Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish

Correlation between bioluminescent blinks and swimming behavior in the splitfin flashlight fish Anomalops katoptron

BACKGROUND

The light organs of the splitfin flashlight fish Anomalops katoptron are necessary for schooling behavior, to determine nearest neighbor distance, and to feed on zooplankton under dim light conditions. Each behavior is coupled to context-dependent blink frequencies and can be regulated via mechanical occlusion of light organs. During shoaling in the laboratory individuals show moderate blink frequencies around 100 blinks per minute. In this study, we correlated bioluminescent blinks with the spatio-temporal dynamics of swimming profiles in three dimensions, using a stereoscopic, infrared camera system.

RESULTS

Groups of flashlight fish showed intermediate levels of polarization and distances to the group centroid. Individuals showed higher swimming speeds and curved swimming profiles during light organ occlusion. The largest changes in swimming direction occurred when darkening the light organs. Before A. katoptron exposed light organs again, they adapted a nearly straight movement direction.

CONCLUSIONS

We conclude that a change in movement direction coupled to light organ occlusion in A. katoptron is an important behavioral trait in shoaling of flashlight fish.

Selective social interactions and speed-induced leadership in schooling fish

Animals moving together in groups are believed to interact among each other with effective social forces, such as attraction, repulsion, and alignment. Such forces can be inferred using "force maps," i.e., by analyzing the dependency of the acceleration of a focal individual on relevant variables. Here, we introduce a force map technique suitable for the analysis of the alignment forces experienced by individuals. After validating it using an agent-based model, we apply the force map to experimental data of schooling fish. We observe signatures of an effective alignment force with faster neighbors and an unexpected antialignment with slower neighbors. Instead of an explicit antialignment behavior, we suggest that the observed pattern is the result of a selective attention mechanism, where fish pay less attention to slower neighbors. This mechanism implies the existence of temporal leadership interactions based on relative speeds between neighbors. We present support for this hypothesis both from agent-based modeling as well as from exploring leader-follower relationships in the experimental data.

Dynamical order and many-body correlations in zebrafish show that three is a crowd

Zebrafish constitute a convenient laboratory-based biological system for studying collective behavior. It is possible to interpret a group of zebrafish as a system of interacting agents and to apply methods developed for the analysis of systems of active and even passive particles. Here, we consider the effect of group size. We focus on two- and many-body spatial correlations and dynamical order parameters to investigate the multistate behavior. For geometric reasons, the smallest group of fish which can exhibit this multistate behavior consisting of schooling, milling and swarming is three. We find that states exhibited by groups of three fish are similar to those of much larger groups, indicating that there is nothing more than a gradual change in weighting between the different states as the system size changes. Remarkably, when we consider small groups of fish sampled from a larger group, we find very little difference in the occupancy of the state with respect to isolated groups, nor is there much change in the spatial correlations between the fish. This indicates that fish interact predominantly with their nearest neighbors, perceiving the rest of the group as a fluctuating background. Therefore, the behavior of a crowd of fish is already apparent in groups of three fish.

Mechanisms of group-hunting in vertebrates

Group-hunting is ubiquitous across animal taxa and has received considerable attention in the context of its functions. By contrast much less is known about the mechanisms by which grouping predators hunt their prey. This is primarily due to a lack of experimental manipulation alongside logistical difficulties quantifying the behaviour of multiple predators at high spatiotemporal resolution as they search, select, and capture wild prey. However, the use of new remote-sensing technologies and a broadening of the focal taxa beyond apex predators provides researchers with a great opportunity to discern accurately how multiple predators hunt together and not just whether doing so provides hunters with a per capita benefit. We incorporate many ideas from collective behaviour and locomotion throughout this review to make testable predictions for future researchers and pay particular attention to the role that computer simulation can play in a feedback loop with empirical data collection. Our review of the literature showed that the breadth of predator:prey size ratios among the taxa that can be considered to hunt as a group is very large (<100 to >102 ). We therefore synthesised the literature with respect to these predator:prey ratios and found that they promoted different hunting mechanisms. Additionally, these different hunting mechanisms are also related to particular stages of the hunt (search, selection, capture) and thus we structure our review in accordance with these two factors (stage of the hunt and predator:prey size ratio). We identify several novel group-hunting mechanisms which are largely untested, particularly under field conditions, and we also highlight a range of potential study organisms that are amenable to experimental testing of these mechanisms in connection with tracking technology. We believe that a combination of new hypotheses, study systems and methodological approaches should help push the field of group-hunting in new directions.

