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Wing Loading Correlates Negatively with Genetic Structuring of Eight Afro-Malagasy Bat Species (Molossidae)Author(s): Peter J. Taylor, Steven M. Goodman, M. Corrie Schoeman, Fanja H. Ratrimomanarivo andJennifer M. LambSource: Acta Chiropterologica, 14(1):53-62. 2012.Published By: Museum and Institute of Zoology, Polish Academy of SciencesDOI: http://dx.doi.org/10.3161/150811012X654268URL: http://www.bioone.org/doi/full/10.3161/150811012X654268

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INTRODUCTION

Bats in general exhibit low fecundity coupledwith long lifespan compared with similar-sized ter-restrial mammals, making them interesting modelsto study with respect to possible life history cor-relates of molecular diversity. By com parison, thelifespan of female shrews is ten times shorter, theyproduce an additional litter per year and 3.7 timesmore offspring, lactate for a 2.4 times shorter peri-od, and wean litters three times heavier than similar-sized female insectivorous bats (Barclay and Harder,2003).

Based on comparisons at broad taxonomic levels,it has been recently suggested that variation inmtDNA diversity in mammals and birds cannot beexplained by life history variables but instead is dueto profound erratic or intrinsic variation in mutationrates, which according to the longevity hypothesismay in turn affect factors such as lifespan (Nabholz

et al., 2008, 2009). However, Martin and Palumbi(1993) show a strong inverse relationship betweennuclear and mitochondrial DNA substitution rateand body size in mammals, evidence for the meta-bolic rate hypothesis whereby smaller organismshaving higher mass-specific metabolic rates may exhibit higher mitochondrial mutation rates (Martinand Palumbi, 1993; Gillooly et al., 2005). In con-trast, Lanfear et al. (2007) found no evidence thatmass-specific metabolic rate drives substitution ratein metazoans. In terms of spatial genetic structuringof populations, a negative correlation between dis-persal ability and genetic structure has been well established in a broad spectrum of animal taxa(Bohonak, 1999).

The degree of spatial partitioning of genetic diversity in bats, to which flight lends a high poten-tial for dispersal, is notably variable. Some spe-cies show high levels of molecular variation, withlittle geographic structuring even over wide areas

Acta Chiropterologica, 14(1): 53–62, 2012PL ISSN 1508-1109 © Museum and Institute of Zoology PAS

doi: 10.3161/150811012X654268

Wing loading correlates negatively with genetic structuring of eight

Afro-Malagasy bat species (Molossidae)

PETER J. TAYLOR1, 2, 6, STEVEN M. GOODMAN3, 4, M. CORRIE SCHOEMAN2, FANJA H. RATRIMOMANARIVO4, 5, and JENNIFER M. LAMB2

1Department of Ecology & Resource Management, School of Environmental Sciences, University of Venda, P. Bag X5050, Thohoyandou 0950, Republic of South Africa

2School of Life Sciences, Biological Sciences Building, South Ring Road, University of Kwa-Zulu Natal, University Road,Westville, Kwa-Zulu Natal 3630, Republic of South Africa

3Field Museum of Natural History, Department of Zoology, 1400 South Lake Shore Drive, Chicago, Illinois 60605, USA4Association Vahatra, BP 3972, Antananarivo 101, Madagascar

5Département de Biologie Animale, Faculté des Sciences, Université d’Antananarivo, BP 906, Antananarivo 101, Madagascar6Corresponding author: E-mail: taylorp@netactive.co.za

We tested the effects of aspect ratio, wing loading and body size (forearm length) on four estimators of molecular diversity (basedon mitochondrial D-loop and cytochrome-b DNA sequences) among eight Afro-Malagasy species of free-tailed (Family Molossidae)bats. As expected based on many previous animal studies conducted at broader taxonomic scales, FST was significantly negativelycorrelated with wing loading (a good proxy for dispersal ability), even after correcting for phylogeny. However, haplotype diversity,nucleotide diversity and k (the mean number of nucleotide differences between sequences) were not significantly correlated withbody size, aspect ratio or wing loading. According to the metabolic rate hypothesis, we expected a significant negative correlationbetween k and body size. No such significant correlation was obtained, which is attributed to species differences in population sizeand the timing of past bottlenecks inferred from population demographic data.

