1. A methodological framework to test competing hypotheses
on the nature of organismal evolution
H. G. Ferron1,2,*, P. C. J. Donoghue2, B. Figueirido3
1Institut Cavanilles de Biodiversitat I Biologia Evolutiva, Paterna, Spain
2School of Earth Sciences, University of Bristol, Bristol, UK
3Universidad de Málaga, Málaga, Spain
*humberto.ferron@uv.es, humberto.ferron@bristol.ac.uk
Macroevolution and Functional morphology research group (https://macrofun.es/)
@Macro_Fun
The long-term patterns and processes of evolution is a key topic in evolutionary research and
the debate over the contingency vs. determinism in evolution has occupied both biologists
and palaeontologists alike for decades. Evolutionary history is replete with parallel natural
evolutionary experiments from which general nomothetic principles can be gleaned. Among
the most powerful of these natural experimental systems is the evolutionary transition to
life in water by tetrapods, a phenomenon that has happened more than 30 times
independently over different lineages. Here, we present a methodological pipeline based on
a novel combination of state-of-the-art techniques in palaeobiology in order to address the
morphological diversity and disparity of extinct and living marine tetrapods from a
functional, ecological and developmental point of view within temporal and phylogenetic
frameworks. The ultimate goal of this methodological framework is to test competing
hypotheses (contingency vs. determinism) on the nature of organismal evolution in marine
tetrapods.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
2. Methodological pipeline (Fig. 1).
- Summarizing and numerically describing the morphological diversity
of extinct and living marine tetrapod lineages, their closest terrestrial
relatives, and a sample of primitively aquatic vertebrates.
- Deriving a theoretical morphospace to sample both realised and
theoretical morphologies and characterising the evolutionary
exploration of this design space using phylomorphospace methods
to infer ancestral morphologies and plot the path of evolution onto
the theoretical morphospace.
- Interrogating this theoretical morphospace in functional terms to
create an adaptive/performance landscape.
- Testing alternative hypotheses on the nature of organismal evolution
using phylogenetic comparative methods (PCMs).
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
3. Morphometric and multivariate analyses.
Several morphometric analyses focused on the whole body by capturing
morphological information in different regions (i.e., trunk, caudal
fins/tails, forelimbs and crania) can be performed with geometric and
classical morphometrics, as well as contour analysis (Fig. 2). With this
information, a theoretical morphospace can be derived (Fig. 1).
Inclusion of developmental stages (semaphoronts) for each of the fossil
and extant lineages to obtain an insight into how accessible design
space is to developmental evolution (Fig. 1).
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
4. Morphometric and multivariate analyses.
Figure 2. Proof of concept of (A) landmark configuration for geometric morphometrics
analysis on the crania of ichthyopterygians and (B) principal component analysis
results and phylomorphospace.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
5. Computational fluid dynamic simulations (CFD).
CFD is a tool for simulating fluid flow and its interaction with solid
surfaces, and it has been used widely in engineering for decades. A
wide range of experimental conditions can be tested including different
swimming speeds and angles of attack as well as considering the
models positioned at different distances to the substrate (i.e., benthic
and pelagic scenarios). This could allow to quantify and visualize several
parameters with functional and ecological relevance such as lift and
drag, pressure distribution around the body, turbulence generation and
vorticity, among others, providing a comprehensive overview of the
hydrodynamics and lifestyle of each species (Fig. 3).
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
6. Computational fluid dynamic simulations (CFD).
Figure 3. Proof of concept of (A) 3D virtual model of Ophthalmosaurus, (B) model
mesh after discretization, and (C, D) distribution of fluid pressure and velocity around
the body, resulting from CFD analysis.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
7. Macroevolutionary analysis.
PCMs can be used to determine whether secondarily aquatic tetrapod
lineages are more similar to one another than any are to their
immediate terrestrial relatives, whether they are attracted to the same
predictable regions of design space, whether these converge on optimal
fish designs (functional ‘attractors’) or discrete but distinct regions of
design space (Riedl’s phylogenetic burden).
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
8. Macroevolutionary analysis.
Morphological disparity and phylomorphospace techniques to explore
the path of evolution onto the theoretical morphospace.
Ancestral character state reconstruction and morphospace occupation
analyses of ontogenetic trajectories to ascertain the presence of fixed
developmental pathways constraining the diversity of potential
‘designs’.
Mantel tests and Stayton metrics to determine the degree of
morphological convergence
Adaptive/performance landscapes to evaluate the relative functional
optimality of both occupied and unoccupied regions of the
morphospace.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
9. Macroevolutionary analysis.
Pareto optimality theory to better characterize the trade-offs between
the different functional traits (Fig. 1).
Phylogenetic generalized least squares analysis (PGLS) to evaluate the
functional/biomechanical components of morphology in convergent
taxa. This will allow detecting functional convergences (Fig. 4).
This can allow testing test whether evolution has explored all functional
optimal morphologies, whether many species are functionally
suboptimal, whether unrealised morphologies are functionally poor and
whether some optimal morphologies have never been achieved in
evolutionary history.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
10. Macroevolutionary analysis.
Figure 4. Proof of concept of (A) heatmaps plotted over the phylomorphospaces (drag
and lift coefficients, CD and CL) and (B) morphofunctional correlations.
Ancestral character state reconstruction of
ontogenetic trajectories
Figure 1. Methodological pipeline.
