The ecology of collective behavior

Disruption of collective behaviour correlates with reduced interaction efficiency

Group-living organisms commonly engage in collective behaviour to respond to an ever-changing environment. As animals face environmental change, establishing the mechanisms of information used to collectively behave is critical. Western honeybees (Apis mellifera) are highly social insects that tightly coordinate many individuals to ensure optimum colony function. We used fanning, a collective thermoregulatory behaviour that depends on both social and thermal contexts, as a case study for collective behaviour. To identify potential mechanisms behind the coordination of fanning, we used oxytetracycline, an antibiotic used in apiculture and known environmental pollutant that impairs bee physiology and behaviour. Specifically, we hypothesized that interactions drive the fanning response in honeybees and predicted that oxytetracycline would disrupt social interactions which will lead to a reduced fanning response. We found that longer exposure to antibiotics decreases fanning. Using automated tracking, we show that antibiotic treatment reduces the number of interactions, impeding the social dynamics within these small groups. Our results contribute strong evidence that interactions between individuals may drive the collective fanning response in honeybees. This work emphasizes the importance of understanding the social mechanisms that underlie collective animal coordination and how the effects of pollutants on an individual can scale to affect populations.

Ecological principles for the evolution of communication in collective systems

Communication allows members of a collective to share information about their environment. Advanced collective systems, such as multicellular organisms and social insect colonies, vary in whether they use communication at all and, if they do, in what types of signals they use, but the origins of these differences are poorly understood. Here, we develop a theoretical framework to investigate the evolution and diversity of communication strategies under collective-level selection. We find that whether communication can evolve depends on a collective's external environment: communication only evolves in sufficiently stable environments, where the costs of sensing are high enough to disfavour independent sensing but not so high that the optimal strategy is to ignore the environment altogether. Moreover, we find that the evolution of diverse signalling strategies-including those relying on prolonged signalling (e.g. honeybee waggle dance), persistence of signals in the environment (e.g. ant trail pheromones) and brief but frequent communicative interactions (e.g. ant antennal contacts)-can be explained theoretically in terms of the interplay between the demands of the environment and internal constraints on the signal. Altogether, we provide a general framework for comparing communication strategies found in nature and uncover simple ecological principles that may contribute to their diversity.

Compromise or choose: shared movement decisions in wild vulturine guineafowl

Shared-decision making is beneficial for the maintenance of group-living. However, little is known about whether consensus decision-making follows similar processes across different species. Addressing this question requires robust quantification of how individuals move relative to each other. Here we use high-resolution GPS-tracking of two vulturine guineafowl (Acryllium vulturinum) groups to test the predictions from a classic theoretical model of collective motion. We show that, in both groups, all individuals can successfully initiate directional movements, although males are more likely to be followed than females. When multiple group members initiate simultaneously, follower decisions depend on directional agreement, with followers compromising directions if the difference between them is small or choosing the majority direction if the difference is large. By aligning with model predictions and replicating the findings of a previous field study on olive baboons (Papio anubis), our results suggest that a common process governs collective decision-making in moving animal groups.

Collective synchrony of mating signals modulated by ecological cues and social signals in bioluminescent sea fireflies

Individuals often employ simple rules that can emergently synchronize behaviour. Some collective behaviours are intuitively beneficial, but others like mate signalling in leks occur across taxa despite theoretical individual costs. Whether disparate instances of synchronous signalling are similarly organized is unknown, largely due to challenges observing many individuals simultaneously. Recording field collectives and ex situ playback experiments, we describe principles of synchronous bioluminescent signals produced by marine ostracods (Crustacea; Luxorina) that seem behaviorally convergent with terrestrial fireflies, and with whom they last shared a common ancestor over 500 Mya. Like synchronous fireflies, groups of signalling males use visual cues (intensity and duration of light) to decide when to signal. Individual ostracods also modulate their signal based on the distance to nearest neighbours. During peak darkness, luminescent 'waves' of synchronous displays emerge and ripple across the sea floor approximately every 60 s, but such periodicity decays within and between nights after the full moon. Our data reveal these bioluminescent aggregations are sensitive to both ecological and social light sources. Because the function of collective signals is difficult to dissect, evolutionary convergence, like in the synchronous visual displays of diverse arthropods, provides natural replicates to understand the generalities that produce emergent group behaviour.

Collective behavior in relation with changing environments: Dynamics, modularity, and agency

Collective behavior operates without central control, using local interactions among participants to adjust to changing conditions. Many natural systems operate collectively, and by specifying what objectives are met by the system, the idea of agency helps to describe how collective behavior is embedded in the conditions it deals with. Ant colonies function collectively, and the enormous diversity of more than 15K species of ants, in different habitats, provides opportunities to look for general ecological patterns in how collective behavior operates. The foraging behavior of harvester ants in the desert regulates activity to manage water loss, while the trail networks of turtle ants in the canopy tropical forest respond to rapidly changing resources and vegetation. These examples illustrate some broad correspondences in natural systems between the dynamics of collective behavior and the dynamics of the surroundings. To outline how interactions among participants, acting in relation with changing surroundings, achieve collective outcomes, I focus on three aspects of collective behavior: the rate at which interactions adjust to conditions, the feedback regime that stimulates and inhibits activity, and the modularity of the network of interactions. To characterize the dynamics of the surroundings, I consider gradients in stability, energy flow, and the distribution of resources and demands. I then propose some hypotheses that link how collective behavior operates with changing environments.

