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

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.