Bird-brained computing at TeraGrid

And a final note from TeraGrid about birds before I too fly the coop tomorrow, to Chicago. At the very end of the science session today, Daniel Fink of the Cornell Lab of Ornithology talked about modelling avian distributional dynamics on TeraGrid. Basically, bird watching with big computers.

So why birds? First of all, they are very good bio indicators, the so-called canaries in the coal mine, that can tell us about the health of the environment. Second, there is lots and lots of data - people love birds and there is a vast archive of amateur bird-watching data dating back over decades. One example of this is the citizen science website, eBirds (ebirds.org).

When you’re gathering observational data of this type it needs to be comprehensive – species, place, date, time, and how long did it take how many people to gather the data. This last one is particularly important as it gives you information on how much bias might be involved in the information.

Data sets can contain up to a million hours of volunteer data BUT it can still be sparse in terms of geographical coverage. You have holes in it where there aren’t many observers. Fink and his team are working to help fill the gaps and predict occurrence by associating observations with local environmental data. They’ve tried this with some very different bird species such as the indigo bunting and the solitary sandpiper and it seems to work. For example, their models of indigo bunting distribution show holes in the distribution patterns corresponding to cities. Which is what you would expect from a species that prefers hedgerows and rural environments.

Fink showed off his BirdVis tool that has recently been accepted for publication, where you can scroll through the influence of habitats during breeding periods and during migration, over dynamic time frames – all very impressive.

And with that, I must fly!