Beyond conflict: Kinship theory of intragenomic conflict predicts individual variation in altruistic behaviour

Behavioural variation is essential for animals to adapt to different social and environmental conditions. The Kinship Theory of Intragenomic Conflict (KTIC) predicts that parent-specific alleles can support different behavioural strategies to maximize allele fitness. Previous studies, including in honey bees (Apis mellifera), supported predictions of the KTIC for parent-specific alleles to promote selfish behaviour. Here, we test the KTIC prediction that for altruism-promoting genes (i.e. those that promote behaviours that support the reproductive fitness of kin), the allele with the higher altruism optimum should be selected to be expressed while the other is silenced. In honey bee colonies, workers act altruistically when tending to the queen by performing a 'retinue' behaviour, distributing the queen's mandibular pheromone (QMP) throughout the hive. Workers exposed to QMP do not activate their ovaries, ensuring they care for the queen's brood instead of competing to lay unfertilized eggs. Due to the haplodiploid genetics of honey bees, the KTIC predicts that response to QMP is favoured by the maternal genome. We report evidence for parent-of-origin effects on the retinue response behaviour, ovarian development and gene expression in brains of worker honey bees exposed to QMP, consistent with the KTIC. Additionally, we show enrichment for genes with parent-of-origin expression bias within gene regulatory networks associated with variation in bees' response to QMP. Our study demonstrates that intragenomic conflict can shape diverse social behaviours and influence expression patterns of single genes as well as gene networks.

Towards an integrative approach to understanding collective behaviour in caterpillars

To evolve, and remain adaptive, collective behaviours must have a positive impact on overall individual fitness. However, these adaptive benefits may not be immediately apparent owing to an array of interactions with other ecological traits, which can depend on a lineage's evolutionary past and the mechanisms controlling group behaviour. A coherent understanding of how these behaviours evolve, are exhibited, and are coordinated across individuals, therefore requires an integrative approach spanning traditional disciplines in behavioural biology. Here, we argue that lepidopteran larvae are well placed to serve as study systems for investigating the integrative biology of collective behaviour. Lepidopteran larvae display a striking diversity in social behaviour, which illustrates critical interactions between ecological, morphological and behavioural traits. While previous, often classic, work has provided an understanding of how and why collective behaviours evolve in Lepidoptera, much less is known about the developmental and mechanistic basis of these traits. Recent advances in the quantification of behaviour, and the availability of genomic resources and manipulative tools, allied with the exploitation of the behavioural diversity of tractable lepidopteran clades, will change this. In doing so, we will be able to address previously intractable questions that can reveal the interplay between levels of biological variation. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Colony formation of Phaeocystis globosa: A case study of evolutionary strategy for competitive adaptation

Some algae possess a multi-morphic life cycle, either in the form of free-living solitary cells or colonies which constantly occur in algal blooms. Though colony formation seems to consume extra energy and materials, many algae tend to outbreak in form of colonies. Here, we hypothesized that colony formation is a selected evolutionary strategy to improve population competitiveness and environmental adaptation. To test the hypothesis, different sizes of colonies and solitary cells in a natural bloom of Phaeocystis globosa were investigated. The large colony showed a relatively low oxidant stress level, a nutrient trap effect, and high nutrient use efficiency. The colonial nitrogen and phosphorus concentrations were about 5-10 times higher than solitary cell phycosphere and cellular nutrient allocation decreased with the enlargement of the colonial diameter following the economies of scale law. These features provide the colony with monopolistic competence and could function as an evolutionary strategy for competitive adaptation.

Behavioral variation across the days and lives of honey bees

In honey bee colonies, workers generally change tasks with age (from brood care, to nest work, to foraging). While these trends are well established, our understanding of how individuals distribute tasks during a day, and how individuals differ in their lifetime behavioral trajectories, is limited. Here, we use automated tracking to obtain long-term data on 4,100+ bees tracked continuously at 3 Hz, across an entire summer, and use behavioral metrics to compare behavior at different timescales. Considering single days, we describe how bees differ in space use, detection, and movement. Analyzing the behavior exhibited across their entire lives, we find consistent inter-individual differences in the movement characteristics of individuals. Bees also differ in how quickly they transition through behavioral space to ultimately become foragers, with fast-transitioning bees living the shortest lives. Our analysis framework provides a quantitative approach to describe individual behavioral variation within a colony from single days to entire lifetimes.

When being flexible matters: Ecological underpinnings for the evolution of collective flexibility and task allocation

A central problem in evolutionary biology is explaining variation in the organization of task allocation across collective systems. Why do human cells irreversibly adopt a task during development (e.g., kidney vs. liver cell), while sponge cells switch between different cell types? And why have only some ant species evolved specialized castes of workers for particular tasks? Although it seems reasonable to suppose that such differences reflect, at least partially, the different ecological pressures that systems face, there is no general understanding of how a system’s dynamic environment shapes its task allocation. To this end, we develop a general mathematical framework that reveals how simple ecological considerations could potentially explain cross-system variation in task allocation—including in flexibility, specialization, and (in)activity.

Task allocation is a central feature of collective organization. Living collective systems, such as multicellular organisms or social insect colonies, have evolved diverse ways to allocate individuals to different tasks, ranging from rigid, inflexible task allocation that is not adjusted to changing circumstances to more fluid, flexible task allocation that is rapidly adjusted to the external environment. While the mechanisms underlying task allocation have been intensely studied, it remains poorly understood whether differences in the flexibility of task allocation can be viewed as adaptive responses to different ecological contexts—for example, different degrees of temporal variability. Motivated by this question, we develop an analytically tractable mathematical framework to explore the evolution of task allocation in dynamic environments. We find that collective flexibility is not necessarily always adaptive, and fails to evolve in environments that change too slowly (relative to how long tasks can be left unattended) or too quickly (relative to how rapidly task allocation can be adjusted). We further employ the framework to investigate how environmental variability impacts the internal organization of task allocation, which allows us to propose adaptive explanations for some puzzling empirical observations, such as seemingly unnecessary task switching under constant environmental conditions, apparent task specialization without efficiency benefits, and high levels of individual inactivity. Altogether, this work provides a general framework for probing the evolved diversity of task allocation strategies in nature and reinforces the idea that considering a system’s ecology is crucial to explaining its collective organization.

