Desert ants achieve reliable recruitment across noisy interactions

Mechanistic modeling of alarm signaling in seed-harvester ants

Ant colonies demonstrate a finely tuned alarm response to potential threats, offering a uniquely manageable empirical setting for exploring adaptive information diffusion within groups. To effectively address potential dangers, a social group must swiftly communicate the threat throughout the collective while conserving energy in the event that the threat is unfounded. Through a combination of modeling, simulation, and empirical observations of alarm spread and damping patterns, we identified the behavioral rules governing this adaptive response. Experimental trials involving alarmed ant workers (Pogonomyrmex californicus) released into a tranquil group of nestmates revealed a consistent pattern of rapid alarm propagation followed by a comparatively extended decay period [1]. The experiments in [1] showed that individual ants exhibiting alarm behavior increased their movement speed, with variations in response to alarm stimuli, particularly during the peak of the reaction. We used the data in [1] to investigate whether these observed characteristics alone could account for the swift mobility increase and gradual decay of alarm excitement. Our self-propelled particle model incorporated a switch-like mechanism for ants' response to alarm signals and individual variations in the intensity of speed increased after encountering these signals. This study aligned with the established hypothesis that individual ants possess cognitive abilities to process and disseminate information, contributing to collective cognition within the colony (see [2] and the references therein). The elements examined in this research support this hypothesis by reproducing statistical features of the empirical speed distribution across various parameter values.

The combined role of visual and olfactory cues in foraging by Cataglyphis ants in laboratory mazes

Foragers use several senses to locate food, and many animals rely on vision and smell. It is beneficial not to rely on a single sense, which might fail under certain conditions. We examined the contribution of vision and smell to foraging and maze exploration under laboratory conditions using Cataglyphis desert ants as a model. Foraging intensity, measured as the number of workers entering the maze and arriving at the target as well as target arrival time, were greater when food, blue light, or both were offered or presented in contrast to a control. Workers trained to forage for a combined food and light cue elevated their foraging intensity with experience. However, foraging intensity was not higher when using both cues simultaneously than in either one of the two alone. Following training, we split between the two cues and moved either the food or the blue light to the opposite maze corner. This manipulation impaired foraging success by either leading to fewer workers arriving at the target cell (when the light stayed and the food was moved) or to more workers arriving at the opposite target cell, empty of food (when the food stayed and the light was moved). This result indicates that ant workers use both senses when foraging for food and readily associate light with food.

Dynamic pathogen detection and social feedback shape collective hygiene in ants

Cooperative disease defense emerges as group-level collective behavior, yet how group members make the underlying individual decisions is poorly understood. Using garden ants and fungal pathogens as an experimental model, we derive the rules governing individual ant grooming choices and show how they produce colony-level hygiene. Time-resolved behavioral analysis, pathogen quantification, and probabilistic modeling reveal that ants increase grooming and preferentially target highly-infectious individuals when perceiving high pathogen load, but transiently suppress grooming after having been groomed by nestmates. Ants thus react to both, the infectivity of others and the social feedback they receive on their own contagiousness. While inferred solely from momentary ant decisions, these behavioral rules quantitatively predict hour-long experimental dynamics, and synergistically combine into efficient colony-wide pathogen removal. Our analyses show that noisy individual decisions based on only local, incomplete, yet dynamically-updated information on pathogen threat and social feedback can lead to potent collective disease defense.

Emergent regulation of ant foraging frequency through a computationally inexpensive forager movement rule

Ant colonies regulate foraging in response to their collective hunger, yet the mechanism behind this distributed regulation remains unclear. Previously, by imaging food flow within ant colonies we showed that the frequency of foraging events declines linearly with colony satiation (Greenwald et al., 2018). Our analysis implied that as a forager distributes food in the nest, two factors affect her decision to exit for another foraging trip: her current food load and its rate of change. Sensing these variables can be attributed to the forager's individual cognitive ability. Here, new analyses of the foragers' trajectories within the nest imply a different way to achieve the observed regulation. Instead of an explicit decision to exit, foragers merely tend toward the depth of the nest when their food load is high and toward the nest exit when it is low. Thus, the colony shapes the forager's trajectory by controlling her unloading rate, while she senses only her current food load. Using an agent-based model and mathematical analysis, we show that this simple mechanism robustly yields emergent regulation of foraging frequency. These findings demonstrate how the embedding of individuals in physical space can reduce their cognitive demands without compromising their computational role in the group.

