The Ancient Biogeography of the Old World Fruit Bats (Family Pteropodidae)

Christina Ravinet

A thesis submitted in partial fulfilment of the requirements for the degree of Master of Science and Diploma of Imperial College

Abstract

Ancient biogeography seeks to determine the events that have shaped the distribution of species over large time- and spatial-scales. Little is known about the biogeographic history of the Old World fruit bats (Family Pteropodidae) due to a highly underrepresented fossil record and conflicting results of the few previous results. A species-level phylogeny of the Pteropodidae was obtained from the supertree of Jones et al. (2002); this section of the supertree is extremely unresolved so was updated for use in the present study. Both the original and the updated Pteropodidae supertrees were implemented in Lagrange, a maximum-likelihood method for reconstructing biogeographic history. This method has been developed fairly recently so an alternative method, dispersal-vicariance analysis (DIVA), was also used. Biogeographic realms were used as geographic divisions and Lagrange calculated IndoMalay and Australasia as the most likely ancestral range of the Pteropodidae. From this ancestral range there have been a number of dispersal events into the Afrotropics, Oceania and the Palearctic. Exact dispersal routes are unknown but those into the Afrotropics and Oceania would have required traversing large distances over water and so may have been aided by winds or rafting. Further investigations are required to confirm the findings and to provide a more detailed scenario for Pteropodidae biogeography. In comparison to Lagrange, DIVA underestimates both dispersal and vicariance but, in general, the two methods inferred relatively similar biogeographic histories. La- grange, however, offers a more promising method for future investigations due to the potential advantage of model parameterization.

Table of Contents Abstract ...... ii 1. Introduction ...... 1 1.1 Biogeography and the Old World fruit bats (Pteropodidae) ...... 1 1.2 Biogeographic analysis ...... 3 1.3 Aims and Objectives ...... 6 2. Methods ...... 8 2.1 Pteropodidae supertree construction ...... 8 2.2 Outgroups ...... 9 2.3 Range data ...... 11 2.4 Biogeographic analysis ...... 12 2.4a Species-level analysis in Lagrange ...... 12 2.4b Species-level analysis in DIVA ...... 13 3. Results ...... 14 3.1 Pteropodidae supertree ...... 14 3.2 Biogeographic analysis ...... 15 3.2a Lagrange ...... 15 3.2b DIVA ...... 25 4. Discussion ...... 29 4.1 Biogeographic history of the Pteropodidae ...... 29 4.2 Comparison of methods...... 31 4.3 Limitations and future investigations ...... 32 6. Acknowledgements ...... 35 7. References ...... 36 8. Appendices ...... 40 Appendix 1 – Pteropodidae supertree construction ...... 40 Appendix 2 – Species range matrices ...... 42 Appendix 3 – Literature sources used in Pteropodidae supertree construction ...... 50 Appendix 4 – Lagrange results (a) ...... 52 Appendix 5 – Lagrange results (b) ...... 55 Appendix 6 – DIVA results ...... 62

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1. Introduction

1.1 Biogeography and the Old World fruit bats (Pteropodidae)

The pressing need to determine how species may react to environmental change has driven an increased interest in explaining current patterns of biodiversity (Gaston, 2000). Species are not distributed evenly across the Earth’s surface but instead are more abundant in some areas whilst being rarer in others (Gaston, 2000). The most famous pattern of distribution is the latitudinal gradient, where biodiversity is greatest at the equator and decreases as latitude increases (e.g. Brown & Lo- molino, 1998). Explaining why it is that particular species are found where they are, and indeed why there are as many species as there are, requires the study of biogeography, a science concerned with the distribution of organisms through both space and time (Cox & Moore, 2005; Wiens & Donoghue, 2004). Historical, or ancient , biogeography aims to explain the events that have shaped distributions over large temporal- and spatial-scales whilst ecological biogeography is concerned with the abiotic and biotic factors that do this over much shorter time-scales (Cox & Moore, 2005; Kodandaramaiah, 2009). Understanding why species were able to successfully establish in some places but not in others could provide an important insight into how species will cope in the future as humans continue to modify and destroy habitats (Cox & Moore, 2005).

Figure 1. Paleogeographic map of the Earth, showing the position of land masses as they were 40 million years ago (Ma). Taken from (Rees, 2001).

The Old World fruit bats (Family Pteropodidae) are one of 18 families (Simmons, 2005) that make up the hugely diverse mammalian order of the bats. Bats consist of over 1100 species with around 180 of those belonging to the Pteropodidae family (Simmons, 2005). Whilst many bat families have a worldwide distribution that of the pteropodid bats is restricted to the Old World. Specifically, mem-

1 bers of the Pteropodidae occur in the tropical and sub-tropical regions of Australia, Africa and Asia as well as on many islands of the Indian and Pacific Oceans (Mickelburgh et al. 1992). Jones et al. (2005) estimated that divergence of the Pteropodidae crown group, i.e. the group that contains the last common ancestor of all living pteropodid species, occurred around 24.6-36.1 million years ago (Ma). At this time, the vast water barriers that seperate the land masses of the Old World today were already in place (see Fig 1). Where it was the pteropodid bats originated from, and how they then dispersed throughout the Old World is unknown.

Figure 2. A geological time-scale from 65.5 Ma to the present. Adapted from Gradstein et al. (2004). Approxi- mate occurrences of early pteropodid fossils are shown in red.

Unfortunately there is little in the way of direct evidence with regards to where the pteropodid bats originated. The fossil record for all bats is notoriously poor (see Eiting & Gunnell, 2009; Gunnell & Simmons, 2005) but it is even more so for the Pteropodidae. Teeling et al. (2005) estimated that the record for this family is underrepresented by a staggering 98%. Uncovered in Krabi Mine, Thailand, the earliest pteropodid fossil is a tooth dating back to the Late Eocene (see Fig 2) (Ducrocq, Jaeger & Sige, 1993). Such fragmentary fossils, however, are difficult to place within the phylogeny with con- fidence (Gunnell & Simmons, 2005). From the Oligocene there is just one fossil – Archaeopteropus transiens – which was discovered in Italy (Revilliod, 1922) but its classification as a pteropodid is dis- puted (see Schutt & Simmons, 1998). Somewhat younger than these two fossils is that of Propotto, which was discovered in Africa and dates back to the Early Miocene (Walker, 1969).

With the fossil record so uninformative it is necessary to use other means to infer the historical biogeography of the Pteropodidae family. It has been proposed that the region in which a group originated from, i.e. its centre of origin, can be identified from where that group has its highest diversity (Crisci et al. 2003). Based on current distributions (Fritz et al. 2009; Grenyer et al., 2006), this would place Australasia as the most likely centre of origin for the pteropodids. Discouragingly there are no fossils from this region that are old enough to support this claim. Furthermore, the theory that the area of greatest diversity is the centre of origin is unlikely to be plausible as it requires the assump- tion that speciation has occurred at a constant rate (Cox & Moore, 2005) and does not allow for the very real possibility that a group may colonise a second area and undergo an adaptive radiation (Brown & Lomolino, 1998).

Recently, two independent biogeographical studies have been carried out on family-level phylogenies of the Chiroptera. As well as inter-family relationships differing between the two, contrasting methods were used and consequently very different results were obtained. In both studies ancestral distributions were inferred for each family. For the Pteropodidae, Teeling et al. (2005) acquired an Asian origin whilst Eick et al. (2005) argue for an African origin. Both of these studies, however, should be interpreted with caution. Firstly, the methods used in both have since come under harsh scrutiny (see later) and, secondly, a family-level analysis within the order ignores interesting biogeographic events that may have occurred at the species-level. Possible ancestral ranges have been hypothesised in several studies investigating the phylogenetic relationships of the Pteropodidae. Hollar and Springer (1997) and Giannini and Simmons (2003) suggest an Indo-Australo-Pacific origin and a SE Asian-Melanesian origin, respectively, based on the distributions of basal taxa. A species- level analysis of the biogeography of the Pteropodidae, which specifically employs biogeographic methods, is currently missing.

1.2 Biogeographic analysis

The methods available for reconstructing biogeographical histories have advanced greatly in the past few decades (Brown & Lomolino, 1998). A brief outline of the methods relevant to this particular study will be given. For a more in-depth account of how biogeography has developed as a discipline see Brown and Lomolino (1998) and Cox and Moore (2005).

In their investigation into the biogeography of the bats, Teeling et al. (2005) borrowed from the techniques used in ancestral character state reconstruction. Character mapping is used to assign character states to ancestral taxa in order to find the scenario that best explains the states of the modern taxa (Pagel, 1999). Using the approach of parsimony, for example, the preferred scenario will be the one that incurs the fewest transitions from one state to another (Fitch, 1971). When applying this method to biogeographic reconstructions, the characters are simply substituted with ranges. However, the models of evolution used in character reconstructions are not suitable for use in biogeographic reconstructions (Ree & Smith, 2008; Xiang & Thomas, 2008). In character evolution it is assumed that when two daughter lineages arise they will both inherit the character state of their ancestor; when inheriting ranges it is not necessarily the case that daughter lineages inherit the same range as their ancestor nor is it necessary for both to inherit the same ranges as one another (Ree et al., 2005).

A variety of programs have been developed specifically for inferring the ancient biogeography of a group. One such method is that of dispersal-vicariance analysis (DIVA) (Ronquist, 1996; Ronquist, 1997), which has been used in many biogeographic investigations including that by Eick et al. (2005). DIVA - implemented in DIVA v 1.1 (Ronquist, 1996) - is described as an events-based method with the events being dispersal, vicariance, duplication and extinction. Dispersal into a new area and extinction from an area both receive a cost of one per unit, whilst vicariance and duplication are free from cost (Ronquist, 1997). Vicariance and duplication are both caused by speciation. When the ancestor occurs in one area duplication occurs; both of the daughter lineages receive the same area as one another (Scenario 1, Fig 3). Vicariant speciation occurs if the ancestor has a widespread range; it assumed that the range is split in such a way that the daughter lineages receive mutually exclusive ranges (Scenario 2, Fig 3) (Ronquist, 1996). Given a phylogeny and distributions of all terminal taxa, both of which are assumed to be correct, a parsimony framework is employed to find the reconstruction that incurs the lowest cost.

Its ease of use and simple assumptions have contributed to the popularity of DIVA (Kodandara- maiah, 2010) but, despite this, is has been heavily criticised and demonstrated to encounter a number of problems. There is a tendency for the ancestor to be assigned a wide distribution; this flaw is acknowledged by the author himself (Ronquist, 1996) who recommends constraining the maximum number of areas that a taxon can occupy. However, Kodandaramaiah (2010) used hypothetical taxa and ranges to illustrate that constraining the maximum areas to a number too low or too high can lead to incorrect dispersal events and vicariant events, respectively. Additionally, DIVA can yield

4 many equally parsimonious scenarios (e.g. Santos et al., 2009) with no way of choosing one over the other. Most importantly, DIVA fails to incorporate important temporal information (Ree et al., 2005) and information on the dispersal abilities of the species involved (Kodandaramaiah, 2009).

DIVA assumes that the phylogeny used is strictly bifurcating (Ronquist, 1996), which means that each node gives rise to only two descendants. It cannot, therefore, account for situations in which there is phylogenetic uncertainty. When evolutionary relationships are not known a polytomy in the tree occurs; relationships cannot always be fully resolved and so some nodes appear to give rise to more than two lineages (Vandamme, 2009). Several modifications of DIVA have occurred, including Statistical-DIVA Yu et al. (2010) and BAYES-DIVA (Nylander et al., 2008), which are able to allow for uncertainty. Although this is an important improvement, the other problems highlighted above still remain.

Figure 3. Range inheritance scenarios. Scenario 1 – the ancestor has a single-area range consisting, both daughter lineages inherit this same range; Scenario 2 – the ancestor has a multiple-area range, one daughter lineage inherits one of these areas and the other daughter lineage inherits the remaining area(s). Scenario 3 – the ancestor has a multiple-area range, one daughter lineage inherits one area and the other daughter lineage inherits the whole range. Adapted from Ronquist (1997) and Ree et al. (2005).

More recently, a maximum-likelihood method known as the dispersal-extinction cladogenesis (DEC) model has been developed (Ree et al., 2005; Ree & Smith, 2008). The DEC model assumes that range evolution events can occur either at the nodes of a tree, i.e. at a speciation event, or along the branches of a tree (Ree & Smith, 2008). Range evolution along branches can involve a dispersal event, in which dispersal of a taxon into a new area expands the range, or a local extinction event, in which movement out of an area contracts the range (Ree & Smith, 2008). Range evolution at a speciation event can result in three different types of range inheritance scenarios (see Ree et al., 2005). Scenarios 1 and 2 are the same as those in DIVA (see Fig 3). Unlike DIVA, however, there is a second possibility for how the range may be inherited when the ancestor is widespread. As well as

5 mutually exclusive inheritance, an alternative is that one daughter lineage can inherit one area whilst the other inherits the whole range (Scenario 3, Fig 3).

The development of the DEC model was driven by the failure of events-based methods such as DIVA to incorporate divergence times and important paleogeographic information (Ree et al., 2005). The model is implemented in a programme known as Lagrange (likelihood analysis of geographic range evolution), in which it is possible to set geographic and dispersal constraints. This allows the inclusion of valuable information such as the dispersal ability of a taxon and connectivity between areas. This information is used to estimate rates of dispersal and local extinction (rate parameters) which, in turn, are used to calculate rates of transitions between the possible ranges (Ree & Smith, 2008). Whilst the use of parameters may add complexity to the model, incorporating such information is something other methods ignore (Kodandaramaiah, 2010). The range inheritance scenarios described earlier are assigned prior probabilities which, along with the transition rates, are used to calculate the likelihood of an ancestral range (Ree et al., 2005; Ree & Smith, 2008).

