The Gotham Project: Patterns of diversification in bats - Are specialists the new generalists?
thegothamproject.png

Proposal for a three-year international collaborative project

Bronzati M.1, Cunha A. 2, Lemer S. 3, Miller S. 4, Oses G.5, Pappalardo P.6, Schneider D. 7, St-Onge P. 8

1 Dept. of Biology, Faculty of Philosophy Science and Letters of Ribeirão Preto, University of São Paulo, São Paulo, Brazil; 2 Dept. of Zoology, University of São Paulo, São Paulo, Brazil; 3 Dept. Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, USA; 4 CERMES, University of West Indies, Cave Hill Campus, Barbados, 5 Institute of Geosciences, University of São Paulo, São Paulo, Brazil; 6. Dept. of Ecology, Pontificia Universidad Católica de Chile, Santiago, Chile; 7 Dept. Cell and Development Biology, Medical University of Vienna, Vienna, Austria; 8 Institut des Sciences de la Mer, Université du Québec à Rimouski, Rimouski, Canada.

CONCEPTUAL FRAMEWORK

This study aims to evaluate the evolution of feeding strategies in bats, regarding the possible implications of adopting different feeding strategies in the diversification rates of lineages within the order Chiroptera. In this sense, this study will answer the following questions:
1. Did lineages with generalist feeding strategies evolve from specialized ancestors in the evolutionary history of Chiroptera?
2. Did this transition from a specialist to a generalist feeding strategy lead to the relaxation of selection pressure on genes involved in feeding (i.e., skull morphology, metabolism)?
3. Are diversification rates of lineages within Chiroptera related to their feeding strategies, and if so, what type of feeding strategy would lead to higher diversification rates in this group?

INTRODUCTION & BACKGROUND

Generalist and specialist strategies

In a constantly changing world, it is very important to understand the processes underlying species responses to environmental changes. Species may adopt different strategies to persist in heterogeneous environments, and among them, specialization and generalization strategies have been studied from different perspectives in many animal groups, e.g., [29], [11], [55]; for more references see [10]. These studies have settled some general hypotheses concerning those different strategies: the resource-use hypothesis [54] (also see [7]), the generalist-to-specialist hypothesis and the dead-end hypothesis [22], [10].

The resource-use hypothesis stresses that generalist species are less susceptible to the lack of resources since they are able to use different resources in different environments and, therefore, are not severely affected by habitat fragmentation [54], [7]. This leads to lower extinction rates but also lower speciation rates in these lineages [54]. The dead-end hypothesis follows this line of thought, stressing that specialization is a path of no return, since species become highly ecologically specialized and lose their capacity of adapting to different resources or novel environments, being, therefore, doomed to extinction [22] (see [33]). In this sense, specialization might be considered a derived condition and most likely irreversible to the generalist condition [22], [30]. This finally leads to the generalist-to-specialist hypothesis, which stresses that most specialist species are likely to have evolved from generalist lineages [22], [49].

In fact, that trend is commonly reported in the literature (e.g., [8], [49], see [10] for a review). However, the fact that specialist and generalist concepts should be treated as a continuum [27], [38], may justify the existence of many other possibilities. Some studies have shown that both transitions, i.e., generalist to specialist or specialist to generalist, are likely to occur at similar rates [36] [37] and species with a specialized ancestor may evolve to adopt generalist strategies [26]. Also, a recent study has shown that broad niche widths are not always associated to low speciation rates but may in fact lead to higher speciation [6]. These facts highlight the importance of investigating the opposite scenario: a specialist to generalist diversification.

Diversification rates

The processes of speciation and extinction determine the species richness in a clade. For this reason, the estimation of diversification rates can shed light into the factors responsible for the patterns of diversity [2], [41]. Recently, the methods for analyzing diversification rates have been growing, incorporating environmental, density-dependent, and trait-dependent effects [48]. Diversification rates can be affected by attributes of the species or environmental factors; biotic interactions could be more important at smaller scales, but large patterns of diversity are driven by the physical environment [5]. We chose bats as a model system because previous work has shown variation in the diversification rates between clades [28], and that allows us to analyze whether the differences in diversification rates are related to ecological traits shared by those clades.

