Movement, Encounter Rate, and Collective Behavior in Ant Colonies

Fire ants exhibit self-medication but lack preventive behavioral immunity against a viral pathogen

Behavioral immunity in ants encompasses collective behaviors that help defend against pathogens and parasites by reducing infection risks and limiting disease spread. However, much of the research has focused on fungal pathogens, leaving the behavioral immunity responses to viral pathogens largely unexplored. This study represents the first attempt to characterize behavioral immunity in ants against viral pathogens using the red imported fire ant, Solenopsis invicta and one of its common viruses, Solenopsis invicta virus 3 (SINV-3), as the model system. Given that SINV-3 infection has been shown to cause adverse effects on fire ants, we hypothesized that fire ants may mount behavioral immunity defenses against SINV-3 infection, specifically through avoidance behavior, organizational segregation worker discrimination, and self-medication. Surprisingly, none of the preventive behavioral immunity behaviors we tested were observed, suggesting fire ants' inability to detect or mount collective defenses against SINV-3 infection. However, SINV-3-infected fire ants exhibited increased consumption of reactive oxygen species (ROS)-containing food, providing evidence of therapeutic self-medication. These findings suggest that while no evidence suggest fire ants employing preventive behavioral immunity against SINV-3, they may mitigate the effects of infection through self-medication, highlighting a different adaptive strategy in response to viral pathogens. This study opens new avenues for understanding the adaptive strategies of ants to cope with viral pathogens.

Foraging trail traffic rules: a new study method of trajectories of the harvester ants

Harvester ants are one of the most extensively studied groups of ants, especially the group foraging ants, Messor barbarus (Linnaeus, 1767), which construct long-lasting trunk trails. Limited laboratory investigations have delved into head-on encounters along foraging trails involving workers moving in opposing directions, with fewer corresponding studies conducted in the natural environment. To address this gap, we devised an in-field experimental design to induce lane segregation on the foraging trunk trail of M. barbarus. Using an image-based tracking method, we analyzed the foraging behavior of this species to assess the costs associated with head-on encounters and to figure out the natural coexistence of outgoing and returning workers on a bidirectional route. Our results consistently reveal heightened straightness and speed in unidirectional test lanes, accompanied by an elevated foraging rate compared to bidirectional lanes. This suggests a potential impact of head-on collisions on foraging behavior, especially on foraging efficiency. Additionally, Kinematic analysis revealed distinct movement patterns between outbound and inbound flows, particularly low speed and sinuous trajectories of inbounding unladen workers. The study of encounter rates in two traffic systems hints at the plausible utilization of individual memory by workers within trails, underscoring the pivotal role of encounters in information exchange and load transfer.

Test of the negative feedback hypothesis of colony size sensing in social insects

Social insects can sense colony size-even without visual information in a dark environment. How they achieve this is yet largely unknown. We empirically tested a hypothesis on the proximate mechanism using ant colonies. In Diacamma colonies, the monogynous queen is known to increase the effort devoted to queen pheromone transmission behaviour (patrolling) as the colony grows, as if she perceives colony size. The negative feedback hypothesis assumes that, through repeated physical contact with workers, the queen monitors the physiological state (fertility) of workers and increases her patrolling effort when she encounters more fertile workers. Supporting this hypothesis, we found that the queen increased her patrolling effort in response to a higher ratio of fertile workers under the experimental condition of constant colony size. Furthermore, chemical analyses and bioassays suggested that cuticular hydrocarbons have queen pheromone activity and can mediate the observed queen-worker communication of fertility state. Such a self-organizing mechanism of sensing colony size may also operate in other social insects living in small colonies.

Regulation of division of labor in insects: a colony-level perspective

Studies of division of labor have focused mainly on individual workers performing tasks. Here I propose a shift in perspective: colonies perform tasks, and task performance should be evaluated at the colony level. I then review studies from the recent literature from this perspective, on topics including evaluating task performance; specialization and efficiency; flexibility and task performance; response threshold models; and variation in behavior arising from diverse sensory experiences and learning. The use of specialized workers is only one of a variety of strategies that colonies may follow in performing tasks. The ability of colonies to produce consistent responses and to compensate for changes in the labor pool supports the idea of a task allocation system that precedes specialization. The colony-level perspective raises new questions about how tasks are done and the strategies used to improve colony task performance.

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.

The ontogeny of selection on genetic diversity in harvester ants

Selection may favour traits throughout an individual's lifetime or at a particular life stage. In many species of social insects, established colonies that are more genetically diverse outperform less diverse colonies with respect to a variety of traits that contribute to fitness, but whether selection favours high diversity in small colonies is unknown. We tested the hypothesis that selection favours genetically diverse colonies during the juvenile period using a multi-year field experiment with the harvester ant, Pogonomyrmex occidentalis. We used controlled matings to generate colonies that varied in genetic diversity and transplanted them into the field. We monitored their survival for seven (the 2015 cohort, n = 149) and six (the 2016 cohort, n = 157) years. Genetically more diverse colonies had greater survival, resulting in significant viability selection. However, in both cohorts survival was not influenced by genetic diversity until colonies were three years old. We suggest that changes in their internal organization enabled colonies to use the benefits of multiple genotypes, and discuss possible mechanisms that can generate this pattern.

Dynamics of cooperative excavation in ant and robot collectives

The solution of complex problems by the collective action of simple agents in both biologically evolved and synthetically engineered systems involves cooperative action. Understanding the resulting emergent solutions requires integrating across the organismal behavior of many individuals. Here, we investigate an ecologically relevant collective task in black carpenter ants Camponotus pennsylvanicus: excavation of a soft, erodible confining corral. These ants show a transition from individual exploratory excavation at random locations to spatially localized collective exploitative excavation and escape from the corral. Agent-based simulations and a minimal continuum theory that coarse-grains over individual actions and considers their integrated influence on the environment leads to the emergence of an effective phase space of behaviors, characterized in terms of excavation strength and cooperation intensity. To test the theory over the range of both observed and predicted behaviors, we use custom-built robots (RAnts) that respond to stimuli to characterize the phase space of emergence (and failure) of cooperative excavation. Tuning the amount of cooperation between RAnts, allows us to vary the efficiency of excavation and synthetically generate the entire range of macroscopic phases predicted by our theory. Overall, our approach shows how the cooperative completion of tasks can arise from simple rules that involve the interaction of agents with a dynamically changing environment that serves as both an enabler and a modulator of behavior.

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.