Lagrange is a fairly new piece of software and is still being developed and updated by the authors. Consequently, only a limited number of studies exist in which this has been a featured method (e.g. Clayton, Soltis & Soltis, 2009; Gobbeler & Klussmann-Kolb, 2010; Lucking et al., 2008) and so its suc- cess still largely remains to be seen. Despite this, Lagrange stands out as the most promising method currently available. Thus its implementation in the present study will help to assess its potential as well as to shed light on the ancient biogeography of the Old World fruit bats. Comparing Lagrange to a method such as DIVA should highlight its greater suitability for biogeographic analyses.

1.3 Aims and Objectives

Lagrange will be implemented in a species-level analysis of the Pteropodidae in order to explore the geographic origins of this family on a more comprehensive level than has been done previously. The supertree phylogeny of Jones et al. (2002) will be used to investigate this question. The Pteropodi- dae section of this tree, however, is extremely unresolved so it shall be updated to include studies that have been published since. Analyses will be performed on this new supertree and compared to those obtained with the Pteropodidae section of the Jones et al. (2002) phylogeny. Due to its recent and ongoing development, Lagrange has had limited time for review. Thus, the results of the main analysis will be compared to those obtained from a secondary analysis using DIVA.

The main research aims are summarised as follows:

 To construct an updated supertree for the Pteropodidae family for use in the present study alongside the original supertree.

 To reconstruct the biogeographical history of the Pteropodidae in a comprehensive, species-level analysis through implementation of Lagrange.

 To perform a secondary analysis in DIVA in order to compare the results against those obtained in Lagrange.

2. Methods

2.1 Pteropodidae supertree construction

Figure 4. The original supertree for the Pteropodidae. Branch lengths are proportional to time, with the timescale shown in red (Ma = millions of years ago).

The protocol in Bininda-Emonds et al. (2008) was used for the construction of the Pteropodidae supertree. A supertree is a phylogenetic tree that is created from the topologies of seperate source trees (Gatesy et al., 2002). These source trees are, in turn, constructed from morphological or molecular characters and they must be independent of one another (Gatesy et al., 2002; Springer & de Jong, 2001). Source trees used included those used in the original Pteropodidae supertree (Jones et al., 2002) and those obtained from literature searches that ran from 2000 (the end date of the origi-

8 nal supertree) to the present. From the source literature, appropriate trees were selected and placed into a matrix to determine whether or not they were independent from one another. Full de- tails of how this was done can be found in Appendix 1. Completion of the supertree construction and dating of the resulting tree was carried out by Olaf Bininda-Emonds (see Appendix 1). In addition to the updated supertree, the original Pteropodidae supertree (Jones et al., 2002) was used also used for analysis (see Fig 4). This tree displays the phylogenetic relationships between 159 pteropodid species. The tree contains 76 internal nodes but 22 of these are polytomies. 158 internal nodes would be required in order for it to be fully resolved, i.e. contain no polytomies. Thus, the original Pteropodidae supertree is 48.1% resolved.

2.2 Outgroups

Figure 5.The two alternative family-level topologies of the Jones et al. (2002) supertree. (a) The original topology. (b) The alternative topology.

Choosing outgroup taxa that are less closely related to the ingroup will increase the amount of time that has passed since they last shared a common ancestor and so the chances of encountering convergent evolution increases (Jones & Teeling, 2009). To avoid convergent evolution, outgroups should be taxa chosen from the group that is sister to the ingroup (Jones & Teeling, 2009). The original bat supertree (Jones et al., 2002) has two alternative family-level topologies (see Fig 5). The topology preferred by Jones et al. (2002) positions the Pteropodidae as the sister group of all other bat families (Fig 5a). The alternative topology places the Pteropodidae in a clade with the Rhinopomati- dae, Rhinolophidae, Hipposideridae, Megadermatidae and Craseonycteridae families (collectively

9 known as the Rhinolophoidea superfamily) (see Fig 5b). For the present study the alternative topology (Fig 5b) was chosen due to the increasing number of studies in its support (e.g. Hutcheon et al. 1998; Teeling et al., 2002; Teeling et al., 2000). Outgroups for the original Pteropodidae supertree, therefore, were selected from each of the Rhinolophoidea families. Those chosen were Rhinopoma hardwickei (Rhinopomatidae), Rhinolophus monoceros (Rhinolophidae), Paracoelops megalotis (Hip- posideridae), Cardioderma cor (Megadermatidae) and Craseinycteris thonglongyai (Craseonycteri- dae). The complete bat supertree of Jones et al. (2002) was pruned to contain the Pteropodidae and these outgroups taxa (see Figure 6). Inclusion of outgroups could not occur with the new Pteropodi- dae tree as, at the time of writing, the status of possible outgroups was not known (Maltby, 2010a).

Figure 6. The original Pteropodidae supertree with outgroups. Branch lengths are proportional to time, with the timescale shown in red (Ma = millions of years ago).

2.3 Range data

The Jones et al. (2002) supertree and the new updated supertree use different taxonomies; the original supertree follows the taxonomy set out in Koopman (1993) whereas the updated supertree uses the more recent version in Simmons (2005). Consequently, it was necessary to use two different sources for the distribution data, each of which used the appropriate taxonomy. Distributions for the 1993 and 2005 taxonomies were obtained from Grenyer et al. (2006) and Fritz et al. (2009), respectively. Data were obtained in the format of shapefiles and the necessary range information was extracted in ArcGIS (ESRI, 2008).

In order to create the species range matrices required for the biogeographic analyses, it was necessary to delimit geographic divisions. The WWF biogeographic realms of Olson et al. (2001) were used (Fig 7). Boundaries for these realms are based on those described by Udvardy (1975) with some modifications. As defined by Udvardy (1975), Australasia contains only Australia and Tasmania. The WWF definition expands this realm to include New Zealand, New Caledonia, New Guinea, the East Melanesian Islands and the islands of Wallacea (Olson et al., 2001). Pteropodid bats are only found in 5 out of the 8 realms – Australasia, Afrotropics, Indo-Malay, Oceania and Palaearctic – so only these were used.

Figure 7. Map showing the boundaries of the biogeographic realms (BBC, n.d.).

The range information extracted from the shapefiles was used to create species range matrices for each of the two taxonomies (see Appendix 2). Species for which distribution data was absent were removed from the matrix and pruned from the appropriate supertree using the ‘drop.tip’ function in the ‘ape’ package of R (Paradis et al. 2004; R Development Core Team, 2010). It was necessary to remove 5 out of 159 species from the original tree and 11 out of 186 from the new tree.

2.4 Biogeographic analysis

2.4a Species-level analysis in Lagrange

Lagrange (Ree & Smith, 2008) is a package run in the programming language Python (van Rossum, 1995) and, as of March 2009, a web-based configuration tool has been available for its implementation (http://www.reelab.net/lagrange/configurator/index). The user uploads a phylogenetic tree and species range data to the configurator and then sets the necessary range and dispersal constraints. This information is saved as a Python script ready for analysis. In order to run the script, the following were downloaded: Python 2.6 with the SciPy 0.8 and NumPy 1.5 libraries (Oliphant, 2007), and Lagrange-20100721 (Ree & Smith, 2008).

Analyses were performed on the following trees: original tree with no outgroups; original tree with outgroups; new tree with no outgroups. Lagrange cannot account for phylogenetic uncertainty and each of these trees contained polytomies; each tree, therefore, was randomly resolved 10 times in R using the ‘multi2di’ function of the ‘ape’ package R (Paradis et al., 2004; R Development Core Team, 2010) and analyses were performed on each of these.

There are three tabs in the Lagrange configurator that contain options to parameterize the analysis; these tabs are ‘range constraints’, ‘dispersal constraints’, and ‘rate parameters’. Under the ‘range constraints’ tab there is an ‘adjacency matrix’ in which it is necessary to select the pairs of areas in which it is possible for a species to occur in only these two. All pairs of areas were considered to be possible, given the dispersal ability of bats (e.g. Tidemann & Nelson, 2004; Webb & Tidemann, 1996). In order to avoid widely distributed ancestral ranges and a avoid lengthy computational time, the maximum number of areas in ancestral ranges was constrained to 2. The ‘dispersal constraints’ tab provides the opportunity to modify dispersal rates between the different areas and also between different time periods. Given that bats are able to fly and that all 5 realms were in existence throughout the time period, dispersal rates were kept constant between areas and through time.

Finally, under the ‘rate parameters’ tab there is the choice of estimating or fixing the baseline rates of dispersal and local extinction; estimation of these rates was chosen.

2.4b Species-level analysis in DIVA

A dispersal-vicariance analysis (DIVA) was implemented in DIVA 1.1 (Ronquist, 1996). It is stated in the manual that DIVA can process up to 180 taxa (Ronquist, 1996) but a bug in the program has reduced this number to 127. Once pruned of taxa for which distribution data is missing, the original supertree contains 154 species without outgroups and 159 with outgroups whilst the new tree contains 175 species. To reduce the number of taxa to below 127, species were pruned from endemic groups, i.e. those in which members are all in the same area, as recommended by Harris (2010). De- leting species from endemic groups avoids affecting the outcome of the analysis as neither dispersal not vicariant events are required for a species to retain the same range as its ancestor. 38 species were removed from the original tree but it was not possible to delete enough endemic species from the new tree so this was omitted from DIVA analyses. DIVA cannot analyse trees with polytomies so both trees were randomly resolved in R (R Development Core Team, 2010).

A NEXUS file containing a description of the tree and distribution information was created for each tree and loaded into DIVA. In order to avoid obtaining wide ancestral distributions, and to remain consistent with the Lagrange analyses, maximum areas were constrained to 2.

3. Results

3.1 Pteropodidae supertree

Figure 8. The updated supertree for the Pteropodidae. Branch lengths are proportional to time, with the timescale shown in red (Ma = millions of years ago).

The updated Pteropodidae supertree (see Fig 8) was constructed from 52 phylogenetic trees obtained from 23 literature sources (see Appendix 3). Of these, 7 were sources also used in the construction of the original supertree. The supertree displays phylogenetic relationships between 186 pteropodid species, 27 more species than the original supertree. The increase in the number of species seen in the new tree is due to a change in taxonomy; this includes both the discovery of new species and reclassification of synonymous species (Maltby, 2010b). The new supertree contains 105

14 internal nodes, 16 of which are polytomies. If it were to be fully resolved then it would contain 185 internal nodes. Therefore, the new Pteropodidae supertree is 56.8% resolved.

3.2 Biogeographic analysis

3.2a Lagrange

Lagrange calculated three values for the root node of the tree: the negative log-likelihood (-lnL) and the estimated dispersal and extinction rates. Of the 10 randomly resolved trees used for each analysis, only the results for the tree that yielded the greatest –lnL value are provided (see Table 1). Varia- tion between the –lnL values for each randomly resolved tree was small, as was the variation in the range inheritance scenarios given for each tree. The analysis performed with the original tree with no outgroups receives the highest lnL value, -254.4, whilst the new tree with no outgroups receives the lowest, -294.7. Estimated rates of dispersal and extinction were very low for all three trees, rang- ing from 0.0077-0.0102 and 0.0677-0.00913, respectively.

Table 1. The –lnL values and dispersal and extinction rates for the root nodes.

Analysis -lnL Dispersal Extinction Original tree, no outgroups 254.4 0.01023 0.009131 New tree, no outgroups 294.7 0.007665 0.009126 Original tree, outgroups 269.3 0.009057 0.006768

For each internal node the ancestral range inheritance scenario is given in the form of a ‘split’. The range on the left of the split is that inherited by the upper descendant branch of the node and the range on the right is inherited by the lower descendant branch (Ree and Smith 2008). To clarify, a split scenario of ‘AA+IM|AA’ indicates that the upper descendant branch of this node inherits ‘AA+IM’ and the lower descendant branch inherits ‘AA’, where AA and IM represent Australasia and IndoMalay respectively. The area(s) involved in the split are those which make up the ancestral range of the node; a split scenario of ‘AA+IM|IM’, therefore, indicates an ancestral range of Austral- asia and IndoMalay. For each split scenario, the lnL value and the relative probability (Rel.Prob) are calculated. Additionally, for each node, scenarios within 2-log likelihood units of the optimal scenario are provided. For all 3 trees Australasia and IndoMalay are the ancestral range of the Pteropodidae (see Table 2). For the original tree with no outgroups a split in which Australasia and IndoMalay are inherited by the upper branch and Australasia is inherited by the lower branch is the most likely scenario with a relative probability of 0.556. When outgroups are included this same scenario is recovered as the most optimal, with a higher probability of 0.848. For the new tree the same range is in-

15 herited by the upper branch but it is IndoMalay and not Australasia that is inherited by the lower branch, with a relative probability of 0.443.

Table 2. The range inheritance scenarios for the ancestral node of the Pteropodidae.

The optimal reconstructions at each node are illustrated for the original supertree with outgroups and the new tree with no outgroups (see Fig 9 and 10). Despite the original supertree with no outgroups receiving a greater –lnL value than the original supertree with outgroups only the reconstruction for the latter is be given. There is little difference between the optimal reconstructions at each node between the two trees and the inclusion of outgroups clarifies how the ancestral range of the Pteropodidae was inherited. The optimal reconstruction for the original tree with no outgroups can be found in Appendix 4. When the optimal range inheritance scenarios are plotted onto the trees (see Fig 9 and 10) it becomes possible to deduce how many times each of the three inheritance scenarios (see Fig 3) have occurred, as well as the number of range expansions and contractions. A split such as ‘AA|AA’ indicates a within-area speciation event (Scenario 1, Fig 3); ‘AA|IM’ represents a mutually exclusive between-area speciation event (Scenario 2 Fig 3); and ‘AA+IM|IM’ specifies the second type of between-area speciation (Scenario 3, Fig 3). In the original tree with outgroups (see Fig 9) the Pteropodidae have undergone 154 speciation events, 120 of which have been within-area and the remaining 34 of which have been between-area. When the ancestral range of a node includes an area not inherited from the previous node then one can conclude that a range expansion (dispersal) event has occurred along the branch connecting the two nodes. Conversely, if an area is absent from the ancestral range of a node, despite being inherited from the previous node, then a range contraction (extinction) event is assumed. There have been 45 dispersal events, 9 of which

16 have been followed by local extinctions, and one extinction event that was not preceded by an expansion (Fig 9, Table 3). The new tree (see Fig 10) has 174 speciation events; 155 of these are within- area events whilst the remaining 19 have occurred between areas. There have been 57 dispersal events with 24 of these being followed by an extinction event (Fig 10, Table3). The log-likelihood values and relative probabilities for the optimal range inheritance scenario of each node of Figures 9 and 10 can be found in Appendix 5.

