Endless skulls most beautiful


COMMENTARY

Endless skulls most beautiful
Daniel J. Fielda,1

The amazing disparity of living birds is self-apparent,
yet immensely challenging to fully quantify. After all,
birds are represented by nearly 11,000 living species,
comprising a mind-boggling spectrum of shapes, sizes,
and colors (1). This incredible variability manifests in
an incalculable number of ways (from habitat type to
diet to life history), but adequately characterizing any
of these axes of variation presents distinct challenges
with respect to analytical complexity and the requisite
scale of data collection.

In PNAS, Felice and Goswami (2) exemplify the
vanguard of comparative vertebrate morphology by
taking up the challenge of characterizing and analyz-
ing avian phenotypic disparity on a scale that was,
until quite recently, unimaginable. The authors focus
on the bird skull, a structure whose extreme evolution-
ary potential has rendered it a frequent topic of study
among those interested in the tempo and mode of
avian adaptive radiation (3–6) (Fig. 1).

Whereas other recent studies have focused on
estimating rates of evolutionary change in the shape
of that most ecologically adaptable avian feature, the
beak (e.g., ref. 4), Felice and Goswami (2) treat the
avian skull as a cohesive whole, devising a methodol-
ogy flexible enough to gather data from nearly all
living bird families, yet detailed enough to (almost)
completely characterize the external morphology of
the skull. They accomplish this impressive feat using
laser-surface scanning and high-resolution computed
tomography, similar to the techniques employed by
Cooney et al. in their work on the avian bill (4), and
Bright et al. on raptor skulls (5). This approach yielded
a vast amount of anatomical data that Felice and
Goswami (2) sought to marshal for quantifying cranial
shape, and additional downstream parameters like
rates of shape change. This demanded an approach
to quantify cranial geometry in a way that would facil-
itate meaningful comparisons across species. To ac-
complish this goal, Felice and Goswami began by
identifying homologous “key landmarks” on each
skull, as well as a hemispherical template with addi-
tional densely packed landmarks. Using an innovative

shape-morphing approach (7), Felice and Goswami (2)
then “morphed” the template into the shape of each
skull, using the key landmarks as anchor points. The de-
gree to which the position of the key landmarks and
additional landmarks were thereby digitally “stretched”
from the hemispherical starting shape allowed Felice
and Goswami to quantify the universe of avian cranial
shapes in unprecedented detail.

From there, Felice and Goswami (2) employed a
likelihood-based approach to identify regions of the
avian skull that appear to evolve as reasonably auton-
omous entities, or modules (8). The authors (2) identi-
fied seven such modules, which together compose
the entire skull. These include the well-studied ros-
trum, as well as the top of the skull, back of the skull,
and palate. The recognition of substantial modularity
in the avian skull challenges conflicting results from
previous studies that employed more idiosyncratic
taxon-sampling schemes and approaches to data col-
lection (9, 10). This modularity is the basis for Felice
and Goswami’s (2) assessment of the avian skull as a
classic example of “mosaic evolution,” whereby dif-
ferent modules exhibit differing rates and modes of
evolutionary change.

Felice and Goswami (2) were able to tackle another
major analytical challenge: discerning the tempo and
mode by which rates of cranial shape change evolved
throughout the phylogenetic history of living birds.
They employed a recent time-scaled evolutionary tree
for birds (11) to determine how quickly shape evolved
among the seven cranial modules along the branches
of the tree, yielding some interesting insights. For ex-
ample, rates of evolutionary change in the avian ros-
trum were especially high along the lineage leading to
(long-billed) hummingbirds following the divergence
from their extant sister taxon, (short-billed) swifts. Ad-
ditionally, elevated rates of change were inferred for
virtually every cranial module in the immediate after-
math of the Cretaceous–Paleogene (K–Pg) mass extinc-
tion event, 66 million years ago, an event that
profoundly influenced avian evolutionary history
(12–15). The K–Pg transition has been posited to have

aMilner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, United Kingdom
Author contributions: D.J.F. wrote the paper.
The author declares no conflict of interest.
Published under the PNAS license.
See companion article on page 555.
1Email: d.j.field@bath.ac.uk.

448–450 | PNAS | January 16, 2018 | vol. 115 | no. 3 www.pnas.org/cgi/doi/10.1073/pnas.1721208115

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been a major driver of the early diversification of modern birds (11,
13, 15–17). Thus, the pulse of shape change inferred in the extinc-
tion’s immediate aftermath—analytically dependent on the ex-
tremely short evolutionary branch lengths estimated by Prum
et al. (11) in that region of the phylogeny—is consistent with a
burst of phenotypic innovation and niche-filling following one of
Earth history’s most severe mass extinction events.

