ORIGINALARTICLE

The roles of geological history andcolonization abilities in geneticdifferentiation between mammalianpopulations in the Philippine archipelago

Lawrence R. Heaney1*, Joseph S. Walsh, Jr1,2 and A. Townsend Peterson1

1Field Museum of Natural History, 1400 South

Lake Shore Drive, Chicago, USA, and2Undergraduate Program in Biological

Sciences, Northwestern University, Evanston,

IL, USA

*Correspondence: Lawrence R. Heaney, Field

Museum of Natural History, 1400 S. Lake Shore

Drive, Chicago, IL 60605, USA.

E-mail: heaney@fieldmuseum.org

Present address: A. Townsend Peterson, Natural

History Museum, The University of Kansas,

Lawrence, KS, USA.

ABSTRACT

Aim To test hypotheses that: (1) late Pleistocene low sea-level shorelines (rather

than current shorelines) define patterns of genetic variation among mammals on

oceanic Philippine islands; (2) species-specific ecological attributes, especially

forest fidelity and vagility, determine the extent to which common genetic

patterns are exhibited among a set of species; (3) populations show reduced

within-population variation on small, isolated oceanic islands; (4) populations

tend to be most highly differentiated on small, isolated islands; and (5) to assess

the extent to which patterns of genetic differentiation among multiple species are

determined by interactions of ecological traits and geological/geographic

conditions.

Location The Philippine Islands, a large group of oceanic islands in Southeast

(SE) Asia with unusually high levels of endemism among mammals.

Methods Starch-gel electrophoresis of protein allozymes of six species of small

fruit bats (Chiroptera, Pteropodidae) and one rodent (Rodentia, Muridae).

Results Genetic distances between populations within all species are not

correlated with distances between present-day shorelines, but are positively

correlated with distances between shorelines during the last Pleistocene period of

low sea level; relatively little intraspecific variation was found within these

‘Pleistocene islands’. Island area and isolation of oceanic populations have only

slight effects on standing genetic variation within populations, but populations

on some isolated islands have heightened levels of genetic differentiation, and

reduced levels of gene flow, relative to other islands. Species associated with

disturbed habitat (all of which fly readily across open habitats) show more genetic

variation within populations than species associated with primary rain forest (all

of which avoid flying out from beneath forest canopy). Species associated with

disturbed habitats, which tend to be widely distributed in SE Asia, also show

higher rates of gene flow and less differentiation between populations than species

associated with rain forest, which tend to be Philippine endemic species. One rain

forest bat has levels of gene flow and heterozygosity similar to the forest-living

rodent in our study.

Main conclusions The maximum limits of Philippine islands that were reached

during Pleistocene periods of low sea level define areas of relative genetic

homogeneity, whereas even narrow sea channels between adjacent but

permanently isolated oceanic islands are associated with most genetic variation

within the species. Moreover, the distance between ‘Pleistocene islands’ is

correlated with the extent of genetic distances within species. The structure of

genetic variation is strongly influenced by the ecology of the species,

predominantly as a result of their varying levels of vagility and ability to

tolerate open (non-forested) habitat. Readily available information on ecology

Journal of Biogeography (J. Biogeogr.) (2005) 32, 229–247

ª 2005 Blackwell Publishing Ltd www.blackwellpublishing.com/jbi 229

INTRODUCTION

The search for an understanding of the causes of differenti-

ation and diversification among island populations has been

an intellectual crucible in evolutionary biology. From the

original ruminations of Darwin and Wallace on the geographic

circumstances of speciation to observations of natural selection

in action, islands have provided a wealth of insight for

biologists (e.g. Grant, 1998; Hall & Holloway, 1998; Whittaker,

1998; Avise, 2000; Schluter, 2000). In particular, the presence

of high levels of endemism, and the processes and circum-

stances that produce those endemic species, has attracted

much attention. Clearly, part of the great appeal of island

systems is their relative simplicity: on islands, terrestrial

populations are discretely bounded, gene flow is likely to be

limited between them, island areas and between-island

distances are easily measured, and island communities tend

to have fewer species than mainland communities. Perhaps this

apparent simplicity has tended to wed biologists to simple

explanations for island phenomena. Biogeographers, in par-

ticular, have often divided into camps preferring either

historical (e.g. Rosen, 1975) or ecological (e.g. MacArthur &

Wilson, 1967) explanations of island phenomena. The

extensive bodies of work by both groups convinces us that

both ecological and historical factors must be important in

generating intraspecific and interspecific diversity in island

settings and that integration of the two perspectives is essential.

We agree with recent authors that historical and ecological

factors should be treated as complementary variables, rather

than competing hypotheses, in explaining patterns of geo-

graphic variation within species (e.g. Bermingham & Moritz,

1998; Whittaker, 1998; Heaney, 2000; Lomolino, 2000; Zink

et al., 2000; Riddle & Hafner, in press).

Recent developments, such as the use of DNA-based

population phylogenies, have been useful in resolving ques-

tions regarding the importance of historical and ecological

factors in influencing patterns of geographic variation in single

species (e.g. Avise, 2000). However, the particular history of

any single taxon will necessarily represent only a portion of

general patterns and causes of differentiation within any large,

historically complex region; this means that general patterns

often cannot be perceived, and general hypotheses often

cannot be tested, based on single species (Powers et al., 1991;

Riddle & Hafner, in press). A multi-species comparative

approach should be most useful for detecting the role of

ecological and historical factors in generating patterns of

variation and differentiation, helping to distinguish their

relative importance, and determining the manner in which

they interact to produce phylogenies and patterns of biological

diversity (e.g. Zink et al., 2000; Hewitt, 2001; Ricklefs &

Bermingham, 2001; Arbogast & Kenagy, 2001; Riddle &

Hafner, in press).

The Philippine archipelago is an exceptional theatre in

which to investigate the roles of past history and current

ecology in structuring geographic variation. The 7000 islands

originated as a set of de novo oceanic islands [with the

exception of one group that was united with mainland

Southeast (SE) Asia] of varying ages and geological histories,

as summarized below. It is an area of high biotic diversity and

exceptional endemism that is in critical need of conservation

(Myers, 1988; Wildlife Conservation Society of the Philippines,

1997; Heaney & Regalado, 1998; Mittermeier et al., 1999;

Holloway, 2003; Mey, 2003). While it is noteworthy that at

least 111 of the 170 native species of terrestrial mammals

(64%) are endemic (Heaney et al., 1998), it is still more

striking that 24 of 84 genera (29%) are endemic, implying

much in situ diversification, and phylogenetic studies suggest

that several large endemic clades are present among fruit bats

and murid rodents (Heaney & Rickart, 1990; Heaney, 2000;

Steppan et al., 2003). Each oceanic island that has remained

continuously isolated from its neighbouring islands is a unique

centre of mammalian endemism, with 25–80% of the non-

volant mammals endemic, even on islands of only a few

hundred square kilometres. Similar patterns are evident among

butterflies (Holloway, 2003) and trichopteran insects (Mey,

2003).