Scaling of ant colony interaction networks

In social insect colonies, individuals are physically independent but functionally integrated by interaction networks which provide a foundation for communication and drive the emergence of collective behaviors, including nest architecture, division of labor, and potentially also the social regulation of metabolic rates. To investigate the relationship between interactions, metabolism, and colony size, we varied group size for harvester ant colonies (Pogonomyrmex californicus) and assessed their communication networks based on direct antennal contacts and compared these results with proximity networks and a random movement simulation. We found support for the hypothesis of social regulation; individuals did not interact with each other randomly but exhibited restraint. Connectivity scaled hypometrically with colony size, per-capita interaction rate was scale-invariant, and smaller colonies exhibited higher measures of closeness centrality and edge density, correlating with higher per-capita metabolic rates. Although the immediate energetic cost for two ants to interact is insignificant, the downstream effects of receiving and integrating social information can have metabolic consequences. Our results indicate that individuals in larger colonies are relatively more insulated from each other, a factor that may reduce or filter noisy stimuli and contribute to the hypometric scaling of their metabolic rates, and perhaps more generally, the evolution of larger colony sizes.

Egg-Laying Behavior of Cataglyphis niger Ants Is Influenced More Strongly by Temperature Than Daylength

Temperature and photoperiod are the two most important factors that affect all aspects of animal life. We conducted two experiments to examine the effect of temperature and photoperiod on egg laying and development in the desert ant Cataglyphis niger. In the first experiment, we examined the effect of decreasing temperatures and shortening daylength on egg-laying behavior. An additional treatment was exposure to natural autumn conditions. Decreasing temperatures impaired egg laying much more than shortening daylength. The effect, however, was rapidly reversible when raising the temperature. When the outdoor treatment was brought inside the lab at a suitable temperature, queens started laying eggs as well. In the second experiment, we first kept the colonies under warmer temperatures and moved them gradually to cooler temperatures, 1-20 days after the eggs were laid. The probability of eggs developing into larvae and pupae under cooler temperatures was positively influenced by the exposure duration to warmer temperatures before the temperature switch. When the eggs developed into larvae, longer exposure to warmer temperatures before the temperature switch led to faster development. However, when the eggs disappeared (and were probably eaten), longer exposure to warmer temperatures before the temperature switch led to slower egg disappearance. We suggest that the decision to lay eggs is reversible to some extent because the workers can consume the eggs if conditions deteriorate. We suggest that this reversibility reduces the cost of laying eggs at the wrong time.

The emergence of a collective sensory response threshold in ant colonies

SignificanceIn this study, we ask how ant colonies integrate information about the external environment with internal state parameters to produce adaptive, system-level responses. First, we show that colonies collectively evacuate the nest when the ground temperature becomes too warm. The threshold temperature for this response is a function of colony size, with larger colonies evacuating the nest at higher temperatures. The underlying dynamics can thus be interpreted as a decision-making process that takes both temperature (external environment) and colony size (internal state) into account. Using mathematical modeling, we show that these dynamics can emerge from a balance between local excitatory and global inhibitory forces acting between the ants. Our findings in ants parallel other complex biological systems like neural circuits.

