Data analysis
We used logistic regression to determine the effects of spatial distance, genetic differentiation (using pairwiseFST values), social form, within-mound relatedness coefficients between workers, and site on whether or not untreated mounds shared with the treated mound. To do this, we constructed generalized linear models with a binomial distribution using the glm function in base R statistical software v3.6.1 (R Core Team, 2019). Distance from the treated mound, pairwise FST values (compared between the treated and untreated mounds), social form of both treated and untreated mounds (i.e., monogyne or polygyne), within-mound relatedness coefficients between workers in both treated and untreated mounds, and site were treated as independent variables. The sharing status of the untreated mounds (i.e., “shared with the treated mound” or “did not share with the treated mound”) was the dependent, binary variable. Mounds that were identified as having shared with the treated mound had\(\delta\)15N values greater than 20‰, as these values were far higher than any natural abundance isotope values observed at our field sites (mean natural abundance \(\delta\)15N values before tracer treatment: 5.00‰ ± 0.15‰). Untreated mounds could only have attained \(\delta\)15N values greater than 20‰ by freely exchanging workers and/or resources with the treated mound. All other mounds were designated as “did not share with the treated mound.” All plots were generated using ggplot2 (Wickham, 2016).