The manner in which this diversification has arisen among

Philippine mammals over evolutionary time, and the ecolog-

ical means by which it has been maintained, have been the

subject of diverse studies of biogeography, diversity gradients,

systematics, and population biology (e.g. Heaney, 1986, 1991a,

2000, 2001; Heideman & Heaney, 1989; Heaney & Rickart,

(habitat association and vagility) and geological circumstances (presence or

absence of Pleistocene land-bridges between islands, and distance between

oceanic islands during periods of low sea level) are combined to produce a simple

predictive model of likely patterns of genetic differentiation (and hence

speciation) among these mammals, and probably among other organisms, in

oceanic archipelagos.

Keywords

Biogeography, Chiroptera, differentiation, diversification, ecological traits, gene

flow, genetic variation, geology, Philippines, Rodentia.

L. R. Heaney et al.

230 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

1990; Rickart et al., 1991, 1993; Heaney et al., 1998, 1999;

Steppan et al., 2003). Among these was an initial examination

of patterns of genetic differentiation in two species of fruit bats

(Peterson & Heaney, 1993); this analysis showed that Cyno-

pterus brachyotis, a species widespread in South East (SE) Asia

that occupies disturbed anthropogenic habitats, had high levels

of heterozygosity, high levels of gene flow, and low levels of

genetic differentiation. In contrast, Haplonycteris fischeri, a

Philippine endemic that occurs in primary rain forest, had low

levels of heterozygosity, low levels of gene flow, and high levels

of genetic differentiation. Further, we found that the two

species showed significantly similar geographic patterns of

genetic differentiation between populations, and that those

patterns were strongly influenced by the extent of island

shorelines during Pleistocene periods of low sea, but not by

current shorelines.

In this study, we extend those observations by increasing the

number of species (from 2 to 7) and the number of islands

(from 6 to 11). We include six fruit bat species because they are

speciose, abundant, and generally easily captured (Heideman

& Heaney, 1989). Several of these species are endemic to (but

widespread within) the archipelago, maximizing the likelihood

that general patterns could be detected. The 11 islands (Fig. 1)

represent many (although not all) of the distinct areas of

endemism in the Philippines, and a range of areas and degrees

of isolation; the number was limited by the availability of

suitably fresh frozen tissues. It should be noted that not all

species occur on all 11 of the islands, and in a few cases we

Figure 1 Philippine archipelago. Extent of

late Pleistocene landmasses (areas delimited

by present 120 m bathymetric contour) sha-

ded (redrawn from Heaney, 1986). Black dots

indicate the origin of samples used in this

study.

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 231

lacked tissues for study from reference islands where the

species is known to occur. We also include Rattus everetti, a

Philippine endemic murid rodent that is the only non-volant

small mammal that occurs widely within the archipelago;

fortunately, it is sufficiently abundant that we were able to

obtain several adequate samples. We used protein electro-

phoresis in this study, an analytical tool of great power that is

technically difficult and not often used currently, but highly

appropriate for investigation of the issues of concern to us

here. Because protein electrophoresis requires relatively large

amounts of fresh or freshly-frozen tissue, our sample sizes for

the fruit bats are sometimes small. However, we have

endeavoured to use statistical analysis cautiously to avoid

falsely detecting patterns, especially in a multi-species com-

parison, with the result that those patterns that we describe

here are likely to be robust. We believe that such information

on population genetics is crucial to developing an under-

standing of the role of geography in influencing the process of

diversification in this highly biodiverse oceanic archipelago.

As part of this study, we test two hypotheses that we proposed

in the earlier paper. The first is that late Pleistocene shorelines of

oceanic islands (i.e. the maximum extent of dry-land islands)

are as important in structuring patterns of intraspecific

variation in the Philippines as they are in delimiting regions

of interspecific diversity. Previous investigation of patterns of

species distribution, diversity, and endemism in Philippine

mammals have shown that shorelines of islands that existed

during Pleistocene periods of low sea level form the primary

boundaries between the highly distinct faunal regions in the

archipelago (25–80% endemism among non-volant mammals

and 7–22% among fruit bats; Heaney, 1986, 1991a, 1993, in

press; Heaney et al., 1998). We predict that these geographic

barriers will also manifest themselves as significant partitions of

genetic variation between island populations common to all

seven species in this study. The second hypothesis is that

ecological attributes of species determine the extent to which

common patterns are exhibited. We expect that basic know-

ledge regarding distribution and habitat preferences of these

species derived from extensive field work in the Philippines

(e.g. Heideman & Heaney, 1989; Heaney et al., 1998, 1999;

Rickart et al., 1991, 1993) will provide indications of levels of

gene flow and consequent degree of differentiation between

populations. We also address three questions unresolved in the

previous study: (1) whether small, isolated island populations

tend to show reduced within-population variability, (2) whe-

ther small, isolated island populations tend to be more

genetically differentiated, and (3) whether the tendency to

develop genetically distinct populations, which we consider to

be an intrinsic component of the process of speciation, is

correlated with, and can be predicted from, readily measured

ecological and geographic/geological parameters.

Study species and site

This study examines seven species of Philippine mammals that

fall into three general ecological and geographic patterns: (1)

three species widespread in SE Asia, all of which are primarily

associated with disturbed habitat; (2) three species that are

endemic to the Philippines but widespread within the oceanic

archipelago and are primarily associated with forest (although

with variation, as noted below); and (3) one species that is a

Philippine endemic associated with forest, but restricted to one

Pleistocene island (Heaney et al., 1989, 1999; Heideman &

Heaney, 1989; Heaney, 1991a; Rickart et al., 1991, 1993).

The three fruit bats to which we refer as ‘widespread

species’ are found throughout SE Asia and are common in

disturbed anthropogenic habitats in the Philippines. They are

C. brachyotis, a small (30–35 g) frugivore; Macroglossus

minimus, a small (15–20 g) nectarivore; and Rousettus am-

plexicaudatus, a medium-sized (70–100 g) frugivore. In the

Philippines, these three bats forage in orchards, other agricul-

tural areas, and disturbed secondary forest. They are most

common at lower elevations and are usually absent in montane

rain forest. Rousettus amplexicaudatus is most common in

clearings and orchards, and are known to regularly fly long

distances (> 20 km night)1) to forage, often across open water

(e.g. Rickart et al., 1993). Macroglossus minimus is usually

found in association with wild or domestic abaca or banana

(Musa spp.) in open secondary forest or agricultural areas, but

also feed on mangroves that grow in patches in estuaries.

Cynopterus brachyotis prefers agricultural areas or secondary

forest, and is rare in primary rain forest except on one small

island (Maripipi) which lacks Philippine endemic fruit bats

(Rickart et al., 1993).

