Using Temporal Occupancy To Predict Avian Species Distributions

Aim Species distribution models (SDMs) are ubiquitous in ecology to predict species occurrence throughout their range. Typically, SDMs are created using presence-only or presence-absence data. We hypothesize that the continuous metric of temporal occupancy, the proportion of time a species is observed at a given site, provides more detail about species occurrence than binary presence-based SDMs.Location North America.Methods We compared SDMs for 189 focal species using four modelling methods to determine whether North American avian species distributions are better predicted using temporal occupancy over presence-absence. We used the North American Breeding Bird Survey and built SDMs based on all sites sampled consecutively between 2001 and 2015, as well as on a subset of only five time points within the 15-year sampling window. Each model used the same environmental inputs to predict species range. Each SDM was cross-validated temporally and spatially.Results Species distributions were generally better predicted using temporal occupancy rather than presence-absence when using either a five-year or fifteen-year sampling window. Species that occurred in a smaller proportion of their predicted range were particularly better predicted with SDMs using temporal occupancy. Temporal occupancy SDMs had lower false discovery and false-positive rates but higher false-negative rates than presence-absence models.Main conclusions Temporal occupancy is a valuable metric that can improve predictions of species occurrence for birds and may improve conservation planning and design efforts.