eBird data are a powerful resource for a wide range of scientific questions. By building tools that engage the global birding community, eBird gathers unprecedented volumes of information on where and when birds occur at high spatial and temporal resolutions. When combined and analyzed appropriately, these data enable next generation visualizations of migration and abundance that inform novel conservation actions.
If you have used eBird data as a core component of an analysis or as a core data set upon which conservation actions were taken, let us know by email, using the subject title ‘eBird Data Use.’
Accessing and analyzing raw eBird data
eBird data bring a number of analytical challenges and it is important to consider how the data are generated when using them for analysis. We outline best practices for analyzing eBird data in: Best practices for making reliable inferences from citizen science data (Johnston et al. 2019). Don’t forget to look at the appendices!
Best Practices for Using eBird Data acts as a supplement to the paper above, showing readers how to implement these best practices with R code. Many of the principles outlined in this resource apply to other analyses with eBird as well as other citizen science datasets.
Download raw data here.
Once you have the data in hand, the R package auk can be used to extract and prepare eBird data for analysis. Learn about auk here.
Status and Trends data products
eBird Status and Trends data products include estimates of relative abundance and trends in relative abundance for over 2000 species globally. The methodology used for Trends data products can be reviewed in the paper published in Methods in Ecology and Evolution. Additional information about how to analyze Trends data in R can be found on our github page and in a webinar detailing how to work with eBird Status and Trends data products.
To download these products, visit: Download eBird Status and Trends Data.