Data from: Polygyny does not explain the superior competitive ability of dominant ant associates in the African ant-plant, Acacia (Vachellia) drepanolobium
Cite this dataset
Boyle, John H. et al. (2018). Data from: Polygyny does not explain the superior competitive ability of dominant ant associates in the African ant-plant, Acacia (Vachellia) drepanolobium [Dataset]. Dryad. https://doi.org/10.5061/dryad.g0t42
1. The Acacia drepanolobium (also known as Vachellia drepanolobium) ant-plant symbiosis is considered a classic case of species coexistence, in which four species of tree-defending ants compete for nesting space in a single host tree species. Coexistence in this system has been explained by trade-offs in the ability of the ant associates to compete with each other for occupied trees versus the ability to colonize unoccupied trees. 2. We seek to understand the proximal reasons for how and why the ant species vary in competitive or colonizing abilities, which are largely unknown. 3. In this study, we use RADseq derived SNPs to identify relatedness of workers in colonies to test the hypothesis that competitively dominant ants reach large colony sizes due to polygyny, i.e., the presence of multiple egg-laying queens in a single colony. 4. We find that variation in polygyny is not associated with competitive ability; in fact, the most dominant species, unexpectedly, showed little evidence of polygyny. We also use these markers to investigate variation in mating behavior among the ant species, and find that different species vary in the number of males fathering the offspring of each queen. Finally, we show that the nature of polygyny varies between the two commonly polygynous species, Crematogaster mimosae and Tetraponera penzigi: in C. mimosae, queens in the same colony are often related, while this is not the case for T. penzigi. 5. These results shed light on factors influencing the evolution of species coexistence in an ant-plant mutualism, as well as demonstrating the effectiveness of RADseq-derived SNPs for parentage analysis.