Division of Labour: Losing out to improve group fitness

A mathematical model provides clues as to why members of a group divide tasks between them even when specialisation reduces the performance of individuals.
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Figures

Simplified model of how division of labour evolves between cells in spatially organized groups.

In the model created by Cooper et al. interactions occur either between helper (yellow) and reproductive (blue) cells, or among generalists (grey). Here, the representative model created for this figure assumes that generalists invest equally into help (h = 1) and personal fecundity (f = 1), whereas specialised cells invest fully into either helping (h = 2; f = 0) or fecundity (f = 2; h = 0). Among generalists (middle), the eventual fecundity of a cell (F) is increased through help from neighbours: in this example, F = f + 0.5 n, where n is the number of neighbours. Reproductives are more efficient than generalists in converting help to fecundity, and this synergistic benefit leads to a higher final fecundity: F = f + n*s, where n represents the number of neighbours and s represents the synergistic benefit. For example, when cells are arranged into a single column, also known as a filament structure (top), and their differentiation is coordinated (left), the fecundity of reproductives (f = 2), which are neighboured by two helpers, increases to five when s = 1.5; the fecundity and help values of individual cells are indicated above and below them, respectively. In filament structures, and also branched structures (bottom), this coordinated differentiation results in the total fecundity (green box) and viability (red box) of the group being higher than in populations that did not specialise and divide their labour (middle). However, when differentiation is not coordinated (right), division of labour decreases total group-level fecundity.

Image credit: Figure created using BioRender.com

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  1. Jos Kramer
  2. Rolf Kümmerli
(2021)
Division of Labour: Losing out to improve group fitness
eLife 10:e75243.
https://doi.org/10.7554/eLife.75243