Formation and dissolution of midge swarms

Using external illumination cues, we induce the formation and dissolution of laboratory swarms of the nonbiting midge Chironomus riparius and study their behavior during these transient processes. In general, swarm formation is slower than swarm dissolution. We find that the swarm property that appears most rapidly during formation and disappears most rapidly during dissolution is an emergent mean radial acceleration pointing toward the center of the swarm. Our results strengthen the conjecture that this central effective force may be used as an indicator to distinguish when the midges are swarming from when they are not.

Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma

BACKGROUND & AIMS

Intratumor molecular heterogeneity is a key feature of tumorigenesis and is linked to treatment failure and patient prognosis. Herein, we aimed to determine what drives tumor cell evolution by performing single-cell transcriptomic analysis.

METHODS

We analyzed 46 hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) biopsies from 37 patients enrolled in interventional studies at the NIH Clinical Center, with 16 biopsies collected before and after treatment from 7 patients. We developed a novel machine learning-based consensus clustering approach to track cellular states of 57,000 malignant and non-malignant cells including tumor cell transcriptome-based functional clonality analysis. We determined tumor cell relationships using RNA velocity and reverse graph embedding. We also studied longitudinal samples from 4 patients to determine tumor cellular state and its evolution. We validated our findings in bulk transcriptomic data from 488 patients with HCC and 277 patients with iCCA.

RESULTS

Using transcriptomic clusters as a surrogate for functional clonality, we observed an increase in tumor cell state heterogeneity which was tightly linked to patient prognosis. Furthermore, increased functional clonality was accompanied by a polarized immune cell landscape which included an increase in pre-exhausted T cells. We found that SPP1 expression was tightly associated with tumor cell evolution and microenvironmental reprogramming. Finally, we developed a user-friendly online interface as a knowledge base for a single-cell atlas of liver cancer.

CONCLUSIONS

Our study offers insight into the collective behavior of tumor cell communities in liver cancer as well as potential drivers of tumor evolution in response to therapy.

LAY SUMMARY

Intratumor molecular heterogeneity is a key feature of tumorigenesis that is linked to treatment failure and patient prognosis. In this study, we present a single-cell atlas of liver tumors from patients treated with immunotherapy and describe intratumoral cell states and their hierarchical relationship. We suggest osteopontin, encoded by the gene SPP1, as a candidate regulator of tumor evolution in response to treatment.

Better tired than lost: Turtle ant trail networks favor coherence over short edges

Creating a routing backbone is a fundamental problem in both biology and engineering. The routing backbone of the trail networks of arboreal turtle ants (Cephalotes goniodontus) connects many nests and food sources using trail pheromone deposited by ants as they walk. Unlike species that forage on the ground, the trail networks of arboreal ants are constrained by the vegetation. We examined what objectives the trail networks meet by comparing the observed ant trail networks with networks of random, hypothetical trail networks in the same surrounding vegetation and with trails optimized for four objectives: minimizing path length, minimizing average edge length, minimizing number of nodes, and minimizing opportunities to get lost. The ants’ trails minimized path length by minimizing the number of nodes traversed rather than choosing short edges. In addition, the ants’ trails reduced the opportunity for ants to get lost at each node, favoring nodes with 3D configurations most likely to be reinforced by pheromone. Thus, rather than finding the shortest edges, turtle ant trail networks take advantage of natural variation in the environment to favor coherence, keeping the ants together on the trails.

We investigated the trail networks of arboreal turtle ants in the canopy of the tropical forest, to ask what characterizes the colony’s choice of foraging paths within the vegetation. We monitored day to day changes in the junctions and edges of trail networks of colonies in the dry forest of western Mexico. We compared the paths used by the ants to simulated random paths in the surrounding vegetation. We found that the paths of turtle ants prioritize coherence, keeping ants together on the trail, over minimizing the average edge length. The choice of paths reduces the number of junctions in the trail where ants could get lost, and favors junctions with a physical configuration that makes it likely that successive ants will reinforce the same path. Our work suggests that design principles that emphasize keeping information flow constrained to streamlined, coherent trails may be useful in human-designed distributed routing and transport networks or robot swarms.

The Collective Behavior of Ant Groups Depends on Group Genotypic Composition

Recently, researchers have documented variation between groups in collective behavior. However, how genetic variation within and between groups contributes to population-level variation for collective behavior remains unclear. Understanding how genetic variation of group members relates to group-level phenotypes is evolutionarily important because there is increasing evidence that group-level behavioral variation influences fitness and that the genetic architecture of group-level traits can affect the evolutionary dynamics of traits. Social insects are ideal for studying the complex relationship between individual and group-level variation because they exhibit behavioral variation at multiple scales of organization. To explore how the genetic composition of groups affects collective behavior, we constructed groups of pharaoh ants (Monomorium pharaonis) from 33 genetically distinct colonies of known pedigree. The groups consisted of either all workers from the same single colony or workers from two genetically different colonies, and we assayed the exploration and aggression of the groups. We found that collective exploration, but not aggression, depended on the specific genotypic combination of group members, i.e., we found evidence for genotype-by-genotype epistasis for exploration. Group collective behavior did not depend on the pedigree relatedness between genotypes within groups. Overall, this study highlights that specific combinations of genotypes influence group-level phenotypes, emphasizing the importance of considering nonadditive effects of genotypic interactions between group members.

