Newswise — Many animal species exist in fission-fusion societies, where the size and composition of conspecific groups change spatially and temporally.

To help investigate such phenomena, social network analysis (SNA) has emerged as a powerful conceptual and analytical framework for assessing patterns of interconnectedness and quantifying group-level interactions.

We leveraged behavioral observations via radiotelemetry and genotypic data from a long-term (>10 years) study on the pitviper Crotalus atrox (western diamondback rattlesnake) and used SNA to quantify the first robust demonstration of social network structures for any free-living snake.

Group-level interactions among adults in this population resulted in structurally modular networks (i.e., distinct clusters of interacting individuals) for fidelis use of communal winter dens (denning network), mating behaviors (pairing network), and offspring production (parentage network). Although the structure of each network was similar, the size and composition of groups varied among them.

Specifically, adults associated in moderately sized social groups at winter dens but often engaged in reproductive behaviors—both at and away from dens—with different and fewer partners. Additionally, modules formed by individuals in the pairing network were frequently different from those in the parentage network, likely due to multiple mating, long-term sperm storage by females, and resultant multiple paternity.

Further evidence for fission-fusion dynamics exhibited by this population—interactions were rare when snakes were dispersing to and traversing their spring-summer home ranges (to which individuals show high fidelity), despite ample opportunities to associate with numerous conspecifics that had highly overlapping ranges.

Taken together, we show that long-term datasets incorporating SNA with spatial and genetic information provide robust and unique insights to understanding the social structure of cryptic taxa that are understudied.

MEDIA CONTACT
Register for reporter access to contact details
RELEVANT EXPERTS
Download PDF
168978784388319_ECE-2023-03-00417.R1_Proof_hi.pdf