Developmental plasticity at the behavioral repertoire level allows animals to incrementally adjust their behavioral phenotypes to match their environments through ontogeny, serving as a lynchpin between ecological factors that cue phenotypic adjustments and evolutionary forces that select upon emergent phenotypic variation. Quantifying the continuous arcs of plasticity throughout animals\' development, however, has often been prohibitively challenging. Here, we leverage recent advancements in high-resolution behavioral tracking and analysis to (i) track the behavior of 45 genetically identical fish clones (Poecilia formosa) reared in near-identical environments during their first four weeks of life at 0.2 s resolution and (ii) quantify the continuous arcs of plasticity across entire behavioral repertoires through development. Doing so, we are able to test one of the most fundamental theoretical predictions from Bayesian models of development that in stable (but initially unknown) environments, behavioral plasticity should gradually decrease from a maximum at the beginning of life. Using two approaches to measure plasticity across ontogeny, we first quantify plasticity in individual behavioral metrics before also developing a novel whole-repertoire approach that calculates plasticity as the degree of \'behavioral entropy\' across a multi-dimensional behavioral phenotype space. We robustly find -- despite experimentally matching as best as possible the assumptions of models that predict decreasing plasticity -- a ~two-week initial increase in plasticity in movement behaviors before plasticity subsequently decreased. Our results challenge a common intuition about the optimal developmental course of plasticity through early ontogeny, thereby also demonstrating the value of long-term behavioral tracking approaches for testing fundamental predictions on phenotypic development. less

Hybridization depends on reproductive isolation, which can be impacted by mate choice. Mate choice may vary temporally, as it is modulated by several factors, including survival expectancy and future opportunities for reproduction. Garcialebias reicherti and G. charrua are annual fishes with parapatric distributions that hybridize in the overlapping area of their distributions. They inhabit temporary ponds that flood during the autumn and dry out during the spring, resulting in decreased survival expectancy and future opportunities for reproduction during the breeding season. We predicted that a decrease in survival expectancy would promote reproduction and reduce reproductive isolation between G. reicherti and G charrua. By simulating desiccation in the early and late breeding season, we investigated the effects of the desiccation risk and the phase of the breeding season on reproductive isolation and reproductive effort of these species. As expected, our findings reveal that decreased survival expectancy influences both reproductive isolation between G. reicherti and G. charrua, and their reproductive effort. Notably, reproductive isolation between these species decreased under a high desiccation risk and in the late breeding season. Additionally, we observed an increase in the frequency of mating and courtship events and aggressive behaviours in the late breeding season. Our study suggests that reproductive isolation between G. reicherti and G. charrua and their reproductive effort can change rapidly within a short period of time, emphasizing the influence of survival expectancy on the temporal dynamics of reproductive isolation and hybridization. less

Zipf\'s law of abbreviation predicts that in human languages, words that are used more frequently will be shorter than words that are used less frequently. This has been attributed to the principle of least effort - communication is more efficient when words that are used more frequently are easier to produce. Zipf\'s law of abbreviation appears to hold for all human languages, and recently attention has turned to whether it also holds for animal communication. In birdsong, which has been used as a model for human language learning and development, researchers have focused on whether more frequently used notes or phrases are shorter than those that are less frequently used. Because birdsong can be highly stereotyped, have high interindividual variation, and have phrase repertoires that are small relative to human language lexicons, studying Zipf\'s law of abbreviation in birdsong presents challenges that do not arise when studying human languages. In this paper, we describe a new method for assessing evidence for Zipf\'s law of abbreviation in birdsong, and we introduce the R package ZLAvian to implement this analysis. We used ZLAvian to study Zipf\'s law of abbreviation in the songs of 11 bird populations archived in the open-access repository Bird-DB. We did not find strong evidence for Zipf\'s law of abbreviation in any population when studied alone, but we found weak trends consistent with Zipf\'s law of abbreviation in 10 of the 11 populations. Across all populations, the negative correlation between phrase length and frequency of use was several times weaker than the negative correlation between word length and frequency of use in human languages. This suggests that the mechanisms that underlie this correlation may be different in birdsong and human language. less

