Objective
The sterile worker castes found in the colonies of social insects are often cited as archetypal examples of altruism in nature. The challenge is to explain why losing the ability to reproduce has evolved as a superior strategy for transmitting genes into future generations. The leading explanation for the evolution of worker sterility is the monogamy hypothesis. The idea is that workers don't need to reproduce because they can transmit their genes indirectly by improving the reproductive success of the queen, who carries the same genes. For this to work, the queen should be monogamously mated, ensuring workers are raising full siblings, the genetic equivalent of their own young (r = 0.5). There has been no appropriate test of this hypothesis, however, and an alternative hypothesis, that worker sterility evolved via the enforcement of cooperation by policing, has not been ruled out. According to the policing hypothesis, workers suppress each other's reproduction by eating each other’s eggs or through aggression, leading to sterility through evolutionary time. Crucially, policing is predicted to evolve when relatedness is low, in contrast to the monogamy hypothesis.
Here, I propose an interdisciplinary approach that combines a cutting-edge phylogenetic comparative analysis across ~500 ant species with novel lab-based experiments on the socially polymorphic ant, Formica exsecta, to test between the low and high relatedness evolutionary pathways to worker sterility. Contrary to common belief, workers in most ant species can lay eggs due to their haplodiploid sex determination system, making them an ideal system for answering this question. This project will fill a crucial gap in our knowledge of how complex life on Earth evolved and potentially overturn the long-held hypothesis that high relatedness is the only route to cooperation.
Fields of science
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-AG-UN - HORIZON Unit Grant
Coordinator
90014 Oulu
Finland
See on map