Active Inferants: An Active Inference Framework for Ant Colony Behavior

In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology. The ant colony is a classic case system in the function of distributed systems in terms of stigmergic decision-making and information sharing. Here we specify and simulate a Markov decision process (MDP) model for ant colony foraging. We investigate a well-known paradigm from laboratory ant colony behavioral experiments, the alternating T-maze paradigm, to illustrate the ability of the model to recover basic colony phenomena such as trail formation after food location discovery. We conclude by outlining how the active inference ant colony foraging behavioral model can be extended and situated within a nested multiscale framework and systems approaches to biology more generally.

Treadmilling and dynamic protrusions in fire ant rafts

Fire ants (Solenopsis invicta) are exemplary for their formation of cohered, buoyant and dynamic structures composed entirely of their own bodies when exposed to flooded environments. Here, we observe tether-like protrusions that emerge from aggregated fire ant rafts when docked to stationary, vertical rods. Ant rafts comprise a floating, structural network of interconnected ants on which a layer of freely active ants walk. We show here that sustained shape evolution is permitted by the competing mechanisms of perpetual raft contraction aided by the transition of bulk structural ants to the free active layer and outward raft expansion owing to the deposition of free ants into the structural network at the edges, culminating in global treadmilling. Furthermore, we see that protrusions emerge as a result of asymmetries in the edge deposition rate of free ants. Employing both experimental characterization and a model for self-propelled particles in strong confinement, we interpret that these asymmetries are likely to occur stochastically owing to wall accumulation effects and directional motion of active ants when strongly confined by the protrusions' relatively narrow boundaries. Together, these effects may realize the cooperative, yet spontaneous formation of protrusions that fire ants sometimes use for functional exploration and to escape flooded environments.

An equation of state for insect swarms

Collective behaviour in flocks, crowds, and swarms occurs throughout the biological world. Animal groups are generally assumed to be evolutionarily adapted to robustly achieve particular functions, so there is widespread interest in exploiting collective behaviour for bio-inspired engineering. However, this requires understanding the precise properties and function of groups, which remains a challenge. Here, we demonstrate that collective groups can be described in a thermodynamic framework. We define an appropriate set of state variables and extract an equation of state for laboratory midge swarms. We then drive swarms through “thermodynamic” cycles via external stimuli, and show that our equation of state holds throughout. Our findings demonstrate a new way of precisely quantifying the nature of collective groups and provide a cornerstone for potential future engineering design.

Collective decision-making when quantity is more important than quality: Lessons from a kidnapping social parasite

Identifying the general principles that shape mechanisms of collective decision-making requires studies that span a diversity of ecological contexts. However, collective decision-making has only been explored in a handful of systems. Here, I investigate the ecologically mediated costs and benefits of collective decisions by socially parasitic kidnapping ants Temnothorax americanus over where to launch raids to steal host brood. I first investigate their sampling strategies and preferences with choice tests. Using more realistic spatial scales, I confirm the findings of others that colonies use a sequential choice strategy, and do not compare options simultaneously. I then ask which ecological conditions could favour the evolution of this strategy by testing the following hypotheses from optimal foraging and mate choice theories: (a) raiding decisions are time constrained or (b) search payoffs are low due to resource uniformity. Spatial distribution and phenological data on nest contents support the time constraints hypothesis. Host nests contain an optimal ratio of brood and workers for a brief period relative to discovery rates. Colonies therefore benefit from raiding most nests they find in this period rather than deliberating over the best choice, favouring host quantity over quality. The decision strategy for raids uncovered here contrasts with best-of-n collective decision-making found in other systems. These findings demonstrate that ecological constraints on information acquisition can alter how collectives process information.

anTraX, a software package for high-throughput video tracking of color-tagged insects

Recent years have seen a surge in methods to track and analyze animal behavior. Nevertheless, tracking individuals in closely interacting, group-living organisms remains a challenge. Here, we present anTraX, an algorithm and software package for high-throughput video tracking of color-tagged insects. anTraX combines neural network classification of animals with a novel approach for representing tracking data as a graph, enabling individual tracking even in cases where it is difficult to segment animals from one another, or where tags are obscured. The use of color tags, a well-established and robust method for marking individual insects in groups, relaxes requirements for image size and quality, and makes the software broadly applicable. anTraX is readily integrated into existing tools and methods for automated image analysis of behavior to further augment its output. anTraX can handle large-scale experiments with minimal human involvement, allowing researchers to simultaneously monitor many social groups over long time periods.

Habitat features and colony characteristics influencing ant personality and its fitness consequences

Several factors can influence individual and group behavioral variation that can have important fitness consequences. In this study, we tested how two habitat types (seminatural meadows and meadows invaded by Solidago plants) and factors like colony and worker size and nest density influence behavioral (activity, meanderness, exploration, aggression, and nest displacement) variation on different levels of the social organization of Myrmica rubra ants and how these might affect the colony productivity. We assumed that the factors within the two habitat types exert different selective pressures on individual and colony behavioral variation that affects colony productivity. Our results showed individual-/colony-specific expression of both mean and residual behavioral variation of the studied behavioral traits. Although habitat type did not have any direct effect, habitat-dependent factors, like colony size and nest density influenced the individual mean and residual variation of several traits. We also found personality at the individual-level and at the colony level. Exploration positively influenced the total- and worker production in both habitats. Worker aggression influenced all the productivity parameters in seminatural meadows, whereas activity had a positive effect on the worker and total production in invaded meadows. Our results suggest that habitat type, through its environmental characteristics, can affect different behavioral traits both at the individual and colony level and that those with the strongest effect on colony productivity primarily shape the personality of individuals. Our results highlight the need for complex environmental manipulations to fully understand the effects shaping behavior and reproduction in colony-living species.