Model organism Chiroptera

Bats belong to the group Chiroptera, the most species-rich group of Mammalia, encompassing more than 1200 species, which represents 20% of all mammalian diversity and are the only mammals capable of true and sustained flight [44], [51]. Van Valen [52] pointed out that “one may hypothesize that bats did originate, but it is harder to go beyond this” and indeed many difficulties in studying bats are known from literature. One problem is related to their position within Mammalia. Early studies considered Chiroptera to be more related to primates and lemurs, but molecular analyses are now positioning bats within the superorder Laurasiatheria, sister group of a clade composed of the Carnivora, Perissodactyla and Artiodactyla [34]. Regarding its internal relationships, there is also a controversial scenario. Bats were classically divided into two clades, the Megachiroptera and the Microchiroptera. However, molecular analyses indicate a paraphyletic condition for microbats with megabats nested among its lineages [51] (Fig. 1). Finally, the pattern observed regarding the diversity of Chiroptera families, with a high number of species-poor clades and a few number of species-rich clades [28], makes Chiroptera an interesting model to test our hypotheses. Some studies demonstrate that the diversification of Chiroptera groups were driven by changes in feeding habits [23] since there was an increase in the diversity of flowering plants and insects in the Tertiary period, allowing bats to explore distinct feeding strategies [3].

Figure_1.png

Figure 1. Left: Cladogram depicting the phylogenetic relationships of Chiroptera and their geographical distribution (modified from [51] ). Right: Greater Horseshoe Bat in flight. Photo by Sung-Chol Kang at Manjang Cave, Cheju Island, Korea;
www.animalpicturesarchive.com/anima/a4/Korean/Chiroptera-Greater_Horseshoe_Bat_J02-in_flight.jpg

Bats display a broad range of specialized morphological, physiological and behavioral traits associated with their feeding ecology (Fig. 2). Overall, we observe seven types of specialized foraging strategies in bats, i.e., insectivorous, sanguinivorous, carnivorous, nectarivorous, herbivorous, frugivorous and piscivorous [21]; [43] . Our study will focus on “specialist” species that feed on only one type of prey (e.g., insects or fruits) and “generalist” species that can feed on more than one type of prey (e.g., both insects and fruits). Previous studies have shown that within the family Phyllostomidae, multiple types of specialist species have radiated [21]; [53]. More than 70% of chiropterans are considered insectivores, an adaptation that is thought to have been reinforced by the evolution of echolocation for spatial orientation [42]. Frugivorous species are mostly, but not exclusively, found within the wider Megachiroptera clade, also known to include some of the largest bats in the world*. However, despite having phylogenetic trends in feeding specialties, several bat species are not restricted to only one diet and are capable of acquiring different types of resources. A good example is Daubenton’s bat (Myotis daubentonii), which is specialized in catching flying insects but can also catch and consume fish [43]. Macrotus spp. was also shown to have the ability of feeding on both insects and fruits [21]. In this context, such species should thus be considered generalists.

