Evolution of the Caecilian Skull

Home , Brasilotyphlus, Caecilian, Caecilia dunni, Caecilia thompsoni, Epicrionops, Epicrionops marmoratus

A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy (PhD) in Animal Biology in the Faculty of Life Sciences.

2011

Emma Sherratt

List of Contents List of Tables 5

List of Figures 5

Abstract 7

Declaration 8

Acknowledgements 10

Preface 11

Chapter 1 Introduction to the Evolution of the Caecilian Skull 13 Background...... 13 The skull: a model system for morphological evolution...... 16 Enter caecilians: the study organisms ...... 17 Bibliography...... 25

Chapter 2 Evolution of Cranial Shape in Caecilian Amphibians 30 Abstract ...... 31 Introduction...... 32 Materials and Methods ...... 34 Study Taxon...... 34 X‐Ray Computed Tomography...... 37 Skull Models and Measurement ...... 38 Preliminary Shape Analysis ...... 40 Evolutionary Allometry Correction ...... 41 Morphospace and Phylogeny ...... 42 Phylogenetic Signal...... 43 Disparity ...... 44 Correlation analyses...... 45 Results ...... 46 Evolution of shape variation...... 46 Phylogenetic Signal...... 49 Differentiation among clades ...... 49 Disparity ...... 50

Dynamics of Shape Variation...... 52 Ecological patterns...... 55 Discussion ...... 58 Large‐scale patterns of diversification...... 58 Factors influencing clade disparity...... 61 Acknowledgements...... 67 References...... 67

Chapter 3 Evolution of Cranial Modularity in Caecilians 76 Abstract ...... 77 Introduction...... 78 Materials and Methods ...... 82 Preliminary shape analysis ...... 82 Integration and modularity analyses...... 83 Patterns of shape variation in modules ...... 87 Results ...... 88 Integration and modularity...... 88 Comparing shape variation in each module...... 90 Discussion ...... 93 Evolutionary implications of modularity ...... 97 Acknowledgements...... 100

Chapter 4 Morphological Integration in the Cranium, Mandible and Atlas of Caecilians 105 Abstract ...... 106 Introduction...... 107 Materials and Methods ...... 112 Samples ...... 112 Shape analysis...... 112 Levels of morphological variation...... 114 Measuring allometry ...... 114 Comparing covariance matrices...... 116 Measuring integration ...... 117 Results ...... 119 Allometry...... 119

Similarity of covariance matrices ...... 121 Covariation of the cranium and mandible ...... 123 Covariation of the cranium and atlas...... 126 Discussion ...... 128 Patterns of integration in the cranium, mandible and atlas...... 128 The caecilian head and neck as an integrated complex ...... 130 References...... 134

Chapter 5 Discussion on the Evolution of the Caecilian Skull 138 Chapter synopsis and future outlook...... 138 Conclusions...... 143 Bibliography...... 144

Appendix 1 High Resolution Xray Computed Tomography 146 Background...... 146 Methods ...... 146 Scan Data...... 148

Appendix 2 – HRXCT Scan Parameters 149

Appendix 3 – Specimens used in this thesis 160

Appendix 4 Landmarks used in this thesis 178

Final word count: 36,957

List of Tables Table 2.1 Testing for phylogenetic signal in shape data corrected for phylogenetic allometry, at the whole order level and at the level of each clade. 49

Table 2.2 Significance values for pairwise comparisons of clade disparity. 52

Table 4.1 Matrix correlations between covariance matrices of the cranium, atlas and mandible. 122

List of Figures Fig. 1.1 Skeleton of a female Potomotyphlus kaupii (an aquatic and viviparous caecilian) and her young, which are developing internally. 18

Fig. 2.1 A consensus phylogeny of caecilian species included in this paper, where polytomies represent unresolved nodes. 35

Fig. 2.2 The 60 landmarks used in this study, marked on cranium surface in dorsal view, lateral view, palatal view and posterior view for internal features. 39

Fig. 2.3. Principal component analysis of all specimens. 47

Fig. 2.4. Phylomorphospace of caecilian species, constructed from principal components (PC) analysis. 48

Fig. 2. 5. Disparity measures for all 10 clades. 51

Fig. 2.6. Correlation between shape change and time. 53

Fig. 2.7. Correlation of clade disparity measures with clade age and number of species sampled. 55

Fig. 2.8. Phylomorphospace of species of the clades Herpelidae, Caeciliidae, Indotyphlidae, Siphonopidae and Dermophiidae. 56

Fig. 3.1. The 60 landmarks used in this study, marked on cranium surface in dorsal view, lateral view, palatal view and internal view from posterior. 84

Fig. 3.2. Two modularity hypotheses, subdividing the cranium by functional regions. 85

Fig. 3.3. Results of modularity hypotheses in the cranium. 89

Fig. 3.4. Evolutionary shape variation of the two modules of the cranium. 91

Fig. 4.1 Articulated anterior skeleton of a caecilian, showing cranium atlas and mandible elements. 109

Fig. 4.2 Landmarks measured to quantify the shape of the three elements 110

Fig. 4.3 Within‐species shape variation attributed to size variation. 119

Fig. 4.4 Among‐species shape variation attributed to size variation (evolutionary allometry). 120

Fig. 4.5 Structure of shape covariation for the cranium‐mandible and cranium‐ atlas at leach level. 123

Fig. 4.6 Shape changes associated with covariation of the cranium and mandible within individuals, within species and among species. 125

Fig. 4.7 Shape changes associated with covariation of the cranium and atlas within species and among species. 127

Abstract The University of Manchester Emma Sherratt Doctor of Philosophy Evolution of the Caecilian Skull 29th March 2010

The results of evolution can be inferred from comparative studies of related organisms. In this doctoral thesis, I use phylogenetic comparative methods along side geometric morphometrics to analyse shape variation in order to infer evolution of the caecilian skull. Caecilians are elongate, limbless amphibians that superficially resemble snakes or earthworms, and use their head as a locomotory organ. I characterise large‐scale patterns of cranial morphological diversity and quantify variation across the main family‐level clades by describing patterns relating to phylogeny, disparity and ecology. Then I examine the origins and evolution of morphological variation in the skull by describing patterns relating to morphological integration and modularity. This thesis demonstrates a variety of existing statistical techniques that can be used to infer processes from large‐scale evolutionary patterns in morphological data using non model organisms.

Throughout the thesis, I show that the evolution of the caecilian skull to be multifaceted. On the patterns of diversity, the most striking is a “starburst” arrangement in shape space, which suggests that early in caecilian evolution ancestral lineages traversed greater expanses of the shape space, while subsequent phylogenetic divergence within the main clades entailed less morphological diversification. This may be related to early diversification into different ecological‐niches, yet more data are needed to test this. The clades differ considerably in their cranial disparity, but there appears to be no unified pattern across the whole order that indicates disparity is coupled with clade age or speciation events. I show that aquatic species are more diverse than their terrestrial relatives, and that there is convergence of cranial shape among dedicated burrowers with eyes covered by bone.

On the patterns of morphological integration and modularity, another remarkable finding is the caecilian cranium is modular with respect to two functional regions, the snout and the back of the cranium. Modularity is important for understanding the evolution of this structure. The main elements of the caecilian anterior skeleton, the cranium, mandible and atlas vertebra, reveal different patterns of morphological integration, suggesting different developmental and evolutionary processes are involved in sorting and maintaining new variation of each structure. Allometry is an important component of integration in each of the structures. Covariation of the cranium‐mandible after size correction is significant and follows the same direction of shape change across all levels and as shown for allometry. In contrast, covariation of the cranium‐atlas follows different directions at each level. These results suggest the two main joint of the caecilian skull differ substantially in their origin and evolution.

I discuss the contribution made in this thesis to caecilian and evolutionary biology and offer an outlook of how theses findings can be used to initiate future studies to better understand of the evolution of the caecilian skull. 7

Declaration No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

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Acknowledgements The first half of my PhD was spent at the Natural History Museum in London. My sincerest thanks go to Tobias Hill, Diego San Mauro, Finn Eaton and Sam Mohun for the banter, the coffee breaks, helping me settle in to London life and being great lab mates. At the museum, I was privileged to use the newly installed x‐ray CT scanner whenever it wasn’t in use by others, that is mainly in the dark hours. For that I am eternally grateful to Richie Abel and Alex Ball. Initial training on the CT machine was done by Richie and also Stig Walsh; thank you for the truly entertaining time I spent with you. PhD student life at the museum wouldn’t have been nearly as good without the support of PhD coordinator Eileen Cox and the student committee members. The hugest thanks go to my London PhD supervisors Mark Wilkinson and Dave Gower, for taking me on field work, helping me through the rough times, always being up for a tea break or beer to enjoy the good times, and most importantly, for believing in me.

The second half of my PhD was spent at the University of Manchester. Friday beers and banter over lunch and coffee wouldn’t have been possible without so many fabulous people in the Evolution Group. Sharon Zytynska, Daniel Engelmoer, Andres Acre, Paul Johnston, David Springate, thank‐you for keeping me sane! Also thanks to members of the Klingenberg lab past and present, especially those who had to read my thesis chapter drafts but gave constructive criticism and shared a laugh. Another huge thanks goes to my Manchester PhD supervisor Chris Klingenberg, for giving me the kick up the backside in my last year of undergraduate study to do well. My first class degree is thanks to you. Thanks also to Chris for the countless meetings, the support, helping me to think more clearly about evolution, and all of your help in teaching me how to write.

On a more personal level, this thesis would not have been possible without all of the following people. Firstly, those who make the awesome music that helps me to not think about my PhD; the support of my friends (especially Zoë Conradi, Hazel Reade, Diane Boyd); the biggest “gros bisous” to my Sister, Mum and Dad for always believing in me and listening to me rant about science; to Grandma Sherratt who never really knew what I was studying but always feigned interest!; and finally to the love of my life, Dave, your kindness and cuddles absolutely made the last 3 years for me. Thank you. 10

Preface The author did her Undergraduate degree at The University of Manchester. She graduated in 2006 with a BSc. (hons.) first class in Zoology with Industrial

Experience. She was awarded the Zoology Award of Excellence.

The topic of this thesis was born out the author’s undergraduate studies, where she learnt to be a comparative biologist at the Natural History Museum and had a chance to learn geometric morphometrics in her final undergraduate year.

On receiving the funding from The University of Manchester’s quota of NERC CASE

Studentships, her supervisors gave her the freedom to take this PhD in any direction, and she chose to focus on caecilians. This enigmatic group of relatively understudied vertebrates must have really enchanted her, since she always wanted to work on lizards!

This PhD took her to two International Conferences: the European Society of

Evolutionary Biology (ESEB) 12th Congress in 2009, Torino Italy, where she presented an earlier version of the paper in chapter 3 of this thesis in the symposium “Evolution of shape: linking micro‐ and macroevolution”; and to

Evolution 2010, the joint annual meeting of the Society for the Study of Evolution

(SSE), the Society of Systematic Biologists (SSB), and the American Society of

Naturalists (ASN), in Portland, OR, USA, where she presented an earlier version of the paper in chapter 2 of this thesis in the “SSB: Ernst Mayr Symposium”.

She was invited on two occasions to present her PhD research, at the Hull‐York

Medical School, and the University of Bangor, and she has presented numerous posters and oral presentations on this PhD research at other UK institutes.

This thesis is dedicated to

My Mum and Dad

and

My love, Dave

Chapter 1 ‐ Introduction to the Evolution of the Caecilian Skull

“Most species do their own evolving, making it up as they go along, which is the way Nature intended. And this is all very natural and organic and in tune with mysterious cycles of the cosmos, which believes that there’s nothing like millions of years of really frustrating trial and error to give a species moral fiber and, in some cases, backbone.”

By Terry Pratchett, from Reaper Man (1991)

Background The diversity of organismal form is a long‐standing research topic in biology. The work of 18th and 19th Centaury comparative anatomists such as Huxley, Cuvier and

Owen initiated the way biologists consider the diversity of forms. Naturalists

Wallace and Darwin looked at the world around them in a different light and proposed a mechanism to explain how variations on a general theme could exist, that is by natural selection and evolution. Nowadays, comparative studies of organisms are an important contribution to our understanding of evolutionary mechanisms.

A fundamental tool for a robust comparative study is the phylogenetic comparative method (e.g. Felsenstein 1985; Grafen 1989; Brooks and McLennan 1991; Harvey and Pagel 1991; Martins and Garland 1991). This is a statistical approach that uses the evolutionary relationships among species to account for the statistical nonindependence of species data, and is a powerful method for inferring the mechanisms underlying patterns of biodiversity. For characterising and quantifying patterns of morphological diversity, one can combine the comparative method with geometric morphometrics (Dryden and Mardia 1998; Polly 2008;

Klingenberg 2010), to make a tool that quantitatively describes and statistically analyses morphological form in an evolutionary context. Patterns of morphological

diversification can shed light on a clade's evolutionary history, and one approach used to reconstruct the history of morphological trait evolution is the phylomorphospace (sensu Sidlauskas 2008): a phylogeny is projected into multivariate shape space, using squared‐change parsimony to estimate the position of internal nodes (Maddison 1991; Rohlf 2001), to allow inference of the mode and magnitude of trait evolution in the absence of time‐calibrated phylogenies and fossil records, or at large scales where multiple phylogenies are required. Examples from a wide‐range of taxa illustrate the effectiveness of this technique in examining patterns of morphological disparity, key‐innovations, divergence, convergence and adaptive radiations (e.g. Klingenberg and Ekau 1996;

Nicola et al. 2003; Clabaut et al. 2007; Pierce et al. 2008; Sidlauskas 2008; Kimmel et al. 2009; Figueirido et al. 2010; Klingenberg and Gidaszewski 2010; Dornburg et al. 2011).

Comparative studies using geometric morphometrics can also be done to investigate patterns of morphological integration, which provide an insight into the role of evolutionary and developmental processes in producing morphological variation (Klingenberg 2002, 2008; 2010). Integration is the inherent connectivity among parts of a system, and is empirically examined by patterns of covariation among measured traits. Developmental integration defines the covariation of traits because they are share developmental interactions (Klingenberg 2008), while evolutionary integration defines the covariation of traits because they are inherited together or selected together (Cheverud 1996). Patterns of developmental and evolutionary integration can be investigated by a conceptual framework built of developmental theory and evolutionary quantitative genetics, and comprising a hierarchy of different levels of measured morphological variation

(e.g. Cheverud 1996; Monteiro et al. 2005; Klingenberg 2010). The developmental part of the framework uses fluctuating asymmetry (FA, the measured difference between left and right sides of an organism), as a tool to correct for genetic and environmental influences on morphological traits, and used to infer the role of developmental pathways and processes in making individual variation

(Klingenberg 2003; Leamy and Klingenberg 2005). The evolutionary part of the framework uses within‐ and among‐species variation to infer the role of evolutionary processes (Lande and Arnold 1983; Felsenstein 1988). Integration patterns among species can be been examined using a variety of phylogenetic comparative methods, such as shape distance methods (Monteiro et al. 2005;

Monteiro and Nogueira 2010) and independent contrasts (Drake and Klingenberg

2010).

This doctoral thesis aims to contribute to the field of comparative biology by demonstrating existing statistical techniques that can be used to quantify large‐ scale evolutionary patterns in morphological data, for inference of the origin and evolution of these traits. In particular, to reveal what can be learnt from museum collections where genetic data is sparsely available, when selection experiments are not feasible and when phylogenies are not completely resolved. In summary, the aforementioned statistical tools offer the opportunity to work with a greater variety of species than just model taxa for a better understanding of our world’s biodiversity.

The skull: a model system for morphological evolution A classical topic of research in evolutionary biology and developmental biology is the vertebrate head (Kuratani 2005; Olsson et al. 2005). The reason for this popularity lies in wealth of information this system can give about the history of vertebrates. A fossil skull, for example, can inform a great deal about how an animal lived and functioned: shape and wear of teeth and jaw bones gives information on dietary habits (Wroe et al. 2005; Barrett and Rayfield 2006), internal detail of the ear region offers information on hearing systems (Walsh et al.

2009), and variation in skull shape of human and non‐human primates has been extremely important in our understanding of how humans evolved (Lieberman

2011). The head is a mosaic of structurally and functionally important features

(e.g. the masticatory complex, sense organs, and brain) and thus is a prime system for studying the roles of evolutionary and developmental processes in evolutionary change.

The features of the skull reveals a tale of evolutionary process, where skeletal components of independent origin became progressively integrated into the structurally and functionally complex system we see in extant and extinct vertebrates (Morriss‐Kay 2001; Kardong 2006). The apparent diversity of skull forms across the vertebrates is a remarkable consequence of small alterations to development interactions in an otherwise highly‐conserved developmental system

(Hanken and Hall 1993). Morphological diversification of the skull is an important element of the evolutionary diversification of the vertebrates. For example, evolutionary modifications to the jaw apparatus permitted a wide‐range of dietary opportunities (e.g. filter‐feeding in baleen whales to egg‐feeding in snakes to bone‐ crushing in Hyenas), while modifications to increase cranial robustness allowed

the skull to become the primary locomotor organ in limbless burrowing vertebrates (Wake 1993). Large‐scale studies of skull variation offer the opportunity to understand adaptive evolution (e.g. Marugán‐Lobón and Buscalioni

2003; Claude et al. 2004; Stayton 2005; Westneat et al. 2005; Goswami 2006;

Marugán‐Lobón and Buscalioni 2006; Wroe and Milne 2007; Cardini and Elton

2008; Sidlauskas 2008; Drake and Klingenberg 2010; Goswami et al. 2010;

Monteiro and Nogueira 2010).

Enter caecilians: the study organisms Caecilians are elongate, limbless amphibians that superficially resemble snakes or earthworms. They represent the third order of living amphibians (Gymnophiona) and are the sister group of salamanders (Caudata) and frogs (Anura). Molecular‐ clock dating places the origin of modern caecilians to around 200MYA (Roelants et al. 2007), and estimates of current species diversity are c.180 species in 34 genera

(Frost 2011), across several major clades of considerable age (Wilkinson et al.

2011). Biogeographical patterns of species distribution are consistent with a

Gondwana origin (Hedges et al. 1993; Zhang and Wake 2009); they have a pantropical distribution, inhabiting Central and South America, sub‐Saharan

Africa, India, and Southeast Asia up to the Wallace line. Caecilians are predominantly terrestrial, differing in the degree of fossoriality (being more surface‐active or dedicated burrowers), while one lineage has secondarily shifted to the aquatic niche (e.g. Nussbaum and Wilkinson 1989; Wilkinson and Nussbaum

1999; Gower et al. 2004).

Caecilian skull morphology is particularly important for studying the evolution of this major clade of vertebrates. Firstly, caecilians lack much of normal vertebrate

post‐cranial skeleton, that is they do not have limbs and associated girdles, only a succession of vertebra and ribs (Fig. 1.1), so the cranium is arguably the most character‐rich part of the skeleton. Most caecilians are head‐first burrowers so the skull is very important in locomotion (Wake 1993). Furthermore, several morphological characters used to delineate evolutionary relationships in caecilians are found in the skull (e.g. Taylor 1968, 1969; Nussbaum and Wilkinson

1989; Wilkinson et al. 2011). Because the caecilian skeleton has been studied for more than 150 years, the work of several comparative studies have greatly increased our understanding of how the skull of caecilians in composed and the homologies of elements across species in an otherwise enigmatic vertebrate clade

(see the reviews of Wake 2003 and Müller 2007).

Figure 1.1 Skeleton of a female Potomotyphlus kaupii (an aquatic and viviparous caecilian) and her young, which are developing internally. This image illustrates that the caecilian post‐cranial skeleton comprises a large number of vertebrae with ribs, but no evidence of limb girdles. Skeleton rendered from a high‐resolution x‐ray computed tomography scan (see Appendix 1 for details).

The caecilian head is quite unlike other living amphibians. The skull is robust, having relatively few large foramen, heavily ossified, and though superficially resembles the skull of fossil amphibians, it is more likely to be a derived condition as a result of adaptation to the burrowing lifestyle (see Anderson 2008 for review of Amphibian relationships). Most species have a solidly‐roofed skull, where the temporal region is closed (stegokrotaphic), while others have an open temporal region (zygokrotaphic), and these skull variations are considered by many to represent variations in the fossorial/burrowing lifestyle (e.g. Taylor 1968, 1969;

Nussbaum 1983; Nussbaum and Wilkinson 1989; Gower et al. 2004). Due to their fossorial lifestyle, the eyes of caecilians are rudimentary and small compared to their amphibian cousins and lack structures and pigments known in well‐ developed vertebrate eyes (Mohun et al. 2010). In some species the external orbit foramen has closed so that the rudimentary eye is covered by bone. This a feature of the dedicated burrowing species, and has evolved several times in caecilian history (Wilkinson and Nussbaum 2006). Caecilians have a unique sensory organ among amphibians, the tentacle, which is positioned in a foramen behind the external nasal opening and used in olfactory chemoreception (Schmidt and Wake

1990; Teodecki et al. 1998). Finally, caecilian have a unique dual jaw‐closing mechanism that comprises an ancestral component, the adductor muscle that pulls the lower jaw up, and a novel component, the abductor muscle that pulls the lower jaw down and back (Nussbaum 1983). The novel component is a muscle that originates from the hyoid region and has been assigned this new function only in caecilians. This jaw‐closing system appears to be the solution to maintaining a fast and powerful bite during the confined conditions of a subterranean lifestyle. There is no doubt that much of the diversity in caecilian cranial morphology is tied to the relative importance of these characteristics. 19

Caecilians remain largely unknown to the scientific community and general public and relatively understudied compared to other amphibians. Caecilians are cryptic, yet it is arguable that they are rare (Measey 2004; Gower and Wilkinson 2005). In museums across the world, particularly including the Natural History Museum in

London, there exists a substantial collection of species available for study (c.180 described species, Frost 2011). The use of high resolution x‐ray computed tomography (Appendix 1) in data collection in this thesis has unlocked the potential of museum collections by allowing a broad and dense sampling of species and detailed study of their skeletal anatomy without damaging the specimens for further research. This thesis makes a substantial contribution by producing the largest digital collection of specimens of a major clade of vertebrates, totaling 524 specimens in c.141 species and including several type specimens (Appendices 2 and 3).

Thesis Synopsis

The main aim of this thesis is to characterise large‐scale patterns of cranial morphological diversity, quantify variation across the main family‐level clades, and to examine the origins and evolution of morphological variation in the skull. To do this, I use geometric morphometrics and comparative methods to measure the morphological variation in the cranium, mandible and the first vertebra (atlas)1.

From this data, I shall infer the evolutionary history of the caecilian cranium, and describe patterns of variation relating to phylogeny, disparity, ecology, morphological integration and modularity. By examining trait evolution of a complex morphological system, I hope to gain a better understanding of the evolutionary history of a major clade of vertebrates.

One of the inspirations for this thesis comes from a study published thirty years ago in French, which is sadly quite forgotten in the literature. Within a detailed study of the diminutive caecilian Microcaecilia unicolor, Renous (1990) compared skull shapes of 38 species using the lateral view figures from work by Taylor

(1969) and Nussbaum (1977, 1979) and warping transformation grids by eye (à la

Thompson 1917; Gans 1974). She demonstrated visually that a great deal of variation lies in the caecilian cranial shape. Her conclusion was that “La forme …du crâne traduisent cette grande diversité écologique / The shape of the cranium translates this [in regards to their underground habits and tropical distribution] great ecological diversity” (Renous 1990 pg 792). Yet she also said that “Les donées

1 Although the atlas is not strictly an element of the skull, it is the point of connection of the skull with the skeleton, which is expected to be influenced by the use of the head in locomotion.

écologique sont malheureusement insuffisantes pour associer avec precision une forme de crane donée à un mode de vie particulier / The data ecological are unfortunately insufficient to associate with precision the cranium shape given to a particular lifestyle” (Renous 1990 pg 793). While ecological data is not much better understood for many species, and thus the evident driving forces of morphological evolution cannot be fully tested, I aim to show in this thesis that a great deal of other valuable insights can be gained from studying patterns of shape variation in this system.

The first results chapter is an investigation into the cranial diversity in caecilians, and aims to provide a the big picture of caecilian cranial evolution (chapter 2). I take an exploratory approach to characterise patterns of cranial shape variation relating to phylogeny, morphological disparity, and where possible, ecology across the 10 main family‐level clades of caecilians. The phylomorphospace approach is used to infer the history of morphological diversification at the level of the whole order and within clades. I compare the 10 clades in terms of their morphological disparity, and I explore general trends in the dynamics of morphological evolution.

I also investigate two patterns relating to ecology. Chapter 2 is the most species‐ rich quantitative study of caecilian cranial morphology to date, and provides an overview of techniques and what can be learnt from large‐scale studies that examine morphological evolution in major clades.