Key words: Molossidae, mutation rate, fixation index, FST, k, mitochondrial DNA, body size

(e.g., family Molossidae, Tadarida brasiliensis me-xicana, Russell et al., 2005 and Mormopterus jugu-laris, Ratrimomanarivo et al., 2008). In contrast,populations of other species may show high levelsof spatial structure, at small (e.g., family Ves per -ti lionidae, Myotis bechsteinii, Kerth et al., 2000; family Phylostomidae, Carollia perspicillata, Me y -er et al., 2009) or large (e.g., family Minio pte ridae,Mi nio pterus natalensis, Miller-Butterworth et al.,2003) geographic scales. In general, phylogeograph-ic structure has been documented in bats with lowdispersal capabilities (Worthington-Wilmer et al.,1994; Burland et al., 1999) but less so in morevagile bat species capable of flying at higher speedsand greater distances, such as members of the Mo -los sidae (McCracken et al., 1994; Webb and Tide -mann, 1996; Russell et al., 2005), which we use hereto test this generalization. Since social and ecol -ogical factors such as harem formation or roostphilo patry may be more important than dispersal capacity per se in determining genetic structure incertain families of bats (McCracken, 1987; Miller-Butter worth et al., 2003), the effects of dispersal capability are best tested by comparisons within a family in which members are more likely to sharecommon sociality traits.

Recent studies on the phylogeography of molos-sid bats occurring on islands in the western IndianOcean (Madagascar, Comoros, Pemba) and southernAfrica have revealed radically different genetic pat-terns in species varying in body size from a fore-arm length of 36 mm in Chaerephon leucogaster to72 mm in Otomops martiensseni (Ratrimomanarivoet al., 2007, 2008, 2009a, 2009b; Lamb et al., 2008,2012; Taylor et al., 2009; Goodman et al., 2010;Tables 1 and 2). Afro-Malagasy molossids shareseveral key morphological and life history traits,such as a wing design basically adapted for fast-fly-ing aerial feeding, tendency for colonial living,crevice or cave roosting behavior, and adaptation tosynanthropic roosting (Peterson et al., 1995; Taylor,2000; Monadjem et al., 2010; Goodman, 2011).Wing design influences dispersal ability. Specifi cal -ly, wing loading (a measure of wing area relative tobody size) is positively correlated with flight speedand negatively correlated with manoeuvrability, andaspect ratio (an index of wing shape) is positivelycorrelated with flight cost efficiency and negativelycorrelated with energy losses in flight (Norberg andRayner, 1987). Hence, bats that are required to makeextended flights have both high aspect ratio and highwing loading (Norberg and Rayner, 1987). There isevidence that bats with broad and short wings (low

aspect ratios), and small geographic range sizes andrestricted dispersal abilities, face a higher risk of ex-tinction than bats with comparatively large geo-graphic range sizes and flexible dispersal abilities(Jones et al., 2003; Safi and Kerth, 2004). Whilstmolossid bats tend to have wings with intermedi-ate to high aspect ratio and high wing loading, thereis substantial variation between African species(Vaughan, 1966; Norberg and Rayner, 1987; Mona -djem et al., 2010). Given these observations, we aimhere to test the effects of dispersal ability, quantifiedas aspect ratio and wing loading (Norberg and Ray -ner, 1987) and body size, quantified as forearmlength, on several indices of genetic variation andstructure in eight Afro-Malagasy members of thisfamily, correcting for the possible effects of sharedphylogenetic history.

MATERIALS AND METHODS

Samples

No new sequences were generated in this study but we obtained sequences from previous studies all conducted in the laboratory of JML (Ratrimomana rivo et al., 2007, 2008,2009a, 2009b; Lamb et al., 2008, 2012; Taylor et al., 2009;Good man et al., 2010; Genbank numbers contained in above-mentioned papers). Table 1 summarizes the number of individ-uals, haplotypes and populations sampled for each of eightAfro-Malagasy species, of which one (Otomops martiensseni)contained two divergent lineages, which were analysed sepa-rately for estimating molecular diversity parameters (wingshape data were only available for the southern and westernAfrican lineage). One species, Chaerephon atsinanana was re-cently described from eastern Mada gascar, having previouslybeen assigned to C. pu milus (Peterson et al., 1995; Goodman etal., 2010).

