Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology.

ABSTRACT: Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data sets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. We devised automated signal processing and machine learning approaches to estimate dates on which songbird communities arrived at arctic breeding grounds. Acoustically estimated dates agreed well with those determined via traditional surveys and were strongly related to the landscape's snow-free dates. We found that environmental conditions heavily influenced daily variation in songbird vo

SUBMITTER: Oliver RY 

PROVIDER: S-EPMC6010323 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature