Monitoring the world's bird populations with community science data

Abstract

Systematic monitoring of species across their geographic ranges is a critical part of conservation but it is resource-intensive, costly, and difficult to organize and maintain in the long-term. Large-scale community science programs like eBird may improve our ability to monitor bird populations, particularly in tropical regions where formal studies are lacking. Here, we estimated population trends for nearly 9000 bird species using global eBird birdwatching data and compared our trends to the population trends designated by BirdLife International. We calculated the rate of agreement between eBird and BirdLife trends and examined the effects of latitudinal affiliation, threat status, number of eBird checklists, eBird trend, BirdLife trend and BirdLife trend derivation on the rate of agreement. We also used a randomization approach to compare observed rates of agreement with the rates of agreement expected by chance alone. We show that the rate of agreement was marginally better than expected by chance and improved significantly for temperate region species of Least Concern with more checklists, and species that eBird or BirdLife identified as increasing. Our results suggest that eBird data are not currently adequate for monitoring populations of the majority of the world's bird species, especially in the developing world where systematic surveys are essential. Increased local participation in community science initiatives like eBird may improve our ability to effectively monitor species. Furthermore, it is important to assess the accuracy of BirdLife trends and the manner in which they are derived, especially for species where BirdLife and eBird data trends disagree.