Bird populations represent a significant proportion of urban and rural
biodiversity. For environmental, economic and health reasons, bird population
monitoring is a crucial issue due to its cohabitation with the human species.
For this purpose, the acquisition of reliable, updated and precise data on bird
population (number of individuals, reproduction, physiological state) can be a
central factor for environmental decisions. However bird population monitoring
is a dynamic problem because populations go through environmental changes, in
particular those generated by human activities (urbanization, pollution,
habitat fragmentation). The current classical techniques are difficult
regarding human resources (banding, tracking, counting) and often invasive (capture,
manipulation), and they present risk for animals.
In this project we want to develop a cheap and non-invasive method for bird population monitoring using passive acoustic recordings. Using automatic detection of vocalizations and analysis of vocalizations dynamics we want to be able to infer information about the group social network. During my PhD project, I will study zebra finches (Taeniopygia guttata) groups acoustic communication both in the lab and in the field, by experimentally changing the group social composition or by creating perturbations (predation stress, new individual).