Once the diversity of skull forms has been quantified (chapter 2), to understand the origin and evolution of morphological variation in the caecilian skull I shall characterise patterns of morphological integration and modularity (chapters 3 and

4). In both chapters, I use the conceptual framework described previously to examine morphological integration and modularity at three levels of variation:

fluctuating asymmetry, within species and among species. The historical persistence of integration patterns, from developmental to evolutionary levels, provides an important insight into understanding the origin and evolution of complex traits.

Morphological integration is often regarded as a pervasive constraint against evolutionary change, while modularity may facilitate adaptive evolution by allowing independent changes to the underlying developmental and genetic interactions within a module without disrupting the function of the entire organism (Wagner and Altenberg 1996; Klingenberg 2005; Wagner et al. 2007). In chapter 3, I address the following questions: Does the caecilian cranium exhibit modularity according to the main functional regions of the snout, cheek region and braincase? If so, do the modules differ in their evolvability? That is, does the evolution of each module differ in magnitude of evolutionary change so as to suggest that different processes have influenced these functionally‐distinct regions?. To address the second question, I again use the phylomorphospace approach to describe patterns of shape variation for each module.

Patterns of skull allometry and integration have previously been described for one species of caecilian, Dermophis mexicanus (Lessa and Wake 1992). With traditional morphometrics , they examined juveniles and adults skulls and concluded that growth is allometric with respect to skull size and that there is a high degree of integration in the skull, as supported by correlations of the variables with each other and size. In chapter 4, I take a large‐scale approach to this problem and use geometric morphometrics to examine morphological integration and allometry in the cranium, mandible and the atlas vertebra across 141 species (chapter 4). The aim of this chapter is to investigate patterns of allometry and integration in the

three structures and to compare the historical persistence of integration patterns in the neck joint (cranium versus atlas) and the mouth (cranium versus mandible) in order to understand the origin and evolution of complex traits.

In the last chapter, I outline the contribution made in this thesis to caecilian and evolutionary biology. I provide a brief discussion on the main findings from the studies on patterns of morphological variation, integration and modularity in the three results chapters of this thesis. I also offer an outlook of how theses findings can be used to initiate future studies to better understand of the evolution of the caecilian skull.

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Chapter 2 ‐ Evolution of Cranial Shape in Caecilian Amphibians

Evolution of Cranial Shape in Caecilian Amphibians*

Emma Sherratt, Christian Peter Klingenberg, Mark Wilkinson, David J. Gower

Contributions: I performed all of the computed tomography scans and segmented the crania, and digitised all of the crania. I constructed the phylogeny with the help of Dave Gower, Mark Wilkinson and unpublished data from Diego San Mauro (Natural History Museum). I performed all geometric morphometrics analyses with initial guidance from Chris Klingenberg (University of Manchester). I wrote the manuscript, with suggestions and comments on earlier drafts from Dave Gower, Mark Wilkinson and Chris Klingenberg.

* A version of this chapter has been submitted to the journal Evolution.

Abstract We present a large‐scale investigation into evolution of morphological variation of a major clade. Caecilian amphibians (Gymnophiona) are elongate, limbless, and predominantly fossorial with the exception of some secondarily aquatic species.

As limbless animals, their heads play an important role in locomotion. We examined cranial shape variation using a comparative phylogenetic approach. There is substantial phylogenetic structure to cranial variation, where major family‐level clades appear as discrete clusters in morphospace, showing that early in caecilian evolution ancestral lineages traversed greater expanses of the shape space.

Phylogenetic divergence within clades involved less morphological change than between clades. The major clades of caecilians differ considerably in their cranial disparity, yet disparity appears uncorrelated with clade age, nor the number of species in each clade. There is a positive correlation between shape change and time, where phylogenetic branch lengths measured from molecular‐clock time trees are proportional to morphological distance in shape space. Semi‐aquatic and aquatic caecilians (clade Typhlonectidae) occupy a novel area of cranial shape space compared to other clades, and are significantly more disparate than their terrestrial sister clade, Caeciliidae. Finally, convergent evolution of cranial shape is evident among species with eyes covered by bone (dedicated burrowers) compared to species with open orbits.

Introduction One of the key aims in evolutionary biology is to understand the history of morphological diversification. A powerful approach to achieve this aim is to map morphological traits onto phylogenies to estimate directly the history of morphological change (e.g. Brooks and McLennan 1991; Sidlauskas 2008;

Klingenberg 2010). Using geometric morphometrics to measure traits, this approach has been used to study key‐innovations, parallelisms and convergence, adaptive radiations, and disparity (e.g. Klingenberg and Ekau 1996; Clabaut et al.

2007; Pierce et al. 2008; Sidlauskas 2008; Adams et al. 2009; Figueirido et al. 2010;

Klingenberg and Gidaszewski 2010). As advances in phylogenetic methods and increases in available data make denser taxon sampling more feasible, morphological evolution can be investigated at increasingly larger scales and with higher resolution. However there are still few studies that have examined variation of complex morphological traits in major clades, and predominantly these have been of mammals (e.g. Marcus et al. 2000; Ricklefs 2004; Stayton 2005; Wroe and

Milne 2007; Astúa 2009; Cooper et al. 2010; Drake and Klingenberg 2010;

Goswami et al. 2010).

We characterize large‐scale patterns of morphological variation in the skull of caecilians (Gymnophiona), one of the three orders of extant amphibians.

Gymnophiona dates back at least 200MY (Roelants et al. 2007), and phylogenetic relationships are increasingly better resolved (Gower et al. 2002; Wilkinson et al.

2003; Wilkinson and Nussbaum 2006; Roelants et al. 2007; San Mauro et al. 2009;

Zhang and Wake 2009). Caecilians are less speciose than frogs or salamanders

(Frost 2010), which makes it feasible to obtain a more complete coverage of extant species in detailed analyses of morphological evolution across a whole order.

Although adults of most caecilian species are fossorial with varying degrees of burrowing behaviour (e.g. Gower et al. 2004), one main lineage (family

Typhlonectidae) contains secondarily aquatic and semi‐aquatic members (Taylor

1968; Wilkinson and Nussbaum 2006). As limbless animals, caecilians use their head for burrowing, which makes their skull an interesting system for investigating evolution of complex traits. Superficial skull shape is relatively conservative among caecilians, and the developmental origin and homology of the cranial elements is fairly well‐resolved (Wake and Hanken 1982; Müller 2007), a benefit for undertaking geometric morphometric studies (Marcus et al. 2000).

This paper reports the first quantitative study of morphological variation of the caecilian skull and the first large‐scale morphometric study to use high‐resolution x‐ray computed tomography for broad and dense sampling. This is also one of few studies that examines morphological variation in modern amphibians quantitatively (but see Yeh 2002; Adams et al. 2009). Our main aim was to understand how a major clade of vertebrates has evolved morphologically. We used geometric morphometrics (Dryden and Mardia 1998; Klingenberg 2010) to characterize the major features of caecilian cranial shape variation, and patterns of species morphospace occupation. We projected a phylogeny into a multivariate morphospace to infer the history of morphological change (e.g. Klingenberg and

Ekau 1996; Nicola et al. 2003; Clabaut et al. 2007; Pierce et al. 2008; Sidlauskas

2008; Klingenberg and Gidaszewski 2010). Using the morphospace we also examined patterns of between‐ and within‐clade shape variation among major clades of caecilians. Patterns of skull variation relating to niche‐shifts, and factors such lineage age and number of species were also investigated.

Materials and Methods

Study Taxon

Caecilians are the monophyletic sister group to frogs (Anura) + salamanders

(Caudata) (e.g. San Mauro 2010), with which the make up the class of modern amphibians (Lissamphibia). Caecilians currently comprise circa 186 known species in 34 genera (Frost 2011) though this number has been rising steadily in recent years (e.g. Kamei et al. 2009; Maciel et al. 2009; Wilkinson et al. 2009;

Gower et al. 2010; Wake and Donnelly 2010; Wilkinson and Gower 2010;

Wilkinson and Kok 2010). The phylogenetic hypothesis for caecilians used in this study (Fig. 2.1) is a topological consensus constructed by hand from multiple sources, including published and unpublished data, the details of which are given in the legend to Fig. 2.1 Relationships for almost all genera have been inferred from molecular data and are well supported. The exceptions for taxa included in this study are Atretochoana, Nectocaecilia, Mimosiphonops, and Parvicaecilia, which have not been included in any molecular analyses to date. Classification (Wilkinson and Nussbaum 2006; Wilkinson et al. in press) and morphological phylogenies

(Nussbaum and Wilkinson 1989; Wilkinson and Nussbaum 1999) were used to position these genera as well as the many species as yet unsampled in molecular phylogenetic analyses. For this study, we divide Gymnophiona into 10 major clades; eight correspond directly with eight of the nine monophyletic families recognized by Wilkinson et al. (in press), while the ninth of those families

(Ichthyophiidae) is subdivided here into two clades: the “Ichthyophiinae” comprising all Caudacaecilia and all but one species of Ichthyophis and the

“Uraeotyphlinae” comprising I. bombayensis and Uraeotyphlus.

Fig. 2.1 A consensus phylogeny of caecilian species included in this paper, where polytomies represent unresolved nodes. The topology is divided into 10 major clades (centre), and crania of representative species of each clade, marked with an arrow, are shown (right) in dorsal, lateral and ventral views. The geographical distribution of each clade is shown above cranial images. The recognized clades correspond mostly to families in the classification of Wilkinson et al. (in press): D = Dermophiidae, Si = Siphonopidae, In = Indotyphlidae, T = Typhlonectidae, C = Caeciliidae, H = Herpelidae, Sc = Scolecomorphidae, U = 35

“Uraeotyphlinae” (Uraeotyphlus + Ichthyophis bombayensis), and Ic = “Ichthyophiinae” (Ichthyophis + Caudacaecilia), R = Rhinatrematidae. Generic‐level resolution provided by molecular data (Roelants et al. 2007; unpublished data) except for Atretochoana, Nectocaecilia, Mimosiphonops and Parvicaecilia, which are determined from morphological data (Roelants et al. 2007; D. San Mauro unpublished). Inter‐specific resolution where known is from the following sources: Typhlonectidae (Wilkinson and Nussbaum 1999); Boulengerula (Loader et al. in press) and Scolecomorphus (Loader 2005); Indo‐Seychelles species of In (Gower et al. in press); Uraeotyphlidae (unpublished data); (Gower et al. 2002; Frost et al. 2006; Roelants et al. 2007); Ichthyophis and Caudacaecilia spp. (Gower et al. 2002; unpublished data).

Adults of all caecilians are carnivorous (O’Reilly 2000). Among those species studied in any detail, most appear to be opportunists preying on a wide range of mostly soil invertebrates, although there is evidence of specialization on different types of earthworms (Jones et al. 2006). Although life history and ecological data for caecilians are sparse, it is clear that they have undergone ecological diversification within tropical ecosystems. Terrestrial species vary in how fossorial they are and the degree to which they are also surface active (e.g. Burger et al.

2004; Gower et al. 2004; Gower et al. 2010). Variation in the ability of caecilians to move within soils is associated with variations in body proportions and trunk musculature (Herrel and Measey 2010) and also robustness of the skull and degree of exposure of the eyes (Nussbaum 1983; Wake 1993; Gower et al. 2004). Reduced or closed orbits and reduced eyes are features of cave dwelling fish and salamanders as well as burrowing mammals and so it is has been reasoned that caecilians with eyes covered by bone are adapted to dedicated burrowing (Gower et al. 2004). One small radiation within the typhlonectid caecilians is secondarily aquatic, living in freshwater streams, slow‐moving rivers and swamps in South

America (e.g. Taylor 1968; Nussbaum and Wilkinson 1995). Obligately aquatic typhlonectids are monophyletic and include the largest lungless tetrapod,

Atretochoana eiselti (Wilkinson et al. 1998). Other typhlonectids are believed to be at least semi‐aquatic (e.g. Nussbaum and Wilkinson 1987, 1989; Wilkinson and

Nussbaum 1999). An aquatic lifestyle in adult caecilians is associated with a reduced burrowing ability (Herrel and Measey 2010) and novel cranial morphologies as well as fins, tracheal lungs and modified circulatory system

(Wilkinson and Nussbaum 1997).

This study sampled 141 taxa: 94 nominal species and an additional 47 populations not identified to species level, at least some of which might be undescribed species

(details in Appendix 3). A total of 524 intact spirit‐preserved specimens were included, primarily from the collections of the Natural History Museum, London

UK, supplemented by loans from other collections. Sampling covered over half of currently recognized species from all known genera, except Brasilotyphlus,

Caecilita, and Sylvacaecilia (four species; phylogenetic position unclear). Sample size per species was limited primarily by material availability but, where possible, included up to 10 specimens of generally equal sex ratio. Only adults were sampled in order to avoid the most substantial confounding effects of ontogenetic variation.

Adults were identified on the basis of having sufficiently well developed gonads to be sexed, and in some species by the absence of non‐adult characters such as spiracles, lateral line systems, foetal teeth and external gills.

X‐Ray Computed Tomography

We obtained skull data by using non‐destructive, high‐resolution x‐ray computed tomography (HRXCT) to examine bone in situ of heads of whole preserved 37

specimens. All HRXCT scans were done with a Metris X‐Tek HMX ST 225 System at the Natural History Museum, London, using a molybdenum target that generates low energy x‐rays well suited for this type of material. Specimens were scanned using a routine whereby three or four animals are scanned at a time, maximising scan productivity with no discernable detriment to resolution (Appendix 1). Scan parameters varied with size class of specimens, because the size of the object in the field of view limits the resolution and can effect the attenuation of bone and soft tissue. Maximal resolution was obtained for each scan by adjusting the number of frames per second (fps) taken and the current and voltage to fit the size of the specimens. Optimal scans were achieved for large specimens by scanning more rapidly (high fps) with high current‐low voltage, resulting in voxels sized 10‐22

μm. Small specimens were scanned slowly with low current‐high voltage, resulting in voxels sized 5‐10 μm. The voxel size equates to the resolution of the image.

Specific scanning parameters are available in Appendix 2.

Skull Models and Measurement

Raw HRXCT scan data were processed prior to taking measurements. Thresholding is the common method of HRXCT image segmentation, a digital technique for removing a particular object (e.g. bone) from a scan. This is possible because different materials are represented in scan data by different grey values, a result of their x‐ray attenuation. Thresholding creates a rendered 3‐dimensional (3D) volume containing only the grey values of the material of interest, using the half maximum height method (Spoor et al. 1993), and was implemented in VG Studio

MAX v.2.0 (Volume Graphics). Non‐cranial bony elements (lower jaws and vertebrae) were digitally removed using the region‐grower tool and dilate

function. The subsequent volume of the cranium was converted into an isosurface, a triangular mesh of approximately one million vertices, demarcating the contours of the outer surface of bone. Isosurface models (herein referred to as surfaces) were processed to remove floating points using Meshlab v.1.2.2 (Cignoni et al.

2009). These surfaces (e.g. Fig. 2.2) are highly detailed, containing information on both the outside and inside of the cranium.

Fig. 2.2 The 60 landmarks used in this study, marked on cranium surface in dorsal view, lateral view, palatal view and posterior view for internal features. Numbers refer to detailed landmark definitions in Appendix 4. Single circles with two numbers refer to paired landmarks (left and right side), and single circles with single numbers for midline landmarks. Double circles with single numbers indicate paired midline landmarks that lie either side of a wide suture. White circles indicate landmarks inside the brain case. Bony elements referred to in the text are labelled.

Measurement data of cranial shape were based on landmarks in 3D. Landmarks are points that can be located reliably and precisely, and have one‐to‐one correspondence across the sample. In this study the landmarks correspond to

(assumed) homologous points on bones at sutures, boundaries of foramina, and

extremes of curvature of structures (e.g. the external naris and foramen magnum), as depicted in Fig. 2.2. These data were collected using Landmark Editor v.3.6

(Wiley et al. 2007). A list of the landmarks used in this study is available in

Appendix 4. Of the 60 landmarks used, four are unpaired and located on the midline and four are paired and medially positioned but are separated where the suture is wide and the elements do not contact. The remaining points are paired

(left/right) and situated over the external cranial surface and inside the braincase

(Fig. 2.2).

The composition of the caecilian skull is somewhat variable across taxa, with some taxa having fewer elements through loss or fusion (e.g. Müller et al. 2005).

Variation in the presence/absence and form of some structures dictated that some potential landmarks were ruled out through not being applicable to all taxa. For example the tentacular foramen does not have a consistent boundary; the orbit is absent (closed) in some species; loss or fusion of bony elements in some groups reduces sutural intersections; and the anterior edge of the squamosal contacts various bones and changes shape greatly. The stapes is absent in adult scolecomorphid caecilians and the fenestra ovalis closed, but a cartilaginous rod is present in early ontogenetic stages (Müller et al. 2005) and so the landmark was placed in the expected position of the fenestra ovalis, following the approach of

Klingenberg (2008). This approach was not used on the orbit because of the variable location of this foramen.

Preliminary Shape Analysis

Cranial shape variation was quantified from landmark data using geometric morphometric methods (Bookstein 1996; Dryden and Mardia 1998; Klingenberg

2010). Each crania surface has its own coordinate system, retaining size from the

original scan. Landmark data from all 524 crania were subjected to a full

Procrustes fit and projection into tangent space (Dryden and Mardia 1998). The

Procrustes fit accounted for object symmetry; shape variables accounting for the symmetric and asymmetric components of shape were extracted (Klingenberg et al. 2002). The Procrustes fit also produces a size component, centroid size, which is the square root of the sum of squared distances of a set of landmarks from their centroid (Dryden and Mardia 1998). Preliminary analysis showed that caecilian cranial shape does not exceed the degree of variation that would cause statistical problems when the curved shape space is projected into the tangent space (see

Dryden and Mardia 1998; Rohlf 1999; Marcus et al. 2000; Slice 2001); the

Procrustes distance on any principal component axis does not exceed 0.2 from the average, the “rule of thumb” cut‐off for tangent space approximations (Dryden and

Mardia 1998). Geometric morphometric analyses were executed in MorphoJ v.1.02d (Klingenberg 2011). All analyses in this study use shape variables from one

Procrustes fit to allow direct comparisons.

30 individuals, one representing each genus, were digitised four times, and the agreement between replicates was measured using a Procrustes ANOVA

(Klingenberg et al. 2002). Measurement error was found to be negligible relative to variation among individuals; therefore the full dataset was digitised once only.

Evolutionary Allometry Correction

Caecilian skulls in this sample ranged in centroid size from 10 to 66 mm, and such size variation necessitates removing shape variation that is predominately due to size variation. Such allometric correction is commonly accomplished with a multivariate regression of Procrustes coordinates on centroid size and taking the 41

residuals from this regression as shape variables for subsequent analyses

(Monteiro 1999). In this case we take into account the phylogenetic structure in the data by computing independent contrasts (Felsenstein 1985) of shape and size variables using the phylogeny in Fig. 2.1. We performed a multivariate regression of the contrasts of symmetric shape on contrasts of centroid size. The resulting slope of the phylogenetic regression was applied to the original symmetric shape and centroid size variables, creating residuals that are corrected for phylogenetic allometry. The ‘allometry‐corrected’ shape variables were used in all subsequent analyses.

Morphospace and Phylogeny

To reconstruct the evolutionary history of morphospace occupation, we mapped shape data onto the phylogeny from Fig. 2.1. The morphospace was produced from a principal component analysis (PCA, Jolliffe 2002) of the allometry‐corrected data.

By estimating the PC scores at internal nodes using squared‐change parsimony

(Maddison 1991; Rohlf 2001), the branches of the phylogeny were drawn onto the morphospace, herein termed a phylomorphospace (Sidlauskas 2008). This method of projecting a phylogenetic tree into multidimensional shape space permits investigation of the history of morphological diversification (e.g. Klingenberg and

Ekau 1996; Nicola et al. 2003; Clabaut et al. 2007; Pierce et al. 2008; Sidlauskas

2008; Klingenberg and Gidaszewski 2010).

The coefficients of each PC can be visualized as shape changes and interpreted anatomically (e.g. Klingenberg 2010). Shape changes are changes in the relative positions of landmarks, and represent shape variation described along a principal component axis, in either direction from the sample average. Shape changes 42

between the extreme ends of each PC axes were visualized by warping a skull surface using the thin‐plate spline method implemented in Landmark Editor

(Wiley et al. 2005; 2007).

To examine whether the major clades have morphologically distinct crania, we performed a canonical variates analysis (CVA, Albrecht 1980) on allometry‐ corrected specimen data with a priori groups corresponding to the 10 clades in

Fig. 2.1. CVA characterizes axes of shape variation that distinguish groups by maximising the between‐group relative to within‐group variation. To calculate the statistical significance of group difference, permutation tests (Good 2000) were performed that randomly allocate observations between pairs of groups (10,000 rounds) to test against the null hypothesis of no difference between the means of the groups.

Phylogenetic Signal

We examined the cranial shape data for phylogenetic signal, the correlation between phylogenetic relatedness and phenotypic similarity (e.g. Blomberg et al.

2003; Cardini and Elton 2008). To do this, PC scores were mapped onto the phylogeny as above, and the tree length was measured in units of Procrustes distance, which is the square root of the sum of squared changes along all branches. Tree length was tested for statistical significance with a simulated permutation procedure involving reshuffling of taxa and their associated variables

(e.g. Laurin 2004) modified for multivariate data (Klingenberg and Gidaszewski

2010). Under the null hypothesis of no phylogenetic signal, the observed tree length would not be any shorter than a simulated tree length calculated by randomly swapping the taxa (and their morphometric values) among the tips of 43

the tree. We reject the null hypothesis when the proportion of randomly simulated trees that are shorter than the original is less than 5%. Phylogenetic signal was assessed at the level of the entire tree and within each of the 10 clades.

Disparity

To examine within‐clade shape variation, disparity, among the 10 main clades, we calculated two indices. (1) Procrustes variance, which estimates disparity by examining the dispersion of all points around the mean shape. Procrustes variance is the mean squared Procrustes distance of each specimen from the average shape of the respective group, and can be calculated as the sum of the diagonal elements of the covariance matrix of each group (Zelditch et al. 2004; Drake and Klingenberg

2010). (2) Convex hull volume, which estimates disparity by examining how far the extreme points are from each other to signify the portion of shape space occupied (e.g. Drake and Klingenberg 2010). Convex hull volumes were calculated from a pooled within‐group PCA. Also known as a multi‐group PCA (Thorpe 1983), a pooled within‐group PCA is an ordination of the within‐group axes of variation where the eigenvalues and eigenvectors are extracted from a pooled within‐group covariance matrix. The first four principal components (PCs) were used because each accounted for more than 5% of the total variation, resulting in a convex hull hypervolume, herein termed volume for simplicity. Both indices of disparity are useful to identify patterns of morphospace occupation because they differ in how they represent the data. The indices for each clade were calculated in R (R

Development Core Team 2009). The convex hull index specifically used the R function convhulln from the GEOMETRY package (Grasman and Gramacy 2010), which utilises the qhull algorithms (www.qhull.org). Both the raw and ‘allometry‐

corrected’ data were used to calculate the two disparity measures. To test the statistical significance of differences in disparity, we used a permutation approach

(10,000 rounds) that randomly assign observations among groups to simulate the null hypothesis of equal dispersion of specimens within groups (e.g. Drake and

Klingenberg 2010).

Correlation analyses

We investigated whether there is a relationship between the amount of shape change and age of lineages. Time calibrated phylogenetic trees are not available for all species in this study, but divergences between 24 species are published elsewhere. The ages of all clades are the mean estimates from Roelants et al.

(2007), except for Herpelidae where the age was supplemented from Zhang and

Wake (2009). Branch lengths were measured in units of time (MY). The average shape of each of the 24 species was mapped to the time‐tree using squared‐ changed parsimony, as described above. The amount of shape change along branches was calculated in units of Procrustes distance. The two distance variables

(shape change and time) were tested for linear correlation using the correlation coefficient.

Disparity measures for clades are expected to be associated with factors such as the number of species in the clade and clade age (e.g. Purvis 2004; Ricklefs 2004).

To test if this is the case for caecilians, we performed correlation analyses of both convex hull volume and Procrustes variance against the number of species and against clade age (MY).