Morphological characters of the skull as well as dental features can be used to distinguish different feeding habits including: size, width of face, rostral length, thickness of dentary, relative size of molars and the W-shape of the upper molar row [21]. The most distinguishing morphological variations in insectivores are those correlated with the hardness of their prey [17] [18]. Durophagous bats exhibit toothrows with few but large teeth, and have cranial crests and canines longer than the maxillary toothrow length [21]. In contrast, non-durophagous bats have long thin jaws, delicate skulls, absent or non-developed cranial crests and also more and smaller teeth as well as small canines [21]. Carnivores are characterized by modifications on the lower toothrow and teeth larger than the palate. Nectarivores exhibit a longer rostrum, reduced teeth number on the palate and a specialized tongue [19] [20]. Frugivorous bats display highly diversified teeth morphologies, palates wider than long, a greater allocation of tooth area at the anterior end of the toothrow and smaller area occupied by canines, in comparison to carnivores. Finally, sanguinivorous (blood-feeding) bats have less molars and well-developed canines and incisors. Freeman [19] also points out that omnivorous bats have a more equal distribution area related to different teeth types. Additionally, the two existing types of echolocation in insectivorous durophagous bats are distinguishable based on skull morphology [21]. Typically, oral-emitting bats are wide/short-faced, which brings jaw muscles closer to the jaw joint. In contrast, nasal-emitting bats are narrow/long-faced, displaying tall sagittal crests and thick dentaries [18].

fig2.png

Figure 2: Examples of cranial ecomorphos in the most diverse family of Chiroptera, phyllostomids, and their relation to the feeding types (modified from [21]).

Molecular data suggest a large gap in the fossil record of bats [51], but a rich fossil register is known from Eocece deposits. These deposits are very important to the knowledge of early bat evolution [46]. Moreover, almost all extant families of Chiroptera have fossil representatives [3]. Hence, fossils are able to provide the possibility of documenting sequence transformation in morphological structures and can play a major role in reconstructing ancestral states [47], [45].

HYPOTHESES

1. Diverse studies in a broad range of model organisms suggest that specialists arise from generalists more frequently than vice versa. In contrast, the opposite scenario has been observed in the most diverse clade of the order Chiroptera - Phyllostomidae [18]. Based on these observations, we hypothesize that multiple transitions from specialists to generalists occurred in the order Chiroptera through its evolutionary history. One of the key parameters fostering such transitions might be dietary change triggering modifications in bat skull morphologies.

2. Adaptation to a changing environmental condition leads to higher selective pressure on specific genes (e.g., genes involved in skull morphology and metabolism). We hypothesize that transition from specialist to generalist leads to relaxation of selection pressure operating on these genes.

3. Diversification rates can be affected by particular attributes of the species. We hypothesize that diversification rates in bats are related to their specialization to feeding types, and based on this premise, we expect that specialists (one type of prey consumed) will have different diversification rates than generalists (two or more prey items consumed).

EXPERIMENTAL DESIGN

Sampling Methods

Feeding habits of extant species will be inferred from their general ecology and data will be obtained from the literature and also from research collaborators. Feeding habits will be inferred based on the general morphology of the skull for extant and fossil species from which there is no ecological data available (Fig. 2). Molecular data will be retrieved from GenBank (245326 available sequences for the order Chiroptera, 3 ongoing genome sequencing projects and three available genomes-ID: 11703, 757 and 614). Species not represented in GenBank will be both sampled according to previous described methods (biopsy samples of the wings membrane using a three mm biopsy punch [25]) and provided by our worldwide network of collaborators.

Reconstructing the phylogeny

With the sequence data available in GenBank, we aim to reconstruct a complete Chiroptera phylogeny. Calibration with fossils is possible in Chiroptera, which allows an accurate calibration of trees. Each gene will be evaluated for saturation with the test of Chia implemented in DAMBE [56], aligned with MUSCLE [14] and edited in MEGA [50]. Subsequently, all informative genes will be concatenated in Mesquite [32] in a final database for phylogenetic inference. With concatenated aligned sequences we will simultaneously estimate phylogenetic relationships, branch lengths and divergence times for the species found using BEAST 1.6.2 software [13], which can include fossils for calibration. The analysis will be run in a Bayesian framework using Markov Chain Monte Carlo (BMCMC) methods to account for uncertainty in parameters indicated above. To evaluate the transition rates (specialists - generalists), we will insert the fossil taxa in the topology using the backbone constraint method.