AntVideoRecord: Autonomous system to capture the locomotor activity of leafcutter ants

The leafcutter ants (LCA) are considered plague in a great part of the American continent, causing great damage in production fields. Knowing the locomotion and foraging rhythm in LCA on a continuous basis would imply a significant advance for ecological studies, fundamentally of animal behavior. However, studying the forage rhythm of LCA in the field involves a significant human effort. This also adds a risk of subjective results due to the operator fatigue. In this work a new development named 'AntVideoRecord' is proposed to address this issue. This device is a low-cost autonomous system that records videos of the LCA path in a fixed position. The device can be easily reproduced using the freely accessible source code provided. The evaluation of this novel device was successful because it has exceeded all the basic requirements in the field: record continuously for at least seven days, withstand high and low temperatures, capture acceptable videos during the day and night, and have a simple configuration protocol by mobile devices and laptops. It was possible to confirm the correct operation of the device, being able to record more than 1900 h in the field at different climate conditions and times of the day.

Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning

Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological approach to track alarm spread within a group of harvester ants, Pogonomyrmex californicus. We initially alarmed three ants and tracked subsequent signal transmission through the colony. Because there was no actual standing threat, the false alarm allowed us to assess amplification and adaptive damping of the collective alarm response. We trained a random forest regression model to quantify alarm behaviour of individual workers from multiple movement features. Our approach translates subjective categorical alarm scores into a reliable, continuous variable. We combined these assessments with automatically tracked proximity data to construct an alarm propagation network. This method enables analyses of spatio-temporal patterns in alarm signal propagation in a group of ants and provides an opportunity to integrate individual and collective alarm response. Using this system, alarm propagation can be manipulated and assessed to ask and answer a wide range of questions related to information and misinformation flow in social networks.

Evidence for the effect of brief exposure to food, but not learning interference, on maze solving in desert ants

Theories of forgetting highlight two active mechanisms through which animals forget prior knowledge by reciprocal disruption of memories. According to "proactive interference", information learned previously interferes with the acquisition of new information, whereas "retroactive interference" suggests that newly gathered information interferes with already existing information. Our goal was to examine the possible effect of both mechanisms in the desert ant Cataglyphis niger, which does not use pheromone recruitment, when learning spatial information while searching for food in a maze. Our experiment indicated that neither proactive nor retroactive interference took place in this system although this awaits confirmation with individual-level learning assays. Rather, the ants' persistence or readiness to search for food grew with successive runs in the maze. Elevated persistence led to more ant workers arriving at the food when retested a day later, even if the maze was shifted between runs. We support this finding in a second experiment, where ant workers reached the food reward at the maze end in higher numbers after encountering food in the maze entry compared to a treatment, in which food was present only at the maze end. This result suggests that spatial learning and search persistence are two parallel behavioral mechanisms, both assisting foraging ants. We suggest that their relative contribution should depend on habitat complexity. This article is protected by copyright. All rights reserved.

Hive geometry shapes the recruitment rate of honeybee colonies

Honey bees make decisions regarding foraging and nest-site selection in groups ranging from hundreds to thousands of individuals. To effectively make these decisions, bees need to communicate within a spatially distributed group. However, the spatiotemporal dynamics of honey bee communication have been mostly overlooked in models of collective decisions, focusing primarily on mean field models of opinion dynamics. We analyze how the spatial properties of the nest or hive, and the movement of individuals with different belief states (uncommitted or committed) therein affect the rate of information transmission using spatially-extended models of collective decision-making within a hive. Honeybees waggle-dance to recruit conspecifics with an intensity that is a threshold nonlinear function of the waggler concentration. Our models range from treating the hive as a chain of discrete patches to a continuous line (long narrow hive). The combination of population-thresholded recruitment and compartmentalized populations generates tradeoffs between rapid information propagation with strong population dispersal and recruitment failures resulting from excessive population diffusion and also creates an effective colony-level signal-detection mechanism whereby recruitment to low quality objectives is blocked.

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.