Results

Evolution of shape variation

Principal component analysis was used to describe the major features of cranial shape variation (Fig. 2.3). PCA revealed that the shape variation is concentrated in fairly few dimensions; the first four PC axes each capture more than 5% of the total variation, and subsequent PCs account for very little. These four PCs correspond to major features of shape variation and are visualized as shape changes in positive and negative directions from the average shape of the whole sample (Fig. 2.3). PC1 contributes 30.7% of the total variation and is associated with landmarks of the snout shifting medio‐laterally, changing the width of the snout relative to the cheek region. The result of a positive change on PC1 away from the average shape produces a broader bullet shape, while a negative change gives a narrower triangular shape. PC2 (16.4%) is primarily associated with changes of landmark position on the tooth rows. Therefore, a positive change away from the average shape of PC2 corresponds results in a more subterminal position of the mouth, with teeth shifted posteriorly to be in line with the posterior margin of the nares. A negative change from the average in PC2 results in a more terminal mouth, with the outer teeth in line with the front of the snout. PC3 (10.4%) consists mostly of changes to the relative proportions of snout versus braincase. A change in the positive direction from the average gives a more elongate head, where the cranium is long and narrow from cheek to snout. A negative change from the mean in PC3 produces a more rounded head, where the braincase is about as long as the snout.

Finally PC4 (6.7%) is associated with shifts of landmarks in the cheek region and changes the size of the mouth. In the positive direction, the cheek region moves

forward, giving rise to a short mouth. In the negative direction, the cheek region moves back and as such elongates the tooth rows and gives rise to a long mouth.

Fig. 2.3. Principal component analysis of all specimens. Shape variation associated with the PC1‐4 are shown as changes from the average in the positive and negative direction along each axis, by warping a surface based on C. tentaculata (see text for details). The magnitude of the changes from the average are given below right of each set of surfaces.

The history of shape change was investigated by projecting a phylogeny into the

PCA morphospace (Fig. 2.4). There is extremely strong phylogenetic structure in the morphospace: species of the same clade cluster together tightly and most clades are clearly separated from each other in the morphospace. The phylogenetic tree in the morphospace reveals that there are several occurrences of morphological change in similar directions along particular axes. For example, PC1 v PC3 and PC1 v PC4 plots show four species (genus Geotrypetes) that diverged 47

from others in their clade (Dermophiidae) to occupy a similar position on these axes to clade Uraeotyphlinae, although PC 3 v PC2 plot indicates the similarity is not on all axes. Also, a few species (Grandisonia and Praslinia) of clade

Indotyphlidae have diverged from the others in that clade in a negative direction along PC2, to occupy a similar position to species of clade Ichthyophiinae. The somewhat tangled branches between clades along PC2, PC3 and PC4 indicate further parallel changes in the shape described by these axes.

Fig. 2.4. Phylomorphospace of caecilian species, constructed from principal components (PC) analysis. PC scores for the average shape of each species (corrected for phylogenetic allometry) were mapped to the phylogeny from Fig. 2.1, using unweighted squared‐change parsimony. Each dot represents one species and coloured by clade. A summary of the clade relationships is shown in top right.

Phylogenetic Signal

There is significant phylogenetic signal at the level of the whole order and in all clades except clade Caeciliidae, which could not be tested due to lack of resolution

(Table 2.1).

Table 2.1 Testing for phylogenetic signal in shape data corrected for phylogenetic allometry, at the whole order level and at the level of each clade. Tree length is in units of Procrustes distance and significance was tested with permutation tests (10,000 rounds). The number of taxa and extent of phylogenetic resolution is given as notes.

Tree length P value Notes Whole Order 0.3833 < 0.0001 141 taxa, polytomies present Major Clades: Dermophiidae 0.024 0.0008 10 taxa, polytomies present Siphonopidae 0.0366 0.0001 17 taxa, polytomies present Indotyphlidae 0.0233 < 0.0001 11 taxa, fully resolved Typhlonectidae 0.0561 0.0021 12 taxa, almost fully resolved Caeciliidae 0.0183 N/A 10 taxa, completely unresolved Herpelidae 0.0111 0.0001 10 taxa, fully resolved Scolecomorphidae 0.0204 0.0004 11 taxa, almost fully resolved Uraeotyphlinae 0.0222 0.0041 15 taxa, almost fully resolved Ichthyophiinae 0.106 0.0014 35 taxa, polytomies present Rhinatrematidae 0.0344 0.0086 10 taxa, polytomies present

Differentiation among clades

CVA was used to test whether the major clades are morphologically distinct. There is substantial among‐clade variation; the Mahalanobis’ distance (generalized distance, D) between clades ranges from 7.9 to 32.5. The means of the 10 clades are significantly different from each other (P < 0.0001 for all pairwise comparisons). CVA creates a new morphospace where the CV axes describe the amount of between‐group variation (transformed by the inverse of within‐group

variation). As a result, the first CV axis (43.4%) separated clade Sc from the others; the second CV (24.8%) separated clades Uraeotyphlinae and Ichthyophiinae from the rest; the third CV (10.2%) separated clade Typhlonectidae from the others; and the fourth (7.7%) separated clade C from the rest. Subsequent CVs (5 to 9), which described differences among the remaining clades, each accounted for less than

5% of the between‐group variation.

Disparity

We calculated the hypervolume of the convex hull and Procrustes variance to compare the 10 major caecilian clades in terms of their disparity. The clades clearly differ in terms of their disparity, and allometry‐corrected data mostly gives lower disparity values than uncorrected data (Fig. 2.5). In most clades low convex hull volumes correspond to low Procrustes variances, and high convex hull volumes correspond to high Procrustes variances (Fig. 2.5). The exceptions, clades

Rhinatrematidae and Scolecomorphidae, have respectively higher and lower

Procrustes variance relative to the convex hull volume. These differences between the two measures of disparity for each clade are reflected in the phylomorphospace (Fig. 2.4): the peripheral species points for Rhinatrematidae are not widely separated (Fig. 2.4), corresponding to a low convex hull value (Fig.

2.5), yet each species is sufficiently different from the next to apportion the group a relatively large Procrustes variance; while Scolecomorphidae has a large convex hull volume (Fig. 2.5), which corresponds to widespread points in the phylomorphospace (Fig. 2.4), yet this clade comprises two distinct clumps thus resulting in a relatively low Procrustes variance.

Fig. 2. 5. Disparity measures for all 10 clades. Abbreviations as in Fig. 2.1. A: Convex hull volume calculated from the first four pooled within‐clade PCs, scale at 1x10‐5. B: Procrustes variance (the sum of the diagonal elements of the covariance matrix of each clade). Black bars represent disparity measures calculated from uncorrected shape data, while adjacent outlined bars are from shape data corrected for phylogenetic allometry.

The P values (nominal) for pairwise differences between clades for the two disparity measures relay somewhat different patterns (Table 2.2), with far fewer differences in convex hull volume being significant even though visual inspection of the volumes indicates a great range of values (Fig. 2.5).

Table 2.2 Significance values for pairwise comparisons of clade disparity (Fig. 2.5). Clade abbreviations explained in caption to Fig. 2.1. P values for convex hull in lower triangle and Procrustes variance in upper triangle. Statistically significant P values (at the 5% level) given in bold type. P values are nominal (not corrected for multiple tests).

D Si In T C H Sc U Ic R D < 0.0001 < 0.0001 0.5912 < 0.0001 < 0.0001 0.0003 < 0.0001 < 0.0001 < 0.0001 Si 0.2020 0.0006 < 0.0001 0.0454 0.0765 0.3361 0.3909 0.9126 0.3317 In 0.0551 0.8458 0.1623 < 0.0001 < 0.0001 0.3090 0.0023 0.0002 0.1622 T 0.9865 0.6799 0.6575 < 0.0001 < 0.0001 0.0378 0.0001 < 0.0001 0.1398 C 0.0009 0.3595 0.0421 0.0714 0.9408 0.0711 0.6712 0.0438 0.0137 H 0.0390 0.1102 0.1900 0.4178 0.9237 0.0400 0.6159 0.0609 0.0833 Sc 0.8542 0.1616 0.3628 0.9264 0.0236 0.0011 0.1598 0.2485 0.9522 U 0.0005 0.6198 0.4241 0.7009 0.6191 0.4316 0.1515 0.3580 0.2684 Ic 0.6052 0.6807 0.9904 0.7146 0.2151 0.0269 0.1465 0.4030 0.2699 R 0.4391 0.9730 0.7244 0.5607 0.9271 0.9973 0.9432 0.9923 0.9453

Dynamics of Shape Variation

To investigate whether there is a relationship between the amount of shape change and the time interval between splits in the tree, we calculated the correlation coefficient between branch lengths measured in Procrustes distance and time (MY) for a subsample of 24 species. There is a positive correlation between the two variables, where Procrustes distance (representing shape change) increases with time (Fig. 2.6). The correlation is somewhat low yet statistically significant (r2 = 0.28, P < 0.0001).

Fig. 2.6. Correlation between shape change and time. From a subset of 24 species, the Procrustes distance along internal braches is plotted against time between nodes (millions of years) estimated from Roelants et al. 2007 and Zhang and Wake 2009. The tree redrawn from Roelants et al. (2007) with each branch labeled that corresponds to points in regression plot. Species as follows: Gser = Geotrypetes seraphini, Stho = Schistometopum thomense, Dmex = Dermophis mexicanus, Mkur = Microcaecilia sp.**, Spau = Siphonops paulensis, Lbra = Luetkenotyphlus brasiliensis, Pcoo = Praslinia cooperi, Hros = Hypogeophis rostratus, Gram = Gegeneophis ramaswamii, Cgun = Caecilia guntheri*, Cind = 53

Chthonerpeton indistinctum, Tnat = Typhlonectes natans, Hsqu = Herpele squalostoma, Bbou = Boulengerula boulengeri, Sulu = Scolecomorphus uluguruensis, Svit = Scolecomorphus vittatus, Uoxy = Uraeotyphlus cf. oxyurus; Umal = Uraeotyphlus cf. malabaricus, Iglu = Ichthyophis glutinosus, Iort = Ichthyophis orthoplicatus, Casp = Caudacaecilia asplenia, Iban = Ichthyophis bannanicus, Rbiv = Rhinatrema bivittatum, Ebic = Epicrionops bicolor*. Note that in Roelants et al. (2007) the species marked * were given only as Caecilia sp. and Epicrionops sp., so C. guntheri and E. bicolor have been used in replacement. Data for the species marked ** is for MW995, field series of the Natural History Museum, London.

To investigate whether there is a relationship between clade disparity and attributes of the entire clade, we calculated correlation coefficients between disparity and number of species sampled in the clade, and clade age. Neither measure of morphological disparity is correlated with the number of species sampled in each major clade (Fig. 2.7A, B): convex hull volume (r2 = 0.002 P =

0.905) and Procrustes variance (r2 = 0.05 P = 0.472). Disparity is also not correlated with clade age (Fig. 2.7C, D): convex hull volume (r2 = 0.11 P = 0.356) and Procrustes variance (r2 = 0.04 P = 0.604). There is also no significant correlation between clade age and number of species sampled (r2 = 0.17 P = 0.232; not shown).

Fig. 2.7. Correlation of clade disparity measures with clade age and number of species sampled. Calculated from shape data corrected for phylogenetic allometry. Convex hull volume (at 1x10‐5) against number of species and clade age (top). Procrustes variance (at 1x10‐3) against number of species and clade age (bottom). Nine clade ages were taken from Roelants et al. (2007), with the age of clade Herpelidae taken from Zhang and Wake 2009. Correlation coefficient and P values given in the text.

Ecological patterns

The history of shape change among open and closed orbit species of the clades

Herpelidae, Caeciliidae, Indotyphlidae, Siphonopidae and Dermophiidae was investigated using the phylomorphospace approach (Fig. 2.8). Species with closed orbits occupy a similar area of morphospace, in the centre of the PCA (Fig. 2.8A) while open‐orbit species are more widely distributed. The closed‐orbit species differ subtly from each other in the position of the tooth rows and the position of landmarks 5 and 6 (suture between maxilla and nasal‐premaxilla) as described by

PC1 (Fig. 2.8B). Along the PC2 axis, the closed‐orbit species differ in the breadth of the snout (Fig. 2.8B). In terms of morphospace occupation, the species with closed 55

orbits collectively occupy a fifth of the space that open orbit species occupy

(convex hull volumes respectively 1.10x10‐5 and 5.42x10‐5, P < 0.0001; Procrustes variance respectively 0.0048 and 0.0085, P < 0.0001).

Fig. 2.8. Phylomorphospace of species of the clades Herpelidae, Caeciliidae, Indotyphlidae, Siphonopidae and Dermophiidae. A: The position of open‐orbit (white) and closed orbit (black) ecomorphotypes are shown. Principal component scores for the average shape of each species were mapped to a phylogeny by same method as in legend of Fig. 2.4. B: Shape changes associated with the first two PC axes are shown using a warped surface based on Caecilia tentaculata Positions along the respective PC axes for each warped surface are given. The average shape of the PCA analysis given (centre right) corresponds to the shape at 0,0 on the phylomorphospace.

The aquatic clade Typhlonectidae was compared to their terrestrial sister clade,

Caeciliidae in terms of disparity and shape dissimilarity. The PCA revealed that species of the aquatic clade T have a distinct cranial shape from those of their terrestrial sister clade Caeciliidae, or indeed from any other clade (Fig. 2.4). Both

Typhlonectidae and Caeciliidae occupy a position at the most extreme positive end 56

of PC2, but differ in position along PC1, PC3 and PC4. From CVA analysis of clades, the difference between Typhlonectidae and Caeciliidae is very large (D = 21.5, P <

0.0001), and similarly large between Typhlonectidae and the other clades (range D

= 19.7 to D = 28.0, P < 0.0001 for all). Moreover, the clades have very different disparities, which are statistically significant as tested by permutation tests (Table

2.2). The convex hull volume of Typhlonectidae (1.06x10‐5) exceeds that of

Caeciliidae by an order of magnitude (1.60x10‐6, P = 0.0714). The Procrustes

Variance of Typhlonectidae (0.00691) is twice as large as that of Caeciliidae

(0.00337, P < 0.0001). Omitting Atretochoana from Typhlonectidae (an outlier of the group) did not change the significant difference of the Procrustes variances.

Discussion In this paper we used broad taxonomic sampling, morphometric tools and a phylogeny to characterize patterns of caecilian cranial shape variation. These patterns represent different aspects of caecilian evolution and proffer an overview of how morphological diversification in a major clade occurs. We first we consider large‐scale patterns, addressing the significance of clade positions in the morphospace, and discuss the mechanisms for maintaining these clusters. Then we shift to smaller‐scale patterns, within clades and among species, and discuss some reasons why clades differ in terms of their morphospace occupation, that is disparity.

Large‐scale patterns of diversification

Caecilian clades (families) conform mostly to a “starburst” pattern in the phylomorphospace, with a relatively tight scatter of within‐clade species mean shapes widely separated from other clades and linked by relatively long branches

(Fig. 2.4). This pattern is unusual inasmuch as many other large‐scale studies of morphological evolution have found variation to be somewhat continuously distributed over the first few PC axes (Stayton 2005; Clabaut et al. 2007;

Sidlauskas 2008; Cooper et al. 2010; Drake and Klingenberg 2010). Some studies have found skull shape variation to be somewhat less continuous, in cases where outliers have been included in analyses, such as dolphins among mammals

(Marcus et al. 2000) and the Indian gharial among crocodilians (Pierce et al. 2008).

Extant carnivorous mammal skull variation is a little more like that in caecilians, with placental and marsupial clades continuously distributed but distinct from each other (Wroe and Milne 2007), yet the space between these clades appears to

be occupied by extinct species (Goswami et al. 2010). Other studies using similar methods to ours have insufficient taxonomic sampling to offer a good comparison

(Nicola et al. 2003; Astúa 2009; Figueirido et al. 2010; Klingenberg and

Gidaszewski 2010). The caecilian example appears the most extreme in terms of partitioning the major clades across the morphospace.

The starburst pattern in morphospace suggests that early in caecilian evolution ancestral lineages traversed greater expanses of the shape space, while subsequent phylogenetic divergence involved less morphological change among species within extant clades (Fig. 2.4). This pattern is similar to those described for other radiations, detected from the fossil record (reviewed in Foote 1997) and from lineage through time plots using molecular phylogenies (Harmon et al. 2003;

Kozak et al. 2005; Burbrink and Pyron 2010). These patterns have been associated with early filling of major ecological niches (Schluter 2000; Harmon et al. 2003;

Stephens and Wiens 2003; Streelman and Danley 2003), followed by more speciation by non‐adaptive mechanisms such as sexual selection or allopatry

(Stephens and Wiens 2003).

Discrete clusters in a morphospace raise the question of what may be causing discontinuous variation. Two possible explanations are constraints and stabilizing selection. Constraints limit phenotypic variation and the potential for evolutionary change, and are often considered in terms of their functional, developmental or genetic basis (e.g. Gould 2002; Brakefield 2006; McGhee 2007). For example, empty morphospace regions may be due to mechanical impossibilities realised as functional constraints (McGhee 2007), or due to restricted genetic variation

(Cheverud 1984; Arnold 1992). These constraint hypotheses do not appear plausible, however, in the context of the empty space in the caecilian morphospace.

This is because much of the unoccupied space is in intermediate positions between clusters of morphologically ‘normal’ and functional caecilian skulls, so it is plausible that this space also corresponds to functional skull morphologies.

Moreover, because the unoccupied space between clusters is structured in a highly complex way, any constraint associated with it would also have to be highly complex or the combination of a multitude of different constraints. For these reasons it is more likely that variation is limited not by constraints but through stabilizing selection within clades.

Simulation studies have found that univariate trait distributions observed for real clades are most similar to the output of evolutionary models that include stabilizing selection (Estes and Arnold 2007). This could mean that there is an adaptive landscape on which the distinct clusters are adaptive peaks (Simpson

1944; Lande 1979; Arnold et al. 2001). Under stabilizing selection, a species mean evolves stochastically but will be pulled towards the optimum of the adaptive peak

(Hansen and Martins 1996). When there are several species around the same adaptive peak, strong stabilizing selection would shift each species mean to be equal, regardless of its ancestry, and lie on the peak optimum. Thus, under pure stabilizing selection, there would be no difference between species and thus no phylogenetic signal.

We found phylogenetic signal was not only significant across the whole order, but also within each of the clades. Phylogenetic signal arises through divergent evolution and is detected when closely related species tend to be more similar to one another than expected by chance (Blomberg et al. 2003; Klingenberg and

Gidaszewski 2010). Under strong divergent selection, species means would be widely scattered but arranged relative to relatedness, opposing the actions of

strong stabilizing selection species that means would be shifted together.

Therefore different processes may operate at different levels, where within‐clade variation appears to have arisen by divergent selection, and been maintained in limits by weak stabilizing selection and genetic drift.

Factors influencing clade disparity

Morphological disparity is not evenly distributed among the clades but concentrated mostly in a few (Fig. 2.5). This apparent variety in clade disparity was not correlated to the number of species sampled nor the age of the clades.

Thus these data suggest morphological diversification is uncoupled to speciation, which differs from several other broad‐level studies (e.g. Ricklefs 2004; Stayton

2005; Pagel et al. 2006; Clabaut et al. 2007; Mattila and Bokma 2008). The observed clade disparities may be unrelated to the number of species sampled because of missing taxa, from extinction of lineages or poor taxon sampling within clades. That neither speciation nor time are factors influencing clade disparity suggests tempo and mode patterns are unrecoverable at this broad‐level due to different processes acting within each clade.

We do have evidence that morphological variation of caecilian crania increased steadily over time. Nevertheless, no clade has dispersed in shape space to the degree that would be expected given the analysis of shape change along branches against time in Fig. 2.6. For example, the youngest clade is approximately 30 MY old, which is equivalent to a Procrustes distance in shape space of 0.04. Given that

Procrustes variance is the mean squared Procrustes distance, this would give a disparity measure of 0.0016, whereas all clades in this study have a much lower disparity (< 0.009). Moreover, the branch lengths in Fig. 2.6 are likely to be underestimates, because parsimony estimates assume change to be linear. Thus

our results imply that branches are very densely packed in the morphospace and are folding over themselves to stay within limits (e.g. Sidlauskas 2008). In summary the lack of correlation between disparity and clade age or number of species, and the lower disparity values than expected given gradual shape change through time, are further lines of evidence that there are limits on morphospace occupation of the clades, such as stabilizing selection. As such, the observed differences among clades are predicted to be due to various biological or ecological factors.

The most disparate of the major clades in this study are Typhlonectidae,

Scolecomorphidae, and Dermophiidae. The first two are relatively young clades while the latter is quite old (Roelants et al. 2007). Geographically, Typhlonectidae are found only in South America, Scolecomorphidae have a split distribution between East and West Africa, and Dermophiidae have a split distribution between

East and West Africa, and Central America. The clades differ in terms of habitat and ecological behaviour; Typhlonectidae are aquatic and semi‐aquatic (Nussbaum and

Wilkinson 1995), Scolecomorphidae are at least partly surface‐active (Gower et al.

2004), and Dermophiidae contains a mixture of more surface‐active and dedicated burrowers with varying abilities to excavate harder substrates (Burger et al. 2004;

Herrel and Measey 2010). These families have little in common exclusive to other caecilians except, as far as is known, they comprise only viviparous species

(Wilkinson and Nussbaum 1998; Gower et al. 2008). Viviparity is derived and has evolved from oviparity at least four times in caecilians: in the ancestry of each of these three families, and a fourth time in a species not included in this study

(Gegeneophis sesachari, Gower et al. 2008). Young of viviparous caecilians differ from those of oviparous species in terms of cranial morphology and ossiﬁcation

sequence (Müller et al. 2005; Müller et al. 2009). Functional data are currently very limited, but indicate different feeding mechanics in various life‐history stages of oviparous and viviparous caecilians (Kleinteich 2010), which corresponds to varying feeding modes of the different types of reproductive ecologies (e.g. O’Reilly

2000; Kupfer et al. 2006; Wilkinson et al. 2008). The need for viviparous caecilian fetuses to feed within their mothers’ oviducts, and the subsequent

‘metamorphosis‘ to the adult morphology and ecology might somehow be associated with greater opportunity for cranial novelty, but much more work is required to test this hypothesis.

Ecology is known to impact substantially upon morphological diversification (e.g.

Losos 1992; Collar et al. 2010). In caecilians, the aquatic and semi‐aquatic typhlonectids are substantially more disparate than terrestrial caecilian families, including their sister group. Adaptation from terrestrial to aquatic niches appears to be accompanied with substantial morphological evolution; aquatic Anolis lizards are quite dissimilar to their terrestrial counterparts (Leal et al. 2002), and aquatic turtles are more morphologically diverse than terrestrial species (Claude et al.

2004). One explanation for the unique morphology and increased disparity in aquatic caecilians is that the cranium is not constrained by the functional requirements of terrestrial burrowing, although this may not be the case for semi‐ aquatic species. Another, possibly associated explanation is a diversification of feeding mechanisms. Feeding mode is associated with great morphological diversification in fish (e.g. Kassam et al. 2004; Wainwright et al. 2004; Bellwood et al. 2006; Sidlauskas 2008), which has been attributed in part to the effectiveness of the suction feeding mode (Liem 1990). In other amphibians substantial morphological diversity has been described from aquatic species (Emerson 1985;

Roth and Wake 1985). Terrestrial caecilians use jaw prehension for prey capture, but at least in some aquatic species this is supplemented with partial suction feeding, to counteract forward momentum in water (O’Reilly 2000), and biomechanical data suggest aquatic caecilians have a very wide gape (O’Reilly

2000; Kleinteich et al. 2008). Lunglessness has evolved once in aquatic caecilians, in the cranially divergent Atretochoana. Lack of lungs frees the cranium from its role in the buccal pump required for pulmonary respiration in lunged amphibians, and relaxation of this constraint may have enabled remarkable cranial novelties to evolve in this lineage (Nussbaum and Wilkinson 1995; Wilkinson and Nussbaum

1997; Wilkinson et al. 1998).

The disparities of several families (Herpelidae, Caeciliidae, Indotyphlidae,

Siphonopidae and Dermophiidae) are expected to have been influenced by the convergence of the closed orbit species. Species with eyes covered by bone appear to have evolved away from those with open orbits of their clade to occupy a similar area of morphospace (Fig. 2.8) where crania have blunt, wedge‐shaped snouts and are quite narrow. This convergence of cranial shape may be due to strict functional demands imposed by burrowing. The closed orbit species come from different clades, so the outcomes are not totally similar, having subtle differences in tooth‐ row and suture positions. Such variability around morphotypes is often seen in other studies of convergence (e.g. Stayton 2006; Revell et al. 2007; Figueirido et al.

2010), which is why it is necessary to use an approach such as presented here to identify converging branches in morphospace.