Evolution of diet and its relationship with diversification rates

Using the continuous-time Markov k-state model [39] , [40] implemented in R package Diversitree [16], we will evaluate ancestral feeding strategies, and the most probable transition between them. For this we will use both the topology as well as the branch lengths obtained from the sample of trees in BMCMC analysis. The categorical variables assigned to determine the transition rates between diet types are: 0 = specialists, indicating one type of prey (e.g., nectarivorous); 1 = generalists, indicating two or more types of prey (e.g., frugivorours and insectivorous). Integrating the continuous-time Markov k-state model, and birth-death models we will evaluate the effect of feeding strategy on diversification rates. This analysis will be performed with MuSSE (Multiple State Speciation and Extinction; [15]) method implemented in R package Diversitree [16]. MuSSE is an extension of the “Binary State Speciation Extinction ” (BiSSE) methods (described in [31]), and computes the probability of a phylogenetic tree and the observed distribution of character states among extant species, given a model of character evolution, speciation and extinction. We will select the best model of diversification using the Akaike Information Criterion (AIC).

Candidate gene approach to examine selection pressure variation

Variation between species are often associated with morphological differences (e.g., body size, shape, color, etc). Each of these characteristics is only partially controlled by genes. The complex interaction between genes and the environment, as well as between multiple genes, exacerbates the difficulty to understand and quantify phenotypic variation. Therefore looking for nucleotide sequence variation in the genome is a straightforward way to tackle the source underlying phenotypic differences. For this study, the identification of single base changes (single nucleotide polymorphisms, or SNPs) is an ideal method to determine the role that natural selection has played in the wide range of phenotypic variation observed in bats. By comparing alleles among species as well as non-synonymous and synonymous mutation ratios we expect to demonstrate that over the course of modern bat evolution, certain genetic changes have been selected for or against whether the species evolved specialist or generalist feeding strategies. To measure this, we will extract high quality DNA from preserved tissue samples using commercial DNA extracting kits and analyze candidate genes using classic Sanger sequencing. We will estimate the dN/dS ratio per site (non-synonymous vs. synonymous single nucleotide mutations) on a set of genes involved in the development of skull morphology and metabolism to compare them among lineages, according to the codon substitution model, described in [24], using the Codeml program of the PAML v.4 package [57], [58]. The genes will be selected based on homologous genes (retrieved from GenBank) known to play these roles in close relative taxa of Chiroptera (Fig. 3).

In addition to the candidate gene approach we will screen annotated genomes of Eptesicus fuscus (ID: 17703), Pteropus vampyrus (ID: 757), Myotis lucifugus (ID: 614), via an in silico approach, for key genes in the development of skull morphology and metabolism to analyze the obtained genes as described earlier. Applying this approach to Chiroptera will be the first attempt to correlate molecular signatures of diversification to morphological patterns and the fossil record.

Folie1_new.png

Figure 3. Flowchart describing the molecular approach to track down signatures of diversification in bats. Approach consists both in silico and in vivo experimental steps. Identifying candidate genes and screening for homologs rely on sequence data available in GenBank (see above).

BROADER IMPLICATIONS FOR THE CONSERVATION OF BATS

Understanding the evolutionary history and predicting future patterns of diversification can have important implications for conservation of bats. Bats are part of the global ecosystem and, like every living organism, play an important role in continued evolution of our planet. Bats not only help maintain balance in the natural world (i.e. pollination, predation on insects, etc), they also influence human culture (i.e., Batman) and even support important advances in medicine. For example, thrombolytic or “clot busting” properties of enzymes in vampire bat saliva are being used to create drugs to help blood clot patients [12]. Despite their value, misconceptions and negative connotation of bats have historically made conservation difficult [3]. In some cultures in Central America, where vampire bats can be a problem for livestock, locals find and destroy bat caves, killing entire colonies whether they are colonies of vampire bats or not.

