Data from: Achromatic plumage brightness predicts stress resilience and social interactions in tree swallows (Tachycineta bicolor)
Taff, Conor C.; Zimmer, Cedric; Vitousek, Maren N. (2019), Data from: Achromatic plumage brightness predicts stress resilience and social interactions in tree swallows (Tachycineta bicolor), Dryad, Dataset, https://doi.org/10.5061/dryad.46mm022
Theory suggests that signal honesty may be maintained by differential costs for high and low quality individuals. For signals that mediate social interactions, costs can arise from the way that a signal changes the subsequent social environment via receiver responses. These receiver-dependent costs may be linked with individual quality through variation in resilience to environmental and social stress. Here, we imposed stressful conditions on female tree swallows (Tachycineta bicolor) by attaching groups of feathers during incubation to decrease flight efficiency and maneuverability. We simultaneously monitored social interactions using an RFID network that allowed us to track the identity of every individual that visited each nest for the entire season. Prior to treatments, plumage coloration was correlated with baseline and stress-induced corticosterone. Relative to controls, experimentally challenged females were more likely to abandon their nest during incubation. Overall, females with brighter white breasts were less likely to abandon, but this pattern was only significant under stressful conditions. In addition to being more resilient, brighter females received more unique visitors at their nest box and tended to make more visits to other active nests. In contrast, dorsal coloration did not reliably predict abandonment or social interactions. Taken together, our results suggest that females differ in their resilience to stress and that these differences are signaled by plumage brightness, which is in turn correlated with the frequency of social interactions. While we do not document direct costs of social interaction, our results are consistent with models of signal honesty based on receiver-dependent costs.
National Science Foundation, Award: 1457151