Automated monitoring systems have become increasingly important for zoological institutions in the study of their animals’ behavior. One crucial processing step for such a system is the re-identification of individuals when using multiple cameras. Deep learning approaches have become the standard methodology for this task. Especially video-based methods promise to achieve a good performance in re-identification, as they can leverage the movement of an animal as an additional feature. This is especially important for applications in zoos, where one has to overcome specific challenges such as changing lighting conditions, occlusions or low image resolutions. However, large amounts of labeled data are needed to train such a deep learning model. We provide an extensively annotated dataset including 13 individual polar bears shown in 1431 sequences, which is an equivalent of 138,363 images. PolarBearVidID is the first video-based re-identification dataset for a non-human species to date. Unlike typical human benchmark re-identification datasets, the polar bears were filmed in a range of unconstrained poses and lighting conditions. Additionally, a video-based re-identification approach is trained and tested on this dataset. The results show that the animals can be identified with a rank-1 accuracy of 96.6%. We thereby show that the movement of individual animals is a characteristic feature and it can be utilized for re-identification.

The monitoring of animals under human care is a crucial tool for biologists and zookeepers to keep track of the animals’ physical and psychological health. Additionally, it enables the analysis of observed behavioral changes and helps to unravel underlying reasons. Enhancing our understanding of animals ensures and improves ex situ animal welfare as well as in situ conservation. However, traditional observation methods are time- and labor-intensive, as they require experts to observe the animals on-site during long and repeated sessions and manually score their behavior. Therefore, the development of automated observation systems would greatly benefit researchers and practitioners in this domain. We propose an automated framework for basic behavior monitoring of individual animals under human care. Raw video data are processed to continuously determine the position of the individuals within the enclosure. The trajectories describing their travel patterns are presented, along with fundamental analysis, through a graphical user interface (GUI). We evaluate the performance of the framework on captive polar bears (Ursus maritimus). We show that the framework can localize and identify individual polar bears with an F1 score of 86.4%. The localization accuracy of the framework is $19.9\pm 7.6$ cm, outperforming current manual observation methods. Furthermore, we provide a bounding-box-labeled dataset of the two polar bears housed in Nuremberg Zoo.

An intense public debate has fuelled governmental bans on marine mammals held in zoological institutions. The debate rests on the assumption that survival in zoological institutions has been and remains lower than in the wild, albeit the scientific evidence in support of this notion is equivocal. Here, we used statistical methods previously applied to assess historical improvements in human lifespan and data on 8864 individuals of four marine mammal species (harbour seal, Phoca vitulina ; California sea lion, Zalophus californianus ; polar bear, Ursus maritimus ; common bottlenose dolphin, Tursiops truncatus ) held in zoos from 1829 to 2020. We found that life expectancy increased up to 3.40 times, and first-year mortality declined up to 31%, during the last century in zoos. Moreover, the life expectancy of animals in zoos is currently 1.65–3.55 times longer than their wild counterparts. Like humans, these improvements have occurred concurrently with advances in management practices, crucial for population welfare. Science-based decisions will help effective legislative changes and ensure better implementation of animal care.

Zoos and aquaria must provide optimal husbandry conditions and the highest welfare standards for their animals. How the welfare state of an animal or a group of animals can be precisely assessed is currently under debate, and new approaches are necessary to reliably evaluate changes in welfare. One particular measure that is easily applicable is behavioral observations. However, for dolphins and other cetaceans under human care, reliable behavior-based measures are rare. Using long-term observations of a group of bottlenose dolphins, we investigate how their activity budgets and different behaviors changed over time and are impacted by construction noise. Additionally, we investigate whether behavioral differences are also reflected in changes in the dolphins’ performance during daily training sessions. Our results show that construction noise significantly alters the dolphins’ behavior. Play behavior decreases during construction periods; most importantly, the frequency of fast swimming activities significantly increased, and at the same time, a decrease in training performance is found. Additionally, inter- and intraindividual behavioral differences are attributed to factors, such as age or weaning. Significant changes in a dolphin’s activity budget can also pose potential welfare concerns. Thus, this study highlights the importance of regularly assessing and analyzing the behavior of dolphins under human care. Behavioral observations are essential welfare indicators and can—when complemented with other measures, such as assessment of training performance—provide zoo staff with important information about each individual’s state of welfare.

Ensuring high standards of animal welfare is not only an ethical duty for zoos and aquariums, but it is also essential to achieve their conservation, education, and research goals. While for some species, animal welfare assessment frameworks are already in place, little has been done for marine animals under human care. Responding to this demand, the welfare committee of the European Association for Aquatic Mammals (EAAM) set up a group of experts on welfare science, cetacean biology, and zoo animal medicine across Europe. Their objective was to develop a comprehensive tool to evaluate the welfare of bottlenose dolphins (Tursiops truncatus), named Dolphin-WET. The tool encompasses 49 indicators that were either validated through peer review or management-based expertise. The first of its kind, the Dolphin-WET is a species-specific welfare assessment tool that provides a holistic approach to evaluating dolphin welfare. Inspired by Mellor’s Five Domains Model and the Welfare Quality^®, its hierarchical structure allows for detailed assessments from overall welfare down to specific indicators. Through combining 37 animal-based and 12 resource-based indicators that are evaluated based on a two- or three-level scoring, the protocol offers a detailed evaluation of individual dolphins. This approach allows for regular internal monitoring and targeted welfare management, enabling caretakers to address specific welfare concerns effectively.

The most common feather sampling method for feather corticosterone measurement is by plucking the feathers from the bird’s skin. This procedure performed on living, restrained birds is qualified as an animal experiment according to German/European legislation, which has to be applied for from the competent authorities. The Directive 2010/63/EU requires the full implementation of the 3-R Principle of Russel and Burch in animal experiments, which means not only to replace the use of animals, but also to reduce the number of animals used and to refine procedures whenever possible. In response to this issue, the aim of this study was to validate an alternative, less invasive sampling method by cutting feathers close to the skin in comparison to the gold standard of plucking them. For this proof-of-principle study, a conventional poultry husbandry with trial groups of geese (Anser anser domesticus) and ducks (Anas sterilis) was selected. All birds were kept under the same living conditions to standardize the influencing factors regarding husbandry, and thus, their stress levels. Feather samples were collected between the shoulders from 46 geese and 51 ducks, both by cutting as well as by plucking, directly after slaughter for meat production. Feather corticosterone levels were measured with Enzyme-Linked Immunosorbent Assay (ELISA). Results were compared using Bland–Altman plots and concordance correlation coefficients (CCC). It could be seen that concordance between corticosterone levels in cut and plucked feathers was rather poor: 0.38 for Anser, and 0.57 for Anas. However, comparing the mean corticosterone values in pg/mm of each species with their respective standard deviations, the differences between the methods were negligible. As the results showed that the differences between the individuals were markedly greater than the differences between the methods, the determination of corticosterone levels in cut feathers is valid compared to using plucked feathers. The validation tests of ELISA showed only acceptable repeatability and reliability. Hence, the results should be verified in further studies. In conclusion, it is recommended for future research to use cut instead of plucked feathers for corticosterone measurement.