Morphological convergence can be thought of as shifts of species means onto an adaptive peak representing an ecological niche, which are then maintained on the peak by stabilizing selection. Adaptation to locomotion in similar environments

often manifests as similarity in whole body morphology (e.g. Losos 1992; Melville et al. 2006; Revell et al. 2007), while convergence in head shape is most commonly associated with diet and feeding related pressures (e.g. Westneat et al. 2005; Wroe and Milne 2007; Figueirido et al. 2010). However head shape is expected to be under selective pressure from both feeding and locomotory demands in limbless vertebrates. Biomechanical studies show that burrowing imposes strong functional demands (Teodecki et al. 1998; Navas et al. 2004; Vanhooydonck et al.

2011) that influence morphological diversification, so there will be selection for particular morphologies and head shape is constrained. Head‐first burrowing has evolved repeatedly in elongate limb‐reduced and limbless vertebrates (e.g. Gans

1975; Wake 1993; Lee 1998; Kearney and Stuart 2004; Eagderi and Adriaens

2010), this is the first study to illustrate such constraint in an evolutionary context through quantitative assessment of skull shape among different species of headfirst burrowing vertebrates.

Examining shape variation in a phylogenetic context has highlighted other instances where several unrelated species have evolved in parallel or convergently along particular axes of shape space. The shape of the snout, as blunt or pointed, is a feature recognized in taxonomy to delimit species (e.g. more U‐ versus V‐shaped heads in Ichthyophis, Kamei et al. 2009) and might be associated with different ecologies given that head shape influences burrowing speed (Teodecki et al. 1998).

Another feature is the mouth position (described by PC2, Fig. 2.3), which can be subterminal, thought to be associated with subterranean lifestyles (Gans 1969;

1974; Nussbaum 1977). Unfortunately, without more detailed ecological data, we can only predict that these reoccurring skull shapes denote more instances of adaptation.

In conclusion, we present a large‐scale investigation into the morphological evolution of a major clade. The possibilities for understanding of complex trait evolution are exemplified using the caecilian cranium. This study is the first to sample densely and broadly across a major clade, using computed tomography to gather detailed morphological data and geometric morphometrics and phylogenetic comparative methods to compare patterns of shape variation. We have shown that increasingly larger‐scale analyses are not only possible with existing statistical methods, but also offer valuable insights on how a major clade has evolved. Future investigations into large‐scale trait evolution will benefit from the statistical tools highlighted in this paper and the growing number of taxa included in phylogenies.

Acknowledgements We thank R. Abel and S. Walsh for training and support to E.S. on the NHM high‐ resolution x‐ray computed tomography scanner. Also we are grateful to D San Mauro, S. D. Biju and R. G. Kamei for important practical assistance. E.S. was funded by NERC CASE Studentship NE/F009011/1.

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Chapter 3 ‐ Evolution of Cranial Modularity in Caecilians

Evolution of Cranial Modularity in Caecilians (Amphibia: Gymnophiona)

Emma Sherratt, Mark Wilkinson, David J. Gower, Christian Peter Klingenberg

Contributions: The specimens, measurement data and phylogeny are the same as in chapter 2. I performed all of the geometric morphometrics analyses with initial guidance from Chris Klingenberg (University of Manchester). I wrote the manuscript, with suggestions and comments on earlier drafts from Chris Klingenberg and members of the Klingenberg lab.

Abstract Modularity describes and explains the patterns of organisation at many levels within an organism, and is related to morphological integration, the cohesion among morphological traits. Modularity and integration were investigated in the skull of limbless amphibians (caecilians) using geometric morphometrics, because in addition to the usual functions of a vertebrate head the caecilian head is also important in locomotion. We tested hypotheses of modularity and examined the similarity of integration patterns across three levels: fluctuating asymmetry (FA), within species and among species. We found the cranium to be organised into two distinct modules, the snout, and the braincase with cheek region, and this pattern is consistent at all levels. Integration patterns for the whole cranium and for the separate modules were very similar between the within‐ and among‐species levels, but differed in the similarity of FA and within‐species levels. Finally, for each module patterns of evolutionary shape variation were investigated by mapping shape variables onto a species‐level phylogeny. The patterns differ between modules and show the snout has undergone substantially more morphological diversification during history of the group than the braincase with cheek region module. We discuss the roles of developmental and evolutionary processes in generating cranial variation and the adaptive significance of modularity in the caecilian skull.

Introduction The modular organisation of organisms is a well‐recognised phenomenon, from organelles and cells to organs and body segments (Cheverud 1996; Wagner 1996;

Von Dassow and Munro 1999; Bolker 2000). Modularity is a hierarchical concept that describes and explains the patterns of organisation at many levels within an organism, and is related to morphological integration, the cohesion among morphological traits (Cheverud 1982; Hallgrímsson et al. 2002; Klingenberg 2005;

Wagner et al. 2007; 2008). Studies of integration and modularity to infer factors controlling and producing morphological variation are thus central in the debate of the relative importance that natural selection and factors intrinsic to the organism play in driving evolutionary change (Fusco 2001; Arthur 2002; Gould 2002;

Breuker et al. 2006a; Klingenberg 2010). Modularity may facilitate adaptive evolution by allowing independent changes to the underlying developmental and genetic interactions within a module without disrupting the function of the entire organism (Wagner and Altenberg 1996; Klingenberg 2005; Wagner et al. 2007).

Accordingly, modularity needs to be examined from both developmental and evolutionary perspectives.

Morphological integration and modularity are inferred from data on the covariation among multiple morphological traits. Modularity is a hierarchical concept (Klingenberg 2005, 2008), and can be studied by measuring covariation among particular traits at different levels, such as within individuals, within species, and among species (Cheverud 1996; Klingenberg 2008). At the developmental level, parts of an anatomical unit are coordinated within by developmental interactions, which mediate the expression of developmental, genetic and environmental‐based variation. There are two classes of

developmental interactions, direct and parallel pathways, which differ in the type of variation they mediate and also in their evolutionary flexibility (e.g. Klingenberg

2008). Empirically, the two can be distinguished by comparing integration patterns among individuals (within species), which are made by both pathways, and patterns of left‐right asymmetry (fluctuating asymmetry, FA) within individuals, which can only come from direct pathways (e.g. Klingenberg 2008;

Zelditch et al. 2008). At the evolutionary level, covariation of traits among species reflects the coordinated evolution of parts, which are inherited together or selected together during divergence (Cheverud 1996; Monteiro et al. 2005;

Klingenberg 2008). Among species variation is estimated using comparative methods (Felsenstein 1985; 2004). The roles of evolutionary processes can be inferred by comparing within‐species patterns of integration to those among species (Lande and Arnold 1983; Felsenstein 1988). Various approaches on this theme have been used to examine the evolutionary covariation among morphological traits across different taxa (e.g. Badyaev and Foresman 2004;

Monteiro et al. 2005; Goswami 2006a; 2006b; Young and Badyaev 2006; 2007; de

Oliveira et al. 2009; Porto et al. 2009; Goswami and Polly 2010; Monteiro and

Nogueira 2010). Furthermore, comparisons that examine the relationship among the three levels (Young and Badyaev 2006; Drake and Klingenberg 2010;

Klingenberg et al. 2010; Monteiro and Nogueira 2010), offer insights into the roles of developmental and evolutionary processes influencing morphological variation.

The vertebrate skull is ideal for studying modularity because it is a complex structure composed of different skeletal units with different developmental origins and functions. Integration among parts of the cranium of different taxa reveals varying influences of development and evolution on the diversity of cranial shape

(e.g. Cheverud 1982; Debat et al. 2000; Hallgrímsson et al. 2004; Goswami 2006a;

Marroig et al. 2009; Martínez‐Abadías et al. 2009; Drake and Klingenberg 2010;

Goswami and Polly 2010; Ivanović and Kalezić 2010; Shirai and Marroig 2010). We propose that the skull of the limbless amphibians, caecilians is an interesting system to study modularity. The caecilian skull has an important role in locomotion (Wake 1993), because many caecilians use their head to burrow in soil, mud and leaf litter. Accordingly, their skulls are compact, heavily ossified, and composed of relatively few bones as a result of loss or fusion (e.g. Marcus et al.

1935; Müller et al. 2005). There is likely to be a trade‐off in skull development between being structurally stable during head‐first burrowing and being able to perform all the regular functions such as feeding, breathing, and housing of the brain and sense organs. Because the caecilian skull is important for many different functions, we predict the skull will exhibit a modular structure. Furthermore, we predict evolutionary modularity facilitates adaptive evolution as different clades evolve along distinct evolutionary trajectories.

This paper comprises two parts. Firstly, we test for modularity in the caecilian cranium, using geometric morphometric tools to examine explicit a priori hypotheses of modularity (Klingenberg 2009). Modularity is examined at three levels of variation (FA, within species and among species) so that the role of developmental and evolutionary processes in integration can be inferred. Of two hypotheses dividing the head according to functional modules, we found that our data supports one, where the cranium consists of a module for the snout and a module for the back of the head. Because a modular setup of the cranium is predicted to allow the different functional regions to evolve separately (Wagner and Altenberg 1996; Monteiro et al. 2005; Monteiro and Nogueira 2010), we then

examined how each module contributes to the variation and evolutionary history of cranial shape. Evolutionary patterns of morphological variation described by each module were investigated by projecting a species‐level phylogeny into the morphospace of each module (e.g. Chapter 2; Klingenberg and Ekau 1996;

Sidlauskas 2008).

Materials and Methods

Preliminary shape analysis

Data were gathered from 524 adult specimens representing 141 taxa (94 described species and 47 undescribed species), sampled from all family‐level clades of the order Gymnophiona (Wilkinson et al. 2011). Skull morphology was investigated by high resolution x‐ray computed tomography (HRXCT) and measured with three‐dimensional landmark‐based geometric morphometrics.

Three‐dimensional models of the cranium (mandible not included here) were extracted from the HRXCT scans. 60 landmark measurements were taken over left and right sides of the cranium on external bone sutures as well as inside on the sphenethmoid and braincase (Fig. 2.1), as in Chapter 2. Details of the specimens sampled, HRXCT and digitising procedures are in Appendix 1, 2, 3.

Geometric morphometric methods were used to analyse cranial shape (Bookstein

1996; Dryden and Mardia 1998; Klingenberg 2010). We performed one generalised Procrustes superimposition for the entire cranium, taking into account object symmetry (Klingenberg et al. 2002). Measurement error in this dataset is negligible in relation to individual variation (Chapter 2). All analyses were executed in MorphoJ v.1.02e (Klingenberg 2011).

We investigated modularity at three levels: FA, within species, and among species.

Covariance matrices were constructed for each. FA of a structure is a common research tool for examining the developmental origin of integration and modularity (e.g. Klingenberg 2008; Zelditch et al. 2008). For this level, we calculated a covariance matrix from the pooled within‐species asymmetry component of shape. Within species, we calculated a pooled within‐species covariance matrix from the residuals of a pooled within‐species multivariate 82

regression of shape on centroid size (Monteiro 1999). This procedure simultaneously corrects for allometry and takes into account group structure in the data. The among‐species covariance matrix was calculated from the residuals of a multivariate regression of the independent contrasts of shape on the independent contrasts of centroid size. This procedure simultaneously corrects for allometry and the statistical non‐independence of species data (Felsenstein 1985;

2004). Independent contrasts were calculated from a species‐level phylogeny, the topology of which is a partially‐resolved consensus of molecular and morphological data from published and unpublished data, and details can be found in Chapter 2.

Integration and modularity analyses

We consider the cranium to be composed of functionally distinct regions: the snout, braincase and cheek region (Fig. 3.1). The braincase comprises the cranial base (os basale) that forms an open‐topped box covered by parietal ‘roofing’ bones. Its function is to accommodate the occipital sensory capsules and the brain.

The cheek region is made up of the squamosal and quadrate bones that are positioned adjacent to the braincase. Primarily it is used in jaw articulation and houses the jaw‐closing muscles (Nussbaum 1983), but also has some use in sound transmission since the quadrate closely contacts the stapes (Wever 1975; Mason

2006). The snout comprises facial and palatal bones, and encompasses the nasal, tentacle and optical sensory capsules. Used in feeding, vision and olfaction, the snout is also the prime point of contact with the environment.

Fig. 3.1. The 60 landmarks used in this study, marked on cranium surface in dorsal view, lateral view, palatal view and internal view from posterior (from top to bottom). Double circle refers to paired midline landmarks that are either side of a wide suture. White circles refer to those placed inside the cranium (left‐side pairs for 34, 51 and 38 not shown). Numbers refer to landmarks described in Appendix 4. Bone elements and regions referred to in this study are labelled. The skull model used here and throughout is based on the species Typhlonectes natans (MW5056).

To examine modularity in the caecilian cranium, we formulated two hypotheses by partitioning the 60 landmarks into two subsets (Fig. 3.2); cheek region plus the snout in hypothesis 1 (Fig. 3.2A) and cheek region plus the braincase in hypothesis

2 (Fig. 3.2B). The rationale for hypothesis 1 is the cheek region articulates with the lower jaw, and thus important in the coordinated action of upper and lower jaw teeth. For hypothesis 2, the cheek region houses jaw muscles that attach to both the braincase and the inner surface of the cheek bone. Also part of the cheek region may be important during hearing, relaying vibrations though the stapes into the occipital region of the braincase.

Fig. 3.2. Two modularity hypotheses, subdividing the cranium by functional regions. The 60 landmarks are divided into two subsets, coloured blue and black: hypothesis 1 (A) specifies the snout with the cheekbones (37 landmarks) as a separate module from the braincase (23 landmarks). Hypothesis 2 (B) specifies the snout (31 landmarks) as a separate module from the braincase with the cheekbones (29 landmarks). See text for biological rationale behind module choice. Adjacency graphs in dorsoventral (top) and lateral view (bottom) define the spatial contiguity of landmarks (Klingenberg 2009). The graphs are complemented by a coloured surface model in dorsal, ventral and lateral views highlighting which bones the landmark sets approximate. Two lateral views are shown, whole (left) and with cheek region and maxillopalatine bone removed (right) to reveal the inner junction of the snout with the braincase.

Modularity is detected in a structure when the covariation between subsets of landmarks (denoting the modules) is less than the covariation within each subset.

The strength of covariation was measured using Escoufier’s (1973) RV coefficient, which is a multivariate extension of the squared correlation coefficient and can be used with geometric morphometric data (Klingenberg 2009). As such, RV coefficient can take a value from 0 to 1, where 0 indicates that the two subsets are completely independent (modular), and 1 indicates that they are completely interdependent (integrated).

To examine modularity across levels, RV coefficients were calculated using the covariance matrices representing the three levels of variation. In order to evaluate the modularity hypotheses, we computed the strength of covariation between modules and compared this to alternative subsets of the same size (Klingenberg

2009). In each case the hypothesis is tested using a null distribution of correlation coefficients that is calculated from 10, 000 alternative subsets. The null hypothesis is the correlation between the two subsets is no smaller than between random subsets. We rejected the null hypothesis if the proportion of alternative subsets with the same or lower strength of covariation of the hypothesis is substantially lower than the total, and thus the proportion is equivalent to a P‐value. Only spatially contiguous subsets were used in making the null distribution. Spatially contiguous means that all the landmarks are connected by edges of the adjacency graph (Fig. 3.2), and adjacency graphs were constructed in such a way as to define biologically meaningful connections between landmarks and to prevent links that are spatially disjointed.

To quantify the overall similarity of the structure of shape variation among levels, matrix correlations were computed between covariance matrices, and tested for

significance against a null distribution of matrix correlations by randomly permuting landmarks (Klingenberg and McIntyre 1998). Matrix correlations were repeated without the diagonal blocks to investigate covariation patterns for among‐landmark variation only.

Patterns of shape variation in modules

To examine patterns of shape variation given by each module, we divided the cranium dataset into two subsets according to modularity hypothesis 2 (Fig. 3.1B).

We performed separate principal components analyses (PCA, Jolliffe 2002) for each module to explore patterns of shape variation (Monteiro and Nogueira 2010).

The PCAs were made from covariance matrices that had been corrected for phylogenetic allometry. This is done by first performing a multivariate regression of independent contrasts of shape and centroid size, then applying that slope to the original shape variables in another multivariate regression and taking the residuals for subsequent analyses (as in Chapter 2).

To reconstruct the evolution of shape of each module, we used an approach that illustrates shape similarity and phylogenetic relationships in a shape space (e.g.

Klingenberg and Ekau 1996; Nicola et al. 2003; Sidlauskas 2008; Klingenberg and

Gidaszewski 2010). PC scores were mapped to a species‐level phylogeny using squared‐change parsimony (Rohlf 2002), then the tree was projected onto each module’s PCA plot.

For each module, the structure of shape variation across levels (inferred from covariance matrices of the within individual, within species and among species variation) was compared using the matrix correlation approach (Klingenberg and

McIntyre 1998).

Results

Integration and modularity

Similarity in integration patterns of the entire cranium was compared with matrix correlations. Between levels, all matrix correlations were statistically significant, but variable in strength: a low matrix correlation between FA and within species

(0.28, P = 0.0723) and between FA and among species (0.31, P = 0.0107), and higher matrix correlation between within‐species and among‐species levels (0.73,

P < 0.0001). If the diagonal elements of the covariance matrices are excluded, so comparing only the covariances among landmarks, the matrix correlations were much lower and not always statistically significant: between FA and within species

(0.02, P = 0.2095), between FA and among species (0.04, P = 0.0165) and between within‐species and among‐species levels (0.66, P < 0.0001).

Modularity hypothesis 1 is the snout with the cheekbones as a separate module from the braincase. Testing this hypothesis (Fig. 3.3A) gave RV coefficients for each level that were not unusually low compared to alternative random partitions: FA

(RV = 0.44, proportion, p = 0.7380), within species (RV = 0.57, p = 0.562), and among species (RV = 0.57, p = 0.520). This means we cannot reject the null hypothesis that the correlation between the two subsets is no smaller than between random subsets.

Fig. 3.3. Results of modularity hypotheses in the cranium. Arrows mark the RV coefficient for each level for the subset according to hypothesis 1 (A) and hypothesis 2 (B), against a frequency distribution of simulated RV coefficients (10,000 alternative subsets) at all three levels. The further the arrow is to the left of the distribution, the greater the likelihood that the hypothesised pattern of modularity is not due to chance.

Modularity hypothesis 2 is the snout is a separate module from the back of the cranium. Testing this hypothesis (Fig. 3.3B) gave RV coefficients for each level that were substantially lower compared to alternative random partitions: FA (RV =

0.24, p = 0.0273), within species (RV = 0.51, p = 0.096), and among species (RV =

0.44, p = 0.0003). The substantially lower proportions for the asymmetry and among species level means we reject the null hypothesis. Within species, the RV

coefficient falls within the bottom 10% of the simulated distribution, and as such is marginally significant for modularity. In summary, our data rejects hypothesis 1 and supports hypothesis 2, thus further results are reported for hypothesis 2.

Comparing shape variation in each module

The dimensionality of shape variation is quite different in the two modules (Fig.

3.4A). A PCA of the snout reveals that much of the variation is concentrated to a few PCs, and the first two PCs share almost the same proportion of the total variation (26.8% and 25.4%). In contrast, shape variation of the back of the cranium is predominantly along the first PC axis (41.3%), with subsequent axes contributing less than 12% and fast decreasing to negligible.

Fig. 3.4. Evolutionary shape variation of the two modules of the caecilian cranium. Separate principal components analyses of snout shape and braincase & cheek region shape reveal the magnitude of shape differences among the main clades. A: The distribution of variation over all PC axes given as a proportion of the total variation in each axis. B: The first two PCs mapped to a phylogeny with the axes of the braincase & cheek region graph reversed for comparative purposes. Coloured dots represent species of each of the ten major clades of caecilians, and the summary of the clade relationships are given in the inset tree (left); D = Dermophiidae, Si = Siphonopidae, In = Indotyphlidae, T = Typhlonectidae, C = Caeciliidae, H = Herpelidae, Sc = Scolecomorphidae, U = Uraeotyphus with Ichthyophis bombayensis, and Ic = Ichthyophinae (Ichthyophis and Caudacaecilia), R = Rhinatrematidae (Chapter 2; Gower and Wilkinson 2009; Wilkinson et al. 2011).

Evolutionary patterns of morphological variation are illustrated by projecting a species‐level phylogeny into the PCA morphospace of each module (Fig. 3.4B). The two modules reveal different patterns of species distributions in the PC morphospace. For the snout data, most clades appears as a starburst with species 91

clustered together, indicating the proportion of within‐ to among clade variation is low. The proportion of within‐ to among clade variation is higher in the braincase and cheek region module, meaning the clades are better separated by variation in the snout than the back of the cranium.

The first two PC axes for each module describe the main shape changes from the average shape of each dataset. In the snout, shape variation relates predominantly to the position of the outer tooth row (not shown): On PC1, a change in the negative direction from the mean gives rise to more narrow tooth row that is recessed all the way round the snout. From the mean to positive end of the scale, the tooth row widens and sits inline with the lateral edges of the snout. Along PC2, a change in the negative direction from the mean gives rise to a more terminal mouth (tooth row inline with the front of the nares), whereas a change from the mean to positive end of the scale gives rise to a more subterminal mouth (tooth row heavily recessed from the front of the snout). For the braincase and cheek region module, PCA reveals the dominant shape variation is in the position of the cheek bones relative to the braincase. At the positive end of both PC1 and PC2 the cheek bones are widely separated from the braincase, and a change towards the negative end describes two ways that the cheek bones can shift medially to contact the roof of the braincase.

Comparing across levels using matrix correlations, the structure of shape variation in the snout is very different to that of the braincase with cheek region modules.

For the snout, the matrix correlation between the within‐species and among‐ species levels was high and statistically significant (0.75, P < .0001; excluding diagonals 0.66, P < .0001), while the matrix correlation between FA and within species was not statistically significant (0.31, P = 0.8648; excluding diagonals ‐0.02

P = 0.5168), and the matrix correlation between FA and among species was also not statistically significant (0.35, P = 0.7728; excluding diagonals 0.01, P =

0.9858). For the braincase and cheek module the matrix correlation between FA and within species was moderate and significant (0.43, P < 0.0001; excluding diagonals 0.11, P = 0.0005), the matrix correlation between the within‐species and among‐species levels was high and significant (0.81, P < 0.0001; excluding diagonals 0.74, P < 0.0001), and the matrix correlation between FA and within species was moderate and significant (0.42, P < 0.0001; excluding diagonals 0.12, P

< 0.0001).

Discussion Our data support the hypothesis that the caecilian cranium is organised into two relatively independent modules; the snout and the back of the cranium (braincase with cheek region) are semi independent in the sense that they covary together weakly relative to the strong covariation among their constituent parts. The alternate modularity hypothesis, where the cheek region was included with the snout, was not supported by our data. This indicates the cheek region is developmentally and functionally more connected to the braincase than the snout, as predicted by the role it plays in housing the masticatory muscles and even in hearing (Wever 1975; Nussbaum 1983; Mason 2006). Using the same ‘alternative subsets’ approach, crania and mandibles of various vertebrates have been examined for different patterns of modularity, with some taxa showing distinct modules (mouse manidble e.g. in Klingenberg 2009; Drake and Klingenberg 2010) and others showing tight integration (Hallgrímsson et al. 2009; Ivanović and

Kalezić 2010; Jamniczky and Hallgrímsson 2011), suggesting modularity may be a taxa‐specific property of the developmental system.

Modularity is not an all‐or‐nothing occurrence but a matter of degrees

(Klingenberg et al. 2003). In the caecilian cranium, modularity appears a dominant pattern because the strength of covariation between modules relative to the covariation with is quite weak, as indicated by the low to moderate RV coefficients among modules at each level (Fig. 3.3). Among‐species and within‐species RV coefficients were higher than the asymmetry level, suggesting the presence of additional, non‐developmental, integrating factors acting at these levels.

Developmental level RV coefficient was the lowest in this study and is also the lowest in all others using the same method (Klingenberg 2009; Laffont et al. 2009;

Drake and Klingenberg 2010; Ivanović and Kalezić 2010; Klingenberg et al. 2010;

Jamniczky and Hallgrímsson 2011), yet the reason for this widespread phenomena remains unclear.

We found support for the same two‐partition hypothesis of modularity at all three levels (Fig. 3.3). This suggests that within‐module integration is due to developmental processes, genetic factors and possibly selection (Klingenberg

2005, 2008). Moreover, conservation of the same modular organisation throughout evolutionary divergences suggests there has not been any major restructuring of the patterns of correlated change within modules. Using the same approach to testing hypotheses of modularity, Drake and Klingenberg (2010), also found persistence of modular patterns across developmental, individual and species levels. In contrast, changing patterns of modularity (i.e., changing position of module boundaries) across levels have been illustrated in other systems

(Hallgrímsson et al. 2004; Monteiro and Nogueira 2010), yet these studies used

different methods to evaluate modularity. Across clades of mammals, some studies found modularity patterns that change during evolution (Goswami 2006a;

Mitteroecker and Bookstein 2008), whereas others reported them to remain relatively stable (Porto et al. 2009). It is not clear whether these patterns reflect true differences and evidence of rearrangement of developmental pathways and genetic covariance, or whether the different methods for measuring modularity in different studies cause the inconsistency of results. Certainly, more data is needed on diverse taxa to understand the evolutionary implications of large‐scale maintenance or reshuffling of developmental patterns of integration and modularity.