Figure 9.The optimal reconstruction given by Lagrange for the original supertree with outgroups. The tree has been split into two, (a) and (b), and Pteropus (c) is shown separately. Branches numbered in red are those along which a range transition has occurred (see Table 3). Dates of range evolution events can be estimated from the dated phylogeny in Fig 6.

Figure 9 continued.

Figure 10.The optimal reconstruction given by Lagrange for the original supertree with outgroups. The tree has been split into two, (a) and (b), and Pteropus (c) is shown separately. Branches numbered in red are those along which a range transition has occurred (see Table 3) Dates of range evolution events can be estimated from the dated phylogeny in Fig 8.

Fig 10 continued.

Figure 10 continued.

Table 3. Inferred range transitions for the Lagrange analysis with the original tree (Fig 9) and the new tree (Fig 10). Numbers correspond to the red numbers on the branches of the tree. Numbers in brackets indicate where there have been multiple dispersal events and, if so, how many.

Original tree with outgroups New tree, no outgroups No. Range transition No. Range transition No. Range transition No. Range transition 1 AA -> AA+IM -> IM 28 AA -> AA+IM 1 AA -> AA+AT -> AT 28 IM -> IM+PA 2 IM -> IM+PA 29 IM -> IM+PA 2 AA -> AA+IM 29 IM -> AT+IM 3 IM -> IM+PA 30 AA -> AA+IM 3 AA -> AA+IM+PA (2) 30 IM -> AA+IM 4 IM -> AA+IM+PA (2) 31 AA -> AA+OC 4 AA -> AA+OC 31 AA -> AA+IM -> IM 5 IM -> AA+IM 32 OC -> OC+IM -> IM 5 AA -> AA+IM 32 IM -> IM+PA 6 IM -> AA+IM 33 AA -> AA+AT 6 AA -> AA+AT 33 AA -> AA+IM 7 IM -> IM+PA 34 AA -> AA+IM -> IM 7 IM -> AT+IM -> AT 34 AA -> AA+IM 8 IM -> AA+IM 35 OC -> OC+AT -> AT 8 IM -> AT+IM+PA (2) 35 AA -> AA+OC 9 IM -> AA+IM 36 AA -> AA+OC 9 PA -> AA+IM+PA -> AA+IM (2) 36 AA -> AA+OC 10 IM -> AA+IM 37 AA -> AA+OC 10 IM -> IM+OC -> OC 37 AA -> AA+AT -> AT 11 IM -> AA+IM 38 AA -> AA+IM -> IM 11 AA -> AA+IM -> IM 38 AA -> AA+OC 12 IM -> AA+IM -> AA 39 AA -> AA+AT -> AT 12 IM -> AA+IM+PA (2) 39 AT -> AT+IM -> IM 13 IM -> AT+IM+PA (2) 40 AA -> AA+OC 13 IM -> IM+AT -> AT 40 AT -> AT+IM -> IM 14 AT -> AT+IM 14 AA -> AA+AT -> AT 41 AA -> AA+AT -> AT 15 IM -> AA+IM+PA (2) 15 AA -> AA+IM 42 IM -> AA+IM 16 AA -> AA+AT 16 AA -> AA+IM 43 IM -> AA+IM 17 AA -> AA+IM+PA (2) 17 AA -> AA+AT -> AT 44 IM -> AA+IM -> AA 18 AA -> AA+IM 18 AA -> AA+IM 45 IM -> IM+PA 19 AA -> AA+IM+PA (2) 19 AA -> AA+OC -> OC 46 IM -> AA+IM 20 AA -> AA+OC 20 AA -> AA+IM -> IM 47 IM -> IM+OC+PA (2) 21 AA -> AA+IM 21 AA -> AA+IM 48 AA -> AA+IM 22 AA -> AA+IM 22 AA -> AA+OC -> OC 49 IM -> AA+IM 23 AA -> AA+OC -> OC 23 AA -> AA+OC -> OC 50 IM -> IM+PA 24 AA -> AA+IM 24 AA -> AA+IM -> IM 51 IM -> IM+PA 25 AA -> AA+IM 25 AA -> AA+OC -> OC 52 AA -> AA+IM -> IM 26 AA+IM -> AA 26 AA -> AA+IM -> IM 53 IM -> AA+IM -> AA 27 AA -> AA+IM -> IM 27 AA -> AA+OC -> OC

3.2b DIVA

For the original supertree with no outgroups DIVA yielded 4 equally parsimonious distributions for the ancestral node of the Pteropodidae – Australasia; Australasia and the Afrotropics; Australasia and IndoMalay; the Afrotropics and IndoMalay. Inclusion of outgroups (original supertree with outgroups) reduced the optimal distribution to just one possibility – Australasia.

Other than the optimal distribution of the ancestral node of the Pteropodidae, the biogeographic reconstructions calculated by DIVA for the two different trees are relatively similar. Where there are differences, these are mainly caused by the slight variation in topology caused by each tree being randomly resolved. It should be noted, however, that only 6 nodes of the original tree with outgroups are ambiguous compared to 16 in the original tree with no outgroups. Ambiguous nodes are ones for which there are multiple equally parsimonious distributions (Ronquist, 1996).

Optimal distributions for the original tree with outgroups are illustrated in Fig 11. In contrast to the output of Lagrange, the results given by DIVA consist only of the ancestral range at each node. As there is only one possible between-area range inheritance scenario, a node which has a widespread range, i.e. one that consists of more than one area, will always undergo vicariant speciation (Sce- nario 2, Fig 3). Nodes for which the ancestral range is made up of just one area will undergo duplication (Scenario 1, Fig 3). Extinction, despite being part of the model, is not modelled appropriately and so is never inferred (Ronquist, 1996). There have been 116 speciation events, 19-24 of which are vicariant (between-area) events and the remaining 92-97 of which are duplication (within-area) events. The uncertainty in the values of these events is due to ambiguous nodes. If the ancestral range of a node contains an area not included in the range of the previous node then a dispersal event can be inferred. 54 dispersal events are necessary (see Table 4), within the Pteropodidae, to explain the optimal reconstruction. Optimal distributions for the original tree, no outgroups can be found in Appendix 6.

Figure 11 (Pages 26 and 27). The optimal reconstructions given by DIVA for the original tree with outgroups. Each node is labelled with the most optimal range. Numbers in red correspond to range transition events (see Table 4).

Table 4. Dispersal events inferred by DIVA for the original tree with outgroups (Fig 11). Numbers correspond to the red numbers on the tree. Numbers in brackets indicate where there have been multiple dispersal events and, if so, how many. AA = Australasia; AT = Afrotropics; IM = IndoMalay; OC = Oceania; PA = Palearctic.

No. Dispersal event No. Dispersal event 1 AA -> IM 26 AA -> AA+IM 2 IM -> IM+PA 27 AA -> AA+IM 3 IM -> AA 28 AA -> AA+OC 4 AA -> AA+IM 29 AA -> AA+IM 5 IM -> AA+IM 30 AA -> AA+IM 6 IM -> IM+PA 31 AT -> AT+OC 7 AA -> AA+IM+PA (2) 32 AA -> AA+AT 8 IM -> AA+IM 33 AA -> AA+IM 9 IM -> AA+IM 34 AA -> AA+IM 10 IM -> IM+PA 35 IM -> IM+PA 11 IM -> AA+IM 36 AA -> IM 12 IM -> AA+IM 37 IM -> AA+IM 13 IM -> AA+IM 38 AA -> AA+0C 14 IM ->AT+IM+PA (2) 39 AA -> AA+AT 15 AT -> AT+IM 40 AA -> IM 16 AT -> AA+AT 41 AA -> AA+IM 17 IM -> AT+IM 42 AA -> AA+IM 18 AT -> AA+AT 43 AA -> AA+OC 19 IM -> AA+IM+PA (2) 44 AA -> AA+IM/AA+OC/AA+OC 20 AA -> IM/IM -> AA+IM 45 AA -> OC/AA -> AA+OC/OC -> AA+OC/PA -> PA+OC 21 AA -> AA+IM+PA (2) 46 IM/OC/PA -> AA+IM/AA+OC/AA+OC/PA+OC 22 AA -> AA+IM 47 AA -> IM/OC -> IM/PA -> IM 23 AA -> AA+IM 48 AA -> AA+IM 24 AA -> AA+IM+PA (2) 49 AA -> AA+AT 25 AA -> AA+OC

4. Discussion

4.1 Biogeographic history of the Pteropodidae

For the purposes of interpreting the biogeographic history of the Pteropodidae, only the results obtained with Lagrange shall be discussed. Both the original tree with outgroups (Table 2, Fig 9) and the new tree with no outgroups (Table 2, Fig 10) suggest that the ancestor of the Pteropodidae had a range encompassing IndoMalay and Australasia. In agreement with the ancestral range is the occur- rence of the earliest fossil in Thailand (Ducrocq et al., 1993) which is found within the IndoMalay region. No early pteropodid fossils have been discovered in Australasia but this could be due to poor fossilisation conditions or a lack of sampling (Eiting & Gunnell, 2009). Although different geographic divisions were used, the Asian origin of the Pteropodidae proposed by Teeling et al. (2005) does overlap to some extent with the present findings as IndoMalay includes part of Asia. Additionally, the hypotheses made by Hollar and Springer (1997) and Giannini and Simmons (2003) are similar to the ancestral range inferred in the present study. In stark contrast is the finding by Eick et al. (2005) that Africa is the centre of origin. Sub-Saharan Africa is found in the Afrotropical realm whilst North- ern Africa is included in the Palearctic realm. Although neither of these realms can be completely rejected as possible ancestral areas, scenarios that include them receive a much lower relative probability than the most optimal split (see Table 2). For the original tree with outgroups, for example, scenarios involving Africa and the Palearctic have a probability of 0.145 and 0.023, respectively, compared to 0.556 for the optimal scenario. Furthermore, the African fossil Propotto (Walker, 1969) is younger than the fossil uncovered in Thailand and the only one to have been found in the Palearc- tic, Archaeopteropus transiens (Revilliod, 1922), is likely to be a non-pteropodid bat (Schutt & Sim- mons, 1998).

From the ancestral range of Australasia and IndoMalay, the pteropodid bats expanded their range to include the Afrotropics, Oceania and the Palearctic. The optimal reconstruction of the original tree indicates that there have been 6 dispersals into the Afrotropics, 6 into Oceania and 9 into the Palearctic. The same number of dispersals into the Palearctic is inferred with the new tree but there are 4 and 5 additional dispersals into the Afrotropics and the Palearctic, respectively. Dispersal events into these areas have occurred throughout the history of the Pteropodidae which dates back to around 25 Ma for the old tree (see Fig 6) and 35 Ma for the new tree (see Fig 8). The water barriers separating the ancestral range from Oceania and the Afrotropics were already well established at this time (see Fig 1) and so dispersals into these two realms would have been over water. Genetic

29 studies have shown that water bodies can hinder the dispersal ability of bats (Pulvers & Colgan, 2007) but pteropodids must have reached these areas by some means. Prevailing winds and storms are thought to have aided the dispersal of some organisms across vast water expanses (Dijkstra, 2007; Geiger et al., 2007) so it is conceivable that this may have occurred in bats too. Moreover, a number of Pteropus species, including those that have reached isolated islands, are morphologically adapted to exploit wind currents by soaring (Norberg et al. 2000). An alternative scenario involves what Simpson (1940) describes as “sweepstake routes”, in which intermittent dispersal across a large expanse of water can occur via natural rafts. Such an event is unlikely but it can happen and, when it does, the animals involved will be by chance. This could explain the disjunctive range of genera such as Rousettus in which only some of the species have reached Africa. Rafting has been hypothesised to explain the dispersal of non-pteropodid bats from Africa to South America (Eick et al., 2005; Teeling et al., 2005) and so it is plausible that it may have shaped the distribution of pteropodid bats as well. Dispersals from mainland IndoMalay into the Palearctic would have only required flight over land. The difficulty of dispersing over water should have been taken into consideration when setting dispersal rates between areas and is advised for future investigations.

Dispersal events from IndoMalay into Australasia, or vice versa, have occurred more frequently than dispersals into the other biogeographic realms. Additionally, most within-area speciation events have occurred in these two areas. It would be interesting to investigate possible modes of speciation for pteropodid bats, particularly those found in IndoMalay and Australasia. Lim (2008), for example, speculates that the within-area speciation events identified in bats of the Emballonuridae family have been caused by episodes of changes in the biotic environment.

In general, the range inheritance scenarios for the original and new tree do not differ greatly from one another. The number of dispersal events increases with the new tree but this is due to the greater number of taxa providing more branches along which these events occur. Similarly, the number of speciation events is higher with the new tree simply because a greater number of taxa results in more internal nodes at which speciation events occur. The topology of the new Pteropodi- dae supertree (Fig 8) does not differ greatly from that of the original (see Fig 4). Like the original, the new tree is split into two main clades. One clade includes the cynopterines and nyctimenes whilst the remaining members of the family are found in the other clade. In the original tree, however, the latter clade is divided into two further clades but these clades have not been recovered in the new tree. Whilst resolution of the tree has increased, between-genera resolution in the latter clade has actually decreased.

