Date: September 13, 2018
Source: University of Oxford
Using a combination of AI and weather
forecasting can help scientists to predict the movements of millions of birds
and support their conservation goals, according to new Oxford University
research.
Conducted in collaboration with
Cornell University, the study -- published in the journal Science --
reports that scientists can now reliably predict these waves of bird migration
across the United States, up to seven days in advance. It reveals the
underlying methods that power migration forecasts, which can be used as a bird
conservation tool.
September is the peak of autumn
bird migration, and billions of birds are winging their way south in dramatic
pulses. In this study, the researchers reviewed 23 years of spring bird
migration across the United States using 143 weather radars, highly sensitive
sensors that scientists can use to monitor bird movements. They filtered out
precipitation and trained a machine learning model to associate atmospheric
conditions with levels of bird migration countrywide. Eighty percent of
variation in bird migration intensity was explained by the model.
Benjamin Van Doren, a doctoral
student at the University of Oxford and a Cornell University graduate, said:
"Most of our songbirds migrate at night, and they pay close attention to
the weather. Our model converts weather forecasts into bird migration forecasts
for the continental United States."
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