Temporal and demographic variation in partial migration of the North Atlantic right whale.

Animal movement plays a fundamental role in the ecology of migratory species, and understanding migration patterns is required for effective management. To evaluate intrinsic and environmental factors associated with probabilities of endangered North Atlantic right whales Eubalaena glacialis migrating to a wintering ground off the southeastern United States (SEUS), we applied a multistate temporary emigration capture-recapture model to 22 years of photo-identification data. Migration probabilities for juveniles were generally higher yet more variable than those for adults, and non-calving adult females were the least likely group to migrate. The highest migration probabilities for juveniles and adult males coincided with years of relatively high calving rates, following years of higher prey availability in a fall feeding ground. Right whale migration to the SEUS can be classified as condition-dependent partial migration, which includes skipped breeding partial migration for reproductive females, and is likely influenced by tradeoffs among ecological factors such as reproductive costs and foraging opportunities that vary across individuals and time. The high variability in migration reported in this study provides insight into the ecological drivers of migration but presents challenges to right whale monitoring and conservation strategies.

Wintering habitat model for the North Atlantic Right Whale (Eubalaena glacialis) in the southeastern United States.

The coastal waters off the southeastern United States (SEUS) are a primary wintering ground for the endangered North Atlantic right whale (Eubalaena glacialis), used by calving females along with other adult and juvenile whales. Management actions implemented in this area for the recovery of the right whale population rely on accurate habitat characterization and the ability to predict whale distribution over time. We developed a temporally dynamic habitat model to predict wintering right whale distribution in the SEUS using a generalized additive model framework and aerial survey data from 2003/2004 through 2012/2013. We built upon previous habitat models for right whales in the SEUS and include data from new aerial surveys that extend the spatial coverage of the analysis, particularly in the northern portion of this wintering ground. We summarized whale sightings, survey effort corrected for probability of whale detection, and environmental data at a semimonthly resolution. Consistent with previous studies, sea surface temperature (SST), water depth, and survey year were significant predictors of right whale relative abundance. Additionally, distance to shore, distance to the 22°C SST isotherm, and an interaction between time of year and latitude (to account for the latitudinal migration of whales) were also selected in the analysis presented here. Predictions from the model revealed that the location of preferred habitat differs within and between years in correspondence with variation in environmental conditions. Although cow-calf pairs were rarely sighted in the company of other whales, there was minimal evidence that the preferred habitat of cow-calf pairs was different than that of whale groups without calves at the scale of this study. The results of this updated habitat model can be used to inform management decisions for a migratory species in a dynamic oceanic environment.

Estimating distribution of hidden objects with drones: from tennis balls to manatees.

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.

Kinship of long-term associates in the highly social sperm whale.

The evolution of stable social groups can be promoted by both indirect and direct fitness benefits. Sperm whales (Physeter macrocephalus) are highly social, with a hierarchical social structure based around core groups of adult females and subadults, a rare level of complexity among mammals. We combined long-term satellite tracking (ranging from 11 to 607 days) of 51 individual sperm whales with genetic kinship analysis to assess the pattern of kin associations within and among coherent social units. Unlike findings for other species with similar social structure, we find no consistent correlation between kinship and association apart from close associations between two pairs of first-order relatives. A third pair of first-order relatives did not associate, and overall, the mean relatedness was the same within as among social groups. However, social behaviour can also be promoted by ecological factors such as resource dispersion. We assessed putative foraging behaviour during travel from the satellite-tracking data, which suggested that prey resources were dispersed and unpredictable, a condition that could promote living in groups.