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Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.

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Humpback whales wintering in the Revillagigedo Archipelago, Mexico, have been considered a different subpopulation from those found off mainland Mexico and Baja California. The primary feeding grounds for Revillagigedo humpbacks remain unknown. In February 2003, we deployed 11 Argos satellite-monitored radio tags to track movements and surfacings of humpback whales (five adults without calves, five mothers with calves, one calf) off Socorro Island in the Revillagigedo Archipelago. Tracking ranged from 222 to 10,481 km over 4.9-149.1 d. Eight whales left Socorro Island: five visited other Mexican wintering destinations, seven moved north of these areas. Migration routes were primarily offshore (average 444 km). Two whales were tracked to feeding grounds: one to British Columbia (46 d migration), and one to Alaska (49 d migration). Mean travel speeds were 1.2 km/h in wintering areas, 4.0 km/h during migration, and 2.2 km/h in feeding areas. Overall surfacing rates ranged from 21 to 88 surfacings/h. Surfacing rates differed between the calf and all other whales, and between feeding areas and migratory/wintering areas for the calf and an adult without a calf. The calf also showed diel variation in surfacing rates. The offshore habits of tagged whales may explain scarce resightings of Revillagigedo humpbacks outside the Revillagigedo Archipelago.