Considerations for fitting occupancy models to data from eBird and similar volunteer-collected data

Lay Summary & BULL; The occupancy rate, the proportion of locations at which a species is expected to occur, is a useful metric in ecology. Estimating occupancy rates requires repeatedly collecting data at a set of locations. & BULL; While citizen/community science data are increasingly used in ecological research, the data from eBird and similar projects are not collected specifically to fit the format required for calculating occupancy rates. & BULL; We explore 2 ways to use eBird's data for occupancy models, and we use simulations to show that combining data from repeatedly visited sites and sites visited only once can improve estimates of occupancy rate. & BULL; We conclude that data from eBird, and likely also from similar projects, can be used to estimate occupancy under many circumstances. An occupancy model makes use of data that are structured as sets of repeated visits to each of many sites, in order to estimate the actual probability of occupancy (i.e. proportion of occupied sites) after correcting for imperfect detection using the information contained in the sets of repeated observations. We explore the conditions under which preexisting, volunteer-collected data from the citizen science project eBird can be used for fitting occupancy models. Because the majority of eBird's data are not collected in the form of repeated observations at individual locations, we explore 2 ways in which the single-visit records could be used in occupancy models. First, we assess the potential for space-for-time substitution: aggregating single-visit records from different locations within a region into pseudo-repeat visits. On average, eBird's observers did not make their observations at locations that were representative of the habitat in the surrounding area, which would lead to biased estimates of occupancy probabilities when using space-for-time substitution. Thus, the use of space-for-time substitution is not always appropriate. Second, we explored the utility of including data from single-visit records to supplement sets of repeated-visit data. In a simulation study we found that inclusion of single-visit records increased the precision of occupancy estimates, but only when detection probabilities are high. When detection probability was low, the addition of single-visit records exacerbated biases in estimates of occupancy probability. We conclude that subsets of data from eBird, and likely from similar projects, can be used for occupancy modeling either using space-for-time substitution or supplementing repeated-visit data with data from single-visit records. The appropriateness of either alternative will depend on the goals of a study and on the probabilities of detection and occupancy of the species of interest.