Social niche construction and evolutionary transitions in individuality

Ryan, Paul A., Powers, S., Watson, Richard A. (2016). Social niche construction and evolutionary transitions in individuality. Biology and Philosophy, 31, (1), 59-79.


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Abstract

Social evolution theory conventionally takes an externalist explanatory stance, treating observed cooperation as explanandum and the positive assortment of cooperative behaviour as explanans. We ask how the circumstances bringing about this positive assortment arose in the first place. Rather than merely push the explanatory problem back a step, we move from an externalist to an interactionist explanatory stance, in the spirit of Lewontin and the Niche Construction theorists. We develop a theory of 'social niche construction' in which we consider biological entities to be both the subject and object of their own social evolution. Some important cases of the evolution of cooperation have the side-effect of causing changes in the hierarchical level at which the evolutionary process acts. This is because the traits (e.g. life-history bottlenecks) that act to align the fitness interests of particles (e.g. cells) in a collective can also act to diminish the extent to which those particles are bearers of heritable fitness variance, while augmenting the extent to which collectives of such particles (e.g. multicellular organisms) are bearers of heritable fitness variance. In this way, we can explain upward transitions in the hierarchical level at which the Darwinian machine operates in terms of particle-level selection, even though the outcome of the process is a collective-level selection regime. Our theory avoids the logical and metaphysical paradoxes faced by other attempts to explain evolutionary transitions.
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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