Ants’ Personality and Its Dependence on Foraging Styles: Research Perspectives

The paper is devoted to analyzing consistent individual differences in behavior, also known as “personalities,” in the context of a vital ant task—the detection and transportation of food. I am trying to elucidate the extent to which collective cognition is individual-based and whether a single individual’s actions can suffice to direct the entire colony or colony units. The review analyzes personalities in various insects with different life cycles and provides new insights into the role of individuals in directing group actions in ants. Although it is widely accepted that, in eusocial insects, colony personality emerges from the workers’ personalities, there are only a few examples of investigations of personality at the individual level. The central question of the review is how the distribution of behavioral types and cognitive responsibilities within ant colonies depends on a species’ foraging style. In the context of how workers’ behavioral traits display during foraging, a crucial question is what makes an ant a scout that discovers a new food source and mobilizes its nestmates. In mass recruiting, tandem-running, and even in group-recruiting species displaying leadership, the division of labor between scouts and recruits appears to be ephemeral. There is only little, if any, evidence of ants’ careers and behavioral consistency as leaders. Personal traits characterize groups of individuals at the colony level but not performers of functional roles during foraging. The leader-scouting seems to be the only known system that is based on a consistent personal difference between scouting and foraging individuals.

Distributed physiology and the molecular basis of social life in eusocial insects

The traditional focus of physiological and functional genomic research is on molecular processes that play out within a single multicellular organism. In the colonial (eusocial) insects such as ants, bees, and termites, molecular and behavioral responses of interacting nestmates are tightly linked, and key physiological processes are regulated at the scale of the colony. Such colony-level physiological processes regulate nestmate physiology in a distributed fashion, through various social communication mechanisms. As a result of physiological decentralization over evolutionary time, organismal mechanisms, for example related to pheromone detection, hormone signaling, and neural signaling pathways, are deployed in novel contexts to influence nestmate and colony traits. Here we explore how functional genomic, physiological, and behavioral studies can benefit from considering the traits of eusocial insects in this light. We highlight functional genomic work exploring how nestmate-level and colony-level traits arise and are influenced by interactions among physiologically-specialized nestmates of various developmental stages. We also consider similarities and differences between nestmate-level (organismal) and colony-level (superorganismal) physiological processes, and make specific hypotheses regarding the physiology of eusocial taxa. Integrating theoretical models of distributed systems with empirical functional genomics approaches will be useful in addressing fundamental questions related to the evolution of eusociality and collective behavior in natural systems.

Non-spatial information on the presence of food elevates search intensity in ant workers, leading to faster maze solving in a process parallel to spatial learning

Experience can lead to faster exploitation of food patches through spatial learning or other parallel processes. Past studies have indicated that hungry animals either search more intensively for food or learn better how to detect it. However, fewer studies have examined the contribution of non-spatial information on the presence of food nearby to maze solving, as a parallel process to spatial learning. We exposed Cataglyphis niger ant workers to a food reward and then let them search for food in a maze. The information that food existed nearby, even without spatial information, led to faster maze solving compared to a control group that was not exposed to the food prior to the experiment. Faster solving is probably achieved by a higher number of workers entering the maze, following the information that food is present nearby. In a second experiment, we allowed the ants to make successive searches in the maze, followed by removing them after they had returned to the nest and interacted with their naïve nestmates. This procedure led to a maze-solving time in-between that displayed when removing the workers immediately after they had reached the food and preventing their return to the colony, and that of no removal. The workers that interacted upon returning to the nest might have transferred to naïve workers information, unrelated to spatial learning, that food existed nearby, and driven them to commence searching. Spatial learning, or an increase in the correct movements leading to the food reward relative to those leading to dead-ends, was only evident when the same workers were allowed to search again in the same maze. However, both non-spatial information on the presence of food that elevated search intensity and spatial learning led to faster maze solving.