In contrast, the second cluster of three species are endemic

to the Philippines, but occur nearly throughout the archipel-

ago. They are members of endemic genera, generally are

common in relatively undisturbed rain forest, and are variable

in their presence in heavily disturbed areas lacking good

canopy cover. Haplonycteris fischeri, a small (15–20 g) frugiv-

orous bat, is the most habitat-restricted mammal in this

category; it is common beneath the canopy in primary rain

forest, scarce in secondary forest, and absent in open

agricultural areas. It is often the most abundant fruit bat in

mature forest at middle elevations. Ptenochirus jagori, a

medium-sized (70–90 g) frugivorous bat, is known to move

farther than H. fischeri (Heideman & Heaney, 1989) and

prefers primary rain forest but can maintain populations even

in degraded secondary rain forest. Rattus everetti, a large

(230–420 g) endemic Philippine rodent and the only non-

volant mammal in this study, prefers disturbed forest and

tolerates primary forest, but is absent away from forest

(Rickart et al., 1993; Heaney et al., 1999).

The third group is represented by one species of small

(35–40 g) frugivorous bat, P. minor. It is restricted to a single

Pleistocene island (Greater Mindanao; see below), is common

in primary or good secondary lowland rain forest, tolerates

second-growth, and is scarce outside of forest.

The Philippine archipelago is an especially interesting arena

for investigating biological diversification (Heaney, 1986,

1991a,b; Mitchell et al., 1986; Packham, 1996; Hall, 1998,

2002; Steppan et al., 2003). In brief, the first of the extant

L. R. Heaney et al.

232 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

islands appeared as dry land during the early Oligocene, but

most of the extant islands have originated since the late

Miocene, and many during the Pliocene. One portion of the

archipelago, Palawan and associated small islands, probably

was joined to the Asian mainland during the middle or early

Pleistocene, and is part of the Sunda Shelf biogeographic

region, rather than the Philippine region (Esselstyn et al., in

press). The rest of the archipelago has never had a dry-land

connection to SE Asia, having arisen as a set of de novo islands

from the ocean floor, most often far to the SE of its current

location, as a result of tectonic and volcanic activity, gradual

coalescence, and variable but progressive uplift. Most current

topography is probably close to its maximum level. Since the

archipelago sits on an uplifted platform bracketed by deep

trenches, the depths between some islands are relatively

shallow. Thus, as Pleistocene sea level rose and fell in concert

with the development of continental ice sheets, certain groups

of islands have experienced repeated cycles of coalescence and

fragmentation. During the most recent period of low sea level

in the Pleistocene, c. 18,000 years ago (Fairbanks, 1989; Siddall

et al., 2003), many current islands merged into four large

islands: Greater Luzon, Greater Mindanao, Greater Negros-

Panay, and Greater Palawan (Fig. 1). The present configur-

ation of islands represents a phase of fragmentation due to

high sea level. Each of the ‘Pleistocene islands’ shown in Fig. 1

originated as a de novo oceanic island between c. 25 and

0.5 Ma, and (with the exception of Palawan) has had no dry-

land connection to other islands or continents. We call them

‘Pleistocene islands’ because they reached their largest size

during the late Pleistocene periods of low sea level, not because

they originated during the Pleistocene.

Eleven present-day islands from seven Pleistocene islands

are represented in this study (Fig. 1). During the late

Pleistocene period of low sea level, Luzon, Catanduanes, and

Polillo coalesced into Greater Luzon; Leyte and Biliran

coalesced with modern Mindanao into Greater Mindanao;

and Fuga and Barit also coalesced into a single landmass.

Negros was part of Greater Negros-Panay, while Mindoro,

Sibuyan, and Dalupiri each stood alone and have remained

unconnected to other islands. Each major Pleistocene island

has been documented as a centre of endemism. Greater Luzon

and Greater Mindanao, for example, have 70–80% endemism,

and Mindoro, Greater Negros-Panay, and Sibuyan each have

40–50% endemism, among native non-volant mammal species

(Heaney, 1993, in press).

MATERIALS AND METHODS

Sampling was conducted in and near large tracts of forest

(relative to the size of the islands); on all islands, most

deforestation near our sites dates from the last 10–30 years.

Thus, our estimates of genetic variation should not reflect the

effects of habitat destruction. Bats were collected in mist nets

and euthanized with lethal doses of sodium pentobarbital. Rats

were collected in Victor snap traps. Tissues were harvested

immediately and frozen in liquid nitrogen, and later stored at

the Field Museum in an ultracold freezer at )80 �C. Voucherspecimens were prepared and deposited at the Field Museum,

the Philippine National Museum, and the United States

National Museum of Natural History.

Protein electrophoresis protocols for C. brachyotis and

H. fischeri are described in Peterson & Heaney (1993) and all

data included here for these species are from that study. For

the remaining species, equal portions of heart, liver, and

skeletal muscle tissue were homogenized in a 1 mM disodium

EDTA/100 mM Trizma base/0.2 mM NAD, NADP, and ATP

buffer, centrifuged for 45 min at 12,000 rpm, and supernatants

drawn into capillary tubes for storage. Samples were electro-

phoresed for 4–6 h on 12% starch gels, depending on the

specific analysis desired. Gels were sliced horizontally, and each

slice stained using specific protein assays from Shaw & Prasad

(1970) and Harris & Hopkinson (1978). Each sample was

scored at 32 presumptive genetic loci (enzyme commission

numbers from International Union of Biochemistry and

Molecular Biology, 1992): AAT (2.6.1.1, 2 loci), ACN

(4.2.1.3, 2 loci), ACP (3.1.3.2), ADH (1.1.1.1, 3 loci), AK

(2.7.4.3, 2 loci), ATA (2.6.1.2), CK (2.7.3.2, 2 loci), EST

(3.1.1.1, 2 loci), G3PDH (1.1.1.8), G6PDH (1.1.1.49), GDA

(3.5.4.3), GPI (5.3.1.9), ICD (1.1.1.42, 2 loci), LDH (1.1.1.27, 2

loci), MDH (1.1.1.37, 2 loci), MPI (5.3.1.8), NP (2.4.2.1), PEP

(3.4.11; 5 loci, corresponding to PEP-A, -B, -C, -D, -S), PGD

(1.1.1.44), PGM (5.4.2.2), PK (2.7.1.40), and SOD (1.15.1.1).

For each species, all individuals were analysed on the same gel.

To assure correct assignment of homologies, reference indi-

viduals were included at multiple points on each gel.

Analyses were performed in BIOSYS-1 (Swofford &

Selander, 1981). Allele frequencies and three measures of

within-population variation – mean observed heterozygosity

(Hobs), number of alleles per locus (NALL), and percentage of

loci polymorphic (POLY; 5% criterion) – were calculated.

Departure from Hardy–Weinberg equilibrium was tested by

3 methods (the chi-square goodness-of-fit test, and an exact

probability test (Haldane, 1954); because our samples were

sometimes small, we also used a chi-square test with Levene

(1949) correction for small sample sizes) (Table 1; Appendix

S1 in Supplementary Material). Tests of association between

measures of within-population variation (Hobs, NALL, POLY)

with island area and isolation were performed with linear

regression and non-parametric Spearman rank correlation.

Tests for differences between species in levels of within-

population variation were performed with analysis of variance

and non-parametric Kruskal–Wallis tests.

