Little is known about the migration and movements of migratory tree-roosting bat species in North America, though anecdotal observations of migrating bats over the Atlantic Ocean have been reported since at least the 1890s. Aerial surveys and boat-based surveys of wildlife off the Atlantic Seaboard detected a possible diurnal migration event of eastern red bats (Lasiurus borealis) in September 2012. One bat was sighted approximately 44 km east of Rehoboth Beach, Delaware during a boat-based survey. Eleven additional bats were observed between 16.9 and 41.8 km east of New Jersey, Delaware, and Virginia in high definition video footage collected during digital aerial surveys. Observations were collected incidentally as part of a large baseline study of seabird, marine mammal, and sea turtle distributions and movements in the offshore environment. Digital survey methods also allowed for altitude estimation for several of these bats at >100 m above sea level. These observations provide new evidence of bat movements offshore, and offer insight into their flight heights above sea level and the times of day at which such migrations may occur.

Proposed offshore wind energy development on the Atlantic Outer Continental Shelf has brought attention to the need for baseline studies of the distribution and abundance of marine birds. We compiled line transect data from 15 shipboard surveys (June 2012-April 2014), along with associated remotely sensed habitat data, in the lower Mid-Atlantic Bight off the coast of Delaware, Maryland, and Virginia, USA. We implemented a recently developed hierarchical community distance sampling model to estimate the seasonal abundance of 40 observed marine bird species. Treating each season separately, we included six oceanographic parameters to estimate seabird abundance: three static (distance to shore, slope, sediment grain size) and three dynamic covariates (sea surface temperature [SST], salinity, primary productivity). We expected that avian bottom-feeders would respond primarily to static covariates that characterize seafloor variability, and that surface-feeders would respond more to dynamic covariates that quantify surface productivity. We compared the variation in species-specific and community-level responses to these habitat features, including for rare species, and we predicted species abundance across the study area. While several protected species used the study area in summer during their breeding season, estimated abundance and observed diversity were highest for nonbreeding species in winter. Distance to shore was the most common significant predictor of abundance, and thus useful in estimating the potential exposure of marine birds to offshore development. In many cases, our expectations based on feeding ecology were confirmed, such as in the first winter season, when bottom-feeders associated significantly with the three static covariates (distance to shore, slope, and sediment grain size), and surface-feeders associated significantly with two dynamic covariates (SST, primary productivity). However, other cases revealed significant relationships between static covariates and surface-feeders (e.g., distance to shore) and between dynamic covariates and bottom-feeders (e.g., primary productivity during that same winter). More generally, we found wide interannual, seasonal, and interspecies variation in habitat relationships with abundance. These results show the importance of quantifying detection and determining the ecological drivers of a community's distribution and abundance, within and among species, for evaluating the potential exposure of marine birds to offshore development.

Offshore wind energy development on the US Atlantic Continental Shelf has brought attention to the need for marine spatial planning efforts to reduce potential conflict between wind turbines and marine animals, including seabirds. We evaluated the effects of marine mammals, fishes, and habitat characteristics on the distribution and relative abundance of marine birds off the coast of Delaware, Maryland, and Virginia. From May 2012 to 2014, we collected line transect data from 14 shipboard surveys, and novel high-resolution digital videography data from 14 aerial surveys. We compiled five habitat covariates: three static (distance to shore, sea floor slope, and sediment grain size), and two dynamic (sea surface temperature, salinity). We additionally analysed two seabird community covariates: the density of observed marine mammals and detected fish. Using zero-altered models, we tested our hypothesis that plunge-diving seabird species would show positive associations with marine mammals. Our results provide statistical evidence that, alongside competition, facilitative interactions occur among pelagic communities, where subsurface predators improve the detectability and accessibility of prey to surface-feeding seabirds. This study highlights the importance of quantifying community and ecological influences on avian abundance, particularly in predicting the potential exposure of marine birds and mammals to offshore development.

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