The Great Backyard Bird Count & Being a Citizen Scientist

Every year in mid-February, the Cornell Laboratory of Ornithology and the National Audubon Society organize the Great Backyard Bird Count, or GBBC.  This is a huge continent-wide push to encourage birders of all skill levels to go out, watch birds and report what they find.  This year’s GBBC happens on February 13-16, 2015.  For full information and instructions, check out the website (http://gbbc.birdcount.org).

The GBBC is part of a burgeoning trend of “Citizen Science” that boomed in the late 20th century.  Professional scientists generally conduct specific and focused research aimed at exploring whatever field they specialize in.  This research is often complex and expensive, of course.   In comparison, Citizen Scientists do research with inexpensive gear and their own observational skills, unpaid, in their free time.  Now in the 21st century, most Citizen Science is conducted and shared using the internet.  Think of it as “scientific social networking.”

The power of the Citizen Scientist comes when hundreds or thousands combine forces.  One person measuring rainfall in her back yard and recording it in her own notebook does not do much for the science of meteorology.  However, 15,000 volunteers across the U.S. and Canada measuring their rain and snow and reporting it each morning to CoCoRaHS (http://www.cocorahs.org) become a huge asset for meteorologists, water managers and many others.

Birders have been pioneers of Citizen Science since before it had a name.  What is arguably the oldest, large-scale Citizen Science project is the annual Christmas Bird Count, or CBC (http://birds.audubon.org/cbc), which started in 1900.  This year, thousands of us just completed the 115th consecutive CBC.  In June, the Breeding Bird Survey (http://www.pwrc.usgs.gov/BBS/) will be run for the 49th straight time.  In both of these projects, the dirty work is done by unpaid volunteers motivated by passion.  The professional staff that organize these projects operate on shoestring budgets.

What do we get for this giant effort and miniscule expense?  We get pictures of the world, snapshots of moments in time showing what is where.  And we can compare these snapshots over the years to see what is happening.  Which birds are in trouble?  Which birds are doing well?  What do these shifts mean?  How much “global change” is happening?  Where?  How fast?

These two projects, the CBC and the BBS, are both demanding of their Citizen Scientist volunteers.  Both are conducted at specific locations, and you must contact a coordinator to make advance arrangements.  A Christmas Count is a full and exhausting day, in whatever weather may come your way on the preselected count day.  To run a BBS route, you drive (often a long way) in the middle of the night to get to your assigned starting point, then you are on a go-go-go schedule to finish all 50 of your survey points by mid-morning.

The Great Backyard Bird Count is designed to be the opposite.  It is a big tent project with everyone welcome.  You may count birds anywhere you like, for as long as you please, any time in the four day count period.  And you can do it again and again, at as many places as you choose, or only once.  You don’t need to contact anyone in advance for assignments or approval.  You simply get instructions from the website, do your counts and enter your data.

Because the GBBC allows anyone to participate, you might wonder how reliable the reports are.  The GBBC participants range from people who have had binoculars glued to their hands for 60 years to those who don’t even own them.  But one of the threads that run through all Citizen Science projects is the concept of “big noisy data.”  All data has mistakes in it.  Even the best observer is going to suffer the occasional optical illusion, brain lapse or typo.  But in recent decades, statisticians have made huge advances in figuring out how to use “big noisy data” to find real patterns.

Think of a bad telephone line or a weak radio station.  Even with the crackling and static, you can make out what the voice on the other end is saying.  And there are filters you can put in the line to make the “signal” clearer and stand out from the “noise.”   There does come a point where there is just too much “noise” and the “signal” is lost.  But experience with the GBBC has shown that even with the wide-open invitation to everyone to contribute all their noisy data, there is still a lot of signal and real patterns can be found quite clearly.

There are several “noise filters” that help improve the GBBC data.  When you are putting in your own observations, you will notice that you are given a suggested list of common species.  Some reports may be “flagged,” and you will be asked to confirm the report and describe the bird and how you identified it.  That is one filter.

All those flagged reports get sent to the regional editor (who happens to be me, for middle and west Tennessee).  The editor reviews the reports and may contact the observer for more information.   This is another filter.

However, the most important filter to improve signal and reduce noise is right behind your eyeballs.  Observer education is the number one way we improve data quality on the GBBC and all Citizen Science projects.  This year, I have put together a simple tool that I hope will help many GBBC observers who are relatively new to the art of birding:  a Cheat Sheet.

My Middle Tennessee GBBC Cheat Sheet shows the 49 birds most often reported on the GBBC in this area.   Go to http://bbill.blogspot.com/ to get a full-sized electronic copy.  Please do not use it as your only identification guide!  Use it as a supplement to one of the many good comprehensive bird guides.  It should help you cut through the confusion and focus on the species you are most likely to come across.  And remember, the odds are good that you might find at least one species per outing that is not on my “cheat sheet!”

I’m looking forward to seeing a Great Backyard Bird Count checklist from each and every one of you!

GBBC-Common-2 copy

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