Fixation indices (F-statistics; Wright, 1951, 1965) were used

to summarize the distribution of genetic variation within and

between populations. Confidence limits on estimates of FSTwere established by jack-knifing over loci as recommended by

Weir & Cockerham (1984); we employed a relatively conser-

vative experimentwise error rate (a ¼ 0.001). Hierarchical

fixation indices (Wright, 1978) and variance components

(Cockerham, 1969, 1973; Weir, 1990) were calculated based on

the Pleistocene connections among islands as follows: (Luzon,

Catanduanes, Polillo) (Leyte, Biliran) (Negros) (Mindoro)

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 233

(Sibuyan) (Dalupiri) (Fuga, Barit). Estimates of overall gene

flow between populations (Nm) were derived from the

approximation FST ¼ 1/(1 + 4Nm) as recommended by Slat-

kin & Barton (1989), and also computed by the private alleles

method of Slatkin (1985) using the correction for sample size

of Slatkin (1985) as clarified in Slatkin & Barton (1989). Both

methods provide reasonable estimates of Nm; Slatkin & Barton

(1989) found that these two methods of estimating Nm

bracketed the true values of Nm in some simulations. Gene

flow among pairs of populations (M; Slatkin, 1993) was

calculated by the GST (Nei, 1973) and theta (1; Weir &

Cockerham, 1984) methods, using a program by Slatkin

(1993). We present the results for M as calculated by the GST

method (Nei, 1973, 1977) because estimates of gene flow most

commonly reported in the literature are calculated by this

method (e.g. it is the method used by BIOSYS-1; Swofford &

Selander, 1981). M between Pleistocene islands is simply the

mean of all estimates along that track.

Cavalli-Sforza & Edwards’ (1967) arc genetic distance (as

preferred by Wright, 1978) and Nei’s (1978) unbiased genetic

distance were calculated (Appendix S2). Geographic distances

were measured as nearest shore-to-shore distances from

bathymetric charts (Department of Defense, Defense Mapping

Agency charts, Part 2 – Hydrographic Products, Region 9 –

East Asia) at the smallest practical scales; distances between

Pleistocene shorelines were estimated using the 120 m bath-

ymetric contour from the same charts (Appendix S3). To test

the correspondence of genetic and geographic distances, we

used permutation-based matrix correlation tests (Mantel,

1967; Dietz, 1983). These tested the proportionality of

Cavalli-Sforza and Edwards’ arc genetic distance matrices

and geographic distance matrices (between both present-day

and inferred Pleistocene shorelines), using a FORTRAN

program (MATCORR.EXE) by Dietz (1983). We present the

results of the Spearman rank correlations for matrices rather

than the more commonly used Mantel test (which uses

Pearson product-moment correlation; Mantel, 1967) because

the Spearman test is less sensitive to the actual distance

measure used (Dietz, 1983) and it is more appropriate when

there is less certainty about the reliability of close ranks (Sokal

& Rohlf, 1981).

The ‘small oceanic islands’ in this study (Sibuyan, Barit,

Dalupiri, and Fuga) did not coalesce with large Pleistocene

islands at the last glacial maximum. Each originated as a de

novo oceanic island and has remained continuously isolated, as

described above. Peterson & Heaney (1993) found that

populations of Cynopterus and Haplonycteris on these small,

isolated oceanic islands showed weakly reduced within-

population variability, and predicted that reduced variability

would be found in other species. To test this hypothesis, we

compared Hobs, NALL, and POLY for each species between

large Pleistocene island populations and small oceanic island

populations using analysis of variance and the non-parametric

Kruskal–Wallis test. Peterson & Heaney (1993) also found that

populations on the small, isolated oceanic islands were

consistently distinct from other islands in the Philippines,

and predicted that this pattern would be evident in other

species. To test this hypothesis, we examined genetic distance

and M. All tracks leading to small oceanic islands were

distinguished from all tracks that did not include an oceanic

island (i.e. tracks within and between large Pleistocene islands).

For each species, small oceanic island tracks were compared

with large Pleistocene island tracks by the Kruskal–Wallis test,

which utilizes a conservative number of degrees of freedom.

Throughout our analyses, there are instances in which a

given hypothesis is tested across several species. In such cases,

Table 1 Genetic variation within populations (Hobs, observed heterozygosity) and island areas

Island Area (km2)

Widespread Endemic Narrow endemic

Rousettus

amplexicaudatus

Macroglossus

minimus

Cynopterus

brachyotis

Ptenochirus

jagori

Haplonycteris

fischeri

Rattus

everetti

Ptenochirus

minor

Luzon 104,688 0.145 0.058 0.065 0.022 0.054 0.025 –

Negros 12,704 0.111 0.051 0.083 – 0.056 – –

Mindoro 9736 – 0.050 – – – – –

Leyte 7213 0.115 0.042 0.060 0.032 0.000 0.048 0.027

Catanduanes 1430 0.118 0.025 0.071 0.024 0.036 0.017 –

Polillo 606 0.091 – – – – – –

Biliran 497 0.090 0.033 0.097 0.022 0.036 0.025 0.028

Sibuyan 448 0.103 0.063 0.040 0.034 0.022 – –

Fuga 93 0.090 – – – – – –

Dalupiri 62 0.075 – – – – – –

Barit 5 0.103 – – – – – –

Mean Hobs 0.104 0.046 0.069 0.027 0.034 0.029 0.028

Mean NALL 1.36 1.20 1.45 1.20 1.20 1.20 1.15

Mean POLY 25.5 14.3 26.2 10.3 19.0 11.5 12.0

Summary lines include mean Hobs, mean NALL (number of alleles per population), and mean POLY (proportion of loci polymorphic per popu-

lation).

L. R. Heaney et al.

234 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

it is possible that no individual test of the hypothesis will prove

statistically significant although a significant overall effect

exists. The growing field of meta-analysis (e.g. Gurevitch et al.,

1992) provides many methods for combining results from

different studies. We restrict ourselves to Fisher’s relatively

simple method of combined probabilities (Fisher, 1954; Sokal

& Rohlf, 1981) for testing for overall significance. In our

application of the method, each species is treated as an

independent test of the hypothesis under consideration, e.g.

that Hobs is related to log(area). The sum across species of the

natural logarithms of the P-values for each such regression or

rank correlation is multiplied by )2. This value is distributed

as a chi-square with 2 k degrees of freedom, where k is the

number of separate tests and probabilities (in this case, the

number of species).

Relationships between populations were explored through

phenetic and phylogenetic methods using the genetic distance

measures noted above. UPGMA dendrograms (Sneath & Sokal,

1973) and Distance Wagner trees (Farris, 1972) were generated

in BIOSYS-1 (Swofford & Selander, 1981). Fitch (Fitch &

Margoliash, 1967) trees were generated in PHYLIP (Felsen-

stein, 1989). A maximum parsimony analysis of allele

frequencies was conducted using the FREQPARS program of

Swofford & Berlocher (1987). All of these methods yield

similar topological results, and so the UPGMA dendrograms

using Cavalli-Sforza and Edwards’ arc genetic distance are

presented by convention (Fig. 3).

