Data from: Social networks reveal sex- and age-patterned social structure in Butler's Gartersnakes

Description

Other

Funding provided by: Natural Sciences and Engineering Research Council
Crossref Funder Registry ID: https://ror.org/01h531d29
Award Number: RTI-2020-00738

Methods

We examined the influence of sex, age, and body condition on social patterns in Butler's gartersnakes. We did so with data from a long-term capture-mark-recapture project monitoring a population of snakes under threat from a road construction project. Coverboards were primarily used to locate the snakes across a ~2 ha area with 3 major sampling sites. The sex, weight, and snout-vent length (SVL) of the snakes were recorded at the time of capture as well as the sampling site, the exact location, and the time. Body condition was defined by the scaled mass index which is derived from weight and SVL. Weight was used as a proxy for age. Social networks were constructed from the capture time and location data, and we modeled the relationship between demographic factors, weighted degree, and community betweenness. To derive community betweenness, we subdivided our networks into communities of individuals who tended to associate with each other and calculated the betweenness of the individuals within these communities. We additionally examined sex and age homophily as well as the order of arrival of dyads that shared a capture location. Below, we outline how we used these data to construct social networks and how we then analyzed the resulting data set.

The social networks were constructed based on the temporal and physical proximity of the snakes at the time of capture. In the resulting networks, the edges represent the probability of an association occurring. As such, a 1 indicates that two snakes were found at the same place and the same time. A value less than 1 indicates that the snakes were found further apart (temporally and/or physically). We constructed networks at different scales of proximity. We identify these as the precise and three broad-scale networks. The precise network is derived only from direct associations. The broad-scale networks expand the possible temporal and physical proximity allowances to include possible associations within 14, 10, or 5 days.

The analysis was done with R v4.2.1. We tested for non-random associations using null models that controlled for temporal and physical space use. To test for intra-species communities, we used a Louvain partition and tested the robustness of the resulting communities compared to communities generated from random graphs using the robin package. To test for relationships between phenotypes and network measures, we used mixed-effect hurdle models with node-label permutations.  We tested the inherent type I error rates of these models by simulating the same analyses but with randomly generated values for our independent variables. We derived homophily values from the networks using the igraph package and tested them against values derived from permutated graphs. To examine the order of arrival in shared space, we designated snakes as leaders and followers based on their order of capture at the same location - with leaders captured first. We then used a multi-membership model constructed with the brms package to examine the relationship between sex and age on the order of arrival. More details on these analyses are available in the manuscript and/or by request.