Ant Collective Behavior Is Heritable and Shaped by Selection

AbstractCollective behaviors are widespread in nature and usually assumed to be strongly shaped by natural selection. However, the degree to which variation in collective behavior is heritable and has fitness consequences-the two prerequisites for evolution by natural selection-is largely unknown. We used a new pharaoh ant (Monomorium pharaonis) mapping population to estimate the heritability, genetic correlations, and fitness consequences of three collective behaviors (foraging, aggression, and exploration), as well as of body size, sex ratio, and caste ratio. Heritability estimates for the collective behaviors were moderate, ranging from 0.17 to 0.32, but lower than our estimates for the heritability of caste ratio, sex ratio, and body size of new workers, queens, and males. Moreover, variation in collective behaviors among colonies was phenotypically correlated, suggesting that selection may shape multiple colony collective behaviors simultaneously. Finally, we found evidence for directional selection that was similar in strength to estimates of selection in natural populations. Altogether, our study begins to elucidate the genetic architecture of collective behavior and is one of the first studies to demonstrate that it is shaped by selection.

Foraging through multiple nest holes: An impediment to collective decision-making in ants

In social insects, collective choices between food sources are based on self-organized mechanisms where information about resources are locally processed by the foragers. Such a collective decision emerges from the competition between pheromone trails leading to different resources but also between the recruiting stimuli emitted by successful foragers at nest entrances. In this study, we investigated how an additional nest entrance influences the ability of Myrmica rubra ant colonies to exploit two food sources of different quality (1M and 0.1M sucrose solution) and to select the most rewarding one. We found that the mobilisation of workers doubled in two-entrance nests compared to one-entrance nests but that ants were less likely to reach a food source once they exited the nest. Moreover, the collective selection of the most rewarding food source was less marked in two-entrance nests, with foragers distributing themselves evenly between the two feeders. Ultimately, multiple nest entrances reduced the foraging efficiency of ant colonies that consumed significantly less sugar out of the two available resources. Our results highlight that the nest structure, more specifically the number of nest entrances, can impede the ant's ability to process information about environmental opportunities and to select the most rewarding resource. This study opens new insights on how the physical interface between the nest interior and the outside environment can act upon collective decision-making and foraging efficiency in self-organized insect societies.

A sparse covarying unit that describes healthy and impaired human gut microbiota development

Characterizing the organization of the human gut microbiota is a formidable challenge given the number of possible interactions between its components. Using a statistical approach initially applied to financial markets, we measured temporally conserved covariance among bacterial taxa in the microbiota of healthy members of a Bangladeshi birth cohort sampled from 1 to 60 months of age. The results revealed an “ecogroup” of 15 covarying bacterial taxa that provide a concise description of microbiota development in healthy children from this and other low-income countries, and a means for monitoring community repair in undernourished children treated with therapeutic foods. Features of ecogroup population dynamics were recapitulated in gnotobiotic piglets as they transitioned from exclusive milk feeding to a fully weaned state consuming a representative Bangladeshi diet.

Gene expression variation in the brains of harvester ant foragers is associated with collective behavior

Natural selection on collective behavior acts on variation among colonies in behavior that is associated with reproductive success. In the red harvester ant (Pogonomyrmex barbatus), variation among colonies in the collective regulation of foraging in response to humidity is associated with colony reproductive success. We used RNA-seq to examine gene expression in the brains of foragers in a natural setting. We find that colonies differ in the expression of neurophysiologically-relevant genes in forager brains, and a fraction of these gene expression differences are associated with two colony traits: sensitivity of foraging activity to humidity, and forager brain dopamine to serotonin ratio. Loci that were correlated with colony behavioral differences were enriched in neurotransmitter receptor signaling & metabolic functions, tended to be more central to coexpression networks, and are evolving under higher protein-coding sequence constraint. Natural selection may shape colony foraging behavior through variation in gene expression.

Identifying determinants of bacterial fitness in a model of human gut microbial succession

Human gut microbiota development has been associated with healthy growth but understanding the determinants of community assembly and composition is a formidable challenge. We cultured bacteria from serially collected fecal samples from a healthy infant; 34 sequenced strains containing 103,102 genes were divided into two consortia representing earlier and later stages in community assembly during the first six postnatal months. The two consortia were introduced alone (singly), or sequentially in different order, or simultaneously into young germ-free mice fed human infant formula. The pattern of fitness of bacterial strains observed across the different colonization conditions indicated that later-phase strains substantially outcompete earlier-phase strains, although four early-phase members persist. Persistence was not determined by order of introduction, suggesting that priority effects are not prominent in this model. To characterize succession in the context of the metabolic potential of consortium members, we performed in silico reconstructions of metabolic pathways involved in carbohydrate utilization and amino acid and B-vitamin biosynthesis, then quantified the fitness (abundance) of strains in serially collected fecal samples and their transcriptional responses to different histories of colonization. Applying feature-reduction methods disclosed a set of metabolic pathways whose presence and/or expression correlates with strain fitness and that enable early-stage colonizers to survive during introduction of later colonizers. The approach described can be used to test the magnitude of the contribution of identified metabolic pathways to fitness in different community contexts, study various ecological processes thought to govern community assembly, and facilitate development of microbiota-directed therapeutics.

