Drag force acting on swimming marine mammals is difficult to measure directly. Researchers often use simple modeling and kinematic measurements from animals, or computational fluid dynamics (CFD) simulations to estimate drag. However, studies that compare these methods are lacking. Here, computational simulation and physical experiments were used to estimate drag forces on gliding bottlenose dolphins (Tursiops truncatus). To facilitate comparison, variable drag loading (no‐tag, tag, tag + 4, tag + 8) was used to increase force in both simulations and experiments. During the experiments, two dolphins were trained to perform controlled glides with variable loading. CFD simulations of dolphin/tag geometry in steady flow (1–6 m/s) were used to model drag forces. We expect both techniques will capture relative changes created by experimental conditions, but absolute forces predicted by the methods will differ. CFD estimates were within a calculated 90% confidence interval of the experimental results for all but the tag condition. Relative drag increase predicted by the simulation vs. experiment, respectively, differed by between 21% and 31%: tag, 4% vs. 33%; tag + 4, 47% vs. 68%; and tag + 8, 108% vs. 77%. The results from this work provide a direct comparison of computational and experimental estimates of drag, and provide a framework to quantify uncertainty.

High-resolution non-invasive cetacean tagging systems can be used to investigate the influence of habitat characteristics and management factors on behavior by quantifying activity levels and distance traveled by bottlenose dolphins (Tursiops truncatusandTursiops aduncus) in accredited zoos and aquariums. Movement Tags (MTags), a bio-logging device, were used to record a suite of kinematic and environmental information outside of formal training sessions as part of a larger study titled “Towards understanding the welfare of cetaceans in zoos and aquariums” (colloquially called the Cetacean Welfare Study). The purpose of the present study was to explore if and how habitat characteristics, environmental enrichment programs, and training programs were related to the distance traveled and energy expenditure of dolphins in accredited zoos and aquariums. Bottlenose dolphins in accredited zoos and aquariums wore MTags one day per week for two five-week data collection periods. Overall dynamic body acceleration (ODBA), a proxy for energy expenditure, and average distance traveled per hour (ADT) of 60 dolphins in 31 habitats were examined in relation to demographic, habitat, and management factors. Participating facilities were accredited by the Alliance for Marine Mammal Parks and/or Aquariums and the Association of Zoos & Aquariums. Two factors were found to be related to ADT while six factors were associated with ODBA. The results showed that enrichment programs were strongly related to both ODBA and ADT. Scheduling predictable training session times was also positively associated with ADT. The findings suggested that habitat characteristics had a relatively weak association with ODBA and were not related to ADT. In combination, the results suggested that management practices were more strongly related to activity levels than habitat characteristics.

The way an animal uses its habitat can serve as an indicator of habitat appropriateness for the species and individuals. Bottlenose dolphins (Tursiops truncatusandTursiops aduncus) in accredited zoos and aquariums experience a range of habitat types and management programs that provide opportunities for dolphins to engage in species-appropriate behaviors and potentially influence their individual and group welfare. Data in the present study were collected as part of a larger study titled “Towards understanding the welfare of cetaceans in zoos and aquariums” (colloquially called the Cetacean Welfare Study). Non-invasive bio-logging devices (Movement Tags) recorded the diving behavior and vertical habitat movements of 60 bottlenose dolphins at 31 zoos and aquariums that were accredited by the Alliance for Marine Mammal Parks and Aquariums and/or the Association of Zoos & Aquariums. Bottlenose dolphins wore a Movement Tag one day per week for two five-week data collection periods. Demographic variables, environmental enrichment programs, training programs, and habitat characteristics were associated with habitat usage. Longer dive durations and use of the bottom third of the habitat were associated with higher enrichment program index values. Dolphins receiving new enrichment on a monthly/weekly schedule also used the bottom third of the habitat more often than those receiving new enrichment on a yearly/year+ schedule. Dolphins that were managed in a group that was split into smaller subgroups during the day and were reunited into one group at night spent less time in the top third of the habitat than those who remained in a single group with consistent members at all times. Dolphins that were managed as subgroups with rotating members but were never united as one group spent less time in the bottom third of the habitat than those who remained in a single group with consistent members at all times. Taken together, the results suggested that management practices, such as enrichment and training programs, played a greater role in how dolphins interacted with their environment relative to the physical characteristics of the habitat.

This research presents a framework to enable computer-automated observation and monitoring of bottlenose dolphins (Tursiops truncatus) in a zoo environment. The resulting approach enables detailed persistent monitoring of the animals that is not possible using manual annotation methods. Fixed overhead cameras were used to opportunistically collect ∼100 hours of observations, recorded over multiple days, including time both during and outside of formal training sessions, to demonstrate the viability of the framework. Animal locations were estimated using convolutional neural network (CNN) object detectors and Kalman filter post-processing. The resulting animal tracks were used to quantify habitat use and animal kinematics. Additionally, Kolmogorov-Smirnov analyses of the swimming kinematics were used in high-level behavioral mode classification. The object detectors achieved a minimum Average Precision of 0.76, and the post-processed results yielded 1.24 × 10⁷estimated dolphin locations. Animal kinematic diversity was found to be lowest in the morning and peaked immediately before noon. Regions of the zoo habitat displaying the highest activity levels correlated to locations associated with animal care specialists, conspecifics, or enrichment. The work presented here demonstrates that CNN object detection is viable for large-scale marine mammal tracking, and results from the proposed framework will enable future research that will offer new insights into dolphin behavior, biomechanics, and how environmental context affects movement and activity.

Current estimates of marine mammal hydrodynamic forces tend to be made using camera-based kinematic data for a limited number of fluke strokes during a prescribed swimming task. In contrast, biologging tag data yield kinematic measurements from thousands of strokes, enabling new insights into swimming behavior and mechanics. However, there have been limited tag-based estimates of mechanical work and power. In this work, we investigated bottlenose dolphin (Tursiops truncatus) swimming behavior using tag-measured kinematics and a hydrodynamic model to estimate propulsive power, work and cost of transport. Movement data were collected from six animals during prescribed straight-line swimming trials to investigate swimming mechanics over a range of sustained speeds (1.9–6.1 m s−1). Propulsive power ranged from 66 W to 3.8 kW over 282 total trials. During the lap trials, the dolphins swam at depths that mitigated wave drag, reducing overall drag throughout these mid- to high-speed tasks. Data were also collected from four individuals during undirected daytime (08:30–18:00 h) swimming to examine how self-selected movement strategies are used to modulate energetic efficiency and effort. Overall, self-selected swimming speeds (individual means ranging from 1.0 to 1.96 m s−1) tended to minimize cost of transport, and were on the lower range of animal-preferred speeds reported in literature. The results indicate that these dolphins moderate propulsive effort and efficiency through a combination of speed and depth regulation. This work provides new insights into dolphin swimming behavior in both prescribed tasks and self-selected swimming, and presents a path forward for continuous estimates of mechanical work and power from wild animals.