RESULTS

Departures from Hardy–Weinberg equilibrium

The largest number of departures from Hardy–Weinberg

equilibrium was detected by the Levene (1949) correction for

small sample sizes to the chi-square test. This method detected

17 departures from Hardy–Weinberg equilibrium, of 225

possible polymorphic loci-populations. Many fewer were

detected by the chi-square test for goodness-of-fit and the

exact probability test. All departures were heterozygote defi-

ciencies of small degree and were concentrated in a few loci

[e.g. G6PDH (5), NP (3), and ICD (2)]. Removal of these loci

does not qualitatively affect any of the conclusions presented

here.

Population dendrograms

Two consistent trends are apparent in the UPGMA population

dendrograms (Fig. 3). First, the small oceanic island popula-

tions (Sibuyan, Dalupiri, Fuga, and Barit) are often the most

strongly differentiated from other populations. Sibuyan, in

particular, appears most genetically distinct in three of the five

taxa that are found on that island. The other trend that

emerges is that Biliran and Leyte, the pair of islands with the

shallowest ocean depth between them (< 10 m), are the least

differentiated in two of six taxa and are not well differentiated

in a third. The presumed Pleistocene hierarchy of island

relationships, however, emerges clearly only in the case of R.

everetti, the only non-volant mammal in this study. It should

be noted that cluster analysis of island populations based on

genetic distances constitutes an exploratory technique and is

not appropriate for testing the hypothesis that Pleistocene

shorelines form significant partitions of genetic variation

(Sneath & Sokal, 1973).

Variation within populations: geological correlates

Genetic variability within populations is theoretically related to

effective population size (Wright, 1931). Smaller populations

are expected to lose genetic variation via genetic drift more

rapidly than larger populations, thus achieving a lower

standing level of variation due to mutation-drift balance. This

expectation has received much attention in the conservation

biology literature (e.g. Soule 1976, 1987; Frankham, 1995,

1996; Lande, 1995; Berry, 1998), yet how often this phenom-

enon is important in wild populations is not clear. To test

whether this theoretical relationship is present in these

Philippine mammals, we used island area, which varies over

six orders of magnitude in this study, and the logarithm of

island area, as reasonable proxies for effective population size

(P. minor, represented by only two populations, was not

considered in this analysis). In only one of the six species was a

significant regression of within-population variation and

island area, detected (similar results were obtained for all

three measures of within-population variation; only the results

for Hobs are reported). Rousettus amplexicaudatus, a wide-

spread SE Asian fruit bat, displayed significant regressions of

Hobs vs. island area and the logarithm of island area

{Hobs ¼ 0.098 + 0.000(area), r ¼ 0.775, P ¼ 0.008;

Hobs ¼ 0.071 + 0.005[log (area)], r ¼ 0.735, P ¼ 0.015}.

Ptenochirus jagori displayed a significant regression of the

number of alleles on the logarithm of island area

{NALL ¼ 0.772 + 0.138[log(area)], r ¼ 0.963, P ¼ 0.008},

but NALL is a highly sample-size-dependent measure and

there was also a significant regression of sample size (N) on

island area for this species {N ¼ )14.883 + 7.964[log(area)],

r ¼ 0.938, P ¼ 0.019}, so we exercise caution in interpreting

this result. Fisher’s method of combined probabilities for all

species combined across measures did not yield any significant

overall results for relationships of Hobs, NALL, and POLY with

area or log(area). Non-parametric methods, including Spear-

man rank correlation (Sokal & Rohlf, 1981), did not show

more significant associations of within-population variability

measures and area than would be expected by chance for all

taxa other than R. amplexicaudatus, nor were any significant

overall trends detected using combined probabilities from

non-parametric tests.

We also considered the possibility that isolation of island

populations may have an effect on within-population varia-

bility through lowered frequency of migration. Schmitt et al.

(1995) showed that heterozygosity within island populations of

the fruit bat C. nusatenggara in Indonesia was correlated with

distance to the nearest large source population, and Hisheh

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 235

et al. (1998) found similar results for Eonycteris spelaea in the

same area. The analogy with patterns of interspecific diversity

is clear: more isolated islands are predicted to receive fewer

colonists and tend to have fewer species than islands closer to

source pools of colonists (MacArthur & Wilson, 1967).

Similarly, one might expect that more isolated islands would

receive fewer migrants to augment their genetic diversity.

Various indices of isolation (distance to the nearest island,

distance to the nearest large island, distance to the nearest

Pleistocene island, and distance to the nearest large Pleistocene

island) were used in our study. No more significant results

than expected by chance were obtained for regressions of

measures of within-population variability on isolation indices,

for partial regressions of within-population variability on area

[and log(area)] plus isolation indices, nor for overall trends

across species from combined probabilities. Hence, our data

indicate that neither island area nor isolation of island

populations from sources of migrants have a substantial

overall effect on standing genetic variation within populations

in this system, in spite of variation in island area over six

orders of magnitude.

Variation within populations: ecological correlates

We have documented that the widespread SE Asian species

that occur in the Philippines usually occupy disturbed habitats,

while the Philippine endemic species prefer primary rain forest

(although some can maintain populations in disturbed forest;

e.g. Heideman & Heaney, 1989; Heaney et al., 1998, 1999;

Rickart et al., 1991, 1993). Our previous study of C. brachyotis

and H. fischeri found that the widespread C. brachyotis, which

prefers disturbed, open habitat, showed high levels of variation

within populations, and the endemic species (H. fischeri),

which preferred closed-canopy primary forest, showed low

levels of variation within populations (Peterson & Heaney,

1993). We postulated that this trend constituted a general

pattern. To test this proposition, we performed nested analyses

of variance on Hobs, NALL, and POLY in our seven species

(Table 1), where the levels are ecological category (widespread/

habitat tolerant species vs. endemic/forest-associated species

plus single-Pleistocene-island endemics), species within eco-

logical category, and island populations as the replicates within

species. For all three measures, both levels were significant at

P < 0.01. This result indicates that, while significant hetero-

geneity exists within ecological categories, the widespread SE

Asian species, which prefer disturbed habitat, display sig-

nificantly higher levels of within-population variability than

species endemic to the Philippines, which prefer primary

forest, as predicted.

Since heterozygosity and other measures of within-popula-

tion variation usually do not meet the assumptions of

parametric statistics (they are skewed positively in this case),

we also performed non-parametric statistical tests. Because no

appropriate non-parametric analogue for nested anova is

available, we took two approaches. First, we performed a

Kruskal–Wallis test using each island population of each

species as an independent observation and tested whether or

not widespread SE Asian species had greater within-population

variability than endemic species and the single-island Pleisto-

cene endemic. For all three measures, all tests are significant

(P < 0.01; Table 2). Second, a more conservative approach was

applied, treating each species as an independent observation.

Species means of the three measures of genetic variation were

used to test the hypothesis that widespread species (which

prefer disturbed habitat) have higher levels of within-popula-

tion genetic variation than endemic species (which prefer

primary forest; Table 2, with mean values in Table 1). Hobs was

significantly higher in widespread species (P < 0.05), and

NALL and POLY were nearly so (0.10 < P < 0.05), again

supporting the prediction.

