both our static and temporal analyses suggest that while the major characteristics of giraffe society persist through space and time, there is substantial variation in the strength of patterns of social connectivity both within and between populations at multiple spatiotemporal resolutions.

Behavioral Ecology and Sociobiology