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Western Diamondback Rattlesnake interaction matrices for network analysis

Cite this dataset

Davis, Mark (2022). Western Diamondback Rattlesnake interaction matrices for network analysis [Dataset]. Dryad.


Social network ecology is a powerful framework to assess patterns of interconnectedness and identify group-level interactions. We investigated social network structure in a pitviper (Crotalus atrox) to determine if group-level interactions result in network structures for denning, pairing, and parentage. We tested if network centrality was influenced by body length, sex, home range size/location, or generic relatedness. We revealed that networks were structurally modular but not nested. Sex was the only significant predictor of centrality in the parentage network, likely due to high levels of multiple paternity. Genotypic data revealed interacting focal individuals were unlikely to be related in networks; however, analysis of a larger group of subjects suggests kin-association at communal dens. Den selection may be driven by a combination of social preference, experience, and/or genetic relatedness. We demonstrated strong fission-fusion dynamics connected to annual migrations to summer home ranges and use of communal winter dens. Furthermore, both sexes show high fidelity to home ranges and dens, but females occasionally alter den sites, indicating active manipulation of their social environment. Our study illustrates that comprehensive, long-term datasets incorporating social network analysis with spatial and genetic information provide robust and unique insights to understanding social structure of understudied, cryptic taxa.


Animals selected for this study were typically collected at or near known communal dens during egress in spring (March–April). The presence and location of communal rattlesnake dens at the Suizo study site has been known for nearly three decades and reported earlier. All other snakes we processed in this study were collected in late spring and summer (May–September) when they were dispersed in their home ranges.  

Subjects were captured using conventional snake hooks and plastic grabbers. The capture process, which involved grabbing a snake and placing it into a clear plastic tube for temporary restraint (1 m length; diameter varied in size), was done gently and typically required less than 1 min to minimize handling stress. At the time of capture Global Positioning System (GPS) coordinates were collected as Universal Transverse Mercators (UTMs).

Within 24-h of their initial capture, all subjects were measured (snout-vent length, tail length, head dimensions to the nearest millimeter; body mass to the nearest 1.0 g) and sex confirmed (via probing) while under light anesthesia (isoflurane). For subsequent identification, individuals were photographed, implanted with a unique PIT-tag (AVID, Inc., Norco, California, U.S.A.), and their proximal rattle segments were colored using Sharpie pens.

A subset or focal group of adult C. atrox were collected from 2001–2010 and used in the social network analysis (n = 50 focal animals; 22 males 28 females). These subjects were selected for radio-tracking based on their size (e.g., 800 mm SVL or larger) and general state of health. Each animal had an appropriately sized (5% or less of their total body mass) temperature-sensitive radio-transmitter (models SI-2T and AI-2T, 11-16 g; Holohil Inc., Carp, Ontario, Canada) surgically implanted within the coelom following general procedures used for snakes. After processing, all subjects were released at their exact capture site (e.g., communal den).

Over the course of the study, we radio-tracked the snake subjects minimally 2–4 times per month including during winter. Tracking was increased substantially—sometimes daily or twice daily—from early August through mid-September, the period of birthing. For each radio-tracked subject located, UTM coordinates were recorded using a hand-held GPS unit. Other data recorded included behavior, body and environment temperatures, feeding and ecdysis status, plant associations, subject location (above or below the ground surface) and site number, visible or not visible, and health status.

From these data, observational data were collected and converted to interaction matrices with individuals as rows and columns.