A response to estimating hybridization in the wild using community science data: A path forward. (1st February 2022)

• Record Type: Journal Article
• Authors: Justyn, Nicholas M.; Callaghan, Corey T.; Hill, Geoffrey E.
• Is Part Of: Evolution. Volume 76:Number 2(2022)
• Page Start: 359
• Page End: 361
• Publication Date: 2022-02-01
• Subjects: Aves -- citizen science -- eBird -- hybridization -- speciation; Evolution -- Periodicals; Heredity -- Periodicals; Évolution (Biologie) -- Périodiques; Hérédité -- Périodiques; 338.47004094
• DOI: 10.1111/evo.14390
• Languages: English
• ISSNs: 0014-3820

Abstract

Abstract: When working with a citizen science database like eBird, there are many possible ways to filter or subsample observations. Here, we discuss the potential biases and assumptions that surround different subsampling approaches or filtering that can be done to the eBird database. Restricting observations to species that are known to frequently hybridize, a specific time of the year, or a specific location, has the potential to greatly inflate the calculated per‐individual rate of hybridization. Such filtering also assumes that researchers know a birds' capacity to hybridize with all other species in its range, which we argue is an unfounded assumption. We ultimately conclude that a limited filtering approach is ideal when using a citizen science database to attempt to address a broad question such as: what is the per individual rate of hybridization across all of the bird species in the United States?