Fish-inspired robotic algorithm: mimicking behaviour and communication of schooling fish

This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, alignment, and repulsion, together with predator avoidance, foraging, general obstacle avoidance, and wandering. The novelty of the FIRA algorithm is the combination of predictive elements to counteract processing delays from sensors and the addition of memory. Furthermore, FIRA is specifically designed to work with an indirect communication method that leads to superior performance in collision avoidance, exploration, foraging, and the emergence of realistic behaviors. By leveraging a high-latency, non-guaranteed communication methodology inspired by stigmergy methods inherent in nature, FIRA successfully addresses some of the obstacles associated with underwater communication. This breakthrough enables the realization of inexpensive, multi-agent swarms while concurrently harnessing the advantages of tetherless communication. FIRA provides a computational light control algorithm for further research with low-cost, low-computing agents. Eventually, FIRA will be used to assimilate robots into a school of biological fish, to study or influence the school. This study endeavors to demonstrate the effectiveness of FIRA by simulating it using a digital twin of a bio-inspired robotic fish. The simulation incorporates the robot's motion and sensors in a realistic, real-time environment with the algorithm used to direct the movements of individual agents. The performance of FIRA was tested against other collective flocking algorithms to determine its effectiveness. From the experiments, it was determined that FIRA outperformed the other algorithms in both collision avoidance and exploration. These experiments establish FIRA as a viable flocking algorithm to mimic fish behavior in robotics.

Social competence improves the performance of biomimetic robots leading live fish

Collective motion is commonly modeled with static interaction rules between agents. Substantial empirical evidence indicates, however, that animals may adapt their interaction rules depending on a variety of factors and social contexts. Here, we hypothesized that leadership performance is linked to the leader's responsiveness to the follower's actions and we predicted that a leader is followed longer if it adapts to the follower's avoidance movements. We tested this prediction with live guppies that interacted with a biomimetic robotic fish programmed to act as a 'socially competent' leader. Fish that were avoiding the robot were approached more carefully in future approaches. In two separate experiments we then asked how the leadership performance of the socially competent robot leader differed to that of a robot leader that either approached all fish in the same, non-responsive, way or one that did change its approach behavior randomly, irrespective of the fish's actions. We found that (1) behavioral variability itself appears attractive and that socially competent robots are better leaders which (2) require fewer approach attempts to (3) elicit longer average following behavior than non-competent agents. This work provides evidence that social responsiveness to avoidance reactions plays a role in the social dynamics of guppies. We showcase how social responsiveness can be modeled and tested directly embedded in a living animal model using adaptive, interactive robots.

A study of transfer of information in animal collectives using deep learning tools

We studied how the interactions among animals in a collective allow for the transfer of information. We performed laboratory experiments to study how zebrafish in a collective follow a subset of trained animals that move towards a light when it turns on because they expect food at that location. We built some deep learning tools to distinguish from video which are the trained and the naïve animals and to detect when each animal reacts to the light turning on. These tools gave us the data to build a model of interactions that we designed to have a balance between transparency and accuracy. The model finds a low-dimensional function that describes how a naïve animal weights neighbours depending on focal and neighbour variables. According to this low-dimensional function, neighbour speed plays an important role in the interactions. Specifically, a naïve animal weights more a neighbour in front than to the sides or behind, and more so the faster the neighbour is moving; and if the neighbour moves fast enough, the differences coming from the neighbour's relative position largely disappear. From the lens of decision-making, neighbour speed acts as confidence measure about where to go. This article is part of a discussion meeting issue 'Collective behaviour through time'.

After 150 years of watching: is there a need for synthetic ethology?