Plasticity is a major feature of behavior and particularly important for how animals respond to predators. While animals frequently show plastic responses when directly exposed to predators, with these exposures even leading to permanent behavioral changes and transgenerational effects, whether indirect cues of predator presence can elicit similarly severe responses is unclear. We exposed banded crickets (Gryllodes siglattus) to cues of predator presence throughout development and compared their behavior--as well as the behavior of their offspring--to individuals who had not been reared in the presence of predator cues. Contrary to findings in both G. sigilattus and related species, we did not detect either developmental plasticity in the form of differences between adult behavior or differences in offspring behavior. These findings suggest that chronic exposure to cues of predator presence have a substantially different affect on behaviors than does direct exposure to predators. How habituation might interact with developmental plasticity and transgenerational effects requires further investigation. less

Social structure and individual sociality impact a wide variety of behavioural and ecological processes. Although it is well known that changes in the physical and social environment shape sociality, how perturbations govern sociality at a fine spatial scale remains poorly understood. By applying automated experimental treatments to RFID-tracked wild great tits (Parus major) in a field experiment, we examined how individual social network metrics changed when food resources and social stability were experimentally manipulated at the within-group spatial scale. First, we examined how individual sociality responds when food resources changed from a dispersed distribution (50m apart) to a clustered distribution (1m apart). Second, we tested how sociality changed when individuals were restricted to feeding in a manner that mimics assortative behaviour within flocks. Third, we tested the effects of experimentally manipulating the stability of these social groupings. Finally, we returned the feeders to the original dispersed distribution to test whether effects carried over. Repeatability analyses showed consistent differences among individuals in their social phenotypes across the various manipulations; dyadic association preferences also showed consistency. Nevertheless, average flock size and social centrality measures increased after the food was clustered. Some of these metrics changed further when birds were then forced to feed from only one of the five clustered feeders. There was some support for group stability at individual feeders also impacting individual social network metrics: increase in flock size was more pronounced in the stable than the unstable group. Most of the differences in sociality were maintained when the food distribution returned to the dispersed pattern, and this was caused primarily by the change in resource distribution rather than the social manipulation. Our results show that perturbations in the access to resources and social group stability can change sociality at a surprisingly fine spatial scale. These small-scale changes could arise through a variety of mechanisms, including assortative positioning within groups due to, for instance, similarity among individuals in their preferences for different resource patches. Our results suggest that small-scale effects could lead to social processes at larger scales and yet are typically overlooked in social groups. less

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the real-time dyadic vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework which suggests that vocalizations are adjusted for maximizing perceived response probability. We conducted simulations of a vocal accommodation and an active sampling policy and compared them with real vocal exchange data. Our findings support active sampling as the best model for marmoset monkey vocal exchanges. These results suggest a new function for primate vocal interactions in which they are used by animals to seek information from social environments. less

In the field of motor learning, few studies have addressed the case of non-instructed movement sequences learning, as they require long periods of training and data acquisition, and are complex to interpret. In contrast, such problems are readily addressed in machine learning, using artificial agents in simulated environments. To understand the mechanisms that drive the learning behavior of two macaque monkeys in a free-moving multi-target reaching task, we created two Reinforcement Learning (RL) models with different penalty criteria: \"Time\" reflecting the time spent to perform a trial, and \"Power\" integrating the energy cost. The initial phase of the learning process is characterized by a rapid improvement in motor performance for both the 2 monkeys and the 2 models, with hand trajectories becoming shorter and smoother while the velocity gradually increases along trials and sessions. This improvement in motor performance with training is associated with a simplification in the trajectory of the movements performed to achieve the task goal. The monkeys and models show a convergent evolution towards an optimal circular motor path, almost exclusively in counter-clockwise direction, and a persistent inter-trial variability. All these elements contribute to interpreting monkeys learning in the terms of a progressive updating of action-selection patterns, following a classic value iteration scheme as in reinforcement learning. However, in contrast with our models, the monkeys also show a specific variability in the choice of the motor sequences to carry out across trials. This variability reflects a form of `path selection\', that is absent in the models. Furthermore, comparing models and behavioral data also reveal sub-optimality in the way monkeys manage the trade-off between optimizing movement duration (\"Time\") and minimizing its metabolic cost (\"Power\"), with a tendency to overemphasize one criterion at the detriment of the other one. Overall, this study reveals the subtle interplay between cognitive factors, biomechanical constraints, task achievement and motor efficacy management in motor learning, and highlights the relevance of modeling approaches in revealing the respective contribution of the different elements at play. less

