Can Selfish Symbioses Effect Higher-Level Selection?

Watson, Richard A., Palmius, N., Mills, R., Powers, S., Penn, Alexandra S. (2011). Can Selfish Symbioses Effect Higher-Level Selection?. In: Kampis, G., Karsai, I., Szathm√°ry, E. (Eds.) Advances in Artificial Life. Darwin Meets von Neumann. Lecture Notes in Computer Science, 5778/2011, () ( ed.). (pp. 27-36). : . Springer.


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Abstract

The role of symbiosis in macro-evolution is poorly understood. On the one hand, symbiosis seems to be a perfectly normal manifestation of individual selection, on the other hand, in some of the major transitions in evolution it seems to be implicated in the creation of new higher-level units of selection. Here we present a model of individual selection for symbiotic relationships where individuals can genetically specify traits which partially control which other species they associate with - i.e. they can evolve species-specific grouping. We find that when the genetic evolution of symbiotic relationships occurs slowly compared to ecological population dynamics, symbioses form which canalise the combinations of species that commonly occur at local ESSs into new units of selection. Thus even though symbioses will only evolve if they are beneficial to the individual, we find that the symbiotic groups that form are selectively significant and result in combinations of species that are more cooperative than would be possible under individual selection. These findings thus provide a systematic mechanism for creating significant higher-level selective units from individual selection, and support the notion of a significant and systematic role of symbiosis in macro-evolution.
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Authors

Simon T. Powers
Lecturer
S.Powers@napier.ac.uk
+44 131 455 2718

Areas of Expertise

Bio-inspired Computing
The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.

Associated Projects