Finished! Looks like this project is out of data at the moment!
Help us understand the nesting patterns of these small backyard birds!
Learn moreChoose your own adventure! There are many ways to engage with this project, including many one-question, smartphone-friendly options. Click on one of the boxes below and have fun!
Zooniverse Talk
Chat with the research team and other volunteers!
Nest Quest Go: Sparrows Statistics
View more statsKeep track of the progress you and your fellow volunteers have made on this project.
Every click counts! Join Nest Quest Go: Sparrows's community to complete this project and help researchers produce important results. Click "View more stats" to see even more stats.
By the numbers
Message from the researcher
The work of citizen scientists, such as those who contribute to NestWatch, is what makes our research possible. Because of the efforts of nest monitors, we are able to look at patterns over long periods of time and large geographic areas.
Nest Quest Go: SparrowsAbout Nest Quest Go: Sparrows
Join the Cornell Lab of Ornithology's Citizen-Science Project, NestWatch in understanding the historical nesting patterns of various sparrows, including Black-throated Sparrow, Vesper Sparrow, Savannah Sparrow, Chipping Sparrow, Song Sparrow, Field Sparrow, Lark Sparrow, Eastern Towhee and many more! Generally, for most types of sparrows, the female searches for a nest location and builds her nest with little to no help from the male, who often guards the nesting territory. However, Song Sparrows look for a nesting site together with their mate, often choosing somewhere low to the ground and near humans or water. Join us to learn more about sparrow-nesters!
These nest record cards are a subset of a larger collection of more than 300,000 nest records that NestWatch is working on digitizing and transcribing. Valuable scientific questions can be asked and answered regarding the nesting behavior of birds over time by examining historical records. We hope to bring new discoveries to light using these previously hidden datasets.