eBird Status and Trends Model Results

Description

The eBird Status and Trends project generates estimates of bird occurrence and abundance at a high spatiotemporal resolution. This dataset represents the primary modeled results from the analysis workflow and are designed for further analysis, synthesis, visualization, and exploration.

Update Frequency

Yearly

License

CC BY-NC-ND 4.0

Documentation

https://cornelllabofornithology.github.io/ebirdst/articles/ebirdst-introduction.html

Managed By

See all datasets managed by Cornell Lab of Ornithology.

Contact

https://help.ebird.org/customer/en/portal/emails/new

Usage Examples

Tutorials

• eBird Status and Trends FAQ by Cornell Lab of Ornithology
  
• eBird Status and Trends Visualizations by Cornell Lab of Ornithology
  
• ebirdst - Background, Data Access and Data Structure by Tom Auer and Daniel Fink
  
• ebirdst - Generating Seasonal Abundance and Range Maps and Stats by Matt Strimas-Mackey, Tom Auer, and Daniel Fink
  
• ebirdst - Intro Mapping by Tom Auer and Daniel Fink
  
• ebirdst - Non-raster Data by Tom Auer and Daniel Fink
  

Tools & Applications

• ebirdst R Package by Cornell Lab of Ornithology
  

Publications

• Modeling avian full annual cycle distribution and population trends with citizen science data by Fink et al (2019)
  
• The Colorado River Delta and California’s Central Valley are critical regions for many migrating North American landbirds by DeLuca et al (2021)