The International Union for Conservation of Nature (IUCN) includes 521 bats on its Red List of Threatened Species: 29 are Critically Endangered, facing an extremely high risk of extinction; 37 are Endangered, facing a very high risk of extinction; 173 are Vulnerable, facing a high risk of extinction. Eight species have not been recorded for over 50 years. Additionally, many species are so poorly documented that we may be unaware of their extinction [4]. With few natural predators, the primary reason for declining bat populations are largely anthropogenic. Urban development (deforestation) and agricultural practices (pesticide use) cause habitat destruction, fragmentation, degradation and reduce food sources. Misguided protection and exploitation for human consumption also has lead to population declines. Unless action is taken to increase protection of bat species, extinction, and thereby decreased diversification of bats will continue to be a critical threat. Extinction of more bat species could have significant ecological and evolutionary consequences. For example, the decline of fruit bats (Pteropodidae), which are a disproportionately endangered family, could have devastating effects on islands that rely on their ecological role in maintaining balance [3]. Conservation efforts need to be better highlighted and implemented. Education and outreach, promoting awareness and dismissing myths about bats should be prioritized.

Through this research we will strive to answer the question, are specialists the new generalists? Can bat species that once only fed on one specific type of prey evolve in a way that their feeding strategies include several types of prey? If our results support this assumption, bats may be more resilient to environmental change (e.g., shifts in food resources). In either case, results from this study will have broad implications for the future of bats.


