The Bird Watching Community: Citizen Science at its Finest

Image Credit: Warrieboy, CC BY-SA 4.0, Image Cropped

It’s 5 o’clock in the morning. Whilst the sun has yet to rise and everyone is fast asleep, dedication and passion have awakened you. With a comfortable set of hiking boots, a thermos filled with coffee or tea and a pair of binoculars around your neck you venture into the local forest or mountain area. Hours you spent there searching, looking and listening. When you finally see those recognizable shades of pale brown and chestnut dashing by, or hear that distinctive, vibrant melody interspersed with prolonged pew-pew’s and swift chook-chook’s, you realize that it was well worth waking up so early.

People love watching birds. The study of birds started off as a side activity for hunters, but after the development of optical aids and creation of bird handbooks in the early 1900s it became accessible to a bigger audience and grew out to be a very popular pastime for young and old. Birds are diverse and beautiful in appearance and behaviour, and bird watching appeals to the very human quirk to categorize and collect. It is therefore not so strange that nowadays hundreds of thousands of people go out, be it in nature or in the city, to spot and record their observations of birds.

A Citizen Science Gold Mine

To scientists observations are fundamental. It is through observations that we as ecologists try to understand the processes and interactions of organisms in their environment. Observations and records made by volunteers, like bird watchers, are increasingly incorporated into scientific studies using a collective term known as citizen science or community science. Obviously the birding community, with their millions and millions of records of birds in gardens, city parks, forests, mountain regions and various other areas, is an important citizen science contributor and, as such, a gold mine for ornithologists, ecologists and conservation biologists. In countries where bird watching has a long history, data gathered by citizen scientists have been used for a whole range of purposes: estimation of population size trends and geographical distributions, evaluation of the response to pollution, disease, and habitat and climate change, as well as assessment of the ability to change the timing of seasonal events (like the start of breeding or the start and duration of seasonal migration).

Related: What Does Citizen Science Mean To You?

As citizen science data continued to contribute to scientific projects, scientists started to evaluate the efficacy of citizen-science projects and develop tools that increase the utility of these data by overcoming sampling limitations and controlling for data quality. One project in which bird watchers and research are united and citizen science data used to their best potential, is eBird. Launched in 2002 by the Cornell Lab of Ornithology and the National Audubon Society, eBird started off with the goal to acknowledge and treasure a bird watcher’s knowledge and experience, but grew to be the world’s largest biodiversity-related citizen science project and collaborative enterprise.

eBird: A Collaboratively Evolving Enterprise

eBird is a database with millions of bird observations, a network and community for bird watchers around the globe, and a developer of tools to check and safeguard data quality. They translate and transform the birding community’s enthusiasm into data for research, conservation and education. And, best of all, it’s accessible to everyone (check the link below for why that’s important).

Related: Knocking Down the Paywalls: The Quest for Accessible Science

eBird is constantly growing and evolving, with two main aims. Firstly, like most global databases, they aim to increase the volume of their data, both in terms of number of participants, known as eBirders, and number records. Contributions are stimulated through rewards and tools, for instance by sharing species information, photos and audio recordings, and maps and animations based on the very data they have provided themselves. In addition, eBirders can keep personalized bird lists, receive alerts on rare birds and track where and when to find their most favourite species. Through this engagement, eBirders become increasingly invested and their contribution to the database increases.

Secondly, eBird aims to improve the quality of their data. Their sampling and recording protocols are low-threshold and engage a wide audience of contributors but have the downside that they produce noisier data. Common sources of bias are variation among observers (e.g. between novice and experienced birders), misdetection (e.g. species is present but fails to be detected), misclassification (e.g. species incorrectly recorded as present when it is actually absent), and irregularly distributed data (in time and space). Some of these sources can be accounted for (by, for instance, separating the observation process from the detection process), whereas other types of noise require the affected records to be removed.


The passion of birdwatchers young and old is a goldmine for conservationists and researchers, and projects like eBird help facilitate links between those two communities (Image Credit: Walton LaVonda, U.S. Fish and Wildlife Service)

To deal with the large volume of observations coming in, eBird implemented an automated screening process that combines human expertise and artificial intelligence into a human/computer learning network (HCLN). Records are filtered by region and month, and subsequently checked against the likelihood of observing that record in that particular region and month, based on all historical records in eBird’s database. If the record’s likelihood is below a certain threshold, it gets flagged and reviewed by an expert volunteer reviewer. The strength of the HCLN is its ability to detect crucial stages in a species’ life history where occurrence patterns change, for instance at the transition between breeding season and migration, and this ability continues to improve as more and more data comes in. In a similar fashion, the HCLN’s ability to account for observer variability and spatial bias in predictions continues to grow as well.

Related: Corina Newsome on #BlackBirdersWeek

Using eBird’s database to study changing migratory patterns or spatiotemporal variation in phenology to advance ecology and climate change research is of course fascinating and important for science. But the great thing about eBird is that it has actually had a very tangible impact on conservation action as well. Besides research and monitoring, eBird has been involved in data-driven conservation planning (e.g. species status assessments), habitat management and protection (e.g. spatial and temporal occurrence information to help land manager’s decision-making), species management (e.g. information on nesting and migration phenology to inform placement of nest boxes), and policy (e.g. listing of threatened and endangered species).

In the world of birds, citizen science data are gaining momentum, both in scientific projects and real-word conservation action. Thanks to the work of initiatives like eBird (but find more here and here), and the constant passion of the birding community, gold mines of data are accessible and ready to be used by everyone around the globe.

Stefan Vriend is a population ecologist finishing up his PhD at the Norwegian University of Science and Technology. His thesis focuses on the effects of changing environments on nestbox-breeding bird populations. Specifically he studies the spatial variation in their demography, selection and traits. In addition, he works as a developer at SPI-Birds, a network and database that connects data from and researchers on bird populations. You can read more about his previous articles on his Ecology for the Masses profile here, and follow him on Twitter @StefanJGVriend.

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