Sequencing and Tree Building

Standard methods for the extraction and sequencing of themitochondrial cytochrome b (cyt b) gene and D-loop and the nuclear Rag2 gene are explained in detail elsewhere (Lamb etal., 2008, 2011). A tree for use in phylogenetic correction wascreated by analysis of 2031 base pairs of the concatenated Rag2and cytochrome b genes (Lamb et al., 2011). Two non-molossidoutgroup cyt b sequences of 325 base pairs downloaded fromthe NCBI GenBank (Natalus major AY621021.1, Mormoopsblainvilei AF338685.1) were aligned in Clustal W (Thompsonet al., 1994) with a representative sample of each species in-cluded in the analysis (see Table 1), namely C. atsinananaHQ 384479, C. leucogaster HM802905, C. pumilus (Kwa-Zulu-Natal, South Africa) HM802906, Mops leucostigmaHM802914, M. midas HM802915, Mormopterus jugula-ris HM802919, Otomops madagascariensis HM802922 and O. mar tiensseni HM802923. Of the 2031 nucleotides analysed,182 were variable and parsimony-uninformative, and 226 were parsimony-informative. A neighbour-joining tree was cre-ated in PAUP 4.0b10 (Swofford, 2002) using the GTR + I + G

54 P. J. Taylor, S. M. Goodman, M. C. Schoeman, F. H. Ratrimomanarivo, and J. M. Lamb

substitution model as determined in jModeltest 0.1.1 (Guin-don and Gascuel, 2003). Genetic distances between haplotypeswithin and between species were calculated and corrected inPAUP 4.0b10 according to the appropriate substitution model.Bayesian Inference was implemented in MrBayes version 3.0b4(Huelsenbeck and Ronquist, 2001). Bayesian analyses were runusing four Markov chains for five million generations each,sampling every 100 generations. The chains were heated withthe temperature scaling factor T = 0.02. We discarded the first50,000 trees as burn-in, after having checked in a preliminaryrun that this was more than sufficient to achieve stationarity, and constructed a 50% majority rule consensus tree from the remaining trees.

Analyses of Molecular Diversity

The following indices of molecular diversity were calculat-ed from cyt b and D-loop sequences using DnaSP 4.0 (Rozas etal., 2003); haplotype diversity, nucleotide diversity (Nei, 1987),and average number of nucleotide substitutions, k (Tajima,1983, 1989) as reported by Ratrimomanarivo et al. (2007, 2008,2009a, 2009b), Lamb et al. (2008) and Taylor et al. (2009). Toobtain estimates of FST based on D-loop sequences (which werenot reported in any of the above-mentioned studies except forTaylor et al., 2009) we used the AMOVA routine of Arlequin 3.0(Excoffier et al., 2005). FST is an index of the proportion of total genetic variance explained by geographic differences andprovides a robust estimate of genetic structure due to populationsubdivision. The D-loop datasets analyzed varied in the numberof geographical localities and the number of nucleotides sam-pled as shown in Table 1. As there were differences in numbersof base pairs of the D-loop analyzed in different species, westandardized k (average number of nucleotide differences) bycalculating the number of differences per 100 base pairs. Correl -ation coefficients were obtained between wing loading, aspectratio, forearm length and both standardized and un-standardizedvalues of k; since correlation coefficients obtained for the twolast-mentioned indices differed by less than 0.3, we report hereonly the results for un-standardized k.

Flight Parameters

The extended right wing of each bat (after Norberg andRayner, 1987) was photographed for the African taxa with anOlympus C730 digital camera (Olympus America Inc., New

Wing loading correlatesand genetic structuring in eight species of molossids 55

Species n No. of haplotypes No. of localities No. of nucleotides Distribution

Otomops madagascariensis 23 17 6 290 Madagascar endemicO. martiensseni N/E 21 10 3 290 N and E Africa and ArabiaO. martiensseni S/W 31 8 8 290 S and W AfricaMormopterus jugularis 50 50 18 351 Madagascar endemicMops midas 24 10 7 304 Madagascar and South AfricaM. leucostigma 61 12 16 380 Madagascar and ComorosChaerephon pumilus S Africa 34 13 6 312 Mainland AfricaC. atsinanana 83 5 10 354 Eastern Madagascar endemicC. leucogaster 71 11 17 338 Madagascar, Comoros, Pemba

