As regular CFZ-watchers will know, for some time Corinna has been doing a column for Animals & Men and a regular segment on On The Track... particularly about out-of-place birds and rare vagrants. There seem to be more and more bird stories from all over the world hitting the news these days so, to make room for them all - and to give them all equal and worthy coverage - she has set up this new blog to cover all things feathery and Fortean.

Wednesday, 3 August 2016

How birds soar to great heights

Mathematical models offer clues to greater efficiency for glider pilots

Date: August 1, 2016
Source: University of California - San Diego

Migratory birds often use warm, rising atmospheric currents to gain height with little energy expenditure when flying over long distances.

It's a behavior known as thermal soaring that requires complex decision-making within the turbulent environment of a rising column of warm air from the sun baked surface of the earth.

But exactly how birds navigate within this ever-changing environment to optimize their thermal soaring was unknown until a team of physicists and biologists at the University of California San Diego took an exacting computational look at the problem.

In this week's online version of the journal Proceedings of the National Academy of Sciences, the scientists demonstrated with mathematical models how glider pilots might be able to soar more efficiently by adopting the learning strategies that birds use to navigate their way through thermals.

"Relatively little is known about the navigation strategies used by birds to cope with these challenging conditions, mainly because past computational research examined soaring in unrealistically simplified situations," explained Massimo Vergassola, a professor of physics at UC San Diego.

To tackle the problem, he and his colleagues, including Terrence Sejnowski, a professor of neurobiology at the Salk Institute and UC San Diego, combined numerical simulations of atmospheric flow with "reinforcement learning algorithms" -- equations originally developed to model the behavior and improved performance of animals learning a new task. Those algorithms were developed in a manner that trained a glider to navigate complex turbulent environments based on feedback on the glider's soaring performance.








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