4.2 Comparison of methods

Lagrange reconstructs Australasia and IndoMalay as the ancestral range of the Pteropodidae regard- less of which tree the analysis is performed on. For the original tree with no outgroups, DIVA also infers this range but there is ambiguity due to 3 other equally parsimonious distributions. The inclusion of outgroups resulted in DIVA reconstructing only Australasia as the ancestral range (see Fig 11). Comparison of the results obtained from Lagrange and DIVA will be with the original tree with outgroups (Figs 9 and 11, respectively). Reconstructions yielded from the original tree with no outgroups were similar although it should be noted that, for DIVA, there were more ambiguous nodes when outgroups were excluded.

The lower number of within-area speciation events calculated by DIVA has been caused by the pruning of endemic taxa necessary to make the tree smaller but the other types of range evolution events do not occur when a group is endemic. The overestimation of dispersal events by DIVA, when compared to Lagrange, may have been caused by constraining ‘maxareas’ to 2, which can lead to false dispersal events (Kodandaramaiah, 2010). Maximum areas in Lagrange were also constrained to 2 but it is unclear what, if any, effect this may have had on the results. In addition, DIVA has also inferred a higher number of vicariance events than Lagrange. Whilst Lagrange distinguishes between two different types of between-area speciation events (Scenarios 1 and 2, Fig 3), DIVA does not and so it could be this that is causing the discrepancies in the number of vicariance events between the two. For the most part, deviations between the results are due to the inability of DIVA to distinguish between these two scenarios. Additional differences have been caused by the slight variation in topology due to the polytomies being randomly resolved. The majority of nodes, however, have been assigned the same ancestral distribution by both programmes.

Another difference between the two programs, which has important consequences, is the amount of information provided in the output. Both DIVA and Lagrange infer a number of ambiguous nodes but whilst the relative probabilities calculated by Lagrange make it possible to identify the most likely scenario, DIVA does not have any means for distinguishing between different distributions. Further- more, any distributions that are slightly less parsimonious than the most optimal will be disregarded by DIVA.

Lagrange was chosen as the primary analytical method due to its ability to incorporate a large amount of temporal and spatial information by setting constraints (Ree et al., 2005; Ree & Smith,

2008). The capacity of this potential advantage of Lagrange was not realised in the present study; given the dispersal ability of the bats and the large geographic divisions used, parameters were kept constant over time and between areas. Choosing to do this may have resulted in a model lacking the sophistication required to explain the data but there is also the danger of creating a model that is too complicated (Clayton et al., 2009). Future investigations will benefit from using the parameters to create several models that can be compared. Striking a balance between the a simple and complex model is not necessary in DIVA as it in unable to integrate paleogeographic information (Ree et al., 2005). The cost of dispersal and vicariance is assumed to remain constant over time and between areas (Kodandaramaiah, 2010) and dates of lineage divergences cannot be taken into consideration (Ree et al., 2005). Neglecting the important temporal information that is provided by a dated phylogeny means inferred range inheritance scenarios cannot be accurately explained by particular events (Donoghue & Moore, 2003).

Lagrange is not yet user friendly. Explicit documentation on how to use the program is lacking as is literature on how to properly interpret the results of an analysis. The web-based configurator provides a more straightforward method for creating the necessary Python script but certain aspects, such as placing fossil constraints, are not yet available. Nonetheless, implementation of Lagrange by the author was found to be easier than that of DIVA. Although DIVA has been described as simple to use (Kodandaramaiah, 2010), this was not the experience of the author. The DIVA manual (Ronquist, 1996) fails to specify how to make a NEXUS file exactly to the specific requirements of the programme, nor does it properly define error messages making them difficult to rectify.

The ability of Lagrange to incorporate paleogeographic and temporal information, distinguish between more range inheritance scenarios, and to calculate relative probabilities of these scenarios makes it a more suitable choice than DIVA in biogeographic analyses.

4.3 Limitations and future investigations

Xiang and Thomas (2008) demonstrate that biogeographic reconstructions can change greatly de- pending on whether or not fossils are included. Despite this, fossil data was omitted from the analyses of the present study as it is not yet possible to place fossil constraints via the web-based configurator of Lagrange. Furthermore, the taxonomic uncertainty surrounding the early Pteropodidae fossils would require caution. In repeating the analyses, it would be advisable, as recommended by Xiang and Thomas (2008), to perform analyses both with and without fossils and then to compare

32 the results. Another factor which may have influenced the results was choice of outgroup taxa. The species chosen from each of the Rhinolophoidea families was simply the first encountered when pruning the bat supertree. This resulted in 4 out of the 5 species having a range that included Indo- Malay which may biased the results. A more ideal approach may have been to use the ancestral range of each family but to determine this would have required a biogeographic analysis in itself. Alternatively, it may be advisable to pick representative species at random. How informative the results of the present study are has been restricted by the use of biogeographic realms as geographic divisions. Given the large sizes of these realms it is difficult to interpret results with precision. Finer divisions will provide a more detailed biogeographic reconstruction but the cost of this is a lengthier computational time. Finally, the supertree itself is a further limitation. The use of supertrees in evolutionary analysis is somewhat controversial; Gatesy et al. (2002), for example, dismiss supertrees as being inaccurate and advises against their use in analytical studies. However, until phylogenetic studies are expanded to cover a wider number of taxa, the Pteropodidae supertree provides an in- valuable estimate for a complete-species level phylogeny of the family (see Bininda-Emonds, 2004).

Upon the improvements required of the present study, a more accurate and detailed hypothesis for the ancient biogeography of the Pteropodidae will be attainable. When this occurs it will be possible to answer a number of interesting questions such as why it is that the Pteropodidae is so species- rich and why members of this family are restricted to the Old World. Shifts in the diversification rates have been identified (Jones, Bininda-Emonds & Gittleman, 2005) in the Pteropodidae but the traits responsible have not (Isaac et al., 2005). Increases in the diversity of a group can be caused by dispersals into new areas (Moore & Donoghue, 2007) so it would be valuable to determine whether or not the biogeography of the Pteropodidae correlates with shifts in diversification rates. If dispersal into a new area has caused an increase in species richness then the next step would be to ask what it is about these areas that have facilitated diversification. This requires the integration of ecology, which has become somewhat disconnected from historical biogeography (Wiens & Donoghue, 2004). Understanding patterns of pteropodid distributions will ultimately allow predic- tions to be made about how these bats will respond to global change. This is of particular relevance to the Pteropodidae as around a third of recognised species are threatened and 13 of these are already at risk from climate change (IUCN, 2010).

Finally, with technological advances, it should become possible to extend the present study to en- compass the entirety of the Chiroptera. Lagrange is continuously being modified and updated by Richard Ree and Steven Smith; at the time of writing, a C++ version of Lagrange, that is able to per-

33 form analyses in a reduced length of time (Ree, 2010), is being tested. If this version succeeds then, coupled with the completion of the new bat supertree (Maltby, In Prep.), obtaining a hypothesis of the biogeographic history of all bats, at the species-level, is within reach.

6. Acknowledgements

My biggest thanks go to my supervisor, Dr Kate Jones, whom suggested biogeography as a topic for this thesis. Kate made me feel very welcome in her lab and was always willing to provide me with help and advice. Most importantly she was able to reassure me and calm my nerves upon the many times I was feeling panicked. I’d also like to thank Alanna Maltby for always being happy to help me, and there were many times it was needed, despite being on a tight schedule for her own research. Whilst I have not met him in person, Olaf Bininda-Emonds cannot go without thanks. Olaf went out of his way to ensure that the updated Pteropodidae supertree was ready in time for me to perform my analyses on.

From Imperial College I would like to thank Professor Tim Barraclough for his valuable advice on biogeography and his comments on my write-up for which I am incredibly grateful. I would also like express my appreciation for the help I received from Rodolphe Bernard on using ArcGIS.

A number of people deserve thanks for responding to my emails when I was in need of help. For advice on how to use Lagrange I would like to thank Richard Ree, Stephen Smith and Nick Matzke. Additionally, AJ Harris provided me with the help needed to overcome the errors I encountered when using DIVA. For their general suggestions on biogeographic analyses I would like to thank Jenny Xiang and Paul Upchurch.

I would like to thank all of the friends I have made at Silwood Park for making the past year such an enjoyable and memorable experience. Spending long days writing up my thesis in the computer lab would not have been doable if it were not for the great company. The residents of Southwood 3, in particular, deserve the greatest thanks.

Finally, I would like to thank my parents who have supported me, both financially and emotionally, throughout my thesis and the rest of the Masters course. Without them, I would not have been able to achieve any of this.

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8. Appendices

Appendix 1 – Pteropodidae supertree construction

 Literature searches were performed in BIOSIS Previews, Web of Science and Zoological Re- cords. The topic for each search was ‘Pteropodid*’ with each of the following, one at a time: ‘phylogen*’, ‘systematic*’, ‘cladistic*’, ‘taxonom*’, ‘cladogram*’, ‘phenogram*’, and ‘fossil*’.  References for each source paper were downloaded into an Endnote Library; each paper was either obtained online as a PDF or photocopied from an original kept at the ZSL Library.  An independence matrix was created in Excel to identify trees both within- and between- publications that were non-independent from one another i.e. those built from the same data sources with the same operational taxonomic units (OTUs).  When non-independent trees were encountered either the most comprehensive or the one favoured by the author(s) was kept whilst the other was discarded. If no tree was preferred then both were kept and downweighted later on.  Each source tree was drawn in Mesquite and saved in a project folder named ‘Pteropodi- dae.nex’. This required creating Nexus files containing relevant OTUs for each tree, downloading this into Mesquite, and then recreating the tree topology according to the source.  A reference taxonomy, obtained from Wilson and Reeder (2005) was also created in the project folder.  To ensure that all the OTUs of the source trees matched the reference taxonomy a Perl script known as ‘synonoTree.pl v2.1’ (Bininda-Emonds, 2010f) was run. This created a file called ‘mismatch.txt’ containing all the OTUs that needed to be corrected in order to agree with the reference taxonomy. The Perl script was run again and the process repeated until all OTUs were correct.  The resulting output file, ‘Pteropodidae_synonoTree.tre’, was sent along with ‘Pteropodi- dae.nex’ and the independence matrix to Olaf Bininda-Emonds who then completed the supertree construction as follows (Bininda-Emonds, 2010a).  A Perl script known as ‘SuperMRP.pl v1.2.2beta’ (Bininda-Emonds, 2010e) was run on the ‘Pteropodidae_synonoTree.tre’ file. This script converts the treefile into a data file, ‘Ptero- podidae_synonoTree_MRP.nex’, containing a matrix representation of the trees and a list of the trees along with their associated characters (Bininda-Emonds, 2010g). It is possible to represent trees in a matrix in which the rows are the terminal taxa of the tree and the rows are the internal nodes; if multiple trees are put into a matrix then applying parsimony will result in a supertree (Ragan, 1992).  The matrix was checked for species that had the same character states as these are ones found only in the Wilson and Reeder (2005) reference taxonomy. These species were removed and then the ‘SuperMRP.pl’ script was run again to create the final MRP.  Weighting of the trees was carried out in Excel. Independent trees received a weight of 1 whilst any non-independent trees received a weight according to how many versions there were, i.e. two trees will each be assigned a weight of 0.5. The reference tree was given a

weight of 0.001. The weight of each tree was divided by the number of characters for the corresponding tree in order to calculate the weights for each character. Weight values were then inserted into ‘Pteropodidae_synonoTree_MRP.nex’.  A Perl script known as ‘perlRat.pl v2.0beta’ (Bininda-Emonds, 2010b) was run on ‘Pteropodi- dae_synonoTree_MRP.nex’ in order to create a ratchet command (Bininda-Emonds, 2010g). This command is necessary to run a parsimony ratchet analysis in PAUP* v4.0b10 (Swofford, 2003).  This file was opened in PAUP* v4.0b10 (Swofford, 2003) and the ratchet command created in the previous step was run. Applying parsimony to a matrix representation of trees will result in the creation of a supertree (Ragan, 1992). The ratchet involved 50 batches, each of which consisted of 200 reweighting steps. The trees from the ratchet were used as the start- ing point of a heuristic search, in which TBR branch swapping was the method used.  Of the 50000 trees saved from the heuristic search, the 75% majority-rule tree was taken as the preliminary supertree.  Species that had been deleted previously were then re-added to the tree.  The molecular dataset of Bininda-Emonds et al. (2008) was used as a source for dating the Pteropodidae supertree.  The Perl script ‘seqCleaner.pl v1.2beta’ (Bininda-Emonds, 2010d) was used to prune this dataset so that it only contained Pteropodidae species. After pruning, the molecular datasets that were: RAG2, MT-RNR1 (12S rDNA), MT-RNR2 (16S rDNA), MT-CYB (cytochrome b) and C-MOS.  ModelTEST 3.7 (Posada & Crandall, 1998) was used to find the optimal model of evolution required for the datasets to fit to the topology of the Pteropodidae supertree. MT-RNR1, MT-RNR2 and MT-CYB evolved under a strict molecular clock but RAG2 and C-MOS did not.  These datasets were then fitted to the tree in PAUP* v4.0b10 (Swofford, 2003).  Using the Perl script ‘relDate.pl v3’ (Bininda-Emonds, 2010c), relative branch lengths were calibrated using 35. 969 Ma as an estimate for the divergence date of the root node of the Pteropodidae. This calibration point was obtained from (Jones et al., 2005).