Experimental investigation of ant traffic under crowded conditions

Efficient transportation is crucial for urban mobility, cell function and the survival of animal groups. From humans driving on the highway, to ants running on a trail, the main challenge faced by all collective systems is how to prevent traffic jams in crowded environments. Here, we show that ants, despite their behavioral simplicity, have managed the tour de force of avoiding the formation of traffic jams at high density. At the macroscopic level, we demonstrated that ant traffic is best described by a two-phase flow function. At low densities there is a clear linear relationship between ant density and the flow, while at large density, the flow remains constant and no congestion occurs. From a microscopic perspective, the individual tracking of ants under varying densities revealed that ants adjust their speed and avoid time consuming interactions at large densities. Our results point to strategies by which ant colonies solve the main challenge of transportation by self-regulating their behavior.

Measuring collective behavior: an ecological approach

Collective behavior is ubiquitous throughout nature. Many systems, from brains to ant colonies, work without central control. Collective behavior is regulated by interactions among the individual participants such as neurons or ants. Interactions create feedback that produce the outcome, the behavior that we observe: Brains think and remember, ant colonies collect food or move nests, flocks of birds turn, human societies develop new forms of social organization. But the processes by which interactions produce outcomes are as diverse as the behavior itself. Just as convergent evolution has led to organs, such as the eye, that are similar in function but are based on different physiological processes, so it has led to forms of collective behavior that appear similar but arise from different social processes. An ecological perspective can help us to understand the dynamics of collective behavior and how it works.

Designing minimal and scalable insect-inspired multi-locomotion millirobots

In ant colonies, collectivity enables division of labour and resources^1-3 with great scalability. Beyond their intricate social behaviours, individuals of the genus Odontomachus⁴, also known as trap-jaw ants, have developed remarkable multi-locomotion mechanisms to 'escape-jump' upwards when threatened, using the sudden snapping of their mandibles⁵, and to negotiate obstacles by leaping forwards using their legs⁶. Emulating such diverse insect biomechanics and studying collective behaviours in a variety of environments may lead to the development of multi-locomotion robotic collectives deployable in situations such as emergency relief, exploration and monitoring⁷; however, reproducing these abilities in small-scale robotic systems with simple design and scalability remains a key challenge. Existing robotic collectives^8-12 are confined to two-dimensional surfaces owing to limited locomotion, and individual multi-locomotion robots^13-17 are difficult to scale up to large groups owing to the increased complexity, size and cost of hardware designs, which hinder mass production. Here we demonstrate an autonomous multi-locomotion insect-scale robot (millirobot) inspired by trap-jaw ants that addresses the design and scalability challenges of small-scale terrestrial robots. The robot's compact locomotion mechanism is constructed with minimal components and assembly steps, has tunable power requirements, and realizes five distinct gaits: vertical jumping for height, horizontal jumping for distance, somersault jumping to clear obstacles, walking on textured terrain and crawling on flat surfaces. The untethered, battery-powered millirobot can selectively switch gaits to traverse diverse terrain types, and groups of millirobots can operate collectively to manipulate objects and overcome obstacles. We constructed the ten-gram palm-sized prototype-the smallest and lightest self-contained multi-locomotion robot reported so far-by folding a quasi-two-dimensional metamaterial¹⁸ sandwich formed of easily integrated mechanical, material and electronic layers, which will enable assembly-free mass-manufacturing of robots with high task efficiency, flexibility and disposability.

Distributed Adaptive Search in T Cells: Lessons From Ants

There are striking similarities between the strategies ant colonies use to forage for food and immune systems use to search for pathogens. Searchers (ants and cells) use the appropriate combination of random and directed motion, direct and indirect agent-agent interactions, and traversal of physical structures to solve search problems in a variety of environments. An effective immune response requires immune cells to search efficiently and effectively for diverse types of pathogens in different tissues and organs, just as different species of ants have evolved diverse search strategies to forage effectively for a variety of resources in a variety of habitats. Successful T cell search is required to initiate the adaptive immune response in lymph nodes and to eradicate pathogens at sites of infection in peripheral tissue. Ant search strategies suggest novel predictions about T cell search. In both systems, the distribution of targets in time and space determines the most effective search strategy. We hypothesize that the ability of searchers to sense and adapt to dynamic targets and environmental conditions enhances search effectiveness through adjustments to movement and communication patterns. We also suggest that random motion is a more important component of search strategies than is generally recognized. The behavior we observe in ants reveals general design principles and constraints that govern distributed adaptive search in a wide variety of complex systems, particularly the immune system.

Timing Information Propagation in Interactive Networks

Animal behavior is greatly influenced by interaction between peers as well as with the environment. Understanding the flow of information between individuals can help decipher their behavior. This applies to both the microscopic and macroscopic levels, from cellular communication to coordinated actions by humans. The aim of this work is to provide a simple but sufficient model of information propagation to learn from natural coordinated behavior, and apply this knowledge to engineered systems. We develop a probabilistic model to infer the information propagation in a network of communicating agents with different degrees of interaction affinity. Another focus of the work is estimating the time needed to reach an agreement between all agents. We experiment using swarms of robots to emulate the communication of biological and social media groups for which we are able to provide upper bounds for the time needed to reach a global consensus, as well as to identify individuals that are responsible for slow convergence.

