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Evolutionary Biomechanics$
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Graham Taylor and Adrian Thomas

Print publication date: 2014

Print ISBN-13: 9780198566373

Published to Oxford Scholarship Online: April 2014

DOI: 10.1093/acprof:oso/9780198566373.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 13 April 2021

Trade-offs: selection, phylogeny, and constraint

Trade-offs: selection, phylogeny, and constraint

Chapter:
(p.123) 8 Trade-offs: selection, phylogeny, and constraint
Source:
Evolutionary Biomechanics
Author(s):

Graham K. Taylor

Adrian L. R. Thomas

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198566373.003.0008

This chapter uses multi-objective optimization theory to examine how natural selection resolves trade-offs among multiple conflicting performance objectives. Because physical constraint is universal, it is not usually possible to improve performance in one dimension without degrading performance in another. The optimizing tendency of natural selection is therefore best understood as implementing a constrained multi-objective optimization. Although we cannot, from first principles, predict exactly how natural selection is expected to weight these various performance objectives, it is usually possible to say something qualitative about how the importance of a given performance objective varies with ecology or behaviour. The most natural way to analyse the outcome of the optimization is therefore by using the concept of Pareto optimality, and the concepts of dominated and non-dominated solutions, which avoids the need to identify an explicit weighting function relating fitness to performance. This approach is illustrated by identifying the Pareto sets of soaring birds with respect to different combinations of soaring performance objectives, by mapping the morphospace describing flight morphology to a performance space describing soaring flight performance. The analysis shows that Procellariiformes in general, and albatrosses in particular, are optimized for performance objectives associated with straight-line soaring flight. In contrast, Acciptriformes in general, and vultures in particular, are optimised for performance objectives associated with circling soaring flight. This analysis solves a long-standing puzzle in animal flight research: the question of why all soaring birds are not albatross-shaped. More generally, it provides a way of understanding the astonishing variety of forms found in nature.

Keywords:   multi-objective optimization, Pareto optimality, Pareto set, trade-off, morphospace, adaptation, soaring, flight performance, albatross, vulture

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