For patterns of integration, described by covariance matrices, strong similarity between the FA and within‐species level is consistent with the hypothesis that all new variation is organised by the same direct developmental pathways.

Differences indicates that the new variation from genetic or environmental factors are incorporated into phenotype by parallel developmental pathways in addition to those channelling the random perturbations of the developmental system

(Klingenberg 2005, 2008). In the caecilian cranium, the structure of shape variation within species is not very similar to FA, indicating the genetic and environmental factors causing variation among individuals produce different patterns of shape to the developmental processes generating differences among sides of the cranium. This discrepancy appears to be due predominantly to variation of the snout, not the braincase, since the within‐species and FA levels were uncorrelated in the snout, and moderately correlated in the back of the cranium. These results are consistent with a previous study that showed different modules have different patterns of similarity across levels, indicating different

developmental pathways are acting in each module (Klingenberg et al. 2001).

Other studies examining matrix correlation between individual (or pooled within‐ species) and FA covariance matrices of a whole structure reveal the similarity of variation at different levels is, like modularity, also not all‐or‐nothing but a matter of degrees (e.g. Debat et al. 2000; Klingenberg et al. 2003; Santos et al. 2005;

Breuker et al. 2006b; Zelditch et al. 2008; Drake and Klingenberg 2010;

Klingenberg et al. 2010; Webster and Zelditch 2011b). The discrepancy in across‐ taxa findings suggest further work in this field is necessary to understand how these patterns of similarity and dissimilarity relate to particular underlying processes of the developmental system (e.g. Breuker et al. 2006a).

Similarity of the covariance matrices for within‐ and among‐species levels is consistent with the hypothesis of neutral evolution, although is more likely to indicate the same evolutionary processes influencing each level, such as selection acting in similar directions and by similar amounts at each level (e.g. Lande 1980;

Cheverud 1982). We found high matrix correlations between the within‐ and among‐species covariance matrices for both modules, and thus an equally high matrix correlation for the whole cranium, indicating the influence of similar evolutionary processes modifying the covariance structure both levels. Few others have examined the structure of shape variation in ways directly comparable to our study. In one case though, the conservation of the structure of cranial variation across evolutionary divergences in caecilians contrasts the differences between the covariance structure in domestic dogs and carnivores, probably owing to the action of artificial selection on the former (Drake and Klingenberg 2010).

Evolutionary implications of modularity

In caecilians, modularity is expected to have had a substantial influence in the divergence of caecilian cranial shape. Patterns of evolutionary shape variation for the snout and back of cranium are very different, indicating that the evolution of the snout has occurred relatively independent to that of the braincase and cheek region. During caecilian evolutionary history there have been repeated notable modifications to the snout and back of the cranium, particularly to traits such as mouth position and temporal fenestration (Nussbaum 1977; Nussbaum and

Wilkinson 1989; Wilkinson and Nussbaum 2006). In the snout region the maxillary tooth row can be positioned in line with the anterior‐most projection of the snout, or it can be recessed far under the nasal capsules (‘terminal’ vs ‘subterminal’ mouth, Nussbaum and Wilkinson 1989). While, at the back of the cranium, the cheek region can be in contact with the dorsal roof of the braincase, or widely separated forming a temporal fenestra (‘stegokrotaphic’ vs ‘zygokrotaphic’,

Nussbaum and Wilkinson 1989). These different characters of the two regions have evolved many times in caecilian history and all combinations are found in living species (Wilkinson and Nussbaum 2006), which has been made possible by the snout and back of cranium being distinct developmental and evolutionary modules.

The patterns of evolutionary shape variation described by the snout are very different to that of the braincase and cheek region (Fig. 3.4B). The noticeable differences are in the separation of the major clades, which are markedly more distinct and spread out in the morphospace of the snout than back of cranium.

These patterns indicate the evolutionary history of the snout has involved much more shape divergence than the braincase. It has been suggested that different

modules may differ in their levels of evolvability (e.g. Martínez‐Abadías et al. 2009;

Goswami and Polly 2010), and our results suggest the snout has a larger propensity to evolutionary change than the back of the cranium. Moreover, when the pattern of evolutionary shape variation from the snout data is compared to that of the whole cranium, described in our earlier study on caecilian diversification (Chapter 2), it appears that the snout contributes more to cranial variation. That is, the snout graph (Fig. 3.4B) and graph for whole cranium (Fig.

2.4), are remarkably similar. Therefore divergence of snout shape dominates cranial shape diversity among caecilian species.

What factors have influenced the snout to change more over caecilian history?

Natural selection is likely to have been a very important process in the historical divergence of snout shape in caecilian species. The snout is the main point of contact with the environment in limbless animals, and caecilians exhibit a range of ecological lifestyles. Some species are fully or semi‐aquatic, while most are terrestrial and are dedicated burrowers or more surface‐active (Nussbaum and

Wilkinson 1995; Burger et al. 2004; Gower et al. 2004; Gower et al. 2010).

Furthermore, feeding mode is different between aquatic and terrestrial species

(O’Reilly 2000), so divergence in feeding and digging behaviour has probably been influenced by selection. The relatively weaker matrix correlation between within‐ species and among‐species levels for the snout (0.75) compared to the braincase

(0.81) is consistent with the expectation that selection on it is stronger than for the back of the cranium.

Another possible explanation for why the snout has changed more over caecilian history lies in the internal differences of the underlying developmental pathways of each modules. Of the two developmental modes that cause variation, integration

arising from parallel variation is more evolutionary flexible than from direct pathways (Klingenberg 2005; Webster and Zelditch 2011a). The different correlation coefficients of the FA and within‐species covariance matrices in the snout and back of cranium, suggest there may be a difference among the modules in the use of direct and parallel pathways to distribute variation. The very low matrix correlation for the snout suggests covariation is predominantly by parallel pathways, which are more easily modified by selection and so allow greater evolutionary change. Thus it may not be only differing degrees of selection on each module but also differences in the propensity for developmental pathways to change in response to selection. Certainly, our data cannot answer these questions completely and further studies on development of the caecilian cranium are needed.

In summary, our data support the hypothesis that the caecilian cranium has a modular organisation, where there are two functional modules, the snout and the back of the cranium (braincase and cheek region). Thus modular organisation is likely to be important for adaptive evolution of the cranium, so that snout, which interacts with the environment can be modified independently to the back of the cranium. The modular structure of the caecilian cranium at the developmental level has likely enabled the diversity of cranial forms in the group by decoupling in evolution the features that perform different functions. Thus to increase understanding of the factors controlling and producing morphological variation which in turn drive evolutionary change, we strongly encourage studies further studies that examine both patterns of developmental and evolutionary integration across different taxa.

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Chapter 4 ‐ Morphological Integration in the Cranium, Mandible and Atlas of Caecilians

Morphological Integration in the Cranium, Mandible and Atlas of Caecilians (Amphibia: Gymnophiona)

Emma Sherratt, David J. Gower, Mark Wilkinson, Christian Peter Klingenberg

Contributions: The crania measurement data are the same as in chapter 2. I segmented and digitised the mandibles. Data on the atlas were obtained with help from two project students (Martin Hughs and George Bruce). I performed all of the geometric morphometrics analyses with initial guidance from Chris Klingenberg (University of Manchester). I wrote the manuscript, with suggestions and comments on earlier drafts from Chris Klingenberg and members of the Klingenberg lab..

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Abstract Morphological integration is the coordinated variation among interacting parts of an organism. Allometry, the correlated change of with size change, is an important component of integration. Integration is inferred from covariation of multiple traits, which can be measured using geometric morphometrics. Here, we measure covariation within and among the main elements of the anterior skeleton (the cranium, mandible, and atlas vertebra) of caecilian amphibians, which are elongate, limbless, and mostly head‐first burrowers so their head serves to facilitate locomotion. We investigate patterns of integration and allometry within and among skeletal elements, across different levels of variation (fluctuating asymmetry, FA, within species and among species) in order to infer the roles of developmental and evolutionary processes in morphological diversification. For each skeletal element, the patterns of within‐ and among‐species allometry are very similar. For both the atlas and mandible, patterns of within‐element integration are very similar across all three levels. For the cranium, patterns of integration within and among species are very similar to each other but differ substantially to the FA level. Between‐element patterns are wildly different; the cranium‐mandible appears to be highly conserved, with significant covariation and similar directions of integrated shape change across levels. In contrast, directions of integrated shape change in the cranium‐atlas differ across levels, and is no significant covariation at the FA level. Studies such as ours that examining different complex structures using a combination of fluctuating asymmetry and broad taxon sampling are useful for understanding the origin and evolution of morphological variation.

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Introduction To understand morphological diversification, biologists have long studied how the genetic, functional and developmental correlation of traits influence inheritance so as to constrain or facilitate the evolution of morphological complexes (Lande 1980;

Cheverud 1996; Wagner and Altenberg 1996; Klingenberg 2005; Arnold et al.

2008). Strong correlation among traits is considered a constraint, concentrating variation in some directions of trait space along so‐called lines of least‐resistance

(Schluter 1996; Klingenberg 2010) and limiting variation in others (Arnold et al.

2008; Klingenberg 2010). Yet constraints themselves can evolve when the underlying factors shaping traits shift, change or breakdown the correlation (e.g.

Rolian et al. 2010; Kelly and Sears 2011), permitting and perhaps even facilitating evolutionary change (Wagner and Altenberg 1996; Klingenberg 2005). Thus correlation of traits and its action as constraints have a major role in evolution.

The correlated evolution of traits from a phenotypic perspective is known as morphological integration (Klingenberg 2008), which broadly encompasses joint variation of multiple traits across a hierarchy of levels, from within‐individual variation to long‐term evolution. These levels of variation are inherently related

(Cheverud 1982a, b, 1996; Klingenberg 1996; Klingenberg 2010). Thus to study correlated evolution at the phenotypic level, and its influence on morphological diversification, one must look to its origins in the developmental system

(Klingenberg 2005).

Correlated change of traits can arise because they share a common developmental pathway or because of parallel influences of external factors independently acting on separated pathways (Klingenberg 2003, 2004). Whether variation is genetic, environmental or developmental, it is transmitted via one of these pathways to

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influence the morphological traits under study. Fluctuating asymmetry (FA), the left‐right difference between sides of an organism, can be used to control for genetic and environmental variation in studies among individuals (e.g. Klingenberg

2008; Zelditch et al. 2008). Comparisons of patterns of integration in FA and individuals (within a species) can be done to infer the role of developmental processes underlying morphological variation. This reasoning has been applied, using geometric morphometric methods to measure morphological variation, in a variety of organisms (e.g. Klingenberg and Zaklan 2000; Willmore et al. 2005;

Ivanović and Kalezić 2010; Klingenberg et al. 2010; Monteiro and Nogueira 2010;

Webster and Zelditch 2011). From an evolutionary perspective, genetic variation underlying the phenotype of interest is available for evolution by natural selection or drift (Lande 1980; Cheverud 1982a). Comparing patterns of integration within species to patterns among species allows inference of the role of evolutionary processes in morphological diversification. Examining patterns across all three levels has proved promising to understand the role of developmental and evolutionary processes in creating the diversification of forms (Monteiro et al.

2005a; Young and Badyaev 2006; Drake and Klingenberg 2010; Monteiro and

Nogueira 2010).

The vertebrate head performs a variety of functions, such as feeding, sense and breathing. In caecilians, a limbless order of amphibians, the head also serves to facilitate locomotion (Wake 1993). Most caecilians are terrestrial and use their head to dig through leaf litter and soil, powered forward by internal concertina movement of truck muscles (Herrel and Measey 2010), like an earthworm. The anterior skeleton of a caecilian comprises three main skeletal elements, the cranium, the mandible, and the atlas vertebra (Fig. 4.1). The cranium is well‐

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ossified, compact and robust, and houses the sensory system. The mandible (lower jaw) lies ventral to the cranium, either positioned inline with the front of the snout or recessed under the snout, and operated by a unique jaw‐closing mechanism

(Nussbaum 1983). The atlas (first cervical vertebra) is a highly modified and specialised (Wake 1980), forming the joint between the cranium and the body vertebrae. The mandible articulates with the cranium at the quadrate to form the mouth, while the atlas articulates with the cranium at the occipital region on the braincase to form the neck joint (Fig. 4.1 and 4.2). Together, it is predicted that there is a degree of integration within and between the skeletal elements to maintain particular forms of each elements as well as maintain coordinated function of the joints.

Fig. 4.1 Articulated anterior skeleton of a caecilian, showing cranium atlas and mandible elements. The mandible articulates with the cranium at the quadrate, and there is a small amount of rotation about this joint (streptostyly). The atlas bone articulates with the cranium by two cotyles positioned at the ventrolateral corners of the foramen vertebrale, which allows flexion‐extension (up and down movements) but no rotation and very little lateral flexion (side to side movement).

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Fig. 4.2 Landmarks measured to quantify the shape of the three elements. Across the top: the cranium shown in dorsal, palatal, posterior and lateral views. Bottom left: the mandible in palatal, ventral and lateral views. Bottom right: the atlas bone in anterior, posterior and lateral views. White landmarks are those inside the cranium braincase. Double circles indicate paired landmarks on midline (see text for explanation). Note that the cranium and atlas bone are not drawn to the same scale. Abbreviations: o.con = occipital condyle, o.cot = occipital cotyle, f.ve = foramen vertebrale, p.d. = pseudodentary, r.a. = retroarticular process. The cranium articulates with the mandible at *, and with the atlas at §.

This study compares integration patterns across different levels of variation to assess the roles of developmental and evolutionary processes in producing morphological variation within a major order of vertebrates. We quantified correlated morphological variation within and among the main functional elements of the caecilian anterior skeleton (i.e., cranium, mandible, atlas bone) at each of the three levels of variation: FA, within species and among species. The geometric morphometric toolkit is well‐suited to measuring morphological

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variation and studying correlated trait changes (Polly 2008; Klingenberg 2010). To examine integration patterns within each element, we measured allometry within and among species and compared patterns of shape variation due to size between levels. After correcting for allometry, we statistically compared patterns of within‐ element integration across all three levels. Finally, to examine patterns of among‐ element integration we calculated the covariation between the cranium and atlas and between the cranium and mandible at all levels.

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Materials and Methods

Samples

The study uses 524 adult individuals from 141 taxa (94 described species and 47 undescribed species), representing all major clades of the order Gymnophiona

(Wilkinson et al. 2011). Skeletal morphology was investigated by high resolution x‐ ray computed tomography (HRXCT) at the Natural History Museum, London

(Appendix 1). The main bone elements were extracted from the scans using VG

Studio MAX v.2.0 (Volume Graphics 2001) and rendered as surface models, known also as isosurfaces, and herein referred to as surfaces. Details of the specimens sampled, HRXCT and digitising procedures are in Appendix 1, 2 and 3. From the scans, a total of 285 atlas bones, 443 mandibles and 524 crania were available for measurements, from only adult specimens. The uneven number of elements per individual is a result of damage to the specimens, but as many as possible were included. For the analyses of crania and atlas, 285 individuals from 94 taxa were sampled. For the analyses of crania and mandible, 443 individuals from 119 taxa were sampled. The two samples are not completely nested; in the study of the crania and atlas 10 species (from 8 genera) are not included in the other as the mandibles were damaged, however other species from the same genera were included, with exception of the monotypic genera Atretochoana, Nectocaecilia and

Praslinia.

Shape analysis

Shape of the three elements was measured by geometric morphometric methods, using landmarks digitised in three dimensions on the surfaces using Landmark

Editor v.3.6 (Wiley et al. 2007). On the atlas bone surfaces 20 landmarks were 112

digitised, 6 unpaired landmarks on the midline and 7 paired on left and right sides

(Fig. 4.2, bottom left).

The caecilian mandible is composed of 2 hemimandibles joined at the midline with connective tissue. This permits some degree of rotation at the midline and may cause asymmetry in the structure if considered whole. Thus hemimandibles were digitised separately, using 13 landmarks on each (Fig. 4.2, bottom right). Finally,

60 landmarks were digitised on the cranium as in Chapter 1; four unpaired on the midline, four paired and positioned either side of wide midline sutures, and 48 paired over the external surface and inside the cranium (Fig. 4.2, top). Anatomical details of the landmarks used in this study are detailed in Appendix 4.

All subsequent analyses were performed using MorphoJ v.1.02f (Klingenberg

2011). The raw landmark coordinates for the three elements were subject to a full

Procrustes fit and projection into tangent space (Dryden and Mardia 1998). The crania and atlas bone have object symmetry, and so the Procrustes fit produced shape variables of both symmetric and asymmetric components (Klingenberg et al.

2002). The hemi‐mandibles have matching symmetry and were treated separately.

Measurement error was assessed for each element using the Procrustes ANOVA method (Klingenberg and McIntyre 1998). For the cranium and mandible, 30 specimens were digitised three times each, and for the atlas, all specimens were digitised twice. In all cases, the mean squares (MS) of digitising error was substantially lower than the MS for FA and thus negligible in this sample.

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Levels of morphological variation

Covariation among traits of morphological structures was examined at three levels by extracting particular components from the phenotypic variation: First, fluctuating asymmetry (FA) represents the within‐individual level and originates from variation in the developmental system (Klingenberg 2003). FA was calculated as the pooled within‐species shape asymmetry extracted using a Procrustes

ANOVA with individual and side as effects (Klingenberg and McIntyre 1998).

Second, within‐species level used the pooled within‐species symmetric shape data.

Finally, the among‐species level denotes evolutionary variation. Using comparative methods (Felsenstein 1985) independent contrasts were calculated using a species‐level phylogeny, the topology of which is a partially‐resolved consensus of molecular and morphological data from published and unpublished data, detailed in Chapter 2. All subsequent analyses are performed on these components of variation.

Measuring allometry

To examine how much shape variation can be explained by allometric size change, we performed multivariate regressions of shape data on centroid size (Monteiro

1999). The size component, centroid size, is calculated as the square root of the sum of squared distances of a set of landmarks from their centroid (Dryden and

Mardia 1998). Allometry was measured within species using a multivariate regression of the pooled within‐species symmetric shape and centroid size. This level represents variation among adults of each species, but since caecilians have indeterminate growth, it likely represents a mixture of static and ontogenetic allometry (Klingenberg 1996). Evolutionary allometry was measured among 114

species using a regression of the independent contrasts of symmetric shape and centroid size. Results of the regression analyses are given as shape changes associated with size change, the proportion of shape variation in the sample attributed to size variation, as well as a significance test for the strength of the fit between the variables, calculated with permutation tests (Good 2000). Shape changes (multivariate equivalent of the slope) were illustrated as warped surfaces.

Two slope vectors were extracted, by applying a scale factor in the positive and negative directions from the mean, and applied to a template surface model which warps to the shape using the thin‐plate spline method implemented in Landmark

Editor (Wiley et al. 2005; 2007). The warped surfaces demonstrate the shape differences between the negative and positive extremes of the regression slope, which are equivalent to the covariation of shape and size in the cranium, mandible and atlas. The surfaces used as templates for the warps are of the species Caecilia tentaculata.

Since caecilians in this sample have a great range in total body length (65 mm to

985 mm), with around at least a 5‐fold increase in centroid size of the cranium

(10.0 mm to 66.0 mm), atlas (2.0 to 10.0 mm) and mandible (3.5 to 22.3 mm), size is expected to be a significant factor in shape variation and covariation. Therefore for further analysis, the shape data used to represent the within‐ and among‐ species levels will be size‐corrected. For this purpose, we take the regression residuals from the pooled‐within species regression (for within species level) and independent contrasts regression (for among‐species level), and use them as size‐ corrected shape variables in subsequent analyses. FA is not corrected for size because the proportion due to allometry is negligible (< 1% for all elements).

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Comparing covariance matrices

To investigate morphological integration within each skeletal element, we calculated matrix correlation between covariance matrices. The matrix correlation is tested for significance with matrix permutations of the correlation coefficient between corresponding elements of the covariance matrices (Klingenberg and

McIntyre 1998). It tested for significance against a null hypothesis of no correlation between matrices. The null distribution of matrix correlations was created from random permuted sets of three rows and columns (10,000 rounds), a procedure which maintains the association between x, y and z dimensions of landmarks in 3D shape data (Klingenberg and McIntyre 1998). The diagonal blocks of the covariance matrix represent the within landmark variation, so matrix correlation coefficients and permutation tests were also calculated without the diagonal blocks to compare among landmark variation only.

Covariance matrices were constructed for each level and each skeletal element: the

FA covariance matrices were constructed from the pooled within‐species asymmetric shape component; within‐ species covariance matrices were constructed from the pooled within‐species size‐corrected individual shape data; among‐species covariance matrices were constructed from size‐corrected independent contrasts of shape. To compare levels, we used calculated matrix correlation coefficients between pairs of covariance matrices and each correlation coefficient was tested for significance with matrix permutations.

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Measuring integration

To measure morphological integration between the three skeletal elements, we calculated covariation using two‐block partial least squares (PLS) analysis. PLS is used in morphometric studies to examine patterns of covariation between any two sets of variables that contain the same measured individuals (Rohlf and Corti

2000). PLS analysis takes two sets (e.g. cranium and mandible), constructs a combined covariance matrix, and then constructs a set of new variables that successively account for the covariation between the blocks. PLS is methodologically similar to principal components analysis (Jolliffe 2002); PLS finds the major axes of covariation in the data, so the first PLS axis accounts for the most covariation, and subsequent axes successively less. A correlation coefficient for each axis is calculated, giving the strength of the correlation between pairs of

PLS axes, that is one axis from each block. For each PLS analysis, we calculated

Escoufier’s (Escoufier 1973) RV coefficient , which is a multivariate extension of the squared correlation coefficient. The RV coefficient ranges from 0 to 1, where 0 indicates the two blocks do not covary, and 1 indicates they strongly covary. We also performed a significance test for each PLS analysis, against the null hypothesis of complete independence of the two blocks, is calculated from 10,000 random permutations.

PLS analysis was used to examine morphological integration of the cranium with atlas bone and cranium with mandible at each of the three levels of variation. The size‐corrected shape variables for within‐ and among‐species levels were used in the PLS analyses, and for FA, the pooled within‐species asymmetry component of shape.

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Covariation patterns as described by PLS were compared among levels by investigating shape changes visually. To do this, the shape changes associated with the negative and positive ends of the first PLS axis are shown by warping a surface using the technique described for allometric shape change. An arbitrary global scale factor of 0.1 was used for all warps. Therefore the warped surfaces demonstrate a shape 0.1 Procrustes units away from the mean shape towards the negative and positive extremes of the PLS axis. The two extreme shapes together describe the main axis of covariation in shape between the cranium‐atlas and cranium‐mandible.

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Results

Allometry

The proportion of shape variation attributable to size differs according to the structure measured, but statistically significant in all elements (Fig. 4.3 and 4.4).

Fig. 4.3 Withinspecies shape variation attributed to size variation. Percentage of shape variation due to size: atlas 20.8%, cranium 14%, and mandible 3.8%. Shape change vectors extracted from a pooled within‐species multivariate regression of symmetric shape on centroid size. Shape changes associated with allometry are shown by warped surfaces depicting the increase (large) and decrease (small) in size from the average centroid size. Range of centroid size: atlas 2.0 to 10.0 mm, cranium 10.0 mm to 66.0 mm, mandible 3.5 to 22.3 mm. Scale factor (the difference from the mean) for atlas is ± 3.5 mm, cranium ± 20 mm and mandible ± 9 mm, where negative is smaller and positive is bigger.

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Fig. 4.4 Amongspecies shape variation attributed to size variation (evolutionary allometry). Percentage of shape variation due to size: atlas 19.5%, cranium 15.5%, and mandible 3.9%. Shape vectors extracted from a multivariate regression of the independent contrasts of symmetric shape on the independent contrasts of centroid size. Details of the shape vectors and scale factors as in Fig. 4.3.

Within‐species allometry accounts for a large proportion of shape variation in the atlas, and less in the cranium and mandible (Fig. 4.3). For the atlas, size increase involves the occipital cotyles getting larger relative to the size of the foramen vertebrale, and a lengthening of the bone. In the cranium, increasing size is associated with a widening of the snout and cheek region, and a shift of the quadrate bone posteriorly so that at the point of articulation with the mandible, the cranium is substantially wider in large individuals. In the mandible the shape changes associated with an increase in size are more subtle; the pseudodentary is

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more curved and the retroarticular process bends dorsomedially towards the cranium in larger individuals.