Ants Use Multiple Spatial Memories and Chemical Pointers to Navigate Their Nest

Animal navigation relies on the available environmental cues and, where present, visual cues typically dominate. While much is known about vision-assisted navigation, knowledge of navigation in the dark is scarce. Here, we combine individual tracking, dynamic modular nest structures, and spatially resolved chemical profiling to study how Camponotus fellah ants navigate within the dark labyrinth of their nest. We find that, contrary to ant navigation above ground, underground navigation cannot rely on long-range information. This limitation emphasizes the ants' capabilities associated with other navigational strategies. Indeed, apart from gravity, underground navigation relies on self-referenced memories of multiple locations and on socially generated chemical cues placed at decision points away from the target. Moreover, the ants quickly readjust the weights attributed to these information sources in response to environmental changes. Generally, studying well-known behaviors in a variety of environmental contexts holds the potential of revealing new insights into animal cognition.

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We combine multiple technologies to study how ants navigate within their dark nest

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Ants substitute visual cues with gravity, chemical cues, and multi-target memories

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Following a catastrophe, ants quickly readjust the relative importance of cues

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.

How ants move: individual and collective scaling properties

The motion of social insects is often used as a paradigmatic example of complex adaptive dynamics arising from decentralized individual behaviour. In this paper, we revisit the topic of the ruling laws behind the burst of activity in ants. The analysis, done over previously reported data, reconsiders the causation arrows, proposed at individual level, not finding any link between the duration of the ants' activity and their moving speed. Secondly, synthetic trajectories created from steps of different ants demonstrate that a Markov process can explain the previously reported speed shape profile. Finally, we show that as more ants enter the nest, the faster they move, which implies a collective property. Overall, these results provide a mechanistic explanation for the reported behavioural laws, and suggest us a formal way to further study the collective properties in these scenarios.

Limits on reliable information flows through stochastic populations

Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic collective task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems.

Spatial organization and interactions of harvester ants during foraging activity

Local interactions, when individuals meet, can regulate collective behaviour. In a system without any central control, the rate of interaction may depend simply on how the individuals move around. But interactions could in turn influence movement; individuals might seek out interactions, or their movement in response to interaction could influence further interaction rates. We develop a general framework to address these questions, using collision theory to establish a baseline expected rate of interaction based on proximity. We test the models using data from harvester ant colonies. A colony uses feedback from interactions inside the nest to regulate foraging activity. Potential foragers leave the nest in response to interactions with returning foragers with food. The time series of interactions and local density of ants show how density hotspots lead to interactions that are clustered in time. A correlated random walk null model describes the mixing of potential and returning foragers. A model from collision theory relates walking speed and spatial proximity with the probability of interaction. The results demonstrate that although ants do not mix homogeneously, trends in interaction patterns can be explained simply by the walking speed and local density of surrounding ants.

Individual versus collective cognition in social insects

The concerted responses of eusocial insects to environmental stimuli are often referred to as collective cognition at the level of the colony. To achieve collective cognition, a group can draw on two different sources: individual cognition and the connectivity between individuals. Computation in neural networks, for example, is attributed more to sophisticated communication schemes than to the complexity of individual neurons. The case of social insects, however, can be expected to differ. This is because individual insects are cognitively capable units that are often able to process information that is directly relevant at the level of the colony. Furthermore, involved communication patterns seem difficult to implement in a group of insects as they lack a clear network structure. This review discusses links between the cognition of an individual insect and that of the colony. We provide examples for collective cognition whose sources span the full spectrum between amplification of individual insect cognition and emergent group-level processes.

Trophallaxis-inspired model for distributed transport between randomly interacting agents

Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

Short-term activity cycles impede information transmission in ant colonies

Rhythmical activity patterns are ubiquitous in nature. We study an oscillatory biological system: collective activity cycles in ant colonies. Ant colonies have become model systems for research on biological networks because the interactions between the component parts are visible to the naked eye, and because the time-ordered contact network formed by these interactions serves as the substrate for the distribution of information and other resources throughout the colony. To understand how the collective activity cycles influence the contact network transport properties, we used an automated tracking system to record the movement of all the individuals within nine different ant colonies. From these trajectories we extracted over two million ant-to-ant interactions. Time-series analysis of the temporal fluctuations of the overall colony interaction and movement rates revealed that both the period and amplitude of the activity cycles exhibit a diurnal cycle, in which daytime cycles are faster and of greater amplitude than night cycles. Using epidemiology-derived models of transmission over networks, we compared the transmission properties of the observed periodic contact networks with those of synthetic aperiodic networks. These simulations revealed that contrary to some predictions, regularly-oscillating contact networks should impede information transmission. Further, we provide a mechanistic explanation for this effect, and present evidence in support of it.