Felice and Goswami (2) convincingly illustrate that the differ-
ent cranial modules evolve at different rates from one another,
and at rates that are heterogeneous across avian phylogeny. But
what underlies this regional variation in evolvability? Interest-
ingly, the particular embryonic tissues that ultimately develop
into the various cranial modules may shed light on this question.
Felice and Goswami suggest that the cranial modules exhibiting
both the highest estimated evolutionary rates, and the highest
overall levels of disparity, tend to derive either from one partic-
ular embryonic source (the anterior mandibular-stream cranial
neural crest) or from a mix of multiple embryonic cell popula-
tions. Modules representing derivatives of other embryonic pri-
mordia exhibit lower estimates of evolutionary rate and overall
disparity. The question of whether there are general rules gov-
erning the apparent link between embryonic origin and general
evolvability awaits future insights from evolutionary–developmental
perspectives.

Felice and Goswami (2) have generated an awe-inspiring data-
set, pushing frontiers in the study of vertebrate phenotypic evo-
lution. But does their study provide the final word on the evolution
of modern avian cranial disparity? While the taxonomic sample
investigated is unquestionably extensive, it is worth noting that
the 352 extant bird species comprising the dataset scarcely make
up one-thirtieth of extant avian diversity, which leads to some
unavoidable interpretive limitations. For example, lineages with
“unique” bill phenotypes within the context of the dataset, such
as the Painted Snipe Rostratula, are estimated to exhibit high rates

of phenotypic evolution. However, many taxa with similar bill phe-
notypes to Rostratula, such as true snipes (Gallinago, representing
a separate avian family and a convergent acquisition of a Rostra-
tula-like bill), were not included in the dataset. Thus, the apparent
morphological uniqueness of Rostratula, and its associated high-
rate estimate, may be at least partly artifactual. Addressing this
kind of potential over- and underestimation of evolutionary rates
using the present methodology will demand even more extensive
taxon sampling than the already impressive scheme implemented
here (2), so it is best to view the rate estimates presented in the
study as preliminary approximations.

A greater limitation of the present study (2), although perhaps
more challenging to overcome, is its lack of fossil data. Although it
is true that incorporating fossils (which are often incomplete, bro-
ken, and otherwise distorted) into a study of this scope would
present a major methodological challenge, fossils provide a
uniquely valuable perspective on phenotypic evolution (18–22).
As relicts of evolutionary history, fossils yield the only direct evi-
dence that can ever be obtained of phenotypes from early repre-
sentatives of living groups. Basing large-scale macroevolutionary
analyses solely on data from extant organisms eliminates the po-
tential for fossils to inform estimates of early phenotypic disparity
and rates of change. This is problematic, as the exclusion of sev-
eral extinct clades of crown birds, such as the freakish pseudo-
toothed birds [Pelagornithidae (23, 24)] or monstrous terror birds
[Phorusrhacidae (25)] guarantees that Felice and Goswami’s (2)
estimates of avian cranial morphospace are, by definition,
undersampled.

In the absence of fossil data bearing on the morphology of
the most-recent common ancestor of living birds, Felice and
Goswami (2) implement a clever approach: phylogenetic ancestral
state reconstruction using their geometric dataset. Their recon-
struction provides a striking and testable hypothesis (provided the
future discovery of informative fossils) of what the skull of the

Fig. 1. Mosaic evolution produces an evolutionary mosaic: avian diversity encompasses a spectacular variety of cranial forms. In PNAS, Felice and
Goswami (2) suggest that the extreme evolvability of the avian head is a product of mosaic evolution, whereby different regions of the skull have
evolved at different rates, and by different modes. Photos © D.J.F.

Field PNAS | January 16, 2018 | vol. 115 | no. 3 | 449

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most-recent common ancestor of living birds looked like more
than 70 million years ago. However, one does wonder whether
the close geometric resemblance of the reconstruction to a living
representative of the songbirds [a hyperdiverse crown clade that
itself likely originated less than 50 million years ago (11)], might
ultimately prove to be well off the mark. Future fossil discoveries
may be able to answer this question more definitively.

Addressing all of these caveats in the context of a single study
would have been prohibitive; the monumental dataset compiled by
Felice and Goswami (2), and the cutting-edge methods they employ,

make this study nothing less than a major triumph in evolutionary
vertebrate zoology. However, as data collection and analytical meth-
odologies continue to improve, these critiques will ultimately need to
be addressed to move the field, iteratively, toward a more complete
and accurate picture of the tempo and mode by which avian cranial
disparity, in all of its awesome variety, has evolved.

