Evaluating the efficacy of eBird data for modeling historical population trajectories of North American birds and for monitoring populations of boreal and Arctic breeding species

• Main Authors: Jacob Walker, Philip D. Taylor
• Format: Article in Journal/Newspaper
• Language: English
• Published: Resilience Alliance 2020
• Subjects: boreal forest; breeding bird survey; christmas bird count; citizen science; ebird; population trend; envir; anthro-se; Arctic; Canada
• Online Access: https://doaj.org/article/0eabf8977ea644268ea8915ec8e4dd99

Historic population trajectories for most North American bird species are largely unknown for years prior to circa 1970. Additionally, current estimates of population trajectories of boreal and Arctic breeding species are imprecise or biased because of lack of coverage by Breeding Bird Survey (BBS) routes in that region. Citizen science data, in particular eBird data, could fill these information gaps. Bayesian regression models of eBird data were used to estimate population trajectories of 22 boreal or Arctic breeding species of songbirds, 4 migratory songbird species that breed in eastern North America, and 2 species of raptors whose populations crashed due to the pesticide DDT. Models used range-wide data from the U.S. and Canada for spring migration/breeding, fall migration, and winter. To evaluate the model results, comparisons were made between eBird models from different seasons, between eBird indices and area defoliated by spruce budworm (Choristoneura fumiferana), and between eBird, BBS, and Christmas Bird Count (CBC) annual indices and trends. Population trajectories were positively correlated between seasons for most of the species analyzed based on correlations between annual indices, magnitude of trends, and residuals from trend models. Of the species analyzed, those most often associated with spruce budworm outbreaks had the strongest correlations between eBird annual indices and area defoliated by spruce budworm in the boreal forest. Annual indices from eBird models were positively correlated with BBS for most species, and trends calculated through the annual indices from eBird models were strongly correlated with those from the BBS for spring (r = 0.73, n = 25, P < 0.0001), fall (r = 0.64, n = 25, P = 0.0005), and winter (r = 0.81, n = 9, P = 0.0084), and winter eBird trends were correlated with those from the CBC (r = 0.64, n = 12, P = 0.0252). The results suggest eBird analyses could be an important complement to the BBS, CBC, and other surveys for assessing the status of bird species in ...