Social Life in Arid Environments: The Case Study of Cataglyphis Ants

Unlike most desert-dwelling animals, Cataglyphis ants do not attempt to escape the heat; rather, they apply their impressive heat tolerance to avoid competitors and predators. This thermally defined niche has promoted a range of adaptations both at the individual and colony levels. We have also recently discovered that within the genus Cataglyphis there are incredibly diverse social systems, modes of reproduction, and dispersal, prompting the tantalizing question of whether social diversity may also be a consequence of the harsh environment within which we find these charismatic ants. Here we review recent advances regarding the physiological, behavioral, life-history, colony, and ecological characteristics of Cataglyphis and consider perspectives on future research that will build our understanding of organic adaptive responses to desertification.

Effect of Interactions between Harvester Ants on Forager Decisions

Harvester ant colonies adjust their foraging activity to day-to-day changes in food availability and hour-to-hour changes in environmental conditions. This collective behavior is regulated through interactions, in the form of brief antennal contacts, between outgoing foragers and returning foragers with food. Here we consider how an ant, waiting in the entrance chamber just inside the nest entrance, uses its accumulated experience of interactions to decide whether to leave the nest to forage. Using videos of field observations, we tracked the interactions and foraging decisions of ants in the entrance chamber. Outgoing foragers tended to interact with returning foragers at higher rates than ants that returned to the deeper nest and did not forage. To provide a mechanistic framework for interpreting these results, we develop a decision model in which ants make decisions based upon a noisy accumulation of individual contacts with returning foragers. The model can reproduce core trends and realistic distributions for individual ant interaction statistics, and suggests possible mechanisms by which foraging activity may be regulated at an individual ant level.

Beyond contact-based transmission networks: the role of spatial coincidence

Animal societies rely on interactions between group members to effectively communicate and coordinate their actions. To date, the transmission properties of interaction networks formed by direct physical contacts have been extensively studied for many animal societies and in all cases found to inhibit spreading. Such direct interactions do not, however, represent the only viable pathways. When spreading agents can persist in the environment, indirect transmission via 'same-place, different-time' spatial coincidences becomes possible. Previous studies have neglected these indirect pathways and their role in transmission. Here, we use rock ant colonies, a model social species whose flat nest geometry, coupled with individually tagged workers, allowed us to build temporally and spatially explicit interaction networks in which edges represent either direct physical contacts or indirect spatial coincidences. We show how the addition of indirect pathways allows the network to enhance or inhibit the spreading of different types of agent. This dual-functionality arises from an interplay between the interaction-strength distribution generated by the ants' movement and environmental decay characteristics of the spreading agent. These findings offer a general mechanism for understanding how interaction patterns might be tuned in animal societies to control the simultaneous transmission of harmful and beneficial agents.

Confidence sharing: an economic strategy for efficient information flows in animal groups

Social animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication.

Cooperative groups are abundant on all scales of the biological world. Despite much empirical evidence on a wide variety of natural communication schemes, there is still a growing need for rigorous tools to quantify and understand the information flows involved. Here, we borrow techniques from information theory and theoretical distributed computing to study information sharing within animal groups. We consider a group of individuals that integrate personal and social information to obtain improved knowledge of their surroundings. We rigorously show that communication between such individuals can be compressed into simple messages that contain an opinion and a corresponding confidence parameter. While this algorithm is extremely efficient, further reduction in communication capacity may greatly hamper collective performances.