DOI: 10.5061/dryad.f8j02
title: Data from: Task-switching costs promote the evolution of division of labor and shifts in individuality

description: From microbes to humans, the success of many organisms is achieved by
 dividing tasks among specialized group members. The evolution of such
 division of labor strategies is an important aspect of the major
 transitions in evolution. As such, identifying specific evolutionary
 pressures that give rise to group-level division of labor has become a
 topic of major interest among biologists. To overcome the challenges
 associated with studying this topic in natural systems, we use actively
 evolving populations of digital organisms, which provide a unique
 perspective on the de novo evolution of division of labor in an open-ended
 system. We provide experimental results that address a fundamental
 question regarding these selective pressures: Does the ability to improve
 group efficiency through the reduction of task-switching costs promote the
 evolution of division of labor? Our results demonstrate that as
 task-switching costs rise, groups increasingly evolve division of labor
 strategies. We analyze the mechanisms by which organisms coordinate their
 roles and discover strategies with striking biological parallels,
 including communication, spatial patterning, and task-partitioning
 behaviors. In many cases, under high task-switching costs, individuals
 cease to be able to perform tasks in isolation, instead requiring the
 context of other group members. The simultaneous loss of functionality at
 a lower level and emergence of new functionality at a higher level
 indicates that task-switching costs may drive both the evolution of
 division of labor and also the loss of lower-level autonomy, which are
 both key components of major transitions in evolution.
description: SI Exploring the
 Conditions Under Which Division of Labor EvolvesIn this section of the
 paper, we presented an additional experiment performed using the Avida
 digital evolution software in which we vary the environmental conditions
 and explore whether or not division of labor will evolve. Within this
 file, the treatments are: a. unlimited resources b. mutations occur during
 individual replication c. migration rate of 10% We used the shannon column
 to compute the information in the text.controls.txtSI Intrinsic Task-Switching CostsIn this section of the paper, we presented an additional experiment performed using the Avida digital evolution software in which we limited the number of types of tasks available in the environment to 3, while maintaining the same resources levels, and resource requirements for replication (1000 units) as our other experiments. Within this file, the treatments are: e1000-3more. 1000 resources, 0 task-switching costs. d1000-3more. 1000 resources, 25 task-switching costs. e1000-3-more. 1000 resources, 50 task-switching costs. We used the shannon column to compute the information in the text.limited-task-num.txtSI Twenty-Five-Role-Environment ExperimentsIn this section of the paper, we presented an additional experiment performed using the Avida digital evolution software platform in which we provided the organisms with 25 simpler tasks that they could perform. Within this file, the treatments are: d. 1000 resources, 0 task-switching costs. e. 1000 resources, 25 task-switching costs. f. 1000 resources, 50 task-switching costs. We used the shannon column to compute the information in Figure S1(a) and the demereact column to compute the information in Figure S2(b).twenty-five-role.txtTask-Switching Costs Promote Division of LaborThis file describes the results of our central experiment performed using the Avida digital evolution software platform. Specifically, it provides the mean amount of Shannon mutual information among tasks and individuals across three resource requirements (250, 500, and 1000) using three task-switching costs (0, 25, 50). Within this file, the treatments are: a. 500 resources, 0 task-switching costs. d. 500 resources, 25 task-switching costs. e. 500 resources, 50 task-switching costs. a250. 250 resources, 0 task-switching costs. d250. 250 resources, 25 task-switching costs. e250. 250 resources, 50 task-switching costs. a1000. 1000 resources, 0 task-switching costs. d1000. 1000 resources, 25 task-switching costs. e1000. 1000 resources, 50 task-switching costs. We used the shannon column to compute the information in Table 2. Additionally, information from the demereact column is used to discuss the number of types of tasks performed by the various treatments.table2.txt