Bibliography
1. Akey, J.M., Zhang, G., Zhang, K., Jin, L., Shriver, M.D. Interrogating a high-density SNP map for signatures of natural selection. Genome Research 12, 1805-1814, 2002; Akey, J.M., Eberle, M.A., Rieder, M.J., Carlson, C.S., Shriver, M.D., Nickerson, D.A., Kruglyak, L. Population history and natural selection shape patterns of genetic variation in 132 genes. PLoS Biol 2, 10:e286, 2004.
2. Allen, A.P., Gillooly, J.F. Assessing latitudinal gradients in speciation rates and biodiversity at the global scale. Ecology Letters 9, 947-954, 2006.
3. Altringham, J.D. Bats: from evolution to conservation. Oxford University Press, New York, USA, 2011.
5. Benton, M.J. The Red Queen and the Court Jester: species diversity and the role of biotic and abiotic factors through time. Science 323, 728-732, 2009.
6. Birand, A.A., Vose, A., Gavrilets, S. Patterns of species ranges, speciation and extinction. The American Naturalist 179, 1, DOI: 10.1086/663202, 2012.
7. Bofarull, A.M., Royo, A.A., Fernández, M.H., Ortiz-Jaureguizar E., Morales, J. Influence of continental history on the ecological specialization and macroevolutionary processes in the mammalean assemblage of South America: differences between small and large mammals. BMC Evolutionary Biology 8, 97, 2009.
8. Braendle, M., Prinzing, A., Pfeifer, R., Brandl, R. Dietary niche breadth for Central European birds: correlations with species-specific traits. Evolutionary Ecology Research 4, 643-657, 2002.
9. Carstens, B.C.,Lundrigan, B.L., Myers, P. A phylogeny of the Neotropical nectar feeding bats (Chiroptera: Phyllostomidae) based on morphological and molecular data. Journal of Mammalian Evolution. 9, 23-53, 2002.
10. Colles, A., Liow, L.H., Prinzing, A. Are specialists at risk under environmental change? Neoecological, paleoecological and phylogenetic approaches. Ecology Letters 12, 849-863, 2009.
11. Crespi, B.J., Sandoval, P.C. Phylogenetic evidence for the evolution of ecological specialization in Timema walking-sticks. Journal of Evolutionary Biology 13, 249-262, 2000.
12. Currie, S., Bats Helping Humans: Medical Advances. Organization for Bat Conservation, Cranbrook Institute of Science, 2012.
13. Drummond, A.J. and Rambaut, A. 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology 7:214.
14. Edgar, R.C. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797.
15. FitzJohn, R.G. 2010. Quantitative traits and diversification. Systematic Biology 59: 619-633.
16. FitzJohn, R.G.; Golberg, E.E. and Magnuson-Ford, K. 2012. diversitree: comparative phylogenetic analyses of diversification. R package version 0.9-1, http://CRAN R-project.org/package=diversitree.
17. Freeman, P.W. 1979. Specialized insectivory: beetle-eating and moth-feeding molossid bats. Journal of Mammalogy, 62:467-479.
18. Freeman, P.W. 1981. Correspondence of food habits and morphology in insectivorous bats. Journal of Mammalogy, 62, 166-173.
19. Freeman, P.W. 1988. Frugivorous and animalivorous bats (Microchiroptera): dental and cranial adaptations. Biological Journal of the Linnean Society, 33: 249-272.
20. Freeman, P.W. 1995. Nectarivorous feeding mechanisms in bats. Biological Journal of the Linnean Society, 56: 439-463.
21. Freeman, P.W. 2000. Macroevolution in Microchiroptera: recoupling morphology and ecology with phylogeny. Evolutionary Ecology Research, 2:317-335.
22. Futuyma, D.J., Moreno, G. The evolution of ecological specialization. Annual Review of Ecology and Systematics 19, 207-233, 1988; Futuyma, D.J. Evolution. Sinauer Associates, Publishers Sunderland, Massachusetts, USA, 2005.
23. Gianinni, N.P., Kalko, E.K.V. Trophic structure in a large assemblage of phyllostomid bats in Panama. Oikos 105, 209-220, 2004.
24. Goldman, N., Yang, Z. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mot. Biol. Evol. 11. 725-736, 1994.
25. Guevara-Chumacero, L.M., Lopez-Wilchis, R., Pedroche, F.F., Juste. J., Ibanez, C., Barriga-Sosa, I.D.L.A. Molecular phylogeography of Pteronotus davyi
(Chiroptera: Mormoopidae) in Mexico. Journal of Mammalogy 91, 220-232, 2010.
26. Janz N., Nyblom, K., Nylin, S. Evolutionary dynamics of host-plant specialization: a case study of the tribe Nymphalini. Evolution 55, 783-796, 2001.
27. Johnson, S.D., Steiner, K.E. Generalization versus specialization in plant pollination systems. Tree 15, 140-143, 2000.
28. Jones, K.E., Olaf, R.P., Bininda-Emonds, O.R.P., Gittleman, J.L. Bats, clocks, and rocks: diversification patterns in Chiropera. Evolution 59, 2243-2255, 2005.