TABLE 1. Description of samples used for D-loop haplotype and population genetics analyses of Molossidae bats from Africa,including South Africa and Madagascar (based on studies of Ratrimomanarivo et al., 2007, 2008, 2009a, 2009b; Lamb et al., 2008,2012; Taylor et al., 2009; Goodman et al., 2010)

York, USA) and for the Malagasy taxa with a Nikon Coolpix5600 (Nikon Inc., Melville, New York, USA) ensuring that thecamera was positioned at 90° above the wing. After the wingimages were calibrated, wingspan (b, to nearest 0.1 mm) andwing area (S, including body area without the head, and the areaof the uropatagium to the nearest 0.1 mm2), were measured using SigmaScan Pro 5 software (version 5.0.0, SPSS Inc., As -pire Software International, Leesburg, USA). Aspect ratio andwing loading were calculated as AR = b2/S and WL = M ×9.81/S where 9.81 is the gravitational acceleration (ms-2) and Mis mass (kg), respectively (Norberg and Rayner, 1987).

We tested the strength of the relationship between aspect ratio, wing loading, body size, and various indices of molec-ular diversity in eight species of Afro-Malagasy molossids, cor-recting for the possible effects of shared phylogenetic historyusing the method of phylogenetic general least squares re-gression (PGLS — Martins and Hansen, 1997) and a phylogenybased on nuclear Rag2 and mitochondrial cyt b sequences.PGLS re gressions were done using Compare (version 4.2b —Martins, 2004).

RESULTS

Genetic Variability

Cyt b genetic distances (Kimura 2-parametermodel) for molossid bats based on data summa-rized in this study as well as that of Sudman et al. (1994) show that mean genetic distances be-tween species within a genus range from 8.74% to15.30%, whereas the distances between haplo-types within a species range from 0.15% to 1.98% (Fig. 1).

Estimates of genetic variability varied across theeight Afro-Malagasy molossid species studied were:haplotype diversity (cyt b), 0.367–0.991; haplotypediversity (D-loop), 0.468–1.000; nucleotide diversi-ty (cyt b), 0.00048–0.03856; nucleotide diversity(D-loop), 0.00350–0.05260; average number of nucleotide differences (k) per 100 base pairs, 18.2-fold; FST (D-loop), 0.046–1.000 (Table 2).

Variation in Morphological Characteristics

Variation in morphological characteristics was as follows: forearm length (mm), 35.7–64.6; aspectratio, 7.35–9.69; wing loading (Nm-2), 9.34–17.59(Table 2).

Results of Regression Analyses

FST was significantly negatively correlated withwing loading (r = -0.79, F1, 6 = 9.75, P = 0.021) both before and after correcting for phylogeny (r = -0.73, Slope = -0.09, SE Slope = 0.03, P < 0.05— Fig. 2). No other significant correlations were retrieved from the dataset.

DISCUSSION

Comparisons of Species

Results of genetic distance analyses (Fig. 1) accord generally with the Genetic Species Concept(Baker and Bradley, 2006), in that the mean dis-tance between haplotypes within species is consid-erably less than the mean distance between estab-lished con generic molossid species, which in turn is less than the mean distance between recognized

56 P. J. Taylor, S. M. Goodman, M. C. Schoeman, F. H. Ratrimomanarivo, and J. M. Lamb

FIG. 1. Summary of genetic distances among and between species and genera of selected Molossidae bats

genera. There is, however, a wide variation in the cyt b genetic distances between species within theMolossidae (1.1% to 16.4%). In general, amongstAfro-Malagasy molossids, corrected genetic dis-tances between recognized species are low for mammalian sister species (Baker and Bradley, 2006; cf. values presented below). Representing the

FIG. 2. Regression of wing loading on FST (index of geographicstructure). 95% confidence limits are shown. Cl — C. leucogaster,Cp — C. pumilus (South Africa), Ca — C. atsinanana (easternMadagascar), Mrj — M. jugularis, Mpl — M. leucostigma, Mpm — M. midas, Omd — O. madagascariensis, Omt —