The Ecology of Collective Behavior in Ants

Nest choice in Temnothorax spp.; task allocation and the regulation of activity in Pheidole dentata, Pogonomyrmex barbatus, and Atta spp.; and trail networks in Monomorium pharaonis and Cephalotes goniodontus all provide examples of correspondences between the dynamics of the environment and the dynamics of collective behavior. Some important aspects of the dynamics of the environment include stability, the threat of rupture or disturbance, the ratio of inflow and outflow of resources or energy, and the distribution of resources. These correspond to the dynamics of collective behavior, including the extent of amplification, how feedback instigates and inhibits activity, and the extent to which the interactions that provide the information to regulate behavior are local or spatially centralized.

The Role of Dopamine in the Collective Regulation of Foraging in Harvester Ants

Colonies of the red harvester ant (Pogonomyrmex barbatus) differ in how they regulate collective foraging activity in response to changes in humidity. We used transcriptomic, physiological, and pharmacological experiments to investigate the molecular basis of this ecologically important variation in collective behavior among colonies. RNA sequencing of forager brain tissue showed an association between colony foraging activity and differential expression of transcripts related to biogenic amine and neurohormonal metabolism and signaling. In field experiments, pharmacological increases in forager brain dopamine titer caused significant increases in foraging activity. Colonies that were naturally most sensitive to humidity were significantly more responsive to the stimulatory effect of exogenous dopamine. In addition, forager brain tissue significantly varied among colonies in biogenic amine content. Neurophysiological variation among colonies associated with individual forager sensitivity to humidity may reflect the heritable molecular variation on which natural selection acts to shape the collective regulation of foraging.

Challenges and solutions for studying collective animal behaviour in the wild

Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations. Here we review existing methods used to collect data on the movements and interactions of multiple animals in a natural setting. We then survey emerging technologies that are poised to revolutionize the study of collective animal behaviour by extending the spatial and temporal scales of inquiry, increasing data volume and quality, and expediting the post-processing of raw data.This article is part of the theme issue 'Collective movement ecology'.

Local Regulation of Trail Networks of the Arboreal Turtle Ant, Cephalotes goniodontus

This study examines how an arboreal ant colony maintains, extends, and repairs its network of foraging trails and nests, built on a network of vegetation. Nodes are junctions where a branch forks off from another or where a branch of one plant touching another provides a new edge on which ants could travel. The ants' choice of edge at a node appears to be reinforced by trail pheromone. Ongoing pruning of the network tends to eliminate cycles and minimize the number of nodes and thus decision points, but not the distance traveled. At junctions, trails tend to stay on the same plant. In combination with the long internode lengths of the branches of vines in the tropical dry forest, this facilitates travel to food sources at the canopy edge. Exploration, when ants leave the trail on an edge that is not being used, makes both search and repair possible. The fewer the junctions between a location and the main trail, the more likely the ants are to arrive there. Ruptured trails are rapidly repaired with a new path, apparently using breadth-first search. The regulation of the network promotes its resilience and continuity.

The neurogenetics of group behavior in Drosophila melanogaster

Organisms rarely act in isolation. Their decisions and movements are often heavily influenced by direct and indirect interactions with conspecifics. For example, we each represent a single node within a social network of family and friends, and an even larger network of strangers. This group membership can affect our opinions and actions. Similarly, when in a crowd, we often coordinate our movements with others like fish in a school, or birds in a flock. Contributions of the group to individual behaviors are observed across a wide variety of taxa but their biological mechanisms remain largely unknown. With the advent of powerful computational tools as well as the unparalleled genetic accessibility and surprisingly rich social life of Drosophila melanogaster, researchers now have a unique opportunity to investigate molecular and neuronal determinants of group behavior. Conserved mechanisms and/or selective pressures in D. melanogaster can likely inform a much wider phylogenetic scale. Here, we highlight two examples to illustrate how quantitative and genetic tools can be combined to uncover mechanisms of two group behaviors in D. melanogaster: social network formation and collective behavior. Lastly, we discuss future challenges towards a full understanding how coordinated brain activity across many individuals gives rise to the behavioral patterns of animal societies.

A Balanced Mixture of Antagonistic Pressures Promotes the Evolution of Parallel Movement

A common hypothesis about the origins of collective behaviour suggests that animals might live and move in groups to increase their chances of surviving predator attacks. This hypothesis is supported by several studies that use computational models to simulate natural evolution. These studies, however, either tune an ad-hoc model to 'reproduce' collective behaviour, or concentrate on a single type of predation pressure, or infer the emergence of collective behaviour from an increase in prey density. In nature, prey are often targeted by multiple predator species simultaneously and this might have played a pivotal role in the evolution of collective behaviour. We expand on previous research by using an evolutionary rule-based system to simulate the evolution of prey behaviour when prey are subject to multiple simultaneous predation pressures. We analyse the evolved behaviour via prey density, polarization, and angular momentum. Our results suggest that a mixture of antagonistic external pressures that simultaneously steer prey towards grouping and dispersing might be required for prey individuals to evolve dynamic parallel movement.

The Evolution of the Algorithms for Collective Behavior

Collective behavior is the outcome of a network of local interactions. Here, I consider collective behavior as the result of algorithms that have evolved to operate in response to a particular environment and physiological context. I discuss how algorithms are shaped by the costs of operating under the constraints that the environment imposes, the extent to which the environment is stable, and the distribution, in space and time, of resources. I suggest that a focus on the dynamics of the environment may provide new hypotheses for elucidating the algorithms that produce the collective behavior of cellular systems.