Among‐species (evolutionary) allometry accounts for substantially different amounts of shape variation in each element (Fig. 4.4), but each is similar to the proportion from the within‐species allometry. The shape changes associated with an increase in size among species, for all three elements, are also very similar to the within species shape changes.

Similarity of covariance matrices

Matrix correlations (including and excluding the diagonal elements) between covariance matrices representing the three levels are almost always statistically significant (Table 4.1). The exception is between FA and within species of the cranium, where it is marginally significant when including the diagonal blocks and not significant when diagonal blocks were excluded. Comparing between levels, the matrix correlations were always high between the within‐ and among‐species covariance matrices, while the correlation coefficients range from low to high between the FA and within‐species matrices, and the FA and among‐species matrices (among columns, Table 4.1).

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Table 4.1 Matrix correlations between covariance matrices of the cranium, atlas and mandible. Comparing covariance matrices of shape variation within‐ individuals (FA), within‐species (WS) and among species (AS). Matrix correlations were calculated twice, to include the diagonal block (variance of landmarks) and without diagonal block (covariance of landmarks). Significance of each matrix correlation is given in parentheses.

ATLAS FA vs WS WS vs AS FA vs AS including 0.65 (P < 0.0001) 0.91 (P < 0.0001) 0.72 (P = 0.0005) excluding 0.13 (P = 0.0084) 0.87 (P < 0.0001) 0.12 (P = 0.0149) CRANIUM including 0.28 (P = 0.0723) 0.73 (P < 0.0001) 0.31 (P = 0.0107) excluding 0.02 (P = 0.2095) 0.66 (P < 0.0001) 0.04 (P = 0.0165) MANDIBLE including 0.71 (P < 0.0001) 0.88 (P < 0.0001) 0.81 (P < 0.0001) excluding 0.40 (P < 0.0001) 0.77 (P < 0.0001) 0.52 (P < 0.0001)

Comparing between analyses including and excluding diagonal blocks, matrix correlations are always lower in analyses excluding the diagonal blocks (among rows, Table 4.1). Including the diagonal blocks of the covariance matrices gives a matrix correlation based on variation within and between landmarks. For the cranium, matrix correlations are quite varied, while for both the atlases and the mandibles matrix correlations are more consistent and higher. Excluding the diagonal elements of the covariance matrices gives matrix correlations based on variation among landmarks only. In this case, matrix correlations for the all elements are substantially more varied, dropping very low for the FA versus within species and FA versus among species analyses and dropping only a little for within species versus among species. These results indicate that similarity of the covariance matrices is mostly dependant on variances and covariances of the coordinates within landmarks and marginally dependant on covariances among landmarks.

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Covariation of the cranium and mandible

Covariation of the cranium with the mandible was calculated using PLS analyses at all three levels. Cranium‐mandible shape covariation is statistically significant at all levels: the RV coefficient for FA is low but highly significant (RV = 0.09, P <

0.0001), the RV coefficient within species is moderate and significant (RV = 0.15, P

< 0.0001), and the RV coefficient among species is moderately high and significant

(RV = 0.32, P < 0.0001).

Fig. 4.5 Structure of shape covariation for the craniummandible and cranium atlas at leach level. Percentages of total squared covariance as explained by each pair of PLS axes for all PLS analyses. PLS analyses were done from covariance matrices representing the three hierarchical levels of variation: fluctuating asymmetry (top), within species (middle) and among species (bottom).

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At each level, a large proportion of the covariation is concentrated in the first pair of PLS axes and the second pair contribute less that half of the first (Fig. 4.5). Shape change associated with cranium‐mandible covariation are taken from the first pair of PLS axes (Fig. 4.6). At all levels, the shape changes describing the main axis of covariation involve the lateral position of the cheek region (squamosal and quadrate) and curvature of the mandible. When the cheek position shifts medially, the mandible becomes more curved, and when the cheek shifts laterally, the mandible becomes straighter.

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Fig. 4.6 Shape changes associated with covariation of the cranium and mandible within individuals, within species and among species. Shape vectors extracted from the first pair of PLS axes from each level analysis, and shown as warped surfaces. Asterisks indicate the left sides that fit together. PLS axes describe 44% of the covariation within individuals, 47% within species, and 61% among species. Scale factor of all shape warps is 0.1, therefore the asymmetry is exaggerated.

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Covariation of the cranium and atlas

As for the cranium‐mandible, covariation of the cranium with the atlas bone was examined using PLS analysis. Cranium‐atlas shape covariation is statistically significant at two of the three levels: the RV coefficient for FA is low and not significant (RV = 0.06, P = 0.1168), the RV coefficient within species is moderate and significant (RV = 0.17, P < 0.0001), and the RV coefficient among species is moderately high and significant (RV = 0.25, P = 0.0012). The within individual level is omitted from further discussion because it was not significant.

Within species, a large proportion of the covariation between elements is concentrated in the first pair of PLS axes. Among species, covariation is distributed over several pairs of PLS axes. This indicates that there are multiple, almost equally important ways that the cranium and atlas can covary together (Fig. 4.5).

Shape changes associated with the covariation of the cranium and atlas are shown in Fig. 4.7. On PLS 1 of within‐species level, a change in the positive direction from the average gives a more tapered cranium with narrow cheek region and an atlas with a wider foramen vertebrale relative to the cotyles. In the negative direction, the cheek region and snout widens and the atlas foramen vertebrale shrinks compared to the cotyles. Among species, both PLS 1 and PLS2 contribute large proportions of the covariation. In the negative direction on PLS1, the atlas shortens and narrows and the cranium narrows, while in the positive direction, the atlas widens and elongates and the cranium widens. In the negative direction on PLS2, the cranium widens at the snout and the cheek region shifts anteriorly as the atlas widens, while in the positive direction the cranium narrows and tapers to the snout and the cheek region shifts posteriorly as the atlas narrows. Overall the

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shape changes described by the patterns of covariation within‐species are inconsistent with those among‐species in the cranium and atlas.

Fig. 4.7 Shape changes associated with covariation of the cranium and atlas within species and among species. Shape vectors extracted from the first pair of PLS axes within‐species and the first and second pairs of PLS axes among species. Within species, axis PLS1 describes 52% of the covariation, and among species, PLS1 describes 30% and PLS2 20% of the covariation. Scale factor of shape warps is 0.1.

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Discussion Our analyses have found that patterns of within‐element integration across levels differ among the main skeletal elements of caecilians: the cranium, mandible and atlas. Moreover, the patterns of between‐element integration across levels differ between the cranium‐mandible joint and cranium atlas joint. Here, we evaluate the consistency and inconsistency of integration patterns in the light of theory on developmental and evolutionary processes.

Patterns of integration in the cranium, mandible and atlas

In all elements, within‐species allometric coefficients representing shape changes due to size were very similar to those among species. Allometry appears to be a dominant factor of morphological variation in these skeletal elements (e.g.

Cheverud 1982b; Klingenberg and Zimmermann 1992). That evolutionary allometry is similar to the phenotypic allometry within species suggests the within species genetic and phenotypic covariance patterns are similar (Lande 1979;

Cheverud 1982b). The apparent congruence between these levels is in line with what is expected under neutral evolution, but this pattern could also occur if natural selection was acting only on overall body size and change in shape is merely a correlated response (Lande 1979). If long‐term correlated evolution of size and shape is determined by the fitness functions of stabilizing and directional selection, not the genetic covariance structure (Zeng 1988), then the evolutionary allometry may not be due to genetic allometry at the within‐species level, but instead a result of correlated change along a line of least resistance (Schluter

1996).

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Within the main skeletal elements of the caecilian head, patterns of integration

(characterised by covariance matrices) between FA and within‐species levels differ depending on the element of study. In both the atlas and mandible, moderately high matrix correlations between FA and within species variation indicates that patterns of integration are mostly conserved across levels. These results suggest new variation created by the developmental system is passed along similar pathways to those distributing genetic and environmental variation to create shape variation of the atlas and mandible structures (e.g. Klingenberg 2005, 2008).

In the cranium, however, low matrix correlation between FA and within species variation indicate little conservation of developmental integration patterns within species. Therefore it suggests new variation from genetic or environmental influences are incorporated into phenotype by different developmental pathways than those channelling the random perturbations of the developmental system.

Thus he within‐species shape variation of each structures arises by different processes. That the cranium and mandible in caecilians show substantially different patterns of consistency among levels is also demonstrated in the mouse system, where the degree of correlation between FA and individual variation between structures is more similar overall in the mandible (Leamy 1993;

Klingenberg et al. 2003) than the cranium (Debat et al. 2000; Hallgrímsson et al.

2004; Willmore et al. 2006).

For all three elements, within‐species integration patterns are very similar to those among species, which indicates evolutionary divergence in shape of cranium, atlas and mandible follows general patterns that are found in the pool of within species variation. Conserved patterns of integration between within‐ and among‐species levels is consistent with evolutionary change by genetic drift (Lande and Arnold

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1983; Felsenstein 1988), yet historical persistence of integration can also occur if the same selection forces acted at each level, that is producing change by similar magnitudes and in similar directions. Such comparisons between within and among species levels are rare in the literature, but indicate that these levels are not similar in situations where there is selection for changing functional demands of the structure of study (Monteiro et al. 2005b; Monteiro and Nogueira 2010), or intense artificial selection (Drake and Klingenberg 2010).

The caecilian head and neck as an integrated complex

Integration among the cranium and lower jaw is expected owing to the functional constraints imposed by coordinated action of the upper and lower jaw during feeding. Similarly, integration of the cranium and atlas bone is expected because the two elements form an important joint that is responsible for the movement of the head relative to the body column during head‐first burrowing (Wake 1993).

For both the cranium versus atlas and cranium versus mandible analyses, the strength of covariation given by the RV coefficients were similar at each level, where the strongest covariation was among species and the weakest for FA.

However, at the FA level, cranium‐mandible analysis was significant and the cranium‐atlas analysis was not. While covariation within species implies variation from genetic or environmental sources generate a response in each element, the stronger covariation among species reveals other integrating factors, such as environmental factors (e.g. Cheverud 1982a), are acting in addition to the inherited genetic covariance structure. The patterns of integration between skeletal elements at the within‐ and among‐species levels are unlikely to be dominated by underlying developmental integration, since the low covariation at

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the FA level suggests there are few and weak developmental interactions between the elements. A certain degree of coordinated shape variation, particularly asymmetry between elements may be due to the interaction of muscle and other soft tissue with the bone during growth. In studies of rodents that found a correlation in shape variation of the cranium and mandible, where the coordinated shape change was primarily due to post‐natal growth (Zelditch 1988; Cardini and

O'Higgins 2005). Studies in mammals indicate bone remodelling under the influence of mechanical loading is a possible mechanism for direct interactions between skull parts (e.g. Herring 1993; Enlow and Hans 1996; Lieberman 2011), but there is no information whether such bone remodelling also occurs in caecilians.

Similar patterns of covariation and shape change in the cranium and mandible between within‐ and among‐species levels are starkly contrasted with the different patterns shape change in the cranium and atlas (Fig. 4.6 and 4.7). These results imply the two skeletal joints have been influenced by different evolutionary processes; the cranium‐mandible results are consistent with a model of evolutionary change by genetic drift, and the cranium‐atlas result implies processes deviating from the neutral model. Evolutionary integration of the structures may be due to selection on the performance of functionally integrated traits (Zeng 1988), or result from genetic covariation and developmental factors within species (Cheverud 1996; Klingenberg 2008). For the cranium and mandible, either process may be responsible, but it is evident that changes to the shape of either structure are highly conserved. That is, even after correcting for shape change due to allometry, the patterns of shape covariation among the cranium and mandible were very similar to the shape changes in each element associated with

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allometry (Fig. 4.4 and 4.6). Such persistence of covariation patterns strongly suggest factors involved in the covariation of shape with size also strongly influence other aspects of morphology.

For the cranium‐atlas, dissimilarity among the integration patterns within and among species, and their incongruence with allometry may be due to natural selection. The basis of the restructuring between within‐ and among‐species covariance may be a consequence of adaptations of different lineages to different locomotion modes and habitats of caecilians, such as burrowing, surface‐active and aquatic lifestyles (Chapter 2). Among‐species, the two main axes of shape covariation describe differences in the size, shape and position of the atlas cotyles and cranium condyles, which are important features defining the range of movements in the joint, and different lifestyles are likely to have different functional influences on the shape of these structures. Ecological data for are needed to test these hypotheses. Certainly, shifting locomotion modes and habitat are the reason for the diversity in the cranium‐atlas joint of Primates (Manfreda et al. 2006; Lieberman 2011).

This paper reveals diverse patterns about developmental and evolutionary integration. Overall, allometry is an important component of integration in the caecilian cranium, mandible and atlas. Within‐element patterns of developmental integration and within‐species integration differ depending on the element under study, while patterns of within‐species and evolutionary integration are highly concordant. Between‐element patterns are wildly different between the cranium‐ mandible and cranium‐atlas, where the former is more conserved than the latter, which may be a reflection of the functional differences of these structures. In conclusion, these results indicate much can be gained about the origin and

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evolution of morphological variation by examining different complex structures using a combination of fluctuating asymmetry and broad taxon sampling.

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Acknowledgements

ES would like to thank M. Hughs and G. Bruce, and is grateful to the Klingenberg Lab members for help discussions and comments on drafts of the manuscript. ES was funded by a NERC CASE Studentship NE/F009011/1.

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Chapter 5 ‐ Discussion on the Evolution of the Caecilian Skull

Chapter synopsis and future outlook The main aim of this thesis was to characterise large‐scale patterns of cranial morphological diversity, quantify variation across the main family‐level clades, and examine the origins and evolution of morphological variation in the skull. To do this, I inferred the evolutionary history of the caecilian cranium, and described patterns of variation relating to phylogeny, disparity, ecology, morphological integration and modularity. In chapter 2, I addressed some external factors that might influence morphological diversity, such as ecology, clade age and numbers of species. In chapters 3 and 4, I investigated the internal, developmental factors that influence morphological diversity, and how these influence evolution of morphological traits. Overall, the evolution of the caecilian skull is multifaceted, and this thesis is just the beginning for identifying what has made the evolution of the caecilian skull. I shall now briefly discuss how the findings from this study can be used to initiate future studies.

Of all the patterns describing cranial morphological diversity, the most striking pattern was the “starburst” (Fig. 2.4) that suggested early in caecilian evolution ancestral lineages traversed greater expanses of the shape space, while subsequent phylogenetic divergence within the main clades entailed less morphological diversification. This leads to an important question in evolutionary biology: what causes the differences in morphological disparity between and within the main clades. I showed that the main clades of caecilians are mostly very different to each other, and that there was a link between distance in shape space and age of lineages. I also showed that clades differ considerably in their cranial disparity, yet that there was no unified pattern across the whole order that connected disparity

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with clade age or speciation events. This leads to the question, are these patterns due to the tempo and mode of evolution, that is the rate and mechanism of diversification. The data and methods used in this thesis were insufficient to address this question; a molecular phylogeny would be needed to infer a time tree in the absence of a fossil record so that rates of morphological evolution could be examined. In order to achieve this, a far greater number of species must be sampled for molecular data in order to build a phylogeny like the one used in this thesis. Such a task is already underway by Diego San Mauro and David Gower at the Natural History Museum, London. However, this involves a great deal more field work, since many of the species I scanned were collected in the days before molecular phylogenies and are not suitable for such studies now.

Such early filling of morphological space has been associated with early filling of major ecological niches in other taxa, and may indicate caecilians are an old adaptive radiation, although data presented in this thesis are not sufficient to test this hypothesis. I, and many before me (Taylor, Renous, Nussbaum, Wilkinson,

Gower) consider ecology to be a very important influencing factor on the evolution of the caecilian skull. Using the sparse ecological information that is available for certain species, I was able to show that aquatic species are more disparate than their terrestrial relatives, and dedicated burrowers with closed orbits have converged on a small area of morphospace, surrounded by species with open orbits. A pattern I did not discuss in chapter 2, for reasons of uncertainty, is the one of convergence among the species that have a more robust cranium with a closed temporal region (in clades I., H., C., Si., In., and some of D.) compared to the widely spread taxa that have an open temporal region (in clades R., Sc., U., T., some

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of D.), as shown in Fig. 2.4. Many authors have considered this to be a characteristic of difference in fossorial lifestyle, however there is very little ecological evidence to support these claims (Gower et al. 2004). Future studies on caecilians should emphasize collecting ecological data on more species. While caecilians are cryptic, they are probably not rare (Measey 2004; Gower and

Wilkinson 2005). Collecting caecilian in the field is very hard and involves a large amount of digging, but the results presented in this paper illustrate the rewards such field work offers. And future studies will greatly benefit from a more complete understanding of how these animals live. Quantitative studies like the one by Gower and colleagues (Gower et al. 2004) on two species of caecilian in

Tanzania have revealed there is a difference in lifestyle of the terrestrial species, and I encourage further studies of this kind.

I consider biomechanical function to be another influencer of differences within‐ and among‐clade patterns of caecilian skull diversity. Two distinct findings from this thesis point towards this conclusion. Firstly, I showed that the significant modularity hypothesis corresponds to two functionally different regions of the skull: the snout has morphologically diversified more greatly than the back of the cranium, which I think is because the snout is the main point of contact with the environment in caecilians (chapter 3); and also the cheek region, which houses the jaw muscles, covaried more strongly with the braincase, which is likely to be the result of maintaining a functioning jaw system. Secondly, in chapter 4 I showed there are stark differences between the cranium‐mandible and cranium‐atlas, concluding these two joints were integrated by different developmental and evolutionary processes. These results highlights a tradeoff between burrowing and feeding influences on the skull, which may be more or less of a tradeoff in different

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taxa of different clades. These sorts of questions could be addressed using a biomechanical approach.

Renous (1990) compared the biomechanical aspects of skull shape in several species. Her studies lead to tentative results that species differ widely in their gape and concluding that for the species Microcaecilia unicolor, modifications to the jaw shape and muscles allow a wider gape and ability to ingest prey with a large cross‐ section, thus allowing this species to not compete with other “dwarf vertebrates” living in the same environment that feed on similar prey. More recent studies on the functional aspect of the caecilian skull have confirmed the caecilian skull gape is indeed a marvel and appears to sets caecilians apart from burrowing, small‐ gaped snakes (Bemis et al. 1983; Teodecki et al. 1998; Summers and Wake 2003,

2005; Kleinteich et al. 2008; Kleinteich 2010). The trade‐off between modifications to the skull for feeding and burrowing adaptations has been discussed in fossorial lizards (Vanhooydonck et al. 2011), and may also apply to caecilians. A way to address this would be to make complex biomechanical models using detailed anatomical information about muscles and bone from CT scans to examine how the caecilian skull is used during burrowing and feeding, such as have been used to study feeding in lizards (Moazen et al. 2009; Curtis et al. 2010). This approach would benefit caecilian research and evolutionary biology by addressing the functional significance of evolutionary changes in complex morphological structures.

I approached the origin and evolution of morphological variation in the caecilian skull by investigating developmental and evolutionary modularity in the cranium

(chapter 3) and developmental and evolutionary integration among three skeletal elements of the caecilian skull and neck (chapter 4). Development is the process by

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which morphology is produced, and in which genotypic variation leads to phenotypic variation. In the absence of genetic data for caecilians, I was able to gain insights into how development makes the morphology of the cranium, mandible and atlas, and how underlying patterns of integration shape the direction of evolution. The results of both chapters illustrate that much can be learnt about morphological evolution by studying the covariation of anatomical structures at the level of development and evolution (with a pooled within‐species level to offer comparison). Integration and modularity within the cranium or mandible is well studied in mammals, and poorly known in amphibians (but see Ivanović and

Kalezić 2010). Surprisingly, there are few studies that looked at patterns of covariation among different structures of the same organism, from either developmental or evolutionary perspective, against which I could make comparisons with the caecilian system. Surveying the literature, the examples that exist are very wide‐ranging in terms of structures, but quite limited in terms of taxa: covariation of the fore‐ and hind‐wings of bumblebees (Klingenberg et al.

2001), the cranium and mandible in rodents, marmots and primates (Zelditch

1988; Bastir et al. 2005; Cardini et al. 2005; Monteiro et al. 2005; Singh 2010;

McCane and Kean 2011), the cranium and atlas in primates (Manfreda et al. 2006;

Lieberman 2011; McCane and Kean 2011), soft and hard tissue of the cranium

(Jamniczky and Hallgrímsson 2011), the fore‐ and hind‐limbs in various mammals

(Young and Hallgrímsson 2005; Kelly and Sears 2011), and the hands and feet of primates (Rolian et al. 2010). As such, it was difficult to draw conclusions on my results in the light of these disparate examples. Thus, this is an area of research that requires further attention. Future studies using a similarly comparative approach across levels and structures in other taxa are expected to offer more

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insights into the factors that contribute to the origin and evolution of morphological variation.

Conclusions I have discussed some of the findings of this thesis in light of several areas where future studies using caecilians and other taxa will be of benefit to understanding the evolution of morphology. In this thesis I have attempted to use a range of comparative tools and morphometric data in light of developmental and evolutionary theory to provide insights into the evolution of the caecilian skull.

This thesis presents new results about the history of diversification in the caecilian skull and the external and internal influences on the origin and evolution of morphological variation. Several of the patterns described in this thesis shed new light on the findings from other taxa and highlight that there is a need for more equivalent data on other taxa to provide comparison. This thesis also demonstrates what can be gained from using museum collections to study fascinating yet unfamiliar taxa. Thus, I hope that this study will make a useful contribution to developmental and evolutionary biology, and provide inspiration for others. .

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Appendix 1 ‐ High Resolution X‐ray Computed Tomography

Background High‐resolution x‐ray computed tomography (HRXCT) is a technique for gathering volumetric x‐rays of almost any material, which can be digitally dissected for a range of analyses (Ketcham and Carlson 2001, Computers & Geosciences 27:381‐ 400). For biological material, HRXCT is relatively non‐destructive, in that specimens can be examined whole and alcohol‐preserved specimens can stay wet. It may be destructive in respect to damaging DNA, although so can traditional x‐ ray, however most museum material has been treated with formalin or other preserving chemicals which have already had a destructive effect on DNA.

Methods HRXCT was used in this study to make detailed anatomical scans for measurement by 3D landmark methods. All HRXCT scans were made on the Metris X‐Tek HMX ST 225 System at the Natural History Museum, London. The use of HRXCT has made it possible to gather information on rare species and examine anatomical features without dissecting the material.

Whole, alcohol‐preserved specimens were placed in a measuring cylinder, head down and their bodies are wrapped in alcohol‐soaked muslin and sealed in a plastic bag to prevent evaporation (Fig. A1.1 far left). This setup for elongate serpentiform animals allows many heads to be scanned simultaneously. Measuring cylinders for different size classes of specimen: 10ml (diameter 14mm) for small specimens, 25ml (20mm) for medium and 50ml for large (26mm), and drinking straws for extra‐small.

The cylinder is placed on the scanner turntable and centred. During the scan, 2D x‐ ray images are taken while the turntable rotates by approximately 0.1o increments, producing 3142 projections of the object in 360o (Fig A1.1 top middle). X‐rays were generated with a Molybdenum target. These projections are exported to reconstruction software, where they are collated into 3D volume, and then sliced laterally into slices as thick as the resolution of the scan, e.g. 5µm.

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CT volumes consist of hundreds of slices, an image (e.g., tiff file) made up of voxels (3D pixels) that correspond to different densities of the material (Fig A1.1 top right). White is the densest, here representing bone, and black is least dense, representing air, which is measured during the scan as the attenuation of x‐rays in the different materials. Each slice can be dissected digitally, according to the colour of the voxels, to extract certain features of interest. Here the bone has been segmented, by thresholding the slices at the interface between the white and the black voxels (Spoor et al. 1993, Am. J. Phys. Anthropol. 91:469‐484), to produce a 3D rendered isosurface of the skeleton (Fig A1.1 bottom right). The isosurface is made up of a point cloud connected by triangular faces (Fig A1.1 bottom middle). The software used to view and segment the scans was VG Studio MAX 2.0 (Volume Graphics 2001).

Fig. A1.1. A simplified scheme of the sequence of events involved in CT scanning and postprocessing to create surface models for measurement. The specimens are mounted in threes or fours to increase productivity, and only the head region is scanned. The scan is reconstructed to create a 3D volume made up of slices that are digital sections through the specimen. The scan is post‐processed to create isosurfaces of the bone, which can be measured using landmark‐based geometric morphometrics.