29. Kammer, T.W., Baumiller, T.K., Ausich, W.I. Evolutionary significance of differential species longevity in Osagean-Meramecian (Mississippian) crinoid clades. Paleobiology 24, 155-176, 1998.
30. Kelley, S.T., Farrell, B.D. Is specialization a dead-end?: The phylogeny of host use in Dendroctonus bark beetles (Coleoptera: Scolytidae). Evolution 52, 1731-1743, 1998.
31. Maddison, W.P.; Midford, P.E. and Otto, S.P. 2007. Estimating a binary character ’s effect on speciation and extinction. Systematic Biology 56:701–710.
32. Maddison, W.P. and Maddison, D.R. 2011. Mesquite: a modular system for evolutionary analysis. Version 2.75 http://mesquiteproject.org,
33. Munday, P.L. Habitat loss, resource specialization, and extinction on coral reefs. Global Change Biology 10, 1642-1647, 2004.
34. Murphy, W.J., Eizirik, E., O’Brien, S.J., Madsen, O., Scally, M., Douady, C.J., Teeling, E., Ryder, O.A., Stanhope, M.J., de Jong, W.W., Springer, M.S. Resolution of the early placental mammal radiation using bayesian phylogenetics. Science 294, 2348-2351, 2001.
35. Nielsen, R., Bustamante, C., Clark, A.G., Glanowski, S., Sackton, T.B., Hubisz, M.J., Fledel-Alon, A., Tanenbaum, D.M., Civello, D., White, T.J., Sninsky, J.J., Adams, M.D., Cargill, M. A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biology 3, 6: e170, 2005.
36. Nosil, P. Transition rates between specialization and generalization in phytophagous insects. Evolution 56, 1701–1706, 2002.
37. Nosil, P., Mooers, Ø. Testing hypotheses about ecological specialization using phylogenetic trees. Evolution 59, 2256-2263, 2005.
38. Ollerton, J., Killick, A., Lamborn, E., Watts, S., Whiston, M. Multiple meanings and modes: on the many ways to be a generalist flower. Taxon 56, 717-728, 2007.
39. Pagel, M. 1994. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proceedings of The Royal Society of London B 255:37-45.
40. Pagel, M. 1997. Inferring evolutionary processes from phylogenies. Zoologica Scripta 26:331–348.
41. Ricklefs, R.E. Estimating diversification rates from phylogenetic information. TRENDS in Ecology and Evolution 22, 601-610, 2007 .
42. Schnitzler H.-U., Moss C.F., Denzinger A. (2003) From spatial orientation to food acquisition in echolocating bats. Trends in Ecology and Evolution 18(8): 386-394
43. Siemers B.M., Dietz C., Nill D., Schnitzler H.-U. (2001) Myotis daubentonii is able to catch small fish. Acta Chiropterologica 3(1): 71-75
44. Simmons, N.B. An Eocene Big Bang for Bats. Science 307, 527-528, 2005.
45. Slater, G.J., Harmon, L.J., Alfaro, M.E. Integrating fossils with molecular phylogenies improves inference of trait evolution. Evolution. in press.
46. Speakman, J.R. The evolution of flight and echolocation in bats: another leap in the dark. Mamal Review 31, 111-130, 2001.
47. Springer 2001
48. Stadler, T. Inferring speciation and extinction processes from extant species data. PNAS 108, 16145-16146, 2011.
49. Stephens, P.R., Wiens, J.J. Ecological diversification and phylogeny of emydid turtles. Biological Journal of the Linnean Society 79, 577-610, 2003.
50. Tamura, K.: Peterson, D.: Peterson, N.: Stecher, G.: Nei, M. and Kumar, S. 2011. MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution 28:2731-2739.
51. Teeling, E.C., Springer, M.S., Madsen, O., Bates, P., O’Brien, J.O., Murphy, W.J. A molecular phylogeny for bats illuminates biogeography and the fossil record. Science 307, 580-584, 2005.
52. Valen, van, L. The evolution of bats. Evolutionary Theory 4, 103–121, 1979.
53. van Cakenberghe V., Herrel A., Aguirre L.F. (2002) Evolutionary relationships between cranial shape and diet in bats (Mammalia: Chiroptera). Topics in Functional and Ecological Vertebrate Morphology 205-236
54. Vrba, E.S. Ecology in relation to speciation rates: some case histories of Miocene-Recent mammal Clades. Evolutionary Ecology 1, 283-300, 1987; Vrba, E.S. Mammals as a key to evolutionary theory. Journal of Mammalogy 73, 1-28, 1992.
55. Warren, M.S., Hill, J.K., Thomas, J.A., Asher, J., Fox, R., Huntley, B., Roy, D.B., Telfer, M.G., Jeffcoate, S., Harding, P., Jeffcoate, G., Willis, S.G., Greatorex-Davies, J.N., Moss, D., Thomas, C.D. Rapid responses of British butterflies to opposing forces of climate and habitat change. Nature 414, 65-69. 2001.
56. Xia, X. and Xie, Z. 2001. DAMBE: Software package for data analysis in molecular biology and evolution. The Journal of Heredity 92:371-373.
57. Yang, Z. PAML 4: Phylogenetic Analysis by Maximum Likelihood. 24 (8): 1586-1591.2007
58. Yang. Z., PAML: a program package for phylogenetic analysis by maximum likelihood. CABIOS APP. NOTE., 13(5),555-556, 1997
Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3.0 License