Cooperative transport

A prime example of ant coordination is known as Cooperative Transport: the carrying of a large food load by a group of foraging ants to the nest. This task is difficult as it requires the ants to coordinate their efforts, aligning the forces they apply so as to move the load in the direction of the nest.

Efficient carrying requires the ants to assume different roles during the carrying (pulling/lifting/pushing). Moreover, the ants need to be able to navigate while carrying despite suffering from impaired perception, as their antennae and vision are partially blocked.

A factor that helps the ants overcome these difficulties is the constant turnover of carrying ants at the load. While ants that have been carrying for a long time lose orientation those that have just attached to the load carry accurate information regarding the correct route to the nest. Indeed, informed individuals who join the carrying effort act as effective leaders and steer the entire group for a short periods of time.

Remarkably, the ant group can assimilate new incoming information even though the force a leader ant exerts is not particularly strong. We’ve further shown the ant-load system lies near a phase transition, balancing conformism and individuality; if the ants are over conformist and their pull efforts too aligned the resulting collective motion is smooth but the system remains unresponsive to new information. This scenario occurs if the ants carry unnaturally large items,On the other hand, excessive individuality, as happens for small load size, would result in a random-walk-like motion pattern.

Naturally sized loads exhibit a near optimal balance between coordinated forces and sensitivity to incoming information.

The conformism of cooperatively carrying ants imply that most ants do not pull the object towards the direction of the nest but, rather, in the direction in which it already happens to be moving. Tethering the load with a thin string this behavioral rule can result in a pendulum motion perpendicular to the direction to the nest.

Our model of this constrained system predicted another motion regime which consists of full rotations of the load. Surprisingly, experiments with a large number of ants verify the existence of this biologically counter-intuitive behavior.

In the 1970's Nobel prize Laureate Pierre-Gilles De Gennes suggested a conceptual model that describes particle transport through disordered systems. He named his model The "Ant-in-A-Labyrinth". Fifty years later we have realized this model using real ants. The X8 sped up video shows longhorn crazy ants (Paratrechina longicornis) that transport a large food item through a disordered cube array that mimics their natural stone-ridden environment. The ants cooperate to significantly outperform physical models of the kind originally described by De-Gennes.

Further reading

  • Gelblum, Aviram, Ehud Fonio, Yoav Rodeh, Amos Korman, and Ofer Feinerman. "Ant collective cognition allows for efficient navigation through disordered environments." eLife 9 (2020): e55195
  • Ofer Feinerman, Itai Pinkoviezky, Aviram Gelblum, Ehud Fonio, and Nir S. Gov. "The Physics of Cooperative Transport In Groups of Ants". Nature Physics 14.7 (2018): 683-693.
  • Jonathan E. Ron, Itai Pinkoviezky, Ehud Fonio, Ofer Feinerman, and Nir S. Gov. "Bi-stability in cooperative transport by ants in the presence of obstacles". PLOS Computational Biology 14.5 (2018).
  • Aviram Gelblum, Itai Pinkoviezky, Ehud Fonio, Nir Gov, and Ofer Feinerman. “The Ant Pendulum: problem solving through an emergent oscillatory phase.” Proceedings of the National Academy of Sciences (PNAS). 113.51 (2016): 14615-14620 (2016).
  • Aviram Gelblum,Itai Pinkoviezky, Ehud Fonio, Abhijit Ghosh, Nir Gov, and Ofer Feinerman. "Ant groups optimally amplify the effect of transiently informed individuals." Nature communications 6 (2015).