The Darwinian idea of mental continuity is about 150 years old. Although nobody has strongly denied this evolutionary link, both conceptually and practically, relative slow advance has been made by ethology and comparative psychology to quantify mental evolution. Debates on the mechanistic interpretation of cognition often struggle with the same old issues (e.g., associationism vs cognitivism), and in general, experimental methods have made also relative slow progress since the introduction of the puzzle box. In this paper, we illustrate the prevailing issues using examples on 'mental state attribution' and 'perspective taking" and argue that the situation could be improved by the introduction of novel methodological inventions and insights. We suggest that focusing on problem-solving skills and constructing artificial agents that aim to correspond and interact with biological ones, may help to understand the functioning of the mind. We urge the establishment of a novel approach, synthetic ethology, in which researchers take on a practical stance and construct artificial embodied minds relying of specific computational architectures the performance of which can be compared directly to biological agents.

A fellow-following-principle based group model and its application to fish school analysis

Group models based on simple rules are viewed as a bridge to clarifying animal group movements. The more similar a model to real-world observations, the closer it is to the essence of such movements. Inspired by the fish school, this study suggests a principle called fellow-following for group movements. More specifically, a simple-rules-based model was proposed and extended into a set of concrete rules, and two- and three-dimensional group models were established. The model results are intuitively similar to the fish school, and when the group size increases, the milling phase of both the model and fish school tends from unstable to stable. Further, we proposed a novel order parameter and a similarity measurement framework for group structures. The proposed model indicates the intuition similarity, consistency of dynamic characteristics, and static structure similarity with fish schools, which suggests that the principle of fellow-following may reveal the essence of fish school movements. Our work suggests a different approach for the self-organized formation of a swarm robotic system based on local information.

The movement ecology of fishes

Movement of fishes in the aquatic realm is fundamental to their ecology and survival. Movement can be driven by a variety of biological, physiological and environmental factors occurring across all spatial and temporal scales. The intrinsic capacity of movement to impact fish individually (e.g., foraging) with potential knock-on effects throughout the ecosystem (e.g., food web dynamics) has garnered considerable interest in the field of movement ecology. The advancement of technology in recent decades, in combination with ever-growing threats to freshwater and marine systems, has further spurred empirical research and theoretical considerations. Given the rapid expansion within the field of movement ecology and its significant role in informing management and conservation efforts, a contemporary and multidisciplinary review about the various components influencing movement is outstanding. Using an established conceptual framework for movement ecology as a guide (i.e., Nathan et al., 2008: 19052), we synthesized the environmental and individual factors that affect the movement of fishes. Specifically, internal (e.g., energy acquisition, endocrinology, and homeostasis) and external (biotic and abiotic) environmental elements are discussed, as well as the different processes that influence individual-level (or population) decisions, such as navigation cues, motion capacity, propagation characteristics and group behaviours. In addition to environmental drivers and individual movement factors, we also explored how associated strategies help survival by optimizing physiological and other biological states. Next, we identified how movement ecology is increasingly being incorporated into management and conservation by highlighting the inherent benefits that spatio-temporal fish behaviour imbues into policy, regulatory, and remediation planning. Finally, we considered the future of movement ecology by evaluating ongoing technological innovations and both the challenges and opportunities that these advancements create for scientists and managers. As aquatic ecosystems continue to face alarming climate (and other human-driven) issues that impact animal movements, the comprehensive and multidisciplinary assessment of movement ecology will be instrumental in developing plans to guide research and promote sustainability measures for aquatic resources.

Cascading indirect genetic effects in a clonal vertebrate

Understanding how individual differences arise and how their effects propagate through groups are fundamental issues in biology. Individual differences can arise from indirect genetic effects (IGE): genetically based variation in the conspecifics with which an individual interacts. Using a clonal species, the Amazon molly (Poecilia formosa), we test the hypothesis that IGE can propagate to influence phenotypes of the individuals that do not experience them firsthand. We tested this by exposing genetically identical Amazon mollies to conspecific social partners of different clonal lineages, and then moving these focal individuals to new social groups in which they were the only member to have experienced the IGE. We found that genetically different social environments resulted in the focal animals experiencing different levels of aggression, and that these IGE carried over into new social groups to influence the behaviour of naive individuals. These data reveal that IGE can cascade beyond the individuals that experience them. Opportunity for cascading IGE is ubiquitous, especially in species with long-distance dispersal or fission-fusion group dynamics. Cascades could amplify (or mitigate) the effects of IGE on trait variation and on evolutionary trajectories. Expansion of the IGE framework to include cascading and other types of carry-over effects will therefore improve understanding of individual variation and social evolution and allow more accurate prediction of population response to changing environments.

