Environmental conditions change constantly either by anthropogenic perturbation or naturally across space and time. Often, a change in behavior is the first response to changing conditions. Behavioral flexibility can potentially improve an organism's chances to survive and reproduce. Currently, we lack an understanding on the time-scale such behavioral adjustments need, how they actually affect reproduction and survival and whether behavioral adjustments are sufficient in keeping up with changing conditions. We used house mice (Mus musculus) to test whether personality and life-history traits can adjust to an experimentally induced food-switch flexibly in adulthood or by intergenerational plasticity, that is, adjustments only becoming visible in the offspring generation. Mice lived in 6 experimental populations of semi-natural environments either on high or standard quality food for 4 generations. We showed previously that high-quality food induced better conditions and a less risk-prone personality. Here, we tested whether the speed and/ or magnitude of adjustment shows condition-dependency and whether adjustments incur fitness effects. Life-history but not personality traits reacted flexibly to a food-switch, primarily by a direct reduction of reproduction and slowed-down growth. Offspring whose parents received a food-switch developed a more active stress-coping personality and gained weight at a slower rate compared with their respective controls. Furthermore, the modulation of most traits was condition-dependent, with animals previously fed with high-quality food showing stronger responses. Our study highlights that life-history and personality traits adjust at different speed toward environmental change, thus, highlighting the importance of the environment and the mode of response for evolutionary models.

During collective vigilance, it is commonly assumed that individual animals compromise their feeding time to be vigilant against predators, benefiting the entire group. One notable issue with this assumption concerns the unclear nature of predator “detection”, particularly in terms of vision. It remains uncertain how a vigilant individual utilizes its high-acuity vision (such as the fovea) to detect a predator cue and subsequently guide individual and collective escape responses. Using fine-scale motion capture technologies, we tracked the head and body orientations of pigeons (hence reconstructed their visual fields and foveal projections) foraging in a flock during simulated predator attacks. Pigeons used their fovea to inspect predator cues. Earlier foveation on a predator cue was linked to preceding behaviors related to vigilance and feeding, such as head-up or down positions, head-scanning, and food-pecking. Moreover, earlier foveation predicted earlier evasion flights at both the individual and collective levels. However, we also found that relatively long delay between their foveation and escape responses in individuals obscured the relationship between these two responses. While our results largely support the existing assumptions about vigilance, they also underscore the importance of considering vision and addressing the disparity between detection and escape responses in future research.

Individual variation in cognition is being increasingly recognized as an important evolutionary force but contradictory results so far hamper a general understanding of consistency and association with other behaviors. Partly, this might be caused by external factors imposed by the design. Stress, for example, is known to influence cognition, with mild stress improving learning abilities, while strong or chronic stress impairs them. Also, there might be intraspecific variation in how stressful a given situation is perceived. We investigated two personality traits (stress coping and voluntary exploration), spatial learning with two mazes, and problem-solving in low- and high-stress tests with a group of 30 female wild mice (Mus musculus domesticus). For each test, perceived stress was assessed by measuring body temperature change with infrared thermography, a new non-invasive method that measures skin temperature as a proxy of changes in the sympathetic system activity. While spatial learning and problem-solving were found to be repeatable traits in mice in earlier studies, none of the learning measures were significantly repeatable between the two stress conditions in our study, indicating that the stress level impacts learning. We found correlations between learning and personality traits; however, they differed between the two stress conditions and between the cognitive tasks, suggesting that different mechanisms underlie these processes. These findings could explain some of the contradictory findings in the literature and argue for very careful design of cognitive test setups to draw evolutionary implications.

Recent advances in machine learning and computer vision are revolutionizing the field of animal behavior by enabling researchers to track the poses and locations of freely moving animals without any marker attachment. However, large datasets of annotated images of animals for markerless pose tracking, especially high-resolution images taken from multiple angles with accurate 3D annotations, are still scant. Here, we propose a method that uses a motion capture (mo-cap) system to obtain a large amount of annotated data on animal movement and posture (2D and 3D) in a semi-automatic manner. Our method is novel in that it extracts the 3D positions of morphological keypoints (e.g eyes, beak, tail) in reference to the positions of markers attached to the animals. Using this method, we obtained, and offer here, a new dataset - 3D-POP with approximately 300k annotated frames (4 million instances) in the form of videos having groups of one to ten freely moving birds from 4 different camera views in a 3.6m x 4.2m area. 3D-POP is the first dataset of flocking birds with accurate keypoint annotations in 2D and 3D along with bounding box and individual identities and will facilitate the development of solutions for problems of 2D to 3D markerless pose, trajectory tracking, and identification in birds.