Positive Detection Breeding Bird Survey Routes - 1966-2025 - USGS [ds2800] Extended Table

To create this dataset, a number of files from the current BBS Release were combined. The "50-StopData", "SpeciesList", and "Routes" were used and joined together by CDFW staff to create this data. Negative detections were recorded, but removed from this dataset due to size constraints. --------------------------------------------------------------------------------------------------------- The 1966-2025 North American Breeding Bird Survey (BBS) dataset contains avian point count data for more than 700 North American bird taxa (species, races, and unidentified species groupings). These data are collected annually during the breeding season, primarily in June, along thousands of randomly established roadside survey routes in the United States and Canada. Routes are roughly 24.5 miles (39.2 km) long with counting locations placed at approximately half-mile (800-m) intervals, for a total of 50 stops. At each stop, a citizen scientist highly skilled in avian identification conducts a 3-minute point count, recording all birds seen within a quarter-mile (400-m) radius and all birds heard. Surveys begin 30 minutes before local sunrise and take approximately 5 hours to complete. Routes are surveyed once per year, with the total number of routes sampled per year growing over time; just over 500 routes were sampled in 1966, while in recent decades approximately 3000 routes have been sampled annually. No data are provided for 2020. BBS field activities were cancelled in 2020 because of the coronavirus disease (COVID-19) global pandemic and observers were directed to not sample routes. In addition to avian count data, this dataset also contains survey date, survey start and end times, start and end weather conditions, a unique observer identification number, route identification information, and route location information including country, state, and BCR, as well as geographic coordinates of route start point, and an indicator of run data quality.