Collective behaviour in vertebrates: a sensory perspective

Collective behaviour models can predict behaviours of schools, flocks, and herds. However, in many cases, these models make biologically unrealistic assumptions in terms of the sensory capabilities of the organism, which are applied across different species. We explored how sensitive collective behaviour models are to these sensory assumptions. Specifically, we used parameters reflecting the visual coverage and visual acuity that determine the spatial range over which an individual can detect and interact with conspecifics. Using metric and topological collective behaviour models, we compared the classic sensory parameters, typically used to model birds and fish, with a set of realistic sensory parameters obtained through physiological measurements. Compared with the classic sensory assumptions, the realistic assumptions increased perceptual ranges, which led to fewer groups and larger group sizes in all species, and higher polarity values and slightly shorter neighbour distances in the fish species. Overall, classic visual sensory assumptions are not representative of many species showing collective behaviour and constrain unrealistically their perceptual ranges. More importantly, caution must be exercised when empirically testing the predictions of these models in terms of choosing the model species, making realistic predictions, and interpreting the results.

Fitness costs of worker specialization for ant societies

Division of labour is of fundamental importance for the success of societies, yet little is known about how individual specialization affects the fitness of the group as a whole. While specialized workers may be more efficient in the tasks they perform than generalists, they may also lack the flexibility to respond to rapid shifts in task needs. Such rigidity could impose fitness costs when societies face dynamic and unpredictable events, such as an attack by socially parasitic slavemakers. Here, we experimentally assess the colony-level fitness consequences of behavioural specialization in Temnothorax longispinosus ants that are attacked by the slavemaker ant T. americanus. We manipulated the social organization of 102 T. longispinosus colonies, based on the behavioural responses of all 3842 workers. We find that strict specialization is disadvantageous for a colony's annual reproduction and growth during slave raids. These fitness costs may favour generalist strategies in dynamic environments, as we also demonstrate that societies exposed to slavemakers in the field show a lower degree of specialization than those originating from slavemaker-free populations. Our findings provide an explanation for the ubiquity of generalists and highlight their importance for the flexibility and functional robustness of entire societies.

The Spawns of Creative Behavior in Team Sports: A Creativity Developmental Framework

Developing creativity in team sports players is becoming an increasing focus in sports sciences. The Creativity Developmental Framework is presented to provide an updated science based background. This Framework describes five incremental creative stages (beginner, explorer, illuminati, creator, and rise) and combines them into multidisciplinary approaches embodied in creative assumptions. In the first training stages, the emphasis is placed on the enrollment in diversification, deliberate play and physical literacy approaches grounded in nonlinear pedagogies. These approaches allow more freedom to discover different movement patterns increasing the likelihood of emerging novel, adaptive and functional solutions. In the later stages, the progressive specialization in sports and the differential learning commitment are extremely important to push the limits of the creative progress at higher levels of performance by increasing the range of skills configurations. Notwithstanding, during all developmental stages the teaching games for understanding, a game-centered approach, linked with the constraints-led approach play an important role to boost the tactical creative behavior. Both perspectives might encourage players to explore all actions possibilities (improving divergent thinking) and prevents the standardization in their actions. Overall, considering the aforementioned practice conditions the Creativity Developmental Framework scrutinizes the main directions that lead to a long-term improvement of the creative behavior in team sports. Nevertheless, this framework should be seen as a work in progress to be later used as the paramount reference in creativity training.

Natural search algorithms as a bridge between organisms, evolution, and ecology

The ability to navigate is a hallmark of living systems, from single cells to higher animals. Searching for targets, such as food or mates in particular, is one of the fundamental navigational tasks many organisms must execute to survive and reproduce. Here, we argue that a recent surge of studies of the proximate mechanisms that underlie search behavior offers a new opportunity to integrate the biophysics and neuroscience of sensory systems with ecological and evolutionary processes, closing a feedback loop that promises exciting new avenues of scientific exploration at the frontier of systems biology.

Ant Genetics: Reproductive Physiology, Worker Morphology, and Behavior

Many exciting studies have begun to elucidate the genetics of the morphological and physiological diversity of ants, but as yet few studies have investigated the genetics of ant behavior directly. Ant genomes are marked by extreme rates of gene turnover, especially in gene families related to olfactory communication, such as the synthesis of cuticular hydrocarbons and the perception of environmental semiochemicals. Transcriptomic and epigenetic differences are apparent between reproductive and sterile females, males and females, and workers that differ in body size. Quantitative genetic approaches suggest heritability of task performance, and population genetic studies indicate a genetic association with reproductive status in some species. Gene expression is associated with behavior including foraging, response to queens attempting to join a colony, circadian patterns of task performance, and age-related changes of task. Ant behavioral genetics needs further investigation of the feedback between individual-level physiological changes and socially mediated responses to environmental conditions.

Adaptive collective foraging in groups with conflicting nutritional needs

Collective foraging, based on positive feedback and quorum responses, is believed to improve the foraging efficiency of animals. Nutritional models suggest that social information transfer increases the ability of foragers with closely aligned nutritional needs to find nutrients and maintain a balanced diet. However, whether or not collective foraging is adaptive in a heterogeneous group composed of individuals with differing nutritional needs is virtually unexplored. Here we develop an evolutionary agent-based model using concepts of nutritional ecology to address this knowledge gap. Our aim was to evaluate how collective foraging, mediated by social retention on foods, can improve nutrient balancing in individuals with different requirements. The model suggests that in groups where inter-individual nutritional needs are unimodally distributed, high levels of collective foraging yield optimal individual fitness by reducing search times that result from moving between nutritionally imbalanced foods. However, where nutritional needs are highly bimodal (e.g. where the requirements of males and females differ) collective foraging is selected against, leading to group fission. In this case, additional mechanisms such as assortative interactions can coevolve to allow collective foraging by subgroups of individuals with aligned requirements. Our findings indicate that collective foraging is an efficient strategy for nutrient regulation in animals inhabiting complex nutritional environments and exhibiting a range of social forms.