Gordon Lab

Deborah Gordon’s lab group investigates the collective regulation of behavior and collective identity, how collective behavior functions ecologically and how it evolves. We examine how ant colonies work without central control using networks of simple interactions, and how these networks evolve in relation to changing environments. For the Agency project, we are studying how biological agency is implemented at the cooling level by asking how turtle ants in the canopy of the tropical forest create and repair networks of trails in the network of vegetation, using a search and routing algorithms, and how this behavior develops as the colony grows older and larger. Ongoing work in the lab includes a  long-term study tracking a population of harvester ant colonies in the desert of the southwestern US to show how evolution is currently shaping collective behavior in a natural population, studies of the invasive Argentine ant in northern California, and ant-plant mutualisms in Central America. 


The Ecology of Collective Behavior in Ants (2019)

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.

A distributed algorithm to maintain and repair the trail networks of arboreal ants (2018)

We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests and temporary food sources. This species travels only in the trees, so their foraging trails are constrained to lie on a natural graph formed by overlapping branches and vines in the tangled canopy.

The Evolution of the Algorithms for Collective Behavior (2016)

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.

From division of labor to the collective behavior of social insects (2016)

‘Division of labor’ is a misleading way to describe the organization of tasks in social insect colonies, because there is little evidence for persistent individual specialization in task. Instead, task allocation in social insects occurs through distributed processes whose advantages, such as resilience, differ from those of division of labor, which are mostly based on learning.

The Ecology of Collective Behavior (2014)

Similar patterns of interaction, such as network motifs and feedback loops, are used in many natural collective processes, probably because they have evolved independently under similar pressures. Here I consider how three environmental constraints may shape the evolution of collective behavior: the patchiness of resources, the operating costs of maintaining the interaction network that produces collective behavior, and the threat of rupture of the network.