O. martiensseni African SW Clade

extreme of low genetic variation and structure,African and Malagasy populations of M. midas showno notable morphological or genetic differences(maximum cyt b distance between 24 M. midas sam-ples from Madagascar and South Africa was 0.1%,and populations were unstructured; FST = 0.14); thisis best explained by some recent or regular ex-changes between Malagasy and South African pop-ulations (Ratrimomanarivo et al., 2007). Anotherpattern, found in M. condylurus (Africa) and M. leu-costigma (Madagascar), is one where the Malagasypopulation is derived from African stock and hasbeen sufficiently isolated for speciation to have tak-en place (Ratrimomanarivo et al., 2008). The maxi-mum intraspecific genetic distance between 49 M. leuco stigma samples from across Madagascarwas 0.4% (FST = 0.20), whilst the distance betweenM. leuco stigma and its morphologically well-dif-ferentiated sister species, M. condylurus, was 2.5%(Ratrimo manarivo et al., 2008). Similarly, the dis-tance between sister species of O. martiensseni fromAfrica and O. madagascariensis from Madagascarwas 4.4%, whilst southern and northern African lin-eages of O. martiensseni diverged at 3.4% (Lamb etal., 2008). Within each of the above-mentionedthree clades, there was a complete lack of geograph-ic structure (FST = 0.05–0.06).

On the other hand, genetic and morphologicalanalyses of populations of C. leucogaster and C. pu -milus s.l. from Madagascar, the Comoros, Pemba(off-shore Tanzanian island), and eastern, southern,and northern Africa revealed an incompletely re-solved (paraphyletic) species complex comprisingshallow divergences (1.3–3.1%) between recog-nized species, recently resurrected or named species(including C. pusillus from the Comoros and C. atsi-nanana from eastern Madagascar), and un-namedlineages (Ratrimomanarivo et al., 2009b; Taylor etal., 2009; Goodman et al., 2010).

Detailed studies of intra-specific genetic varia-tion in several Afro-Malagasy molossid species ofsimilar body size (of the genera Chaerephon andMormopterus) revealed highly divergent FST valuesfor population genetic structure. Phylogeographicand population genetic analysis of mtDNA se-quences of C. leucogaster from Madagascar andsmaller western Indian Ocean islands (Pemba andMayotte) revealed shallow, minimal geographicstructuring of haplotypes (FST = 0.79 — Ratrimo -ma na ri vo et al., 2009b). Slightly less structure was observed in populations of C. pumilus fromsouthern Africa (FST = 0.44 — Taylor et al., 2009),whilst almost complete geographic subdivision

Wing loading correlatesand genetic structuring in eight species of molossids 57T

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(FST = 0.994) was observed in populations of C. atsi -na nana from eastern Madagascar (Lamb et al.,2012). Con versely, almost no structure was observedin populations of M. jugularis across Mad agascar(FST = 0.05 — Ratrimomanarivo et al., 2009a). Toinvestigate possible determinants of these disparategenetic patterns within the same family of bats fromthe same geographic region, we analysed correla-tions between four standard genetic and three stan-dard morphological indices.

Regression Analysis

Based on the expectation that bats with lowerwing loadings and aspect ratios would disperseshorter distances, limiting widespread gene flow(thus enhancing structure), we expected to find a negative correlation between dispersal ability andFST, an indirect and inverse measure of gene flow(Slatkin, 1987; Slatkin and Barton, 1989). Such a significant correlation was recovered betweenwing loading and FST, even after correcting for phy-logeny. This suggests the absence of phylogeneticbias. Such bias might have been envisaged if dif-ferent molossid genera or clades varied in key lifehistory traits. For example, some species of Oto -mops have uniquely been suggested to undergo sea -sonal migration (Kock et al., 2005; cave colonies ofO. mar tiensseni from Kenya) as well as to formstrict harems (Fenton et al., 2002; roof-dwelling col - onies of O. martiensseni in Durban, South Africa).However, such potentially confounding phylogenet-ic factors did not appear to bias our results.

Bats that make extended flights when time is at a premium, for example during long-distance