Bumblebee activity typically decreases during rainfall, putting them under the threat of the increased frequency of precipitation due to climate change. A novel rain machine was used within a flight arena to observe the behavioural responses of bumblebees (Bombus terrestris) to simulated rain at both a colony and individual level. During rainfall, a greater proportion of workers left the arena than entered, the opposite of which was seen during dry periods, implying that they compensate for their lack of activity when conditions improve. The proportion of workers flying and foraging decreased while resting increased in rain. This pattern reversed during dry periods, providing further evidence for compensatory activity. The increase in resting behaviour during rain is thought to evade the high energetic costs of flying whilst wet without unnecessarily returning to the nest. This effect was not repeated in individual time budgets, measured with lone workers, suggesting that the presence of conspecifics accelerates the decision of their behavioural response, perhaps via local enhancement. Bumblebees likely use social cues to strategise their energetic expenditure during precipitation, allowing them to compensate for the reduced foraging activity during rainfall when conditions improve. less

Dogs and laboratory mice are commonly trained to perform complex tasks by guiding them through a curriculum of simpler tasks (\'shaping\'). What are the principles behind effective shaping strategies? Here, we propose a machine learning framework for shaping animal behavior, where an autonomous teacher agent decides its student\'s task based on the student\'s transcript of successes and failures on previously assigned tasks. Using autonomous teachers that plan a curriculum in a common sequence learning task, we show that near-optimal shaping algorithms adaptively alternate between simpler and harder tasks to carefully balance reinforcement and extinction. Based on this intuition, we derive an adaptive shaping heuristic with minimal parameters, which we show is near-optimal on the sequence learning task and robustly trains deep reinforcement learning agents on navigation tasks that involve sparse, delayed rewards. Extensions to continuous curricula are explored. Our work provides a starting point towards a general computational framework for shaping animal behavior. less

As one of the most common and spectacular manifestations of coordinated behavior, collective motion is the spontaneous emergence of the ordered movement in a system consisting of many self-propelled agents, e.g., flocks of birds, schools of fish, herds of animals, and human crowds. Despite extensive studies on collective motions, a systems-level understanding of different motion patterns of collective behaviors is still lacking. This further hinders the adoption of bio-inspired mechanisms for applications of swarm robotics. Here, by leveraging three large bird-flocking datasets, we systematically investigate the emergence of different patterns of collective motions: mobbing, circling, and transit. We find that flocks with higher maneuverable motions (i.e., mobbing and circling) prefer to evolve a more nested structure of leader-follower (LF) relations and a clear hierarchy to mitigate the damage of individual freedom to group cohesion. In contrast, flocks with smooth motion (i.e., transit) do not display this tactful strategy to organize the group. To explain this empirical finding, we propose a measure based on the perception of motion salience (MS) to quantify the trade-off between individual freedom and group cohesion. Moreover, we perform the correlation analysis between LF and MS, finding that individuals with higher MS tend to lead the group with higher maneuverable motions. Those findings prompt us to develop a swarm model with adaptive MS-based (AMS) interactions and confirm that AMS interactions are responsible for the emergence of nested and hierarchical LF relations in the flocks with highly maneuverable motions. Finally, we implement AMS interactions in swarm robotics that consists of ~10^2 miniature mobile robots. The swarm experiments of collective following and collective evacuation demonstrate that AMS interactions not only empower the swarm to promptly respond to the transient perturbation but also strengthen the self-organization of collective motions in terms of temporal cognition. less