Appendix 2 – Species range matrices

Original tree:

AA AT IM OC PA Acerodon_celebensis 1 0 0 0 0 Acerodon_humilis 1 0 0 0 0 Acerodon_jubatus 0 0 1 0 0 Acerodon_leucotis 0 0 1 0 0 Acerodon_mackloti 1 0 0 0 0 Aethalops_alecto 1 0 1 0 0 Alionycteris_paucidentata 0 0 1 0 0 Aproteles_bulmerae 1 0 0 0 0 Balionycteris_maculata 0 0 1 0 0 Boneia_bidens 1 0 0 0 0 Casinycteris_argynnis 0 1 0 0 0 Chironax_melanocephalus 1 0 1 0 0 Cynopterus_brachyotis 1 0 1 0 1 Cynopterus_horsfieldi 0 0 1 0 0 Cynopterus_nusatenggara 1 0 1 0 0 Cynopterus_sphinx 0 0 1 0 1 Cynopterus_titthaecheileus 1 0 1 0 0 Dobsonia_beauforti 1 0 0 0 0 Dobsonia_emersa 1 0 0 0 0 Dobsonia_exoleta 1 0 0 0 0 Dobsonia_inermis 1 0 0 0 0 Dobsonia_minor 1 0 0 0 0 Dobsonia_moluccensis 1 0 0 0 0 Dobsonia_pannietensis 1 0 0 0 0 Dobsonia_peroni 1 0 1 0 0 Dobsonia_praedatrix 1 0 0 0 0 Dobsonia_viridis 1 0 0 0 0 Dyacopterus_spadiceus 0 0 1 0 0 Eidolon_dupreanum 0 1 0 0 0 Eidolon_helvum 0 1 0 0 0 Eonycteris_major 0 0 1 0 0 Eonycteris_spelaea 1 0 1 0 1 Epomophorus_angolensis 0 1 0 0 0 Epomophorus_gambianus 0 1 0 0 0 Epomophorus_grandis 0 1 0 0 0 Epomophorus_labiatus 0 1 0 0 0 Epomophorus_minimus 0 1 0 0 0 Epomophorus_wahlbergi 0 1 0 0 0 Epomops_buettikoferi 0 1 0 0 0

Epomops_dobsoni 0 1 0 0 0 Epomops_franqueti 0 1 0 0 0 Haplonycteris_fischeri 0 0 1 0 0 Harpyionycteris_celebensis 1 0 0 0 0 Harpyionycteris_whiteheadi 0 0 1 0 0 Hypsignathus_monstrosus 0 1 0 0 0 Latidens_salimalii 0 0 1 0 0 Macroglossus_minimus 1 0 1 0 0 Macroglossus_sobrinus 1 0 1 0 1 Megaerops_ecaudatus 0 0 1 0 0 Megaerops_kusnotoi 0 0 1 0 0 Megaerops_niphanae 0 0 1 0 1 Megaerops_wetmorei 0 0 1 0 0 Megaloglossus_woermanni 0 1 0 0 0 Melonycteris_melanops 1 0 0 0 0 Melonycteris_woodfordi 1 0 0 0 0 Micropteropus_intermedius 0 1 0 0 0 Micropteropus_pusillus 0 1 0 0 0 Myonycteris_brachycephala 0 1 0 0 0 Myonycteris_relicta 0 1 0 0 0 Myonycteris_torquata 0 1 0 0 0 Nanonycteris_veldkampi 0 1 0 0 0 Neopteryx_frosti 1 0 0 0 0 Notopteris_macdonaldi 1 0 0 1 0 Nyctimene_aello 1 0 0 0 0 Nyctimene_albiventer 1 0 0 0 0 Nyctimene_celaeno 1 0 0 0 0 Nyctimene_cephalotes 1 0 0 0 0 Nyctimene_certans 1 0 0 0 0 Nyctimene_cyclotis 1 0 0 0 0 Nyctimene_draconilla 1 0 0 0 0 Nyctimene_major 1 0 0 0 0 Nyctimene_malaitensis 1 0 0 0 0 Nyctimene_masalai 1 0 0 0 0 Nyctimene_minutus 1 0 0 0 0 Nyctimene_rabori 0 0 1 0 0 Nyctimene_robinsoni 1 0 0 0 0 Nyctimene_vizcaccia 1 0 0 0 0 Otopteropus_cartilagonodus 0 0 1 0 0 Paranyctimene_raptor 1 0 0 0 0 Penthetor_lucasi 0 0 1 0 0 Plerotes_anchietai 0 1 0 0 0 Ptenochirus_jagori 0 0 1 0 0 Ptenochirus_minor 0 0 1 0 0 Pteralopex_acrodonta 0 0 0 1 0

Pteralopex_anceps 1 0 0 0 0 Pteralopex_atrata 1 0 0 0 0 Pteralopex_pulchra 1 0 0 0 0 Pteropus_admiralitatum 1 0 0 0 0 Pteropus_aldabrensis 0 1 0 0 0 Pteropus_alecto 1 0 1 0 0 Pteropus_anetianus 1 0 0 0 0 Pteropus_argentatus 1 0 0 0 0 Pteropus_caniceps 1 0 0 0 0 Pteropus_chrysoproctus 1 0 0 0 0 Pteropus_conspicillatus 1 0 0 0 0 Pteropus_dasymallus 0 0 1 0 1 Pteropus_faunulus 0 0 1 0 0 Pteropus_fundatus 1 0 0 0 0 Pteropus_giganteus 0 0 1 0 1 Pteropus_gilliardi 1 0 0 0 0 Pteropus_griseus 1 0 1 0 0 Pteropus_hypomelanus 1 0 1 0 0 Pteropus_insularis 0 0 0 1 0 Pteropus_leucopterus 0 0 1 0 0 Pteropus_livingstonei 0 1 0 0 0 Pteropus_lombocensis 1 0 0 0 0 Pteropus_lylei 0 0 1 0 0 Pteropus_macrotis 1 0 0 0 0 Pteropus_mahaganus 1 0 0 0 0 Pteropus_mariannus 0 0 0 1 0 Pteropus_melanopogon 1 0 0 0 0 Pteropus_melanotus 0 0 1 0 0 Pteropus_molossinus 0 0 0 1 0 Pteropus_neohibernicus 1 0 0 0 0 Pteropus_niger 0 1 0 0 0 Pteropus_nitendiensis 1 0 0 0 0 Pteropus_ocularis 1 0 0 0 0 Pteropus_ornatus 1 0 0 0 0 Pteropus_personatus 1 0 0 0 0 Pteropus_pohlei 1 0 0 0 0 Pteropus_poliocephalus 1 0 0 0 0 Pteropus_pselaphon 0 0 0 1 0 Pteropus_pumilus 0 0 1 0 0 Pteropus_rayneri 1 0 0 0 0 Pteropus_rodricensis 0 1 0 0 0 Pteropus_rufus 0 1 0 0 0 Pteropus_samoensis 0 0 0 1 0 Pteropus_scapulatus 1 0 0 0 0 Pteropus_seychellensis 0 1 0 0 0

Pteropus_speciosus 0 0 1 0 0 Pteropus_temmincki 1 0 0 0 0 Pteropus_tonganus 1 0 0 1 0 Pteropus_tuberculatus 1 0 0 0 0 Pteropus_vampyrus 1 0 1 0 0 Pteropus_vetulus 1 0 0 0 0 Pteropus_voeltzkowi 0 1 0 0 0 Pteropus_woodfordi 1 0 0 0 0 Rousettus_aegyptiacus 0 1 1 0 1 Rousettus_amplexicaudatus 1 0 1 0 0 Rousettus_angolensis 0 1 0 0 0 Rousettus_celebensis 1 0 0 0 0 Rousettus_lanosus 0 1 0 0 0 Rousettus_leschenaulti 1 0 1 0 1 Rousettus_madagascariensis 0 1 0 0 0 Rousettus_obliviosus 0 1 0 0 0 Rousettus_spinalatus 0 0 1 0 0 Scotonycteris_ophiodon 0 1 0 0 0 Scotonycteris_zenkeri 0 1 0 0 0 Sphaerias_blanfordi 0 0 1 0 1 Styloctenium_wallacei 1 0 0 0 0 Syconycteris_australis 1 0 0 0 0 Syconycteris_carolinae 1 0 0 0 0 Syconycteris_hobbit 1 0 0 0 0 Thoopterus_nigrescens 1 0 0 0 0 Cardioderma_cor 0 1 0 0 0 Craseonycteris_thonglongyai 0 0 1 0 0 Rhinopoma_hardwickei 0 1 1 0 1 Rhinolophus_monoceros 0 0 1 0 0 Paracoelops_megalotis 0 0 1 0 0

AA=Australasia; AT=Afrotropical; IM=IndoMalay; PA=Palearctic; OC=Oceania. (Cardioderma cor, Craseonycteris thonglongyai, Rhinopoma hardwickei, Rhinolophus monoceros and Paracoelops megalotis were only included in the range matrix for analyses with outgroups)

New tree:

AA AT IM OC PA Acerodon_celebensis 1 0 0 0 0 Acerodon_humilis 1 0 0 0 0 Acerodon_jubatus 0 0 1 0 0 Acerodon_leucotis 0 0 1 0 0 Acerodon_mackloti 1 0 0 0 0 Aethalops_aequalis 0 0 1 0 0 Aethalops_alecto 1 0 1 0 0 Alionycteris_paucidentata 0 0 1 0 0 Aproteles_bulmerae 1 0 0 0 0 Balionycteris_maculata 0 0 1 0 0 Casinycteris_argynnis 0 1 0 0 0 Chironax_melanocephalus 1 0 1 0 0 Cynopterus_brachyotis 0 0 1 1 1 Cynopterus_horsfieldii 0 0 1 0 0 Cynopterus_luzoniensis 1 0 0 0 0 Cynopterus_minutus 1 0 1 0 0 Cynopterus_nusatenggara 1 0 1 0 0 Cynopterus_sphinx 0 0 1 0 1 Cynopterus_titthaecheilus 1 0 1 0 0 Dobsonia_anderseni 1 0 0 0 0 Dobsonia_beauforti 1 0 0 0 0 Dobsonia_crenulata 1 0 0 0 0 Dobsonia_emersa 1 0 0 0 0 Dobsonia_exoleta 1 0 0 0 0 Dobsonia_inermis 1 0 0 0 0 Dobsonia_magna 1 0 0 0 0 Dobsonia_minor 1 0 0 0 0 Dobsonia_moluccensis 1 0 0 0 0 Dobsonia_pannietensis 1 0 0 0 0 Dobsonia_peronii 1 0 1 0 0 Dobsonia_praedatrix 1 0 0 0 0 Dobsonia_viridis 1 0 0 0 0 Dyacopterus_brooksi 0 0 1 0 0 Dyacopterus_spadiceus 0 0 1 0 0 Eidolon_dupreanum 0 1 0 0 0 Eidolon_helvum 0 1 0 0 0 Eonycteris_major 0 0 1 0 0 Eonycteris_robusta 0 0 1 0 0 Eonycteris_spelaea 1 0 1 0 1 Epomophorus_angolensis 0 1 0 0 0 Epomophorus_crypturus 0 1 0 0 0 Epomophorus_gambianus 0 1 0 0 0 Epomophorus_grandis 0 1 0 0 0

Epomophorus_labiatus 0 1 0 0 0 Epomophorus_minimus 0 1 0 0 0 Epomophorus_wahlbergi 0 1 0 0 0 Epomops_buettikoferi 0 1 0 0 0 Epomops_dobsonii 0 1 0 0 0 Epomops_franqueti 0 1 0 0 0 Haplonycteris_fischeri 0 0 1 0 0 Harpyionycteris_celebensis 1 0 0 0 0 Harpyionycteris_whiteheadi 0 0 1 0 0 Hypsignathus_monstrosus 0 1 0 0 0 Latidens_salimalii 0 0 1 0 0 Lissonycteris_angolensis 0 1 0 0 0 Macroglossus_minimus 1 0 1 0 0 Macroglossus_sobrinus 1 0 1 0 1 Megaerops_ecaudatus 0 0 1 0 0 Megaerops_kusnotoi 0 0 1 0 0 Megaerops_niphanae 0 0 1 0 1 Megaerops_wetmorei 0 0 1 0 0 Megaloglossus_woermanni 0 1 0 0 0 Melonycteris_fardoulisi 1 0 0 0 0 Melonycteris_melanops 1 0 0 0 0 Melonycteris_woodfordi 1 0 0 0 0 Micropteropus_intermedius 0 1 0 0 0 Micropteropus_pusillus 0 1 0 0 0 Myonycteris_brachycephala 0 1 0 0 0 Myonycteris_relicta 0 1 0 0 0 Myonycteris_torquata 0 1 0 0 0 Nanonycteris_veldkampii 0 1 0 0 0 Neopteryx_frosti 1 0 0 0 0 Notopteris_macdonaldi 1 0 0 1 0 Notopteris_neocaledonica 1 0 0 0 0 Nyctimene_aello 1 0 0 0 0 Nyctimene_albiventer 1 0 0 0 0 Nyctimene_cephalotes 1 0 0 0 0 Nyctimene_certans 1 0 0 0 0 Nyctimene_cyclotis 1 0 0 0 0 Nyctimene_draconilla 1 0 0 0 0 Nyctimene_keasti 1 0 0 0 0 Nyctimene_major 1 0 0 0 0 Nyctimene_malaitensis 1 0 0 0 0 Nyctimene_masalai 1 0 0 0 0 Nyctimene_minutus 1 0 0 0 0 Nyctimene_rabori 0 0 1 0 0 Nyctimene_robinsoni 1 0 0 0 0 Nyctimene_sanctacrucis 1 0 0 0 0 Nyctimene_vizcaccia 1 0 0 0 0