58 P. J. Taylor, S. M. Goodman, M. C. Schoeman, F. H. Ratrimomanarivo, and J. M. Lamb

commuting to and from roosts to locate resources(Jones and Rayner, 1989; Fenton et al., 2002; Ber -nard and Fenton, 2003), benefit from both high wingloading and aspect ratio. Conversely, migratory batstypically have long wings of high aspect ratio andlow or average wing loading because they do notnecessarily have to fly fast (Norberg and Rayner,1987; Fleming and Eby, 2003). Our results suggestthat gene flow in Molossidae is correlated withflight speed (i.e. wing loading) rather than flight cost efficiency (i.e. aspect ratio). Wing design of molos-sids is characterised by high aspect ratio but short or average sized wingspans and therefore high wingloading (Vaughan, 1966; Norberg and Rayner,1987). Because their narrow wings are not long andwing areas are small, molossids must fly fast to ob-tain sufficient weight support (Norberg and Rayner,1987). Thus, these bats are highly adapted for speedrather than manoeuvrability to commute and hunt inopen-air habitats free of clutter (Schnitzler andKalko, 2001). There is evidence that bats fly close toor faster than maximum range speed (Vmr) whenthey need a surplus energy net gain, beyond mainte-nance (Grodzinski et al., 2009), for example to min-imize commuting times when food resources are de-clining rapidly over time (Jones and Rayner, 1989).Selection probably also favours speed over flightcost efficiency when molossid bats must find poten-tial mates during the breeding season.

Our data thus provide validity at a finer tax-onomic scale (within a single family of bats) for a relationship between dispersal capability and genetic structure that has been generally establish-ed by broader taxonomic comparisons among dif-ferent families of bats (McCracken et al., 1994;

FIG. 3. Neighbour-joining (NJ) tree illustrating genetic distance relationships (GTR + I + G substitution model) between molossidtaxa included in the analysis and outgroups from the Vespertilionidae and Natalidae. Support levels from congruent Bayesian

inference (BI) and maximum parsimony (MP) analyses are indicated at relevant nodes, in the order (BI/NJ/MP)

Worthington-Wilmer et al., 1994; Webb and Tide -mann, 1996; Burland et al., 1999; Russell et al., 2005).

Such a relationship between dispersal ability andpopulation genetic structure is well known in thecase of many marine invertebrates, where specieshaving pelagic larvae generally show less geneticstructure than those without pelagic larvae (Bo ho -nak, 1999 and references therein); exceptions havebeen explained by invoking historical demographicfactors (Kyle and Boulding, 2000). In a study of five species of carabid beetles, genetic structure(FST) was not correlated with the degree of wing development as expected but rather with habitatpreferences, which could be explained by historicalvicariance patterns (Liebherr, 1988). A review of333 animal species from 27 groups (invertebrate andvertebrates; terrestrial, marine and freshwater) provided strong evidence for the generality of an association (rank correlation coefficient of -0.72)between ranked dispersal ability and FST irrespec-tive of historical factors (Bohonak, 1999). Our datasimilarly demonstrate the importance of dispersalcapability (measured by wing morphology) in shap ing current genetic structure in molossid batsindependently of past vicariance events. How-ever, as indicated below, historical demographic factors have left a legacy on observed patterns of genetic heterozygosity (as depicted by k, the aver-age number of nucleotide differences) among Afro-Mal agasy bats.

A number of studies provide evidence for themetabolic rate hypothesis whereby smaller organ-isms having higher mass-specific metabolic ratesmay exhibit higher mitochondrial mutation rates(Martin and Palumbi, 1993; Gillooly et al., 2005;but see Nabholz et al., 2008, 2009 for an alternativehypothesis related to longevity whereby natural selection favours lower mutation rates in long-livedindividuals due to premature aging effects of somat-ic mutations in mitochondrial DNA). This leads tothe expectation that smaller molossids may possesshigher k values (average number of nucleotide dif -ferences) than larger ones. Since k has been pos -tulated to approximate 4Nμ (where N is total popu -lation size and μ is mutation rate) in a subdividedpopulation, irrespective of migration rate (Strobeck,1987), it can be postulated that smaller species ofmolossid bats are more abundant in the landscapeand/or have higher mutation rates than larger spe -cies. Small molossid bats can exploit a wider rangeof roosts (including human-built struc tures); indeedthis may explain why such taxa, including M. jugu-laris and Chaerephon spp., are more ubiquitous

across their ranges compared to more sparsely distributed larger taxa, including Otomops spp. and M. midas. However, although our data showed a negative association between forearm length and k (r = -0.69) as expected, the relationship was notstatistically significant either before or after correc-tion for phylogeny. The lack of a significant correla-tion is largely because of the much higher value (k = 18.3) for the small-sized M. jugularis comparedwith the very similar-sized C. leucogaster (k = 2.25— Table 2). Although our results are not inconsis-tent with the metabolic rate hypothesis, they do notprovide statistical support for it, but rather accordwith the findings of Lanfear et al. (2007), who foundno evidence that mass-specific metabolic rate drivessubstitution rate in metazoans, and Nabholz et al.(2008, 2009), that variation in mtDNA diversity inmammals and birds cannot be explained by life his-tory variables but instead is due to profound erraticor intrinsic variation in mutation rates.