The Potential for Physiological Performance Curves to Shape Environmental Effects on Social Behavior

As individual animals are exposed to varying environmental conditions, phenotypic plasticity will occur in a vast array of physiological traits. For example, shifts in factors such as temperature and oxygen availability can affect the energy demand, cardiovascular system, and neuromuscular function of animals that in turn impact individual behavior. Here, we argue that nonlinear changes in the physiological traits and performance of animals across environmental gradients—known as physiological performance curves—may have wide-ranging effects on the behavior of individual social group members and the functioning of animal social groups as a whole. Previous work has demonstrated how variation between individuals can have profound implications for socially living animals, as well as how environmental conditions affect social behavior. However, the importance of variation between individuals in how they respond to changing environmental conditions has so far been largely overlooked in the context of animal social behavior. First, we consider the broad effects that individual variation in performance curves may have on the behavior of socially living animals, including: (1) changes in the rank order of performance capacity among group mates across environments; (2) environment-dependent changes in the amount of among- and within-individual variation, and (3) differences among group members in terms of the environmental optima, the critical environmental limits, and the peak capacity and breadth of performance. We then consider the ecological implications of these effects for a range of socially mediated phenomena, including within-group conflict, within- and among group assortment, collective movement, social foraging, predator-prey interactions and disease and parasite transfer. We end by outlining the type of empirical work required to test the implications for physiological performance curves in social behavior.

Spatial cognitive ability is associated with transitory movement speed but not straightness during the early stages of exploration

Memories about the spatial environment, such as the locations of foraging patches, are expected to affect how individuals move around the landscape. However, individuals differ in the ability to remember spatial locations (spatial cognitive ability) and evidence is growing that these inter-individual differences influence a range of fitness proxies. Yet empirical evaluations directly linking inter-individual variation in spatial cognitive ability and the development and structure of movement paths are lacking. We assessed the performance of young pheasants (Phasianus colchicus) on a spatial cognition task before releasing them into a novel, rural landscape and tracking their movements. We quantified changes in the straightness and speed of their transitory paths over one month. Birds with better performances on the task initially made slower transitory paths than poor performers but by the end of the month, there was no difference in speed. In general, birds increased the straightness of their path over time, indicating improved efficiency independent of speed, but this was not related to performance on the cognitive task. We suggest that initial slow movements may facilitate more detailed information gathering by better performers and indicates a potential link between an individual's spatial cognitive ability and their movement behaviour.

Male Sexual Preference for Female Swimming Activity in the Guppy (Poecilia reticulata)

Mate choice that is based on behavioural traits is a common feature in the animal kingdom. Using the Trinidadian guppy, a species with mutual mate choice, we investigated whether males use female swimming activity-a behavioural trait known to differ consistently among individuals in many species-as a trait relevant for their mate choice. In the first experiment, we assessed male and female activity in an open field test alone (two repeated measures) and afterwards in heterosexual pairs (two repeated measures). In these pairs, we simultaneously assessed males' mating efforts by counting the number of sexual behaviours (courtship displays and copulations). Male and female guppies showed consistent individual differences in their swimming activity when tested both alone and in a pair, and these differences were maintained across both test situations. When controlling for male swimming behaviour and both male and female body size, males performed more courtship displays towards females with higher swimming activity. In a second experiment, we tested for a directional male preference for swimming activity by presenting males video animations of low- and high-active females in a dichotomous choice test. In congruence with experiment 1, we found males to spend significantly more time in association with the high-active female stimulus. Both experiments thus point towards a directional male preference for higher activity levels in females. We discuss the adaptive significance of this preference as activity patterns might indicate individual female quality, health or reproductive state while, mechanistically, females that are more active might be more detectable to males as well.