Selection, genetics and evolution of growth and size
Abstract
A considerable body of work in recent decades in the field of evolutionary quantitative genetics has
been motivated by the paradox of stasis. Mismatches between observed dynamics of size in wild
populations and evolutionary predictions must arise from deficient understanding of the theoretical
grounds underlying the evolution in a particular system, and/or the adoption of methodological tools making assumptions that are unrealistic. Although different in their nature, these classes of explanation are difficult to tear apart, as very often quantitative genetics (statistical) tools make either implicit
or explicit assumptions about biology and ecology. In this thesis, I investigate inheritance and/or
selection mechanisms when conventional applications of theory are expected to lead to biased or
erroneous predictions of evolutionary change in size. Specifically, I adopt a methodology to handle
genetic constraints in a fairly phenotypic perspective, which facilitates quantification of bias that
would exist if such constraint was not accounted for (Chapter 3). I use this methodology to tear apart
the selection in Soay sheep body mass that occurs directly through its effect on fitness and indirectly
through its effect on pregnancy during the first year of life. Next, I provide analytical proofs of several
issues with applications of integral projection models (IPMs) that incorporate inheritance and development,
concluding that these will predict no evolutionary change regardless of whether it should,
will, or has occurred (Chapter 4). Another main topic of this thesis is the development of a two-sex
individual-based model (IBM) of horn length (Chapter 6), equivalent to an IPM, that uses quantitative
genetics theory to model trait transmission (with development functions estimated in Chapter 5).
This IBM, parameterised using data from the bighorn sheep (Ovis canadensis) of Ram Mountain, is
used to quantify the evolutionary response to trophy hunting, while accounting for a large number of
ecological complexities.
Type
Thesis, PhD Doctor of Philosophy
Rights
Embargo Date: 2020-05-30
Embargo Reason: Thesis restricted in accordance with University regulations. Print and electronic copy restricted until 30th May 2020
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