Otopteropus_cartilagonodus 0 0 1 0 0 Paranyctimene_raptor 1 0 0 0 0 Penthetor_lucasi 0 0 1 0 0 Plerotes_anchietae 0 1 0 0 0 Ptenochirus_jagori 0 0 1 0 0 Ptenochirus_minor 0 0 1 0 0 Pteralopex_acrodonta 0 0 0 1 0 Pteralopex_anceps 1 0 0 0 0 Pteralopex_atrata 1 0 0 0 0 Pteralopex_pulchra 1 0 0 0 0 Pteralopex_taki 1 0 0 0 0 Pteropus_admiralitatum 1 0 0 0 0 Pteropus_aldabrensis 0 1 0 0 0 Pteropus_alecto 1 0 1 0 0 Pteropus_anetianus 1 0 0 0 0 Pteropus_aruensis 1 0 0 0 0 Pteropus_banakrisi 1 0 0 0 0 Pteropus_caniceps 1 0 0 0 0 Pteropus_capistratus 1 0 0 0 0 Pteropus_chrysoproctus 1 0 0 0 0 Pteropus_cognatus 1 0 0 0 0 Pteropus_conspicillatus 1 0 0 0 0 Pteropus_dasymallus 0 0 1 0 1 Pteropus_faunulus 0 0 1 0 0 Pteropus_fundatus 1 0 0 0 0 Pteropus_giganteus 0 0 1 0 1 Pteropus_gilliardorum 1 0 0 0 0 Pteropus_griseus 1 0 1 0 0 Pteropus_hypomelanus 1 0 1 0 0 Pteropus_insularis 0 0 0 1 0 Pteropus_intermedius 0 0 1 0 0 Pteropus_keyensis 1 0 0 0 0 Pteropus_leucopterus 0 0 1 0 0 Pteropus_livingstonii 0 1 0 0 0 Pteropus_lombocensis 1 0 0 0 0 Pteropus_lylei 0 0 1 0 0 Pteropus_macrotis 1 0 0 0 0 Pteropus_mahaganus 1 0 0 0 0 Pteropus_mariannus 0 0 0 1 0 Pteropus_melanopogon 1 0 0 0 0 Pteropus_melanotus 0 0 1 0 0 Pteropus_molossinus 0 0 0 1 0 Pteropus_neohibernicus 1 0 0 0 0 Pteropus_niger 0 1 0 0 0 Pteropus_nitendiensis 1 0 0 0 0 Pteropus_ocularis 1 0 0 0 0

Pteropus_ornatus 1 0 0 0 0 Pteropus_personatus 1 0 0 0 0 Pteropus_pohlei 1 0 0 0 0 Pteropus_poliocephalus 1 0 0 0 0 Pteropus_pselaphon 0 0 0 1 0 Pteropus_pumilus 0 0 1 0 0 Pteropus_rayneri 1 0 0 0 0 Pteropus_rennelli 1 0 0 0 0 Pteropus_rodricensis 0 1 0 0 0 Pteropus_rufus 0 1 0 0 0 Pteropus_samoensis 0 0 0 1 0 Pteropus_scapulatus 1 0 0 0 0 Pteropus_seychellensis 0 1 0 0 0 Pteropus_speciosus 0 0 1 0 0 Pteropus_temminckii 1 0 0 0 0 Pteropus_tonganus 1 0 0 1 0 Pteropus_tuberculatus 1 0 0 0 0 Pteropus_ualanus 0 0 0 1 0 Pteropus_vampyrus 1 0 1 0 0 Pteropus_vetulus 1 0 0 0 0 Pteropus_voeltzkowi 0 1 0 0 0 Pteropus_woodfordi 1 0 0 0 0 Pteropus_yapensis 0 0 0 1 0 Rousettus_aegyptiacus 0 1 1 0 1 Rousettus_amplexicaudatus 1 0 1 0 0 Rousettus_bidens 1 0 0 0 0 Rousettus_celebensis 1 0 0 0 0 Rousettus_lanosus 0 1 0 0 0 Rousettus_leschenaultii 1 0 1 0 1 Rousettus_madagascariensis 0 1 0 0 0 Rousettus_obliviosus 0 1 0 0 0 Rousettus_spinalatus 0 0 1 0 0 Scotonycteris_ophiodon 0 1 0 0 0 Scotonycteris_zenkeri 0 1 0 0 0 Sphaerias_blanfordi 0 0 1 0 1 Styloctenium_wallacei 1 0 0 0 0 Syconycteris_australis 1 0 0 0 0 Syconycteris_carolinae 1 0 0 0 0 Syconycteris_hobbit 1 0 0 0 0 Thoopterus_nigrescens 1 0 0 0 0

AA=Australasia; AT=Afrotropical; IM=IndoMalay; PA=Palearctic; OC=Oceania.

Appendix 3 – Literature sources used in Pteropodidae supertree construction

ALMEIDA, F. C., GIANNINI, N. P., DESALLE, R. & SIMMONS, N. B. (2009). The phylogenetic relationships of cynopterine fruit bats (Chiroptera: Pteropodidae: Cynopterinae). Molecular Phy- logenetics and Evolution 53, 772-783. BASTIAN, S. T., JR., TANAKA, K., ANUNCIADO, R. V. P., NATURAL, N. G., SUMALDE, A. C. & NAMI- KAWA, T. (2002). Evolutionary relationships of flying foxes (genus Pteropus) in the Philip- pines inferred from DNA sequences of cytochrome b gene. Biochemical Genetics 40, 101- 116. BOGDANOWICZ, W., JUSTE, J., OWEN, R. D. & SZTENCEL, A. (2005). Geometric morphometrics and cladistics: testing evolutionary relationships in mega- and microbats. Acta Chiropterologica 7, 39-49. CAMPBELL, P., SCHNEIDER, C. J., ADNAN, A. M., ZUBAID, A. & KUNZ, T. H. (2004). Phylogeny and phylogeography of Old World fruit bats in the Cynopterus brachyotis complex. Molecular Phy- logenetics and Evolution 33, 764-781. CAMPBELL, P., SCHNEIDER, C. J., ADNAN, A. M., ZUBAID, A. & KUNZ, T. H. (2006). Comparative popu- lation structure of Cynopterus fruit bats in peninsular Malaysia and southern Thailand. Mo- lecular Ecology 15, 29-47. COLGAN, D. J. & DA COSTA, P. (2002). Megachiropteran evolution studied with 12S rDNA and c-mos DNA sequences. Journal of Mammalian Evolution 9, 3-22. COLGAN, D. J. & FLANNERY, T. F. (1995). A Phylogeny of Indo-West Pacific Megachiroptera Based on Ribosomal DNA. Systematic Biology 44, 209-220. ESSELSTYN, J. A., GARCIA, H. J. D., SAULOG, M. G. & HEANEY, L. R. (2008). A new species of Des- malopex (Pteropodidae) from the Philippines, with a phylogenetic analysis of the Pteropo- dini. Journal of Mammalogy 89, 815-825. GIANNINI, N. P., ALMEIDA, F. C., SIMMONS, N. B. & HELGEN, K. M. (2008). The systematic position of Pteropus leucopterus and its bearing on the monophyly and relationships of Pteropus (Chi- roptera: Pteropodidae). Acta Chiropterologica 10, 11-20. GIANNINI, N. P., CUNHA ALMEIDA, F. & SIMMONS, N. B. (2009). Phylogenetic relationships of harpy- ionycterine megabats (Chiroptera: Pteropodidae). Bulletin of the American Museum of Natu- ral History 331, 183-204. GIANNINI, N. P., CUNHA ALMEIDA, F., SIMMONS, N. B. & DESALLE, R. (2006). Phylogenetic relationships of the enigmatic harpy fruit bat, Harpyionycteris (Mammalia: Chiroptera: Pteropodi- dae). American Museum Novitates 3533, 1-12. GIANNINI, N. P. & SIMMONS, N. B. (2005). Conflict and congruence in a combined DNA-morphology analysis of megachiropteran bat relationships (Mammalia: Chiroptera: Pteropodidae). Cladistics 21, 411-437. HOLLAR, L. J. & SPRINGER, M. S. (1997). Old World fruitbat phylogeny: evidence for convergent evolution and an endemic African clade. Proceedings of the National Academy of Sciences of the United States of America 94, 5716-5721. HOOD, C. S. (1989). Comparative morphology and evolution of the female reproductive tract in macroglossine bats (Mammalia, Chiroptera). Journal of Morphology 199, 207-221.

JUSTE B, J., ALVAREZ, Y., TABARES, E., GARRIDO-PERTIERRA, A., IBANEZ, C. & BAUTISTA, J. M. (1999). Phylogeography of African fruitbats (Megachiroptera). Molecular Phylogenetics and Evolu- tion 13, 596-604. JUSTE B, J., IBANEZ, C. & MACHORDOM, A. (1997). Evolutionary relationships among the African fruit bats: Rousettus egyptiacus, R. angolensis, and Myonycteris. Journal of Mammalogy 78, 766- 774. KENNEDY, M., PATERSON, A. M., MORALES, J. C., PARSONS, S., WINNINGTON, A. P. & SPENCER, H. G. (1999). The long and short of it: branch lengths and the problem of placing the New Zealand short-tailed bat, Mystacina. Molecular Phylogenetics and Evolution 13, 405-416. NEWBOUND, C. N., HISHEH, S., SUYANTO, A., HOW, R. A. & SCHMITT, L. H. (2008). Markedly discor- dant mitochondrial DNA and allozyme phylogenies of tube-nosed fruit bats, Nyctimene, at the Australian-oriental biogeographical interface. Biological Journal of the Linnean Society 93, 589-602. O'BRIEN, J., MARIANI, C., OLSON, L., RUSSELL, A. L., SAY, L., YODER, A. D. & HAYDEN, T. J. (2009). Multiple colonisations of the western Indian Ocean by Pteropus fruit bats (Megachiroptera: Pteropodidae): The furthest islands were colonised first. Molecular Phylogenetics and Evolu- tion 51, 294-303. PULVERS, J. N. & COLGAN, D. J. (2007). Molecular phylogeography of the fruit bat genus Melo- nycteris in northern Melanesia. Journal of Biogeography 34, 713-723. ROMAGNOLI, M. L. & SPRINGER, M. S. (2000). Evolutionary relationships among old world fruitbats (Megachiroptera: Pteropodidae) based on 12S rRNA, tRNA valine, and 16S rRNA gene sequences. Journal of Mammalian Evolution 7, 259-284. SCHMITT, L. H., KITCHENER, D. J. & HOW, R. A. (1995). A genetic perspective of mammalian variation and evolution in the Indonesian archipelago: biogeographic correlates in the fruit bat genus Cynopterus. Evolution 49, 399-412. SPRINGER, M. S., HOLLAR, L. J. & KIRSCH, J. A. W. (1995). Phylogeny, molecules versus morphology, and rates of character evolution among fruitbats (Chiroptera: Megachiroptera). Australian Journal of Zoology 43, 557-582. TEELING, E. C., SCALLY, M., KAO, D. J., ROMAGNOLI, M. L., SPRINGER, M. S. & STANHOPE, M. J. (2000). Molecular evidence regarding the origin of echolocation and flight in bats. Nature 403, 188-192.

Appendix 4 – Lagrange results (a) Original tree with no outgroups:

The optimal range inheritance for each node is shown for the original tree with no outgroups. The tree has been split up two halves (a, b), and Pteropus is shown separately.

Appendix 5 – Lagrange results (b)

Original tree with outgroups:

Most recent common ancestor of: Split: lnL: Rel.Prob: Paranyctimene raptor Paracoelops megalotis [IM|IM] -270.4 0.3379 Paranyctimene raptor Pteropus neohibernicus [AA+IM|AA] -269.5 0.838 Paranyctimene raptor Chironax melanocephalus [AA|IM] -269.7 0.6909 Paranyctimene raptor Nyctimene cyclotis [AA|AA] -269.4 0.9466 Nyctimene major Nyctimene cyclotis [AA|AA] -269.3 0.9955 Nyctimene major Nyctimene robinsoni [AA|AA] -269.3 0.9966 Nyctimene aello Nyctimene cyclotis [AA|AA] -269.3 0.9986 Nyctimene aello Nyctimene celaeno [AA|AA] -269.3 0.9975 Nyctimene albiventer Nyctimene cyclotis [AA|AA] -269.3 0.9998 Nyctimene albiventer Nyctimene draconilla [AA|AA] -269.3 0.998 Nyctimene albiventer Nyctimene minutus [AA|AA] -269.3 0.9995 Nyctimene masalai Nyctimene cyclotis [AA|AA] -269.3 0.9999 Nyctimene masalai Nyctimene malaitensis [AA|AA] -269.3 0.9997 Nyctimene cephalotes Nyctimene malaitensis [AA|AA] -269.3 0.9997 Nyctimene vizcaccia Nyctimene malaitensis [AA|AA] -269.3 0.9997 Nyctimene rabori Nyctimene malaitensis [AA|AA] -269.3 0.9997 Nyctimene certans Nyctimene cyclotis [AA|AA] -269.3 0.9976 Sphaerias blanfordi Chironax melanocephalus [IM|IM] -269.5 0.7987 Sphaerias blanfordi Haplonycteris fischeri [IM|IM] -269.4 0.9387 Alionycteris paucidentata Haplonycteris fischeri [IM|IM] -269.3 0.991 Otopteropus cartilagonodus Haplonycteris fischeri [IM|IM] -269.3 0.9976 Cynopterus sphinx Chironax melanocephalus [IM|IM] -269.5 0.8598 Cynopterus sphinx Thoopterus nigrescens [IM|IM] -269.3 0.9634 Cynopterus sphinx Ptenochirus minor [IM|IM] -269.3 0.9923 Cynopterus sphinx Dyacopterus spadiceus [IM|IM] -269.3 0.9969 Cynopterus sphinx Megaerops kusnotoi [IM|IM] -269.3 0.9979 Cynopterus sphinx Cynopterus titthaecheileus [IM|IM] -269.5 0.8597 Cynopterus sphinx Cynopterus brachyotis [IM|IM] -269.7 0.6645 Cynopterus nusatenggara Cynopterus titthaecheileus [IM|IM] -269.5 0.843 Cynopterus horsfieldi Cynopterus titthaecheileus [IM|IM] -269.5 0.8522 Megaerops wetmorei Megaerops kusnotoi [IM|IM] -269.3 0.9765 Megaerops wetmorei Megaerops niphanae [IM|IM] -269.3 0.9771 Megaerops ecaudatus Megaerops kusnotoi [IM|IM] -269.3 0.9994 Ptenochirus jagori Ptenochirus minor [IM|IM] -269.3 0.9966 Latidens salimalii Thoopterus nigrescens [IM|IM] -269.9 0.5325 Penthetor lucasi Thoopterus nigrescens [IM|AA] -269.5 0.8627 Aethalops alecto Chironax melanocephalus [IM|IM] -269.6 0.7408 Balionycteris maculata Chironax melanocephalus [IM|IM] -269.5 0.8079 Myonycteris torquata Pteropus neohibernicus [AA|AA] -269.3 0.9636 Myonycteris torquata Boneia bidens [AT|AA+AT] -269.3 0.9847 Myonycteris torquata Megaloglossus woermanni [AT|AT] -269.3 0.9989 Myonycteris torquata Myonycteris relicta [AT|AT] -269.3 0.9952 Myonycteris torquata Myonycteris brachycephala [AT|AT] -269.3 0.9988 Eidolon helvum Megaloglossus woermanni [AT|AT] -269.3 0.9997 Eidolon helvum Eidolon dupreanum [AT|AT] -269.3 0.9955

