Morphological complexity, disparity, and diversity in the evolution of tetrapods

: (Alternative Format Thesis)

Abstract

Biologists have sought to identify and quantify evolutionary trends since the formalisation of evolutionary biology as a discipline. Prominent among these is the concept of increasing biological complexity. It is unequivocal that, by any proposed criterion, the maximum complexity of organisms has increased since the origins of life. Two problems remain for quantifying evolutionary trends in complexity. Firstly, we lack an agreed definition of complexity, and complexity cannot be measured directly or holistically. There can therefore be no universal empirical framework for quantifying complexity across organisms with fundamentally different systems of structural organisation. Secondly, there are no universally applicable tests for the existence and strength of trends, nor for determining the mechanisms that generate them.

In this work, I gathered large data sets of morphological variation in two major tetrapod clades: birds and mammals. I analysed these data using both new and existing methods, and explore the evolution of complexity on newly constructed time-calibrated distributions of composite trees. I aimed to investigate the existence, strength, and direction of trends in the evolution of morphological complexity, and investigate theoretical links between organismal complexity and
taxonomic diversity. I found strongly heterogeneous trends in the evolution of complexity, with no clear signal of either driven or passive trends of increasing complexity being predominant.

I also established a significant negative correlation between mean complexity in the limb skeletons of bird clades, and species richness in those clades. Greater mean complexity also correlated with greater ecological specialisation, which we propose as a potential driver of complexity-mediated diversity patterns.

Despite the new findings of this thesis, I concluded that the conceptual and methodological frameworks for studying macroevolutionary trends need refinement, and may be too simplistic in their current form to fully disentangle the strong heterogeneity of empirical patterns.

Date of Award	26 Jun 2024
Original language	English
Awarding Institution	University of Bath
Supervisor	Matthew Wills (Supervisor), Araxi Urrutia (Supervisor) & Martin Genner (Supervisor)