Variation between populations: geological correlates

Wright (1943) provided the theoretical underpinnings for a

simple notion, that populations closer to one another should

be more similar to one another than populations farther apart

due to the homogenizing effects of gene flow. The quantitative

theory of ‘isolation by distance’ is mathematically complex and

can be difficult to test in its particulars, but numerous authors,

notably R. Sokal and colleagues (Sokal & Wartenberg, 1983;

Sokal, 1988; Livshits et al., 1991), have relied on non-

parametric, permutation-based, matrix correspondence tech-

niques to test for the presence of an isolation by distance

pattern. We used these methods to test statistically the

proportionality of matrices of genetic distances and geographic

distances between populations. We compared matrices of

genetic distance (results for Cavalli-Sforza and Edwards’ arc

genetic distance are presented in Table 3; other genetic

distance measures yielded similar results) with matrices of

geographic distance between present-day islands. The tests for

all species yield a similar and rather surprising result: matrices

of genetic distances between island populations are not

correlated with the matrix of geographic distances between

present-day islands in any of the six species, nor is an overall

Table 2 Comparisons of genetic variation within populations

between widespread SE Asian species and Philippine endemics

Hobs NALL POLY n

(a)

Widespread SE Asian 641 573 570 23

Philippine endemic 179 247 250 17

P-value 0.001 0.007 0.004

(b)

Widespread SE Asian 18 16.5 17 3

Philippine endemic 10 11.5 11 4

P-value 0.034 0.079 0.077

Sum of ranks and significance values from Kruskal–Wallis test on

observed heterozygosity (Hobs), number of alleles per locus (NALL),

and proportion of loci polymorphic (POLY), using (a) islands as

observations, and (b) species as observations.

L. R. Heaney et al.

236 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

significant correlation detected using combined probabilities

(Table 3).

However, another relevant pattern requires testing. Patterns

of mammalian interspecific diversity in the Philippines are

strongly influenced by the boundaries of islands that existed

during maximal late Pleistocene sea-level lowering, which

represent maximum coalescence during the history of the

archipelago (Heaney, 1986, 1991a, 1993, in press; Steppan

et al., 2003). This pattern of interspecific diversity suggested

another test: we calculated matrix correspondence between

genetic distance matrices and the matrix of geographic

distances between Pleistocene shorelines, inferred from the

120 m bathymetric contour. Spearman rank correlation

yielded significant results for two of six taxa (M. minimus

and P. jagori) and nearly significant results (0.10 > P > 0.05)

for three additional taxa (R. amplexicaudatus, C. brachyotis,

and H. fischeri) for these Pleistocene distances (Table 3). Using

combined probabilities across species, we conclude that genetic

distances are not correlated with distances between present-day

shorelines, but are correlated with distances between late

Pleistocene shorelines. It appears, therefore, that the geological

history (including both long-term isolation between some

islands and Pleistocene coalescence among others) has created

a common pattern of geographic variation between popula-

tions across the six species, partitioned by late Pleistocene

shorelines. Specifically, the geographic distance between per-

manently isolated geo-historical units is positively correlated

with increasing genetic distance.

Variation between populations: ecological correlates

A final prediction about the extent of the common pattern of

differentiation between populations will be addressed here. We

believe that the presence of the widespread species on small,

isolated islands where no endemic species are found (e.g. Barit,

Dalupiri, and Fuga) and the observation that widespread

species will readily cross clearings but endemic species are

rarely found far from primary rain forest or out from beneath

good canopy cover (except P. jagori, as noted below), should

result in lower levels of gene flow between populations of the

endemic species on different islands. If this is correct,

population genetic theory predicts that endemic species will

display higher levels of between-population differentiation

than widespread species. To test this prediction, we examined

estimates of gene flow (Nm) and fixation indices (FST).

Estimates of gene flow generally conform to our predictions

(Table 4). The widespread species exhibit high levels of gene

flow (about two individuals per generation) and two of three

endemic species exhibit low levels of gene flow (around 0.2

individuals per generation). The endemic species P. minor

displays very high levels of gene flow, but this is not surprising,

since it occurs only within a single Pleistocene island and the

results of the previous section indicate that Pleistocene

shorelines are the significant boundaries between regions of

genetic differentiation. The more widespread Philippine

endemic, P. jagori, a member of the same genus, however,

has rather high levels of gene flow, as might be expected of a

species that is known to be relatively tolerant of disturbance,

although not to the extent of the widespread species. We note

that estimates of gene flow may be based on past, rather than

current, gene flow, and that the time to reach genetic

equilibrium is largely a function of effective population size.

Thus, these values should be taken as average long-term

estimates, rather than instantaneous estimates.

With respect to levels of between-population differentiation,

FST is fairly low for widespread species, c. 0.1 (Table 4). Two of

three endemic species (H. fischeri and R. everetti) show

significantly higher levels of between-population differenti-

ation, about five times higher than widespread species. The

Table 3 Spearman rank correlation (rs) tests of proportionality

of genetic and geographic distance matrices between present-

day islands and between Pleistocene islands

Species

Present distance

Pleistocene

distance

rs P-value rs P-value

Widespread species

Rousettus amplexicaudatus 0.088 0.332 0.339 0.057

Macroglossus minimus 0.027 0.472 0.505* 0.039

Cynopterus brachyotis )0.280 0.811 0.627 0.100

Endemic species

Ptenochirus jagori 0.553 0.083 0.556* 0.033

Haplonycteris fischeri 0.149 0.279 0.718 0.061

Rattus everetti 0.829 0.125 0.828 0.333

)2[Eln(P)] 15.816 31.438*

Combined probability P > 0.100 P < 0.005

*Significant correlations and combined probabilities (P < 0.05).

Table 4 Estimates of gene flow (Nm)* and genetic

differentiation (FST)� among islands

Species Nm NmPA FST

FST* + 99.9%

confidence

limits

Widespread species

Rousettus amplexicaudatus 2.25 3.93 0.100 0.101 ± 0.015

Macroglossus minimus 2.13 3.03 0.105 0.105 ± 0.007

Cynopterus brachyotis 2.02 7.29 0.110 0.110 ± 0.063

Endemic species

Ptenochirus jagori 2.84 5.60 0.081 0.081 ± 0.007

Haplonycteris fischeri 0.16 0.95 0.606 0.603 ± 0.152

Rattus everetti 0.23 2.47 0.522 0.520 ± 0.156

Pleistocene endemics

Ptenochirus minor 5.85 2.95 0.041 0.041 ± 0.015

*Nm, calculated from FST, after Slatkin & Barton (1989); NmPA, cal-

culated by the method of private alleles (Slatkin, 1985), corrected for

sample size.

�FST, from BIOSYS-1 output [calculated in the manner of Nei (1977)];

FST*, jack-knifed estimate of FST, after Slatkin (1985), ±jack-knifed

confidence limits (a ¼ 0.001).