Rousettus lanosus Megaloglossus woermanni [AT|AT] -269.3 0.9999 Rousettus lanosus Rousettus madagascariensis [AT|AT] -269.4 0.9442 Rousettus amplexicaudatus Rousettus madagascariensis [IM|AT+IM] -269.4 0.9338 Rousettus amplexicaudatus Rousettus aegyptiacus [IM|IM] -269.3 0.9631 Rousettus amplexicaudatus Rousettus celebensis [IM|IM] -269.3 0.9645 Rousettus obliviosus Rousettus madagascariensis [AT|AT+IM] -269.4 0.9037 Rousettus leschenaulti Rousettus madagascariensis [IM|AT+IM] -269.4 0.8989 Rousettus spinalatus Rousettus madagascariensis [IM|AT] -269.5 0.8537 Rousettus angolensis Boneia bidens [AT|AA] -269.5 0.8347 Rousettus angolensis Nanonycteris veldkampi [AT|AT] -269.3 0.971 Plerotes anchietai Nanonycteris veldkampi [AT|AT] -269.3 0.9934 Casinycteris argynnis Nanonycteris veldkampi [AT|AT] -269.3 0.9988 Casinycteris argynnis Scotonycteris zenkeri [AT|AT] -269.3 0.9966 Scotonycteris ophiodon Scotonycteris zenkeri [AT|AT] -269.3 0.999 Hypsignathus monstrosus Nanonycteris veldkampi [AT|AT] -269.3 0.9975 Hypsignathus monstrosus Epomophorus gambianus [AT|AT] -269.3 0.9997 Hypsignathus monstrosus Epomops franqueti [AT|AT] -269.3 0.9988 Epomops dobsoni Epomops franqueti [AT|AT] -269.3 0.9996 Epomops dobsoni Epomops buettikoferi [AT|AT] -269.3 0.9999 Micropteropus intermedius Epomophorus gambianus [AT|AT] -269.3 0.9992 Micropteropus intermedius Micropteropus pusillus [AT|AT] -269.3 0.9991 Epomophorus wahlbergi Epomophorus gambianus [AT|AT] -269.3 0.9995 Epomophorus angolensis Epomophorus gambianus [AT|AT] -269.3 0.9999 Epomophorus angolensis Epomophorus labiatus [AT|AT] -269.3 1 Epomophorus grandis Epomophorus gambianus [AT|AT] -269.3 1 Epomophorus grandis Epomophorus minimus [AT|AT] -269.3 1 Eonycteris major Pteropus neohibernicus [AA|AA] -269.3 0.9958 Eonycteris major Melonycteris woodfordi [AA|AA] -269.3 0.9947 Eonycteris major Eonycteris spelaea [IM|AA+IM+PA] -269.3 0.9879 Macroglossus minimus Melonycteris woodfordi [AA|AA] -269.4 0.9501 Macroglossus minimus Macroglossus sobrinus [AA|AA] -270.8 0.2229 Syconycteris hobbit Melonycteris woodfordi [AA|AA] -269.3 0.9982 Syconycteris hobbit Syconycteris carolinae [AA|AA] -269.3 0.9921 Syconycteris hobbit Syconycteris australis [AA|AA] -269.3 0.998 Notopteris macdonaldi Melonycteris woodfordi [AA|AA] -269.3 0.9973 Melonycteris melanops Melonycteris woodfordi [AA|AA] -269.3 0.992 Harpyionycteris celebensis Pteropus neohibernicus [AA|AA] -269.3 0.9979 Harpyionycteris celebensis Harpyionycteris whiteheadi [AA|IM] -269.4 0.9283 Aproteles bulmerae Pteropus neohibernicus [AA|AA] -269.3 0.9997 Aproteles bulmerae Dobsonia pannietensis [AA|AA] -269.4 0.9124 Dobsonia minor Dobsonia pannietensis [AA+IM|AA] -270 0.5251 Dobsonia minor Dobsonia beauforti [AA+IM|AA] -270 0.5251 Dobsonia minor Dobsonia peroni [AA|AA+IM] -270 0.5252 Dobsonia minor Dobsonia emersa [AA|AA] -269.3 1 Dobsonia exoleta Dobsonia peroni [AA|AA+IM] -270 0.5252 Dobsonia inermis Dobsonia beauforti [AA|AA] -269.3 1 Dobsonia praedatrix Dobsonia beauforti [AA|AA] -269.3 1 Dobsonia praedatrix Dobsonia viridis [AA|AA] -269.3 1 Dobsonia moluccensis Dobsonia pannietensis [AA|AA] -269.3 1 Styloctenium wallacei Pteropus neohibernicus [AA|AA] -269.3 0.9997 Styloctenium wallacei Neopteryx frosti [AA|AA] -269.3 0.9918 Pteralopex anceps Pteropus neohibernicus [AA|AA] -269.3 0.999 Pteralopex anceps Pteralopex atrata [AA|AA] -269.5 0.8532 Pteralopex anceps Pteralopex pulchra [AA|AA] -269.3 0.9979

Pteralopex acrodonta Pteralopex atrata [AA|AA] -269.5 0.8548 Acerodon leucotis Pteropus neohibernicus [AA|AA] -269.9 0.5287 Acerodon leucotis Acerodon jubatus [AA|AA+IM] -270.5 0.3078 Acerodon leucotis Acerodon mackloti [IM|AA] -269.9 0.5688 Acerodon celebensis Acerodon mackloti [AA|AA] -269.3 0.9912 Acerodon humilis Acerodon jubatus [AA|AA] -270.3 0.3869 Pteropus melanotus Pteropus neohibernicus [AA+IM|AA] -269.3 0.9893 Pteropus melanotus Pteropus lombocensis [AA+IM|AA] -269.3 0.9894 Pteropus melanotus Pteropus melanopogon [AA+IM|AA] -269.3 0.9882 Pteropus melanotus Pteropus dasymallus [AA+IM|IM] -269.3 0.9848 Pteropus melanotus Pteropus admiralitatum [AA+IM|AA] -269.3 0.9918 Pteropus melanotus Pteropus alecto [IM|AA+IM] -269.6 0.7741 Pteropus melanotus Pteropus faunulus [IM|IM] -269.3 0.9969 Pteropus melanotus Pteropus speciosus [IM|IM] -269.3 0.9992 Pteropus caniceps Pteropus alecto [AA|AA+IM] -270 0.4766 Pteropus caniceps Pteropus vampyrus [AA|AA] -269.6 0.7302 Pteropus caniceps Pteropus argentatus [AA|AA] -269.3 0.9974 Pteropus giganteus Pteropus vampyrus [IM|AA+IM] -269.4 0.93 Pteropus giganteus Pteropus lylei [IM|IM] -269.3 0.9874 Pteropus rayneri Pteropus admiralitatum [AA|AA] -269.3 0.9999 Pteropus rayneri Pteropus chrysoproctus [AA|AA] -269.3 0.9991 Pteropus rayneri Pteropus fundatus [AA|AA] -269.3 0.9998 Pteropus nitendiensis Pteropus admiralitatum [AA|AA] -269.3 1 Pteropus nitendiensis Pteropus pselaphon [AA|AA+OC] -269.3 0.9703 Pteropus insularis Pteropus pselaphon [OC|AA+OC] -269.4 0.9163 Pteropus tuberculatus Pteropus pselaphon [AA|AA+OC] -269.4 0.9067 Pteropus leucopterus Pteropus pselaphon [OC|AA+OC] -270.1 0.4578 Pteropus vetulus Pteropus pselaphon [AA|OC] -269.5 0.852 Pteropus livingstonei Pteropus melanopogon [AT|AA] -269.3 0.9734 Pteropus griseus Pteropus lombocensis [AA|AA] -269.3 1 Pteropus griseus Pteropus gilliardi [AA|AA] -269.3 1 Pteropus woodfordi Pteropus gilliardi [AA|AA] -269.3 0.9992 Pteropus scapulatus Pteropus gilliardi [AA|AA] -269.3 0.9999 Pteropus mahagnus Pteropus gilliardi [AA|AA] -269.3 1 Pteropus poliocephalus Pteropus lombocensis [AA|AA] -269.3 1 Pteropus poliocephalus Pteropus macrotis [AA|AA] -269.3 0.9991 Pteropus poliocephalus Pteropus pohlei [AA|AA] -269.3 0.9998 Pteropus molossinus Pteropus lombocensis [OC|AA] -270.2 0.4166 Pteropus rodricensis Pteropus lombocensis [OC|OC] -270.2 0.4236 Pteropus mariannus Pteropus neohibernicus [AA|AA] -269.3 0.9999 Pteropus mariannus Pteropus hypomelanus [AA|AA] -269.3 1 Pteropus mariannus Pteropus tonganus [OC|AA+OC] -269.3 0.9845 Pteropus pumilus Pteropus neohibernicus [AA|AA] -269.3 0.9999 Pteropus personatus Pteropus neohibernicus [AA|AA] -269.3 1 Pteropus personatus Pteropus samoensis [AA|AA] -269.3 1 Pteropus personatus Pteropus temmincki [AA|AA] -269.3 0.9993 Pteropus seychellensis Pteropus samoensis [AA|AA] -269.3 1 Pteropus seychellensis Pteropus aldabrensis [AT|AT] -269.6 0.7703 Pteropus seychellensis Pteropus niger [AT|AT] -269.3 0.9611 Pteropus voeltzkowi Pteropus niger [AT|AT] -269.3 0.9929 Pteropus rufus Pteropus niger [AT|AT] -269.3 0.9982 Pteropus anetianus Pteropus samoensis [AA|OC] -269.7 0.7038 Pteropus conspicillatus Pteropus neohibernicus [AA|AA] -269.3 1 Pteropus conspicillatus Pteropus ornatus [AA|AA] -269.3 1

Pteropus conspicillatus Pteropus ocularis [AA|AA] -269.3 0.999 Cardioderma cor Paracoelops megalotis [IM|IM] -269.6 0.7128 Cardioderma cor Rhinopoma hardwickei [IM|IM] -269.7 0.6464 Cardioderma cor Craseonycteris thonglongyai [IM|IM] -269.6 0.7462 Rhinolophus monoceros Paracoelops megalotis [IM|IM] -269.4 0.9335

New tree with no outgroups:

Most recent common ancestor of: Split: lnL: Rel.Prob: Plerotes ancheitae Paranyctimene raptor [AA+IM|IM] -295.6 0.4431 Plerotes ancheitae Nanonycteris veldkampi [AA+IM|AA] -294.9 0.827 Plerotes ancheitae Rousettus lanosus [AA+IM|IM] -295.1 0.7319 Plerotes ancheitae Pteropus leucopterus [AA|IM] -295.1 0.693 Plerotes ancheitae Rousettus obliviosus [AA|AA] -294.8 0.9379 Plerotes ancheitae Neopteryx frosti [AA|AA] -294.8 0.9595 Macroglossus minimus Rousettus obliviosus [AA|AA] -294.8 0.9776 Macroglossus minimus Styloctenium wallacei [AA|AA] -294.8 0.9892 Macroglossus minimus Notopteris neocaledonica [AA|AA] -294.7 0.9949 Macroglossus minimus Melonycteris melanops [AA|AA] -294.7 0.9984 Macroglossus minimus Syconycteris hobbit [AA|AA] -294.8 0.9066 Macroglossus minimus Macroglossus sobrinus [AA|AA+IM+PA] -296.4 0.1824 Syconycteris australis Syconycteris hobbit [AA|AA] -294.8 0.9878 Syconycteris carolinae Syconycteris hobbit [AA|AA] -294.8 0.9925 Melonycteris fardoulisi Melonycteris melanops [AA|AA] -294.8 0.9819 Melonycteris fardoulisi Melonycteris woodfordi [AA|AA] -294.8 0.9935 Notopteris macdonaldi Notopteris neocaledonica [AA|AA] -295.3 0.5803 Rousettus amplexicaudatus Rousettus obliviosus [AA|AA] -294.8 0.9797 Rousettus celebensis Rousettus obliviosus [AA|AT] -294.9 0.8302 Rousettus spinalutus Pteropus leucopterus [IM|IM] -295 0.7545 Rousettus aegyptiacus Rousettus lanosus [IM|IM] -295 0.743 Rousettus aegyptiacus Pteralopex acrodonta [IM|IM] -295 0.7443 Rousettus aegyptiacus Rousettus leschenaultii [AT+IM+PA|PA] -296.6 0.1629 Rousettus aegyptiacus Rousettus madagascariensis [AT+IM+PA|AT] -295.6 0.4242 Eonycteris major Rousettus lanosus [IM|IM] -295.3 0.5682 Eonycteris major Eonycteris spelaea [IM|IM] -295.5 0.4694 Eonycteris major Eonycteris robusta [IM|IM] -294.8 0.991 Pteralopex taki Nanonycteris veldkampi [AA|AA] -294.7 0.9974 Pteralopex taki Megaloglossus woermanni [AA|AA] -294.7 0.9977 Pteralopex taki Pteralopex pulchra [AA|AA] -294.8 0.9857 Pteralopex taki Pteralopex anceps [AA|AA] -294.7 0.9964 Lissonycteris angolensis Megaloglossus woermanni [AT|AT] -295 0.8048 Lissonycteris angolensis Melonycteris relicta [AT|AT] -294.8 0.9675 Myonycteris brachycephalus Melonycteris relicta [AT|AT] -294.7 0.9951 Myonycteris brachycephalus Myonycteris torquata [AT|AT] -294.7 0.9987 Pteralopex atrata Nanonycteris veldkampi [AA|AA] -294.7 0.9996 Rousettus bidens Nanonycteris veldkampi [AA|AA] -294.7 0.9997 Rousettus bidens Eidolon helvum [AA|AA] -294.8 0.9153 Rousettus bidens Harpyionycters whiteheadi [AA|AA] -294.8 0.9938 Aproteles bulmerae Harpyionycters whiteheadi [AA|AA] -294.8 0.9574 Aproteles bulmerae Dobsonia emersa [AA|AA] -294.8 0.9643 Dobsonia peroni Dobsonia emersa [AA|AA] -295 0.7798