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Scan Data 228 scans were made, covering over 600 individual specimens, and totalling around 200 scanning hours. Parameters for all saved scans are given in Appendix 2. Trial and error tests indicted that for this biological material, better scans are made with high voltage (kV) and low current (µA) and for longer (low frames per second, fps) shown in Figure A1.2.

Fig. A1.2. Screen shots of the projections (top), slice (middle) and isosurface (bottom) for two scans of the same specimens. The one at 125kV 100µA and 1.4 fps clearly produces a better isosurface, indicating for this material it is better to increase the voltage and reduce the current and scan specimens for longer when they are small (resolution > 8µm).

The scans produced during the course of this PhD project are stored on four hard drives (1TB each) kept in the Lower Vertebrates collection at the Natural History Museum, London. Access to the scans by appointment only, contact Dr Mark Wilkinson ([email protected]) or Dr David Gower ([email protected]) for more information.

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Appendix 2 – HRXCT Scan Parameters A %% <% <% <% <" ',/D78 7+'(*1*) TN/)'3W@2&5345T.&UVW@2&5/1>'(043@2 &'()*(/0('1'/23452.+6*71080 &'()*(/0('1'/23452.+6*71080 C(E'3D*80D4782DE*80+30 F/0('1'/2/1>',0+D)'3 F/0('1'/2D0+D/(71/D/ B*710+60)71/2>*710+60)'@2F/0('1'/JJ5 B*710+60)71/2>*710+60)'@2F/0('1'/JJ5@2 C'4E*+*4324/710+3'3 LE'+/D)08/2 O4'()'*+*43 CQ1,/(/0('1'/ B*710+60)71/2>*710+60)'@2&'()*(/0('1'/2 &'()*(/0('1'/2S7)74/S/)''@2&5)/>0'@2 &'()*(/0('1'/2)/>0'2TL&UVW@2&57+'(*1*)2 &'()*(/0('1'/2S7)74/S/)''@2&5)/>0'@2 B*710+60)71/2D/'D/+73 H060+0*4E'32)/8/3[/88''@2H52Z7110)' R(EDEQ*4E'323'SS'80+3'3 &53452T.&UVW@2&5345T&MXCNW &53452T.&UVW@2&5345T&MCNW N/),'(/01('1'/2+'(0Z*)' %&"'('")$ &'()*+*,*-. &'()*>/>'03-. B&=!%CDE*8 F/1>'GH!$-/ FD0+D&9:$ C4/71C&G%<-/ LE'+&MCN;!!<;-/ O4'(LP&=$<<=-/ CQ1,/(/0('1'/ &71I3(/+-/ &71I3(/+-> &71I3(/+-0 &71I3(/+-Z BD/'D-/ H060+-> R3'SS-/

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Appendix 3 – Specimens used in this thesis Locality Nguru Mountains, Pemba Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Nguu Mountains, FR Mshimba's Shamba Mr. Shamba Mwalala's Mr. Shamba Mwalala's Mr. Shamba Mwalala's Mr. Ngangao Mountain Shamba Ngangao Mountain Shamba Ngangao Mountian FR Ngangao Mountian FR Ngangao Mountian FR Ngangao Mountian FR Mkungwe,Uluguru Mts, Uluguru N Mkungwe,Uluguru Mts, Uluguru N Mkungwe,Uluguru Mts, Uluguru N FR Kuzizumbwi Uluguru Uluguru Uluguru Uluguru Uluguru Uluguru TL 203 198 205 240 225 195 190 157 205 275 258 200 298 325 290 290 303 288 290 115 165 225 177 185 185 175 168 170 455 510 175+ F F F F F F F F F F F F F M M M M M M M M M M M M M Sex other ID ID MW 7253 MW 6578 MW 6624 MW 6625 MW 6632 BMNH 2002.975 BMNH 2002.976 BMNH 2002.977 BMNH 2002.978 BMNH 2002.103 BMNH 2002.105 BMNH 2002.106 BMNH 2002.107 BMNH 2002.109 BMNH 2002.110 BMNH 2002.111 BMNH 2002.114 BMNH 2002.118 BMNH 2002.120 BMNH 2005.214 BMNH 2005.215 BMNH 2005.216 BMNH 2005.996 MW 6764 MW 6766 MW 6767 MW 6768 MW 6779 MW 6785 G656 MW 2401 Taxon

Boulengerula sp. (Nguru) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. (Nguu) Boulengerula sp. Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula taitanus Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Boulengerula ulugurensis Caecilia albiventris Caecilia albiventris

160

Locality Andagoya, s.Colombia Andagoya, s.Colombia Andagoya, s.Colombia Andagoya, s.Colombia Andagoya, Cayenne Surinam Maccasseema, Brit.Guiana Surinam FG FG Brasil Brasil Brasil Colombia Lisa, Codonto, Pena Colombia Lisa, Codonto, Pena W.Ecuador R.San Juan, Colomb Choco Novita, N.W.Ecuador St.Javier, Ecuador Paramba, Ecuador R.Lita, N.W. Ecuador Chiriboga, W.Andes Milligalli, Ecuador W.Ecuador French Guiana French Guiana French Guiana French Guiana French Guiana French Guiana TL 500 446 422 393 374 460 435 660 332 456 300 460 460 485 320 255 627 720 985 627 595 465 806 860 533 515 752 610 539 622 460+35 F F F F F F F F F M M M M M M M M M M M M M M M M Sex other ID RR 1946.9.5.12 RR 1946.9.5.14 RR 1946.9.5.9 RR 1946.9.5.52 RR 1946.9.6.83 ID V2101 BMNH 191510.21.75 BMNH 191510.21.76 BMNH 1916.4.25.31 BMNH 1916.4.25.32 (BM)111.1.1.1b BMNH 1858.6.1.38 BMNH 1866.8.14.341 BMNH 1887.1.22.30 BMNH 70.3.10.58 MW 5673 MW 5693 MZUSP 135285 MZUSP 135286 MZUSP 135287 BMNH 1913.11.12.131 BMNH 1913.11.12.132 BMNH 60.6.16.85 BMNH 1910.77.11.72 BMNH 1901.3.29.67 BMNH 98.3.37 BMNH 1901.3.29.88 BMNH 1940.2.20.13 BMNH 85.2.23.14 BMNH 60.6.16.87 MW 3945 MW 3947 MW 3951 MW 4099 MW 5138 MW 5817 Taxon

Caecilia albiventris Caecilia dunni Caecilia dunni Caecilia dunni Caecilia dunni Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia gracilis Caecilia guntheri Caecilia guntheri Caecilia guntheri Caecilia nigricans Caecilia nigricans Caecilia nigricans Caecilia nigricans Caecilia pachynema Caecilia pachynema Caecilia pachynema Caecilia tentaculata Caecilia tentaculata Caecilia tentaculata Caecilia tentaculata Caecilia tentaculata Caecilia tentaculata 161

Locality Malaya Rio Coqueta Cauca Valley, Colombia Rio Coqueta Cauca Valley, Villeta, Colombia Malaysia Borneo, Sarawak, bungalow,Perak, Larut Hills, nr.Maxwells (peninsular) Malaysia West W.Malaysia G.Benom, Pahang, Brazil Brazil Brazil Brazil Brazil Brazil Brazil Brazil Espirito Santo Brazil Carugatatuba Brazil Tijuca nr. Sta. Catharina, S.Brazil Joinville, St.Catherina Cameroon Cameroon Cameroon Chiriqui Panama mexico mexico coast Guatemala Pacific Finca Santa Julia, Guatemala Finca Santa Julia, Guatemala TL 750 975 205 169 305 420 330 340 245 350 325 335 320 260 345 238 350 195 333 315 360 275 275 265 340 410 320 450 440 415 F F F F F F F M M M M M M M M ?F Sex other ID RR 1947.2.13.86 RR 1947.2.13.84 RR 1946.9.5.33 ID BMNH 1902.5.29.179 BMNH 1902.5.15.26 MW 3789 BMNH 98.9.22.208 ZRC1.10593 BMNH 1967.2775 UKMMZ 1247 ZMUC.R0234 ZMUC.R0268 MW 15 MW 16 MW 20 MW 23 MW 24 MW 26 MW 6475 MNRJ 18644 MNRJ 870 4021 BMNH 1930.4.3.1 BMNH 1907.8.28.1 NHMW 14859 MW 5739 MW 5741 BMNH 1901.12.19.137 (BMNH)111.1.2.2.a (BMNH)111.1.2.2.b BMNH 1864.1.26.397 MVZ 179246 MVZ 179395 Taxon

Caecilia thompsoni Caecilia thompsoni Caudacaecilia asplenia Caudacaecilia larutensis Caudacaecilia larutensis Caudacaecilia nigroflava Caudacaecilia sp. Chthonerpeton braestrupi Chthonerpeton exile Chthonerpeton indistinctum Chthonerpeton indistinctum Chthonerpeton indistinctum Chthonerpeton indistinctum Chthonerpeton indistinctum Chthonerpeton indistinctum Chthonerpeton sp.A Chthonerpeton sp.B Chthonerpeton sp.B Chthonerpeton sp.C Chthonerpeton viviparum Chthonerpeton viviparum Crotaphatrema bornmuelleri Crotaphatrema lamottei Crotaphatrema lamottei Dermophis gracilior Dermophis mexicanus Dermophis mexicanus Dermophis mexicanus Dermophis mexicanus Dermophis mexicanus 162

Locality Coast Intac, Ecuador n.w.Ecuador Santo Domingo de los Colorados, Medellin, Andes of Colombia E. Peru Marcapata Valley, British Guyana? British Guyana? Ghats) (Western Kerala Peak, Periah Ghats) (Western Kerala Peak, Periah Ghats) (Western Kerala Periah, Assam, India (NE India) Assam, India (NE India) Assam, India (NE India) Ghats Southern tip of Western Ghats Southern tip of Western Ghats Southern tip of Western Ghats Southern tip of Western Labe, French Guinea Ashanti Kumasi, Obuasi, S.Ashanti Obuasi, S.Ashanti Gold Navlongo Vall, Bawhu, Upper White Volta Cape Mt.Liberia Grand Liberia Cote D'Ivoire Africa West Gaboon Ghana TL 230 300 310 208 320 205 325 175 165 155 212 173 177 199 182 195 164 220 360 270 170 320 270 185 192 210 160 230 225 F F F F F F F F F F M M M M M M M M Sex other ID RR 1946.9.5.66 RR 1946.9.5.61 RR 1946.9.5.64 RR 1946.9.5.65 RR 1946.9.5.54 RR 1946.9.5.69 RR 1946.9.5.39 RR 1946.9.5.40 RR 1946.9.5.34 RR 1946.9.5.37 RR 1946.9.5.36 RR 1946.9.5.56 RR 1946.9.6.84 ID BMNH 78.1.25.48 MNHG 2554.47 BMNH 1956.1.15.87 BMNH 1897.11.12.23 BMNH 1946.9.5.63 ROM 35126 ROM 38113 BMNH 1874.4.29.453 BMNH 1874.4.29.454 MW 295 DU SDB 1304 DU SDB 1306 DU SDB 1307 MW 581 MW 582 MW 598 MW 610 BMNH 1909.2.23.10 BMNH 1907.10.25.10 BMNH 1917.4.13.33-35 BMNH 1917.4.13.33-36 BMNH 1927.9.27.164 BMNH 1935.9.2.67 BMNH 1935.9.2.68 MW 6270 SMNS 9640 BMNH 1867.10.3.14 BMNH 1885.2.18.4 DRC 0103 Taxon

Epicrionops bicolor Epicrionops lativittatus Epicrionops marmoratus Epicrionops parkeri Epicrionops peruvianus Epicrionops sp.A Epicrionops sp.B Gegeneophis carnosus Gegeneophis carnosus Gegeneophis carnosus Gegeneophis fulleri Gegeneophis fulleri Gegeneophis fulleri Gegeneophis ramaswamii Gegeneophis ramaswamii Gegeneophis ramaswamii Gegeneophis ramaswamii Geotrypetes angeli occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini occidentalis Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini 163

Locality Gabon Cameroon Cameroon Cameroon Cameroon Cameroon Cameroon Guinea Silhouette Id Seychelles Silhouette Id Seychelles Frigate Id Seychelles Frigate Id Seychelles Mahe, Seychelles Mahe Island prob. Seychelles, Granitic Seychelles Granitic Seychelles Granitic Seychelles Granitic Seychelles Granitic Seychelles Praslin, Ferdernand, Fond Seychelles Granitic Costa Rica Cariblanco, Nicaragua San Ramon, Belize upper Raspaculo, Belize ?upper Raspaculo, Cameroon Cameroon Cameroon Cameroon Cameroon Cameroon 65 TL 170 195 240 230 250 200 230 257 240 250 260 220 112 170 185 140 130 155 145 460 180 285 145 270 310 345 350 425 320 390 F F F F F F F M M M M M M M M ?F hg Sex other ID RR1946.9.5.24 ID MOR P613 MW 4543 MW 5571 MW 5580 MW 5581 MW 5701 MW 5702 MOR 4 BMNH 1907.10.15.143 BMNH 1907.10.15.144 BMNH 1956.1.13.38 BMNH 1956.1.13.39 BMNH 1910.3.18.84 BMNH 1987.2109 BMNH 1987.2111 BMNH 1987.2112 BMNH 1987.2115 BMNH 1987.2116 BMNH 1977.353 BMNH 1987.2110 BMNH 1907.10.9.10 BMNH 1908.5.29.122 BMNH 87.4.12.12 BMNH 1992.509 no tag ('Cope') MW 4532 MW 4534 MW 4596 MW 4601 MW 4608 MW 6425 Taxon

Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes seraphini Geotrypetes sp. alternans Grandisonia alternans Grandisonia alternans Grandisonia alternans Grandisonia brevis Grandisonia brevis Grandisonia larvata Grandisonia larvata Grandisonia larvata Grandisonia larvata Grandisonia sechellensis Grandisonia sechellensis Grandisonia Gymnopis multiplicata Gymnopis multiplicata Gymnopis multiplicata Gymnopis syntrema Gymnopis syntrema Herpele squalostoma Herpele squalostoma Herpele squalostoma Herpele squalostoma Herpele squalostoma Herpele squalostoma 164

Locality Silhouette Id Seychelles Silhouette Id Seychelles Silhouette Id Seychelles Silhouette Id Seychelles Silhouette Id Seychelles Silhouette Id Seychelles N Thailand Valley, Me Wang Thailand Muang Leip, Thailand Valley, Meang, Mea Wang Pa Thailand Valley, Meang, Mea Wang Pa China Yunnan, China Yunnan, China Yunnan, China Yunnan, China Yunnan, India W.Ghats, Periyar, India W.Ghats, Periyar, India Thalapuzha 2, W.Ghats, India W.Ghats, Periyar, India Biseli, W.Ghats, India Biseli, W.Ghats, Matang, N.Borneo India W.Ghats, Travancore? Neduvangaad, India Kerala, Nadu, India Tamil Nadu, India Tamil Province Bombay Surat Waghei Vietnam Vietnam Dao, District, Tam Vinh Yen Vietnam Dao, District, Tam Vinh Yen TL 225 245 240 255 234 287 205 205 218 170 274 305 293 301 246 237 215 230 216 239 211 290 250 494 270 215 325 320 280 410 388 F F F F F F F F F F F F M M M M M M M M M M M? M? M? Sex other ID ID UMMZ 179847 UMMZ 179848 UMMZ 179853 UMMZ 179854 UMMZ 179855 UMMZ 179870 BMNH 1921.4.1.338 BMNH 1961.2055 BMNH 1961.2056 BMNH 1961.2057 UMMZ 205167 UMMZ 205169 UMMZ 205186 UMMZ 205194 UMMZ 205200 MW 273 MW 276 MW 288 MW 291 MW 460 MW 489 ZMB 9830 BMNH 72.2.19.59A BMNH 94.3.15.3 MW 1463 MW 1471 MW 441 BMNH 88.6.11.1 A.M. Herp 48938 MVZ 224080 MVZ 224082 Taxon

Hypogeophis rostratus Hypogeophis rostratus Hypogeophis rostratus Hypogeophis rostratus Hypogeophis rostratus Hypogeophis rostratus acuminatus Ichthyophis acuminatus Ichthyophis acuminatus Ichthyophis acuminatus Ichthyophis bannanicus Ichthyophis bannanicus Ichthyophis bannanicus Ichthyophis bannanicus Ichthyophis bannanicus Ichthyophis beddomei Ichthyophis beddomei Ichthyophis beddomei Ichthyophis beddomei Ichthyophis beddomei Ichthyophis beddomei Ichthyophis beddomei Ichthyophis biangularis Ichthyophis bombayensis Ichthyophis bombayensis Ichthyophis bombayensis Ichthyophis bombayensis Ichthyophis bombayensis Ichthyophis laosensis cf. Ichthyophis bannanicus cf. Ichthyophis bannanicus cf. Ichthyophis 165

Locality Lanka, District, Sri Lanka District, Sri Lanka District, Sri Lanka District, Sri Lanka Vietnam near Haldummula, Badulla Welegama, near Haldummula, Badulla Welegama, near Haldummula, Badulla Welegama, near Haldummula, Badulla Welegama, Na Sa Beng, NE Thailand Na Sa Beng, NE Thailand Na Sa Beng, NE Thailand Na Sa Beng, NE Thailand Na Sa Beng, NE Thailand Na Sa Beng, NE Thailand Matale District, Sri near Rattota, Kandehena, Matale District, Sri near Rattota, Kandehena, Malgalla, near Opata, Galle District, Sri Lanka Malgalla, near Opata, Galle District, Sri District, Sri Lanka, Suudagala, Ratnapura Matara Hanuford Estate, near Deniyaya, Indonesia Java, India district, Manipur, Tamenglong thailand Malaysia Sarawak, Malaysia Borneo, W. Sinkawang, Lanka Lanka District, Sri Lanka, TL 289 337 359 352 295 335 320 332 270 321 394 428 401 386 365 347 210 500 291 235 225 330+ F F F F F F F M M M M M M M Sex other ID ID VUB 697/8 BMNH 2000.348 BMNH 2000.349 MW 3833 MW 3834 AK 852 AK 853a AK 853b AK 854 AK 855 AK 856 MW 1745 MW 1749 MW 1773 MW 1775 MW 1789 MW 1792 BMNH 80.5.7.3 BNHS 5210 USNM 72293 MW 3785 BMNH 63.12.4.5 Taxon

Ichthyophis cf. bannanicus cf. Ichthyophis glutinosus cf. Ichthyophis glutinosus cf. Ichthyophis glutinosus cf. Ichthyophis glutinosus cf. Ichthyophis kohtaoensis Ichthyophis kohtaoensis Ichthyophis kohtaoensis Ichthyophis kohtaoensis Ichthyophis kohtaoensis Ichthyophis kohtaoensis Ichthyophis glutinosus Ichthyophis glutinosus Ichthyophis glutinosus Ichthyophis glutinosus Ichthyophis glutinosus Ichthyophis glutinosus Ichthyophis javanicus Ichthyophis khumhzi Ichthyophis kohtaoensis Ichthyophis monochrous Ichthyophis monochrous Ichthyophis 166

Locality Kohima District, Nagaland, India Kohima District, Sri Lanka, Aziuram village, Tamenglong district, Manipur, district, Manipur, village, Tamenglong Aziuram NE India Manipur, NE India Manipur, NE India Manipur, Badulla near Passara, Group, Cannavarella Sri Lanka Ceylon (Sri Gammaduwa, Polgahawela, Ceylon (Sri Gammaduwa, Polgahawela, sub-division, village, Tseminyu New Sendenyu Malaysia West State Park, Perlis Assam, India Thailand Tao, Ban Tung Thailand Tao, Ban Tung Thailand Tao, Ban Tung Belitung, Indonesia Belitung, Indonesia Mwe Hauk Village, Burma Mwe Hauk Village, Burma Mwe Hauk Village, Burma Burma Cambodia Siem Reap, Doi Suthep Thailand Doi Suthep Thailand Malaysia Janda Baik, West Malaysia West Jerai, Ngau, Thailand Pa Koh Lanka) Lanka) India - TL 243 287 220 241 400 235 210 308 313 250 300 205 348 130 173 375 407 416 385 225 280 310 250 242 246 F F F F F F F F F M M M Sex other ID HKV 65987 ID BNHS 5213 BNHS 5218 SDB 1512 SDB 1513 MW 1725 (BMNH) 111.1.3.1.A BMNH 1972.1853 BMNH 1972.1853A BNHS 5221 FRIM 1232 ZRC1.7707 AK 451 AK452 AK455 MW 4455 MZB 12893 CAS 212265 CAS 212266 CAS 212267 NHMW 9095 FMNH 262776 CNHM 189243 CNHM 189244 FRIM 277 JS 00167 BMNH 1969.2917 Taxon

Ichthyophis moustakius Ichthyophis moustakius Ichthyophis moustakius Ichthyophis moustakius Ichthyophis orthoplicatus Ichthyophis pseudangularis Ichthyophis pseudangularis Ichthyophis pseudangularis Ichthyophis sendenyu Ichthyophis sp. Ichthyophis (Assam) sp. Ichthyophis Tao) (Ban Tung sp. Ichthyophis Tao) (Ban Tung sp. Ichthyophis Tao) (Ban Tung sp. Ichthyophis (Belitung) sp. Ichthyophis (Belitung) sp. Ichthyophis (Burma) sp. Ichthyophis (Burma) sp. Ichthyophis (Burma) sp. Ichthyophis (Burma) sp. Ichthyophis (Cambodia) sp. Ichthyophis (Doi Suthep) sp. Ichthyophis (Doi Suthep) sp. Ichthyophis (Janada Baik) sp. Ichthyophis (Jerai) sp. Ichthyophis Ngau) Pa (Koh sp. Ichthyophis 167

Locality Koh Pa Ngau, Thailand Pa Koh Malaysia Pulau Langkawi, West Laos Nakai District, Khammouan province, Malaysia West Penang, Khao Luang, Thailand peninsular Khao Luang, Thailand peninsular India Thekkada, W.Ghats, India Thekkada, W.Ghats, India W.Ghats, Maramalai, India Thekkada, W.Ghats, India Thekkada, W.Ghats, India W.Ghats, Valley, Kallar Cameroon Cameroon Cameroon Cameroon Mamfe Dis, Cameroon Makumunu, Assumbo, Mamfe Dis, Cameroon Makumunu, Assumbo, Mamfe Dis, Cameroon Makumunu, Assumbo, Mamfe Dis, Cameroon Makumunu, Assumbo, Ghats Western Ghats Western India Gujrat, Ghats Western Ghats Western Ghats Western Ghats Western Brazil Sao Paulo, Alegre Porto Alegre Porto Alegre Porto 98 95 87 TL 216 280 285 282 277 245 205 197 174 258 246 201 125 120 115 125 103 220 175 202 240 225 213 210 330 260 295 250 F F F F F F F F M M M M M M M M M M M M Sex other ID HKV 62813 RR 1946.9.5.70 RR 1946.9.5.76 RR 1946.9.5.80 RR 1946.9.5.84 MW40 ID BMNH 1969.2918 MW 4379 FMNH 256425 AMB 6575 BMNH 1969.2915 BMNH 1969.2916 MW 183 MW 189 MW 218 MW 747 MW 752 MW 768 MW 4544 MW 4548 MW 4591 MW 5551 BMNH 1936.3.4.30-47 BMNH 1936.3.4.30-47 BMNH 1936.3.4.30-47 BMNH 1936.3.4.30-47 ZM-42 pair ZM-42 pair AMNH 89788 CM 67513 CM 67514 CM 67515 CM 90088 BMNH 2005.3 MCP 2062 MCP 2063 MCP 685 Taxon

Ichthyophis sp. (Koh Pa Ngau) Pa (Koh sp. Ichthyophis (Langkawi) sp. Ichthyophis (Laos) sp. Ichthyophis (Penang) sp. Ichthyophis supachaii Ichthyophis supachaii Ichthyophis tricolor Ichthyophis tricolor Ichthyophis tricolor Ichthyophis tricolor Ichthyophis tricolor Ichthyophis tricolor Ichthyophis russeli cf. Idiocranium russeli cf. Idiocranium russeli cf. Idiocranium russeli cf. Idiocranium russeli Idiocranium russeli Idiocranium russeli Idiocranium russeli Idiocranium Indotyphlus battersbyi Indotyphlus battersbyi battersbyi Indotyphlus cf. battersbyi Indotyphlus cf. battersbyi Indotyphlus cf. battersbyi Indotyphlus cf. battersbyi Indotyphlus cf. brasilliensis Luetkenotyphlus brasilliensis Luetkenotyphlus brasilliensis Luetkenotyphlus brasilliensis Luetkenotyphlus 168