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 237

geographically restricted P. minor displays very low levels of

differentiation within its single Pleistocene island (although we

have few sampling sites), a trend that we discuss below. The

more widespread endemic species, P. jagori, presents an

illustrative exception to the other endemic species. It displays

low levels of within-population variation, but unlike the other

endemic species, its habitat tolerances are moderately broad

(i.e. it often forages in open habitats and readily maintains

populations in secondary forest), and it displays high levels of

overall gene flow. We interpret this result as evidence that it is

the not the categorization of a species as an endemic per se that

is usually associated with low gene flow, but rather with the

usual (but not ubiquitous) tendency of endemic species to

have low tolerance for disturbed, open habitat, since P. jagori

apparently has the broadest habitat tolerance of any endemic

Philippine fruit bat (although less than the widespread SE

Asian species). Morphological data (Walsh, 1998) show a

similar but less pronounced trend, in that levels of within-

population variation in P. jagori are similar to those of other

endemic species, while levels of between-population variation

resemble those of widespread species.

Wright’s (1978) hierarchical F-statistics (Table 5) show how

overall variation between populations may be apportioned into

variation between Pleistocene islands and variation between

present-day islands within Pleistocene islands. Two of three

Philippine endemics show the overwhelming proportion of

their between-population variation structured by the bound-

aries of Pleistocene islands (H. fischeri, 92%; R. everetti, 97%).

They exhibit almost no variation between present-day islands

within Pleistocene islands. This lack of differentiation between

populations within Pleistocene islands is consistent with the

observation of low FST in P. minor, which occurs only on a

single Pleistocene island. The third endemic species, P. jagori,

also displays over half of its variation between populations at

the between-Pleistocene-island level (59%), consistent with its

moderately broad habitat preferences. Two of three widespread

species also display substantial proportions of their between-

population genetic variation at the between-Pleistocene-island

level (C. brachyotis, 79%; M. minimus, 34%). In contrast,

R. amplexicaudatus shows relatively little of its between-

population genetic variation structured according to the

boundaries of Pleistocene islands (7%).

Overall patterns

Two less commonly employed modes of analysis will be

discussed here to help further illuminate the pattern and extent

of genetic differentiation in these Philippine mammals.

Cockerham’s (1973) extension of Wright’s method of variance

components is used to show the complete breakdown of total

genetic variation (Table 6), including variation within present

island populations which Wright’s hierarchical F-statistics do

not illustrate. Additionally, Slatkin’s (1993) M-statistics are

used to estimate gene flow between all pairs of islands (Fig. 2).

Some clear trends emerge. First, almost no differentiation is

found between present-day island populations within Pleisto-

cene islands for these species (Table 6). Second, there is an

overall pattern of genetic differentiation between Pleistocene

island groups. Two of three endemic species exhibit substantial

proportions of their total genetic variation at the between-

Pleistocene-island level (H. fischeri and R. everetti). Most of the

widespread species also show more variation between Pleisto-

cene islands than between present-day islands within Pleisto-

cene islands, as does the endemic species, P. jagori. Only

R. amplexicaudatus appears to display a pattern of variation in

which Pleistocene shorelines do not form the primary parti-

tions of genetic variation.

Several further generalizations about patterns of gene flow

between populations as inferred from allozyme data can be

discovered by estimating gene flow (Nm) between all pairs of

populations using M-statistics (Slatkin, 1993; Fig. 2). The first

general pattern that emerges is that levels of gene flow are

higher between Leyte and Biliran than between Luzon and

Catanduanes for most species, including all endemic species.

This pattern of genetic similarity is consistent with two factors:

(1) Leyte and Biliran are presently closer to one another than

are Luzon and Catanduanes and may experience higher rates of

present-day gene flow; and (2) Leyte and Biliran are separated

by a much shallower ocean channel than are Luzon and

Catanduanes (Heaney, 1986) and genetic similarity may reflect

the more recent separation of Leyte and Biliran. The second

general pattern that emerges is that gene flow to Sibuyan

appears almost uniformly attenuated (except in M. minimus).

Table 5 Wright’s (1978) hierarchical F-statistics illustrating

genetic differentiation among Pleistocene islands vs. present-day

island populations

Species Level FXY

Variance

component

Percentage

variance

Widespread species

Rousettus amplexicaudatus GPI 0.003 0.0113 7

ISL 0.045 0.1449 93

Total 0.048 0.1562 100

Macroglossus minimus GPI 0.021 0.0280 34

ISL 0.040 0.0536 66

Total 0.061 0.0816 100

Cynopterus brachyotis GPI 0.070 0.0855 79

ISL 0.021 0.0226 21

Total 0.088 0.1081 100

Endemic species

Ptenochirus jagori GPI 0.029 0.0223 59

ISL 0.020 0.0152 41

Total 0.048 0.0375 100

Haplonycteris fischeri GPI 0.537 0.7818 92

ISL 0.100 0.0675 8

Total 0.583 0.8493 100

Rattus everetti GPI 0.492 0.8279 97

ISL 0.030 0.0253 3

Total 0.507 0.8532 100

GPI, among Pleistocene islands; ISL, among present-day islands within

Pleistocene islands.

L. R. Heaney et al.

238 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

This could be the result of smaller or more isolated islands

being more difficult targets for migrants to hit, although the

decrease in levels of migration does not appear to be sufficient

to influence levels of within-population variability, as noted

below. Finally, endemic species display lower levels of gene

flow between Pleistocene islands than within Pleistocene

Table 6 Cockerham’s (1973) method of complete variance partitioning. Each level is expressed as a percentage of the total variance

Widespread Endemic Narrow endemic

Rousettus

amplexi-caudatus (16/29)

Macroglossus

minimus (15/30)

Cynopterus

brachyotis (9/14)

Ptenochirus

jagori (15/29)

Haplonycteris

fischeri (10/14)

Rattus

everetti (10/26)

Ptenochirus

minor (7/29)

Variable loci only

GPI 2.4 3.6 6.7 3.8 30.7 23.9 –

ISL 4.8 3.4 2.6 1.4 0.8 1.3 3.5

W/I 92.8 93.0 90.7 94.8 68.5 74.8 96.5

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0

All loci (monomorphic loci calculated as 100% at lowest level)

GPI 1.4 1.8 4.3 1.9 21.9 9.2 –

ISL 2.6 1.7 1.7 0.7 0.6 0.5 0.8

W/I 96.0 96.5 94.0 97.4 77.5 90.3 99.2

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Results are tabled separately for all loci and for variable loci only. Numbers in parentheses indicate the number of variable loci over the total number

of loci for each taxon. Negative variance components are treated as equal to zero.

GPI, between Pleistocene islands; ISL, between present-day islands within Pleistocene islands; W/I, within present-day islands.

Figure 2 Estimates of gene flow between

selected populations [M after Slatkin (1993)].

Estimates of gene flow between Pleistocene

islands are averages of all estimates along that

track. Abbreviations are: BIL, Biliran; CAT,

Catanduanes; LEY, Leyte; LUZ, Luzon; NEG,

Negros; SIB, Sibuyan. Philippine endemic

species are on the right, non-endemics are on

the left.