The Malagasy endemic M. jugularis occurs invery high numbers throughout its range and is re-ported to have undergone exponential demographicexpansion ≈ 120,000 to 240,000 years BP, a time tenfold deeper than that any other Mala gasy molossidreported to have undergone similar expansions(Ratrimomanarivo et al., 2009a). Thus, demograph-ic history may also influence k and explain the observed differences and the lack of a significant association between k and forearm length. SouthernAfrican populations of the small-sized C. pumi-lus were shown to have expanded approximately3,000 to 59,000 years BP, a period that includes thelast glacial maximum, which is postulated to haveresulted in local extinction, fragmentation of popu-lations, and bottleneck events. Thus, although the mutation rate in C. pu milus may be similar tothat of M. jugularis (due to similar mass-specificmetabolic rates), the evidence for more recent bottlenecks in the history of C. pu milus from south-ern Africa may explain the lower k value (12.4) for this species. The demographic history of thesmall-sized C. leucogaster indicates an even morerecent bottleneck and expansion event (≈ 11,000years BP), which may again explain the lower k(= 2.2) (Ratrimomanarivo et al., 2009b). Further -more, since C. leucogaster is more specialized in its bioclimatic niche (largely restricted to lowlandportions of western Madagascar) than M. jugula-ris (which is widespread across different elevationson Madagascar), one would assume the total popu-lation of C. leucogaster would be much smaller thanM. jugularis.

Wing loading correlatesand genetic structuring in eight species of molossids 59

The lack of significant correlation between hap-lotype and nucleotide diversity and body size orwing parameters is in large part due to the distinctdifferences observed between the similar-sizedOtomops spp. and M. midas (Table 2). Thus, nu-cleotide diversity is an order of magnitude lower inM. midas (for both cyt b and D-loop) and haplo-type diversity is considerably lower. Populations of M. midas from South Africa and Madagascar arehardly differentiated whereas in Otomops, distinctspecies characterize these two regions and there isfurther subdivision between northern and southernAfrican lineages. These differences between twogen era of large-sized molossids may be due to a more recent bottleneck in M. midas or undocu-mented differences in social factors and/or roostphilopatry, which merit further study.

CONCLUSIONS

Our data advocate a significant role for dispersalability, as estimated by wing loading, in shaping ge-netic structure (FST), but not genetic variation (k andnucleotide or haplotype diversities) at an intra-family level in Afro-Malagasy molossid bats. Al -though we found a negative correlation (r = -0.69)between forearm length (body size) and k (numberof nucleotide differences) as predicted by the meta-bolic rate hypothesis, this was not statistically sig-nificant and we ascribe some of the variation in k topostulated historical bottlenecks at widely varyingtimes in the past from ca. 10,000 (C. leu co gaster) toca. 200,000 (M. jugularis) years BP. More completetaxon (New and Old World) and gene (including nu-clear genes) sampling is required to provide furtherrobust tests of the above hypotheses and to establishtheir general applicability within Molossidae andother families of bats having divergent life historiesand evolutionary histories. Although our studyshowed no evidence of significant effects of sharedphylogeny, this may in part be due to limitations due to incomplete taxon sampling in the currentlyavailable molossid phylogeny (Lamb et al., 2011). A complete and robust phylogeny of Molossidae iscritical not only to resolving out standing problemsof paraphyly in many of the re cognised but also tocorrecting for the effects of shared phylogeny in fu-ture studies to elucidate the causal basis of observedpatterns of genetic variability.

ACKNOWLEDGEMENTS

PJT and JML acknowledge the financial support of theSouthern African Biodiversity Initiative (SABI) of the National

Research Foundation (NRF). A considerable portion of thefield work conducted in Madagascar associated with data pre-sented herein was financed by grants from the John T. andCatherine D. MacArthur Foundation and the VolkswagenFound ation. We thank the Direction des Eaux et Forêts andMadagascar National Parks for providing authorizations for thecapture, collection and exportation of specimens.

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Received 18 May 2011, accepted 16 February 2012