Dobsonia minor Dobsonia emersa [AA|AA] -294.7 0.9995 Dobsonia minor Dobsonia magna [AA|AA] -294.7 0.9998 Dobsonia minor Dobsonia praedatrix [AA|AA] -294.7 1 Dobsonia minor Dobsonia anderseni [AA|AA] -294.7 1 Dobsonia moluccensis Dobsonia praedatrix [AA|AA] -294.7 1 Dobsonia moluccensis Dobsonia pannietensis [AA|AA] -294.7 0.9984 Dobsonia inermis Dobsonia praedatrix [AA|AA] -294.7 0.9983 Dobsonia inermis Dobsonia viridis [AA|AA] -294.7 0.999 Dobsonia exoleta Dobsonia emersa [AA|AA] -294.7 0.9996 Dobsonia exoleta Dobsonia crenulata [AA|AA] -294.7 0.9999 Dobsonia exoleta Dobsonia beauforti [AA|AA] -294.7 1 Harpyionycteris celebensis Harpyionycters whiteheadi [AA|IM] -294.9 0.8806 Eidolon dupreanum Eidolon helvum [AT|AT] -294.9 0.8533 Acerodon celebensis Nanonycteris veldkampi [AA|AA] -294.7 0.9998 Acerodon celebensis Pteropus woodfordi [AA|AA] -295.2 0.6363 Acerodon celebensis Acerodon jubatus [AA+IM|IM] -294.9 0.9001 Acerodon celebensis Acerodon leucotis [AA|AA+IM] -294.9 0.89 Acerodon makloti Acerodon leucotis [AA|IM] -294.8 0.9054 Acerodon makloti Acerodon humilis [AA|AA] -294.8 0.9846 Pteropus insularis Pteropus woodfordi [AA|AA] -294.8 0.9341 Pteropus insularis Pteropus yapensis [AA|AA] -294.8 0.913 Pteropus insularis Pteropus mariannus [AA|AA] -294.8 0.9601 Pteropus insularis Pteropus chrysoproctus [AA|AA] -294.7 0.9994 Pteropus insularis Pteropus faunulus [AA|AA] -294.7 0.9995 Pteropus insularis Pteropus banakrisi [AA|AA] -294.7 0.9998 Pteropus nitendiensis Pteropus banakrisi [AA|AA] -294.7 1 Pteropus rennelli Pteropus faunulus [AA|AA] -294.7 0.9997 Pteropus griseus Pteropus chrysoproctus [AA|AA] -294.7 0.9999 Pteropus tuberculatus Pteropus chrysoproctus [AA|AA] -294.7 1 Pteropus aruensis Pteropus mariannus [AA|AA] -294.8 0.9607 Pteropus aruensis Pteropus gilliardorum [AA|AA] -294.7 0.9991 Pteropus aruensis Pteropus caniceps [AA|AA] -294.7 1 Pteropus aruensis Pteropus mahagnus [AA|AA] -294.7 1 Pteropus macrotis Pteropus gilliardorum [AA|AA] -294.7 0.9991 Pteropus melanopogon Pteropus gilliardorum [AA|AA] -294.7 0.9991 Pteropus pselaphon Pteropus gilliardorum [AA|AA] -294.7 0.9991 Pteropus ualanus Pteropus mariannus [AA|AA] -294.8 0.9607 Pteropus ualanus Pteropus intermediu [AA|AA] -294.8 0.9609 Pteropus lombocensis Pteropus mariannus [AA|AA] -294.8 0.9636 Pteropus melanotus Pteropus yapensis [AA|AA] -294.8 0.933 Pteropus keyensis Pteropus yapensis [AA|AA] -294.8 0.9646 Pteropus personatus Pteropus woodfordi [AA|AA] -294.7 0.998 Pteropus giganteis Pteropus woodfordi [AA|AA] -294.7 0.9983 Pteropus giganteis Pteropus scapulatus [AA|AA] -294.9 0.8817 Pteropus giganteis Pteropus temminckii [AA|AA] -295.2 0.6658 Pteropus giganteis Pteropus rayneri [AA|AA] -294.9 0.8877 Pteropus giganteis Pteropus tonganus [AA|AA] -294.9 0.8907 Pteropus giganteis Pteropus speciosus [IM|IM] -295.4 0.5414 Pteropus giganteis Pteropus rodricensis [AT+IM|AT] -294.9 0.8584 Pteropus giganteis Pteropus vampyrus [AT+IM|IM] -294.9 0.852 Pteropus giganteis Pteropus rufus [IM|AT] -294.9 0.8627 Pteropus giganteis Pteropus lylei [IM|IM] -294.9 0.8675 Pteropus aldabrensis Pteropus rufus [AT|AT] -294.7 0.9968 Pteropus aldabrensis Pteropus seychellensis [AT|AT] -294.7 0.9996

Pteropus niger Pteropus seychellensis [AT|AT] -294.7 0.9999 Pteropus dasymallus Pteropus speciosus [IM|IM] -294.9 0.8617 Pteropus pumilus Pteropus speciosus [IM|IM] -294.7 0.9987 Pteropus capistratus Pteropus tonganus [AA|AA] -294.7 0.9978 Pteropus capistratus Pteropus vetulus [AA|AA] -294.7 0.9984 Pteropus ocularis Pteropus tonganus [AA|AA] -294.8 0.9891 Pteropus ocularis Pteropus poliocephalus [AA|AA] -294.7 0.9998 Pteropus ocularis Pteropus ornatus [AA|AA] -294.7 0.999 Pteropus alecto Pteropus tonganus [AA|AA] -295 0.7697 Pteropus alecto Pteropus hypomelanus [AA|AA] -294.8 0.9856 Pteropus alecto Pteropus neohibernicus [AA|AA] -294.8 0.9912 Pteropus alecto Pteropus conspicillatus [AA|AA] -295.2 0.6472 Pteropus admiralitatum Pteropus hypomelanus [AA|AA] -294.9 0.8192 Pteropus admiralitatum Pteropus pohlei [AA|AA] -294.7 0.9999 Pteropus anetianus Pteropus rayneri [AA|AA] -295.1 0.7243 Pteropus samoensis Pteropus rayneri [OC|AA] -294.9 0.8427 Pteropus cognatus Pteropus rayneri [AA|AA] -294.8 0.9939 Pteropus cognatus Pteropus fundatus [AA|AA] -294.7 0.9985 Pteropus livingstonii Pteropus temminckii [AA|AA] -295 0.7456 Pteropus livingstonii Pteropus voeltzkowi [AT|AT] -295 0.7704 Pteropus molossinus Pteropus woodfordi [OC|AA] -294.8 0.9423 Casinycteris argynnis Nanonycteris veldkampi [AT|AT] -295.2 0.6317 Casinycteris argynnis Hypsignathus monstrosus [AT|AT] -294.8 0.9829 Casinycteris argynnis Epomophorus wahlbergi [AT|AT] -294.7 0.9984 Casinycteris argynnis Micropteropus pusillus [AT|AT] -294.7 0.9993 Casinycteris argynnis Scotonycteris zenkeri [AT|AT] -294.7 0.9996 Scotonycteris ophiodon Scotonycteris zenkeri [AT|AT] -294.7 0.9998 Micropteropus intermedius Micropteropus pusillus [AT|AT] -294.7 0.9996 Epomophorus grandis Epomophorus wahlbergi [AT|AT] -294.7 0.9993 Epomophorus grandis Epomophorus labiatus [AT|AT] -294.7 0.9998 Epomophorus grandis Epomophorus angolensis [AT|AT] -294.7 1 Epomophorus grandis Epomophorus minimus [AT|AT] -294.7 1 Epomophorus crypturus Epomophorus angolensis [AT|AT] -294.7 1 Epomophorus gambianus Hypsignathus monstrosus [AT|AT] -294.8 0.9943 Epomops buettikoferi Hypsignathus monstrosus [AT|AT] -294.7 0.9985 Epomops buettikoferi Epomops franqueti [AT|AT] -294.7 0.9991 Epomops buettikoferi Epomops dobsonii [AT|AT] -294.7 0.9996 Aethalops aequalis Paranyctimene raptor [IM|IM] -295.3 0.562 Aethalops aequalis Megaerops niphanae [IM|IM] -294.8 0.9288 Aethalops aequalis Dyacopterus spadiceus [IM|IM] -294.8 0.9782 Aethalops aequalis Sphaerias blanfordi [IM|IM] -294.8 0.9607 Aethalops aequalis Latidens salimalii [IM|IM] -294.8 0.9718 Aethalops aequalis Otopteropus cartilagonodus [IM|IM] -294.8 0.964 Aethalops aequalis Thoopterus nigrescens [IM|IM] -295.1 0.7356 Aethalops aequalis Chironax melanocephalus [IM|IM] -294.9 0.8654 Aethalops aequalis Penthetor lucasi [IM|IM] -294.7 0.9954 Aethalops aequalis Balionycteris maculata [IM|IM] -294.8 0.9879 Aethalops aequalis Aethalops alecto [IM|IM] -294.9 0.8674 Alionycteris paucidentata Otopteropus cartilagonodus [IM|IM] -294.7 0.9953 Haplonycteris fischeri Otopteropus cartilagonodus [IM|IM] -294.8 0.9946 Dyacopterus brooksi Dyacopterus spadiceus [IM|IM] -294.8 0.982 Cynopterus titthaecheilus Megaerops niphanae [IM|IM] -294.8 0.9405 Cynopterus titthaecheilus Ptenochirus minor [IM|IM] -294.8 0.9638 Cynopterus titthaecheilus Cynopterus sphinx [IM|IM] -295.1 0.7346

Cynopterus titthaecheilus Cynopterus horsfieldii [IM|IM] -294.9 0.8468 Cynopterus brachyotis Cynopterus horsfieldii [IM|IM] -294.8 0.9073 Cynopterus brachyotis Cynopterus luzoniensis [IM|IM] -294.8 0.9074 Cynopterus minutus Cynopterus luzoniensis [AA+IM|AA] -294.9 0.8433 Cynopterus minutus Cynopterus nusatenggara [AA+IM|AA] -296.3 0.2077 Megaerops wetmorei Ptenochirus minor [IM|IM] -294.7 0.9982 Ptenochirus jagori Ptenochirus minor [IM|IM] -294.7 0.999 Megaerops ecaudatus Megaerops niphanae [IM|IM] -294.8 0.9599 Megaerops kusnotoi Megaerops niphanae [IM|IM] -294.9 0.8769 Nyctimene certans Paranyctimene raptor [AA|AA] -295.2 0.6433 Nyctimene certans Nyctimene robinsoni [AA|AA] -295 0.811 Nyctimene certans Nyctimene albiventer [AA|AA] -294.7 0.9954 Nyctimene certans Nyctimene vivcaccia [AA|AA] -294.7 0.9976 Nyctimene major Nyctimene vivcaccia [AA|AA] -294.7 0.9994 Nyctimene aello Nyctimene robinsoni [AA|AA] -294.9 0.8156 Nyctimene aello Nyctimene cyclotis [AA|AA] -294.9 0.8177 Nyctimene rabori Nyctimene cyclotis [AA|AA] -295 0.7849 Nyctimene minutus Nyctimene cyclotis [AA|AA] -294.7 0.9987 Nyctimene minutus Nyctimene draconilla [AA|AA] -294.7 0.9993 Nyctimene malaitensis Nyctimene draconilla [AA|AA] -294.7 0.9998 Nyctimene keasti Nyctimene cyclotis [AA|AA] -294.7 0.9994 Nyctimene sanctacrucis Nyctimene cyclotis [AA|AA] -294.7 0.9999 Nyctimene masalai Nyctimene cyclotis [AA|AA] -294.7 1 Nyctimene cephalotes Nyctimene robinsoni [AA|AA] -294.7 0.9975

Appendix 6 – DIVA results Original tree with no outgroups:

The optimal distributions for each node are shown for the original tree with no outgroups. The tree has been split up into two halves (a) and (b).