Locality Prov Napo, Limon Cocha, Ecuador Napo, Prov Ecuador British Guyana British Guyana British Guyana British Guyana British Guyana Wineparu, Guyana Venezula Venezula Surinam British Guyana British Guyana British Guyana British Guyana British Guyana Angouleme, French Guiana Angouleme, French Guiana British Guyana British Guyana British Guyana British Guyana French Guiana French Guiana Kaw, TL 215 265 245 220 181 210 155 141 157 140 163 169 140 136 188 142 128 162 114 153 181 173 159 146 123 113 135 210 167 F F F F F F M M M M M M M M M M M Sex other ID A-58412 RR 1946.9.5.32 ID MZUSP 114589 MZUSP 114590 MZUSP 114592 MZUSP 114593 MCZ 1638 BMNH 80.12.5.147 MW red127 UMMZ 214080 UMMZ 214083 UMMZ 214085 UMMZ 214086 UMMZ 214087 BMNH 1968.1283 MBUCZ 5126 MBUCZ 5359 RMNH 26795 AMNH 166045 AMNH 166046 AMNH 166048 AMNH 166049 AMNH 166058 MZUSP 30984 MZUSP 30985 MW 5655 MW 5657 PK 1566 PK 1627 SMNS 12900 SMNS 12901 MW 5626 MNHNP 1903.30 Taxon

Luetkenotyphlus cf. brasilliensis cf. Luetkenotyphlus brasilliensis cf. Luetkenotyphlus brasilliensis cf. Luetkenotyphlus brasilliensis cf. Luetkenotyphlus Microcaecilia albiceps Microcaecilia albiceps E Microcaecilia sp. E Microcaecilia sp. E Microcaecilia sp. E Microcaecilia sp. E Microcaecilia sp. E Microcaecilia sp. Microcaecilia rabei Microcaecilia rabei Microcaecilia rabei Microcaecilia rabei A Microcaecilia sp. A Microcaecilia sp. A Microcaecilia sp. A Microcaecilia sp. A Microcaecilia sp. B Microcaecilia sp. B Microcaecilia sp. C Microcaecilia sp. C Microcaecilia sp. D Microcaecilia sp. D Microcaecilia sp. D Microcaecilia sp. D Microcaecilia sp. Microcaecilia unicolor Microcaecilia unicolor 169

Locality Kaw, French Guiana Kaw, French Guiana Kaw, French Guiana Kaw, French Guiana Kaw, Brasil Rio de Janeiro, Upper Amazon Canelos, Ecuador N.W.Ecuador St Javier. W.Ecuador Peru Carabaya, Chaquimayo, E.Ecuador Prov. Rio Oglan, Nopo Pastaza E.Ecuador Prov. Copataza R.Nopo Pastaza Panama Ancon, Panama City Panama Island, Seychelles Prasline Island, Seychelles Prasline French Guiana French Guiana French Guiana French Guiana French Guiana French Guiana Angouleme, French Guiana French Guiana TL 153 198 184 200 185 590 485 872 631 747 660 812 520 360 330 260 355 390 350 390 230 165 170 229 157 197 205 172 107 177 349 F F F F F F F F F F F F F M M M M M M M M M M ?F Sex other ID RR 1946.9.5.68 RR 1946.9.5.8 RR 1946.9.5.5 RR 1946.9.5.7 RR 1946.9.5.17 RR 1946.9.5.18 ID MNHNP 1903.32 MNHNP 1903.A31 MNHNP 1903.A32 MNHNP 1903.31 KUH 93271 BMNH 61.9.2.6 BMNH 1880.12.8.141 BMNH 1901.3.29.66 BMNH 1946.9.5.6 BMNH 1908.3.11.1 BMNH 1956.1.15.84 BMNH 1956.1.15.85 BMNH 1887.12.12.1 BMNH 1926.1.20.72 MCZ 4268 BMNH 1996.91 IRNSB 12447 IRNSB 12448 IRNSB 12449 IRNSB 12450 BMNH 1907.10.15.153 BMNH 1907.10.15.154 MW 2051 MW 2395 MW 3979 MW 3980 MW 5589 MW 5631 MW 5669 MW 5695 MZUSP 60016 Taxon

Microcaecilia unicolor Microcaecilia unicolor Microcaecilia unicolor Microcaecilia unicolor Mimosiphonops vermiculatus Nectocaecilia petersii Oscaecilia bassleri Oscaecilia bassleri Oscaecilia bassleri Oscaecilia bassleri Oscaecilia bassleri Oscaecilia bassleri Oscaecilia ochrocephala Oscaecilia ochrocephala Oscaecilia ochrocephala nicefori Parvicaecilia kaupii Potomotyphlus kaupii Potomotyphlus kaupii Potomotyphlus kaupii Potomotyphlus cooperi Praslinia cooperi Praslinia Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema bivittatum Rhinatrema ron 170

Locality Tanaznia Tanaznia Tanaznia Tanaznia Kaieteur National Park, British Guyana National Park, Kaieteur British Guyana National Park, Kaieteur Region, Pwani near Bagamoyo, Ferry, Ruvu Region, Pwani near Bagamoyo, Ferry, Ruvu Region, Pwani near Bagamoyo, Ferry, Ruvu Region, Pwani near Bagamoyo, Ferry, Ruvu nr Witu, Kenya Peccatoni, nr Witu, Kenya Peccatoni, Ngatana, E.Africa forest below Largoa Amelia, Sao Tome forest below Largoa Amelia, Sao Tome forest below Largoa Amelia, Sao Tome Sao Tome Carnival, Sao Tome Carnival, Alegre, Sao Tome Porto Reserve Sali Forest Reserve Sali Forest Uluguru Mountians Uluguru Mountians, Tanzania Mountains Rubeho Kilombero Scarp FR, Tanzania West Kilombero Scarp FR, Tanzania West Kilombero Scarp FR, Tanzania West Kilombero Scarp FR, Tanzania West Uluguru Mountians, Tanzania FR, North Pare Kindoroko FR, North Pare Kindoroko TL 151 184 295 355 330 295 300 296 285 250 350 355 175 180 280 345 380 305 230 315 395 345 215 160 310 195 233 F F F F F F F F F F F F F M M M M M M M M M M Sex other ID IRSNB 1991 IRSNB 1994 RR 1946.9.5.53 ID PK 1569 PK 1656 BMNH 2005.1400 BMNH 2005.1412 BMNH 2005.1419 BMNH 2005.1421 MCZ 20143 MCZ 20150 BMNH 95.11.15.3 BMNH 2000.302 BMNH 2000.308 BMNH 2000.310 BMNH 2000.320 BMNH 2000.321 BMNH 2000.333 BMNH 2005.1387 BMNH 2005.1388 BMNH 2005.168 BMNH 2005.172 BMNH 2005.312 BMNH 2005.890 BMNH 2005.893 BMNH 2005.894 BMNH 2005.895 BMNH 2005.169 BMNH 2005.955 BMNH 2005.956 Taxon

Rhinatrema shiv Rhinatrema shiv Schistometopum gregorii Schistometopum gregorii Schistometopum gregorii Schistometopum gregorii Schistometopum gregorii Schistometopum gregorii Schistometopum gregorii Schistometopum thomense Schistometopum thomense Schistometopum thomense Schistometopum thomense Schistometopum thomense Schistometopum thomense Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii Scolecomorphus kirkii 1 Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 171

Locality Kindoroko FR, North Pare Kindoroko FR, North Pare Kindoroko FR, North Pare Kindoroko FR, North Pare Kindoroko FR, North Pare Kindoroko FR, North Pare Kindoroko Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Chome FR, South Pare Nilo FR Nilo FR Nilo FR Nilo FR Nilo FR Nilo FR Mgambo F.R. Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains Nguu Mountains TL 295 288 235 217 205 285 280 250 320 218 300 255 270 320 355 287 306 152 421 288 290 275 330 380 352 280 275 320 280 342 310 F F F F F F F F F F F F F F F M M M M M M M M M M M M M M M M Sex other ID ID BMNH 2005.959 BMNH 2005.963 BMNH 2005.967 BMNH 2005.969 BMNH 2005.972 BMNH 2005.984 BMNH 2005.902 BMNH 2005.906 BMNH 2005.907 BMNH 2005.909 BMNH 2005.911 BMNH 2005.912 BMNH 2005.913 BMNH 2005.914 BMNH 2002.855 BMNH 2002.857 BMNH 2002.858 BMNH 2002.859 BMNH 2002.873 BMNH 2002.878 BMNH 2002.894 BMNH 2002.968 BMNH 2002.980 BMNH 2002.981 BMNH 2002.982 BMNH 2002.984 BMNH 2002.985 BMNH 2002.986 BMNH 2002.988 BMNH 2002.989 BMNH 2002.990 Taxon

Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 3 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 4 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 5 Scolecomorphus sp. 172

Locality Ikwamba F.R., Ukaguru Mts F.R., Ikwamba Ukaguru Mts F.R., Ikwamba Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Nguru FR Tanzania Uluguru Mts., Nyingwa, Uluguru Mountians, Tanzania Uluguru Mountians, Tanzania Muheza Kwamkoro, Amani Nature Reserve, Muheza Kwamkoro, Amani Nature Reserve, Nilo FR Nilo FR Nilo FR Nilo FR Nilo FR Nilo FR E.Ecuador Prov. Bopataze R. Napo Pastaza E.Ecuador Prov. Bopataze R. Napo Pastaza Espirito Santo Brazil District, Tanga Region, Tanzania Tanzania Region, District, Tanga Tanzania Region, District, Tanga TL 195 188 238 245 270 230 245 225 240 295 235 255 235 240 315 260 210 223 273 184 208 243 225 360 375 370 325 405 185 F F F F F F F F F F F F M M M M M M M M M M M M Sex other ID RR 1946.9.5.57 ID BMNH 2005.1537 BMNH 2005.1539 MW 7056 MW 7060 MW 7062 MW 7063 MW 7066 MW 7069 MW 7072 MW 7073 MW 7077 MW 7086 BMNH 1937.8.17.1 BMNH 2002.99 BMNH 2005.170 BMNH 2000.512 BMNH 2002.100 BMNH 2002.861 BMNH 2002.870 BMNH 2002.871 BMNH 2002.872 BMNH 2002.875 BMNH 2002.877 BMNH 1956.1.15.88 BMNH 1956.1.15.89 BMNH 2005.9 MZUSP 133017 MZUSP 133018 MZUSP 133019 Taxon

Scolecomorphus sp. 6 Scolecomorphus sp. 6 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. 7 Scolecomorphus sp. Scolecomorphus ulugurensis Scolecomorphus ulugurensis Scolecomorphus ulugurensis Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Scolecomorphus vittatus Siphonops annulatus Siphonops annulatus Siphonops annulatus paulensis Siphonops cf. paulensis Siphonops cf. paulensis Siphonops cf. 173

Locality Espirito Santo Brazil Espirito Santo Brazil Espirito Santo Brazil Alto Paraguay Primavera, Loma Ghoby, Alto Paraguay Primavera, Loma Ghoby, Alto Paraguay Primavera, Loma Ghoby, Ceplac Ceplac Ceplac Ceplac French Guiana French Guiana French Guiana French Guiana Colombia Colombia Colombia Colombia Colombia Colombia Venezuela Venezuela Venezuela Venezuela Venezuela Venezuela 98 90 80 TL 320 360 165 142 170 400 350 395 197 153 166 210 275 285 305 255 460 395 430 320 300 375 385 280 370 300 410 340 F F F F F F F F F F F M M M M M M M M M M M Sex other ID ID MZUSP 133026 MZUSP 133027 BMNH 2005.5 BMNH 2005.7 BMNH 2005.8 CZlarge CZsmall no tag BMNH 1956.1.1.72 BMNH 1956.1.1.73 BMNH 1956.1.1.75 MZUSP 133020 MZUSP 133022 MZUSP 133024 MZUSP 133025 MW 5835 MW 5818 MW 5820 MW 5838 MW 5055 MW 5056 MW 5057 MW 7331 MW 7332 MW 7342 MW 787 MW 793 MW 794 MW 795 MW 798 MW 799 Taxon

Siphonops cf. paulensis Siphonops cf. paulensis Siphonops cf. Siphonops hardyi Siphonops hardyi Siphonops hardyi Siphonops hardyi Siphonops hardyi Siphonops hardyi Siphonops paulensis Siphonops paulensis Siphonops paulensis A Siphonops sp. A Siphonops sp. A Siphonops sp. A Siphonops sp. compressicauda Typhlonectes compressicauda Typhlonectes compressicauda Typhlonectes compressicauda Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes natans Typhlonectes 174

Locality Coimbatore Dist (India Madras) nr. Kondotti nr. Kondotti Payyanur Cherat, Payyanur Cherat, Payyanur Cherat, Payyanur Cherat, Payyanur Cherat, Payyanur Cherat, India Malabar, India Malabar, Malabar Coast', Southern peninsular India Anamallai Hills Estate Lalpari P.o Iryiparai India Malabar, India Kerala, Kannam, Chittadi Estate Manangallor India Kerala, Travancore, Kottayam, Sabari Hills, Vandiperiyar India Malabar, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, India Ernakulam, Kerala, Muvattupuzha, Azhukkamoozhi, Kattalakada TL 239 210 215 190 212 186 256 210 230 217 144 179 232 240 185 194 230 191 256 188 203 225 232 205 240 207 224 192 188 183 F F F F F F F F F F F F F F F F F F M M M M M M M M M M Sex other ID RR 1949.9.5.16 RR 1946.9.5.55 ID MW 1654 MW 2504 MW 456 MW 476 MW 479 MW 483 MW 487 MW 454 BMNH 80.12.12.14 BMNH 80.12.12.16 BMNH 1874.4.29.181 BMNH 1950.1.4.81 BMNH 80.12.12.17 MW 1416 MW 309 MW 326 BMNH 1940.1.5.1 MW 1711 MNHNP 1994.419 MW 718 MW 726 MW 730 MW 735 MW 738 MW 740 MW 715 MW 716 MW 720 MW 721 MW 1311 Taxon

Uraeotyphlus cf. menoni cf. Uraeotyphlus menoni cf. Uraeotyphlus oxyurus cf. Uraeotyphlus oxyurus cf. Uraeotyphlus oxyurus cf. Uraeotyphlus oxyurus cf. Uraeotyphlus oxyurus cf. Uraeotyphlus oxyurus cf. Uraeotyphlus gansi Uraeotyphlus gansi Uraeotyphlus malabaricus Uraeotyphlus malabaricus Uraeotyphlus malabaricus Uraeotyphlus narayani Uraeotyphlus narayani Uraeotyphlus narayani Uraeotyphlus narayani Uraeotyphlus oommeni Uraeotyphlus oxyurus Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus 175

Locality India India India India Azhukkamoozhi, Kattalakada Perakkonam near Konni Aruvabullam, India Kerala Periah, India Kerala Periah, India Kerala, Kottayam, Kottayam, India Kerala, Kottayam, Kottayam, Kattayad India Kerala, Kottayam, Kottayam, near Thodupuzha, Kerala, Peralamattayam, near Thodupuzha, Kerala, Peralamattayam, near Thodupuzha, Kerala, Peralamattayam, near Thodupuzha, Kerala, Peralamattayam, India Thodupuzha, Kerala India Thodupuzha, Kerala b Valparai nr. a Valparai nr. a Valparai nr. Ooruvasal Ooruvasal India Malabar, TL 184 187 281 255 194 218 209 230 192 226 208 187 226 195 203 235 195 196 230 215 185 F F F F F F F M M M M M M M M M Sex other ID ID MW 1312 MW 1528 MW 1566 MW 259 MW 263 MW 206 MW 207 MW 210 MW 225 MW 1353 MW 1356 MW 1357 MW 1358 MW 427 MW 431 MW 2115 MW 2434 MW 2449 MW 2451 MW 2492 BMNH 80.12.12.15 Taxon

Uraeotyphlus sp. A sp. Uraeotyphlus A sp. Uraeotyphlus A sp. Uraeotyphlus B1 sp. Uraeotyphlus B1 sp. Uraeotyphlus B2 sp. Uraeotyphlus B2 sp. Uraeotyphlus B2 sp. Uraeotyphlus B2 sp. Uraeotyphlus C sp. Uraeotyphlus C sp. Uraeotyphlus C sp. Uraeotyphlus C sp. Uraeotyphlus C sp. Uraeotyphlus C sp. Uraeotyphlus D sp. Uraeotyphlus D sp. Uraeotyphlus D sp. Uraeotyphlus E sp. Uraeotyphlus E sp. Uraeotyphlus X sp. Uraeotyphlus 176

Locality TL Sex Museum National d’Histoire Naturelle, Laboratoire des Museum National d’Histoire Naturelle, Laboratoire Staatliches Museum für Naturkunde Stuttgart (SMNS) Bombay Natural History Society (BNHS) Natural Bombay Field tag of Alex Kupfer (AK) Field tag of Alex Kupfer Forest Research Institute Malaysia (FRIM) Institute Malaysia Research Forest Raffles Museum of Biodiversity Research (ZRC) Research Museum of Biodiversity Raffles Brazil. (MZUSP), Brazil. Field tag of Mark Wilkinson (MW) Amphibiens et Reptiles, Paris, France. (MNHNP). France. Paris, Amphibiens et Reptiles, Natural History Museum Vienna (NHMW) Natural ---- Field tag of Philippe Kok (PK) Field tag of Philippe Kok Universidade de São Paulo, Museu de Zoologia, São Paulo, São Paulo, Museu de Zoologia, de São Paulo, Universidade Field tag of Delhi University SDB (DU SDB) Field tag of Delhi University Carnegie Museum of Natural History (CM) Carnegie Museum of Natural Museu Nacional Rio de Janeiro (MNRJ) Smithsonian Institution National Museum of Natural History Smithsonian Institution National Museum of Natural Field tag of Jeetsukumaran (JS) Field tag of Jeetsukumaran Field tag of Mark-Oliver Rödel (MOR) Field tag of Mark-Oliver (USNM) Australian Museum (AM Herp) Australian other ID ID Taxon University of Kansas, Museum of Natural History, Division of Herpetology, Division of Herpetology, History, Museum of Natural of Kansas, University American Museum of Natural History (AMNH), American Museum of Natural Museum of Vertebrate Zoology, Berkley (MVZ), Zoology, Museum of Vertebrate The State Museum of Natural History Stuttgart (SMNS), The State Museum of Natural Raffles Museum of Biodiversity Research (ZRC), Research Museum of Biodiversity Raffles California Academy of Sciences, Department of Herpetology, San Francisco San Francisco of Sciences, Department Herpetology, California Academy Museum fur Naturkunde, Berlin (ZMB), Naturalis Nationaal Natuurhistorisch Museum Leiden (RMNH), Naturalis Vrije Universiteit Brussel (VUB), Vrije Universiteit Museum of Comparative Zoology, Harvard University (MCZ ), University Harvard Zoology, Museum of Comparative Naturhistorisches Museum, Zoologische Abtheilung (NHMW), Naturhistorisches Museum, Zoologische Specimens from the following institutes: Museu de Ciências e Tecnologia da PUCRS, Porto Alegre, Brazil (MCP), Alegre, Brazil Porto da PUCRS, Museu de Ciências e Tecnologia Field Museum, Division of Amphibians and Reptiles, Chicago (FMNH), Field Museum, Division of Amphibians and Reptiles, Natural History Museum, London UK (BMNH), Natural Museum of Natural History, Gothenburg (MNHG), History, Museum of Natural Zoologisk Museum, Københavns Universitet (ZMUC), Universitet Museum, Københavns Zoologisk Lawrence, Kansas (KUH), Institut Lawrence, Kansas Royal des Sciences Naturelles de Belgique, Bruxelles (IRSNB), des Sciences Naturelles de Belgique, Bruxelles Royal Royal Ontario Museum (ROM), Royal (CAS), 177

Appendix 4 ‐ Landmarks used in this thesis Cranium: All landmarks described are for left and right sides except 19, 42, 43 and

46 that are unpaired on the midline. Asterix (*) indicates paired landmarks along the midline either side of wide sutures.

Number Anatomical description 1 & 2 Anteromedial edge of nares, on nasal bones. Anterior suture of premaxila/nasopremaxilla (n.pmx), where left and right n.pmx *3 & 4 tooth rows meet. Anterior corner of maxillopalatine (max.p), where left and right max.p. tooth row 5 & 6 begin. Posteriomedial edge of nares, on the septomaxilae when present, otherwise on 7 & 8 nasal bones. 9 & 10 Posterior end of vomerine tooth row. 11 & 12 Posterior end of maxillopalatine, where skull widens for lower temporal fossa. 13 & 14 Posterior tip of vomers projecting over the parasphenoid. 15 & 16 Anteriolateral point on processus ascendens of the quadrate. Widest point of os basale, medially situated on otic capsule, on basipterygoid 17 & 18 process. 19 Intersection of nasal and frontal bones. Parietal ridge, either side of suture between parietals (muscle scar for m. cutaneous *20 & 21 dorsalis and M. depressor mandibulae) *22 & 23 Dorsomedial edge of foramen magnum. 24 & 25 Lateral edge of foramen magnum, above occipital condyles. 26 & 27 Lateral edge of occipital condyles 28 & 29 Posteriolateral corner of frontals where they contact parietals. 30 & 31 Posteriolateral corner of parietal, by otic capsule. 32 & 33 Posterior point on processus ascendens of the quadrate. Anteriodorsal edge of orbital foramen, on the sphenethmoid (point of insertion for 34 & 35 cartilage taenia marginalis dorsalis) 36 & 37 Anterior edge of exterior foramina for jugular nerve. Posterioventral edge of orbital foramen, on the pleurosphenoid portion of the os 38 & 39 basale (point of insertion for cartilage taenia marginalis ventralis) 40 & 41 Dorsal point of squamosal ridge (muscle scar for M. depressor mandibulae insertion) 42 Posterior projection of infraorbital extension of the sphenethmoid Medial of sphenethmoid on posterior side, between the olfactory nerve (Id and Iv) 43 foramina 44 & 45 Anterior edge of external foramina for carotid artery. 46 Ventromedial edge of foramen magnum 47 & 48 Posterior edge of foramen ovale for the stapes 49 & 50 Anteriolateral point on stapedial process, by contact with quadrate. 51 & 52 Anterior edge of orbital foramina, on the sphenethmoid, where foramen is widest. Posterior inflexion point where maxillopalatine splits to surround the choanae, 53 & 54 where when present, pterygoid contacts max.p. 55 & 56 Posterior end of maxillopalatine inner tooth row. Lateral edge of left and right olfactory (Iv) nerve foramina on posterior side of 57 & 58 sphenethmoid. *59 & 60 Anteriomedial suture of vomers, where vomerine tooth rows meet.

178

Atlas: 7 paired landmarks of left and right and 6 unpaired midline landmarks.

Number Anatomical description 1 Midpoint of the posterior neural arch 2&3 Posterioventral corner of the post‐zygapophyses 4 Dorsomedial edge of the foramen vertebrale 5 Most dorsomedial point on edge of the centrum 6&7 Most lateral point on edge of the centrum 8 Most ventromedial point on edge of the centrum Anterior‐most ventral edge of post‐zygapophyses, where it meets the body of the 9&10 atlas 11&12 Lateral edge of foramen vertebrale where it meets the condyles 13 Most ventral point of the foramen vertebrale, between the cotyles 14 Lateromedial point between the cotyles 15&16 Ventral most edge of the right cotyle and left cotyle respectively 17&18 Most lateral point on edge of the cotyles 19&20 Anterior edge of hypoglossal nerve foramen within the foramen vertebrale

Mandible: All landmarks described are for one hemi‐mandible.

Number Anatomical description Anterior corner of pseudodentary (pd) on palatal side, adjacent to midline joint 1 between hemimandibles Anterior edge of inner mandibular tooth series (when present), else posterior 2 corner of pd, adjacent to midline joint between hemimandibles Lateral edge of pd on palatal side, inline with posterior‐most extent of midline joint 3 between hemimandibles 4 Posterior‐most point of pd on palatal side (end of tooth row) 5 Anterior edge of canalis primordialis of the pseudoarticular (pa) Lateral edge of groove for the quadrate (cranium), anterior to the processus 6 condyloides of the pa 7 Most posteriodorsal point of retroarticular process 8 Most posterior projection of pd. on lateral side 9 Ventral edge of retroarticular process at point of inflexion 10 Medial point on processus internus of the pa 11 Anterior edge of pd nerve foramen on internal side of pd Posterior edge of pd on ventral side, adjacent to midline joint between 12 hemimandibles 13 Anterior edge of foramen for the exit of the ramulus intermandibularis

179