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rsos160553_si_002.py (2.51 kB)

Code required to run the simulations and reproduce the Figures has been uploaded as part of the supplementary material.S2. Analysis of the data in Python. After compiling S1, this script can be launched from the same directory to re-generate Figure 1 and Figure 2 from the main text (uses NumPy and matplotlib libraries). from How self-organization can guide evolution

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posted on 2016-11-03, 07:08 authored by Jonathan Glancy, James V. Stone, Stuart P. Wilson
Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection, and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.

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