Relatively little is known about the distribution, abundance and spatio-temporal variability of marine birds in their habitats of the Eastern coast of the U.S. A number of surveys have been conducted over the last 10-15 years, but analyzing these data in a unifed framework is difficult due to the use of different sampling methods, spatial and temporal scales, as well as lack of sampling design. Thus, we incorporate a multi-scale approach to develop models for the space-time distribution and abundance of marine birds to identify potential high-use areas in need of further study. With data taken from past and ongoing survey efforts, we provide relative abundance and density estimates for marine birds over a wide geographical area during multiple years. Due to the excessive zero-counts and extremely large counts exhibited in the data, a double-hurdle model was formulated that includes a negative binomial and a generalized Pareto distribution mixture. Spatial heterogeneity is modeled using a conditional auto-regressive (CAR) prior, and a Fourier basis was used for seasonal variation. We demonstrate our model by creating probability maps that show areas of high-abundance and aggregation for twenty-four species of marine bird.
