Data and code for "Bird song plasticity and multimodal shift along noisy rivers"

Abstract

Ambient noise is well known to affect animal acoustic communication, and in some cases, they might even use signals in another modality (vision, touch, odors...) to ensure that information is transmitted efficiently. To date, there are only a handful of examples of the so-called "multimodal shifts", when the animals balance the use of different modalities to the ambient noise conditions. We study the white-throated dipper, a songbird strictly tied to fast-flowing rivers for feeding and breeding. Because the rivers can be very loud, we hypothesise that dippers may use some visual cues to complement their song. A good candidate visual cue is their blinking: their eyelids are covered with snow-white feathers, which sharply contrast with their head's brown plumage. In this study, we investigate how the dipper's blink rate varies according to the river noise, song amplitude, and social context. We counted the number of blinks of singing birds through a scope in a color-banded population of dippers. At the same time, we recorded their song with calibrated recording equipment to measure song amplitude and composition. We recorded the social context (presence of conspecifics around) and measured the river noise level at each song post. In a second step, we tested whether the birds increased blinking rates during agonistic interactions using a playback experiment.In this repository, we uploaded the scripts used to perform the acoustic analysis of dipper songs (i.e., measuring song amplitude and frequencies) in the "PythonScripts" folder. We also uploaded the dataset used for statistical analyses, as well as the R code used for statistical analyses, in the folder "Data_and_Rscripts". Detailed documentation is contained in a "readme" file in each folder.