Acknowledgments
The author thanks A. Y. Hsiang, J. S. Berv, and T. S. Field for editorial assistance.
D.J.F. is supported by a 50th Anniversary Prize Fellowship at the University of Bath.

1 Gill F, Donsker D, eds (2017) IOC World Bird List, Vol 7. Available at www.worldbirdnames.org/ioc-lists/crossref/. Accessed December 5, 2017.
2 Felice RN, Goswami A (2018) Developmental origins of mosaic evolution in the avian cranium. Proc Natl Acad Sci USA 115:555–560.
3 Bhullar B-AS, et al. (2016) How to make a bird skull: Major transitions in the evolution of the avian cranium, paedomorphosis, and the beak as a surrogate hand.
Integr Comp Biol 56:389–403.

4 Cooney CR, et al. (2017) Mega-evolutionary dynamics of the adaptive radiation of birds. Nature 542:344–347.
5 Bright JA, Marugán-Lobón J, Cobb SN, Rayfield EJ (2016) The shapes of bird beaks are highly controlled by nondietary factors. Proc Natl Acad Sci USA
113:5352–5357.

6 Fabbri M, et al. (2017) The skull roof tracks the brain during the evolution and development of reptiles including birds. Nat Ecol Evol 1:1543–1550.
7 Schlager S (2017) Morpho and Rvcg—Shape analysis in R. Statistical Shape and Deformation Analysis, eds Zheng G, Li S, Székely GJ (Academic, London), pp
217–256.

8 Goswami A, Finarelli JA (2016) EMMLi: A maximum likelihood approach to the analysis of modularity. Evolution 70:1622–1637.
9 Klingenberg CP, Marugán-Lobón J (2013) Evolutionary covariation in geometric morphometric data: analyzing integration, modularity, and allometry in a
phylogenetic context. Syst Biol 62:591–610.

10 Kulemeyer C, Asbahr K, Gunz P, Frahnert S, Bairlein F (2009) Functional morphology and integration of corvid skulls—A 3D geometric morphometric approach.
Front Zool 6:2.

11 Prum RO, et al. (2015) A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526:569–573.
12 Feduccia A (1995) Explosive evolution in tertiary birds and mammals. Science 267:637–638.
13 Longrich NR, Tokaryk T, Field DJ (2011) Mass extinction of birds at the Cretaceous-Paleogene (K-Pg) boundary. Proc Natl Acad Sci USA 108:15253–15257.
14 Feduccia A (2014) Avian extinction at the end of the Cretaceous: Assessing the magnitude and subsequent explosive radiation. Cretac Res 50:1–15.
15 Berv JS, Field DJ (2018) Genomic signature of an avian Lilliput effect across the K-Pg extinction. Syst Biol 67:1–13.
16 Ericson PGP, et al. (2006) Diversification of Neoaves: Integration of molecular sequence data and fossils. Biol Lett 2:543–547.
17 Jarvis ED, et al. (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346:1320–1331.
18 Donoghue MJ, Doyle JA, Gauthier J, Kluge AG, Rowe T (1989) The importance of fossils in phylogeny reconstruction. Annu Rev Ecol Syst 20:431–460.
19 Bever GS, Lyson TR, Field DJ, Bhullar BS (2016) The amniote temporal roof and the diapsid origin of the turtle skull. Zoology (Jena) 119:471–473.
20 Slater GJ, Harmon LJ, Alfaro ME (2012) Integrating fossils with molecular phylogenies improves inference of trait evolution. Evolution 66:3931–3944.
21 Gauthier J, Kluge A, Rowe T (1988) Amniote phylogeny and the importance of fossils. Cladistics 4:105–209.
22 Hsiang AY, et al. (2015) The origin of snakes: Revealing the ecology, behavior, and evolutionary history of early snakes using genomics, phenomics, and the fossil

record. BMC Evol Biol 15:87.
23 Mayr G, Rubilar-Rogers D (2010) Osteology of a new giant bony-toothed bird from the Miocene of Chile, with a revision of the taxonomy of Neogene

Pelagornithidae. J Vertebr Paleontol 30:1313–1330.
24 Ksepka DT (2014) Flight performance of the largest volant bird. Proc Natl Acad Sci USA 111:10624–10629.
25 Degrange FJ, Tambussi CP, Moreno K, Witmer LM, Wroe S (2010) Mechanical analysis of feeding behavior in the extinct “terror bird” Andalgalornis steulleti

(Gruiformes: Phorusrhacidae). PLoS One 5:e11856.

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