Pheromone trail networks in antsPosted by Simon on Sep 22 2009 in Uncategorized • 6 comments
Among the everyday challenges an ant colony faces, the exploration and the exploitation of its environment is one of the most critical. In some species food collection is achieved by thousands of workers travelling along well-defined foraging trails. These trails emerge from a succession of pheromone deposits and can result in a complex network of interconnected routes. The CouzinLab is investigating how ants manage to build such networks whose structure facilitates the navigation of workers in the foraging area of the colony. These trail networks assemble the individuals into a spatial structure that favors encounters and exchanges. As a consequence their topology as well as their geometry infuence the efficiency of the food harvesting and the dynamics of information transfer within the colony. Understanding the processes that account for the emergence of such networks allow us to better grasp the way an insect colony as a whole deals with information from its environment and how it adapts to uncertain worlds.
Insect colonies display fascinating behaviors that combine efficiency with both flexibility and robustness. From the traffic management on a foraging network to the building of efficient structures along with the dynamic task allocation between workers, examples of complex and sophisticated behaviors are numerous and diverse among social insects. Surprisingly, the complexity of these collective behaviors and structures does not reflect the relative simplicity of an insect. Of course, insects are elaborated “machines”, with the ability to modulate their behavior on the basis of the processing of many sensory inputs. Nevertheless, the complexity of an individual insect in terms of cognitive abilities may be high in an absolute sense, while remaining not sufficient to effectively supervise a large system and to explain the complexity of all the behaviors at the colony scale. In most cases, a single insect is not able to find by itself an efficient solution to a colony problem, while the society to which it belongs finds “as a whole” a solution very easily.
This collective cognition is mostly based on a decentralized organization of insects’ activities. No particular individual supervises the whole colony, no blueprint is used to coordinate animals’ task. Rather each individual behaves according to the information it gathers from its local environment, without reference to the global structure. The repeated interactions that take place among the conspecifics ensure the propagation and the transformation of this information through the colony and organize the activity of each individual. Insect colonies can be considered as a distributed cognition system: the colony’s answers to external challenges result from the integration of the partial information gathered by each individual through a sophisticated network of interactions.
Among the everyday challenges an insect colony faces, the exploration and the exploitation of resources in its environment is probably the most critical one. In some species food collection is achieved exclusively by solitary individuals, whereas in others it is achieved mostly collectively by thousands of workers traveling along well-defined foraging trails. These trails emerge from a succession of pheromone deposits, first by the scouts that have discovered the food source and that have returned to the nest, then by the workers that are recruited by these scouts from inside the nest. In some species the workers lay a chemical trail more or less permanently and a network of interconnected exploratory trails can emerge as a result of mass recruitment to a new area (that is for instance the case of the Argentine ant Linepithema humile).
The following video shows the emergence of an exploratory trail network built by a colony of Argentine ants Linepithema humile (real experimental duration: 30 min.):
In several ant species this network displays a particular geometry: the mean angle between trail bifurcations as they branch out from the nest is 50°-60°. Therefore an ant exiting the nest and moving to the food sources located at the periphery of the network generally faces symmetrical bifurcations, i.e. the two trails that follow a bifurcation deviate by approximatively 30° from the original direction of the ant. An ant coming back to its nest on the other hand faces asymmetrical bifurcations: At the bifurcation, the trail leading to the nest that follows the bifurcation deviates less (30°) from the ant original direction than the other trail (120°) that would lead away from the nest.
In recent works it has been suggested that the geometry of the trail network can help ants to navigate in their foraging environment, in particular in species where the individuals are principally guided by the pheromone trail and do not use environmental cues (landmarks or sun compass) to orient themselves. These results strongly suggest that ants can use the network geometry as a polarization cue indicating the general direction of the nest or the food sources. However these studies do not explain how ants achieve the particular configuration of the bifurcations. In particular they do not elucidate the preferential emergence of 60° angles between trail bifurcations as they branch out from the nest. In this project we propose to investigate the mechanisms used by ants to achieve polarized bifurcations as they collectively draw their pheromone trail network.
Central to this question are the concepts of stigmergy and self-organization. Stigmergy is a class of mechanisms where individuals influence each others’ activities thanks to an indirect communication mediated by modifications of the environment. The pheromone trail laying behaviour of ants is a well known example of stigmergic communication: an ant deposits on the ground a trail of pheromone (modification of the environment) that stimulates other ants to follow this trail towards the food source (modification of the conspecifics’ activity). In many cases in insect societies stigmergy is coupled with self-organization. This latter is a set of dynamical mechanisms whereby structures and solutions appear at the global level of a system from interactions among its lower-level components, without being explicitly coded at the individual level. In the previous example the recruited ants also deposit pheromone during their way back to the nest and then reinforce the trail that becomes more and more attractive. As time goes on this positive feedback allows the emergence of a well traveled path between the colony’s nest and a food source.
The coupling between stigmergy and self-organization is a powerful explanatory principle for construction and more generally for spatial structuration in social insects. It explains that the complexity of a spatial structure achieved collectively does not necessarily result from complex individual behaviours, but may arise from relatively simple interactions between the individuals involved in the collective task. It also shows that a functional structuration of space may appear without planification or reference to a blueprint.