Birding game creates citizen science data where none exists

People around the world go geocaching, an outdoor treasure-hunting game using GPS-enabled devices. Now, there’s Avicaching.

The male black-throated green warbler.

Avicaching, which began last spring, is a game for bird watchers that combines eBird – an online checklist program that collects sightings from citizen birders – with elements from geocaching, where players search for as many birds as possible in specific locations and record their findings in eBird.

The goal is to help collect eBird data in underrepresented locales.

“People tend to go birdwatching in places that have water or that are convenient,” said Ian Davies, an eBird project assistant at the Cornell Lab of Ornithology. “We wanted to reduce this sampling bias in where people visit, so the game sends people to places where they normally wouldn’t be birding.”

eBird identified 50 locations in Tompkins and Cortland counties that had very little data. Players gained points by going to these sites, standing in one place for up to 60 minutes and logging their sightings on eBird. Each week, eBird weighted locations so sightings from undersampled areas garnered more points.

The Lab of Ornithology and eBird have now announced the winners of the June to December 2015 Avicaching contest. Lee Ann van Leer, Gary Kohlenberg and Kevin McGowan came first, second and third, respectively, by collecting the most points. Each participant’s name was entered in a lottery, with one entry for every point gained. Thanks to a little luck and 1,556 total points, van Leer’s name was also picked as the lottery winner; she won a pair of Zeiss binoculars.

With initial success from the local pilot Avicaching game, eBird staff plan to expand Avicaching locations throughout Western New York, and potentially further afield in the future.

With some 50 participants visiting the less-frequented birding locales, eBird staffers have already found improvements in the scientific models used to analyze data to generate species prediction models that predict how likely you are to see a certain bird species on a given day in a given place.

Since unevenly distributed data is an issue for citizen science globally, such ‘caching’ games “can serve as a framework to reduce sampling bias in citizen science [in general]; it provides a starting point applicable to a wide variety of disciplines,” Davies said. 

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Melissa Osgood