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 239

islands, with one exception (H. fischeri: Greater Luzon/Greater

Negros-Panay). Widespread species show no clear differences

in estimates of gene flow within and between Pleistocene

shorelines. This result indicates that the permanent oceanic

barriers between Pleistocene islands are of greater conse-

quence, especially for endemic species, than recent seawater

barriers within Pleistocene islands which have been inundated

by sea-level rise during the past 18,000 years. This is true in

spite of the fact that some of the more recently formed water

gaps within Pleistocene islands are larger than distances

between Pleistocene islands (Appendix S3).

These overall patterns show the influences of both geological

and ecological processes: the Pleistocene history of the

Philippine archipelago has created a common pattern of

significant differentiation between, but not within, Pleistocene

islands. Further, widespread species associated with disturbed

habitats show less variation between and more variation within

populations than species endemic to the Philippines associated

with primary rain forest.

Differentiation of small oceanic island populations

In general, the populations on the small, isolated oceanic

islands in this study (Sibuyan, Barit, Dalupiri, and Fuga)

displayed only weakly reduced within-population variability as

might be expected due to their small size and isolation. Hobs,

NALL, and POLY were significantly lower in oceanic island

populations only for R. amplexicaudatus, and combining

probabilities across the five relevant species did not detect a

significant overall result. There was, however, a consistent

trend for small oceanic island populations to be more strongly

genetically differentiated than large Pleistocene island popula-

tions. Cavalli-Sforza and Edwards arc genetic distance and M

were significantly higher and lower, respectively (both

P < 0.01), along tracks leading to small oceanic islands than

along other island tracks in three of five species (C. brachyotis,

H. fischeri, and R. amplexicaudatus) and nearly so in one

species (P. jagori; both P � 0.10). Combining probabilities

yields a significant overall result for both measures (P < 0.001)

and we conclude that tracks to small, isolated oceanic islands

are characterized by higher genetic distances and lower

estimates of gene flow than tracks between large Pleistocene

islands.

DISCUSSION

Geological history vs. ecology?

This investigation of genetic variation in Philippine mammals

makes two general points clear. First, geological history is of

paramount importance in structuring patterns of variation

between populations of the seven species we studied. The

geological history of the Philippine archipelago has been

characterized by the long-term uplift and short-term (Pleisto-

cene) coalescence and fragmentation of groups of islands. The

maximal late Pleistocene shorelines define biogeographic units

with no history of dry-land connections to other islands or

continents. Populations of mammals on modern islands within

‘Pleistocene islands’ have been separated from one another for

c. 18,000 years; these show little or no genetic variation

between them. In contrast, populations on islands separated by

permanent barriers to dispersal have developed substantial

genetic differentiation. This pattern is concordant with

patterns of interspecific diversity in Philippine mammals; late

Pleistocene shorelines delimit faunal regions for mammals

with high levels of endemism among non-volant mammals (up

to 80%) and moderate levels of endemism among fruit bats

(up to 21%; Heaney, 1986, 1991a, 1993, in press).

The importance of Pleistocene history in structuring

genetic variation within mammalian species in the islands

of Wallacea has also been addressed by Schmitt et al. (1995),

Hisheh et al. (1998), and Maharadatunkamsi et al. (2003).

Their examination of differentiation in the fruit bats

C. nusatengarra and E. spelaea from the Lesser Sunda Islands

of Indonesia concluded that patterns of genetic distances

between island populations are associated with recent

colonization from west to east along the island arc (we note

they are also consistent with the isolation-by-distance effect),

and are more closely correlated with distances between

Pleistocene shorelines than with distances between present

shorelines, although the overall level of population subdivi-

sion that they recorded was markedly lower than in this

study. In contrast to Schmitt et al.’s (1995) and Hisheh

et al.’s (1998) results, we detected little evidence of a

relationship of island area (which is presumably related to

effective population size) or island isolation (which is

presumably related to levels of gene flow) to amounts of

variation within populations. Similarly, Juste et al. (2000)

found that, of several insular populations of an African fruit

bat, Eidolon helvum, the most isolated of these showed much

greater genetic differentiation than the others, in association

with reduced gene flow.

Second, the ecological attributes of individual species

influence the extent to which, and the manner in which,

common historical signals are expressed. Our knowledge of

natural history and distributions of these mammals success-

fully predicted whether or not they would demonstrate large or

small degrees of genetic differentiation between populations

(including, in most respects, the ecologically intermediate

P. jagori) and whether or not they would display relatively high

or low levels of variation within populations. This result has

important implications for understanding evolution – any

attempt to make general statements about rates of genetic

change between populations must take into account the

ecological attributes of the species in question. We also stress

that these insights into the common regional pattern of

variation and particularly into the differences in expression of

that pattern are unlikely to have been gained by the examina-

tion of a single species. Generalizations about the patterns of

geographic variation and their causes are best achieved

through comparative studies such as this one, and similar

studies (e.g. Caccone, 1985; Waples, 1987; Brumfield &

L. R. Heaney et al.

240 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

Capparella, 1996; Zink et al., 2000; Riddle & Hafner, in press).

Thus, we conclude that geological history and ecological traits

produce interactive processes, and must be considered

simultaneously for accurate conclusions about general genetic

processes in nature to be reached.

Small islands + isolation = speciation?

One of the motivations for studying geographic variation is the

identification of especially distinctive populations. To the

degree that the origin of new species is an extension of

divergence between populations within species, identifying

divergent populations can provide insight into the processes of

speciation. In his classic volume, Mayr (1963) identified

‘geographical isolates’ as those populations most likely to

produce new species; discussing island populations in partic-

ular, he characterized geographical isolates as typically inhab-

iting islands of small area and differing environmental

conditions, having low population sizes, possessing distinctive

morphologies or behaviours, and being spatially or temporally

separated from other populations by barriers to gene flow. For

the Philippine mammals in this study, populations inhabiting

the small, isolated oceanic islands (Sibuyan, Barit, Dalupiri,

and Fuga) that were not connected as part of any large

Pleistocene island appear to qualify as geographical isolates.

These small oceanic islands are much smaller in area than the

large Pleistocene islands and have never had dry-land connec-

tions to them. All of them except Sibuyan also have depauperate

mammal faunas (Heaney et al., 1998, L.R. Heaney et al.,

unpubl. data). These island populations do not show evidence

of substantially reduced genetic variation within any given

species. We assume that effective population size is limited by

island area. While these small oceanic islands are indeed small

by most standards, they do not appear to be small enough to

erode within-population genetic variability as has been sugges-

ted for other small island populations of mammals (Berry, 1986,

1998). Using the population density estimates of Heideman &

Heaney (1989) for fruit bats on Negros Island as first

approximations, it seems likely that bat populations on even

the smallest of our islands number at least in the thousands – far

above the numbers typically believed to cause noticeable loss of

genetic variation (Lande & Barrowclough, 1987).

Although the populations on small, isolated islands do not

show reduced genetic within-island variation within a given

species, they are more genetically distinct. For each species, all

oceanic island populations possess unique alleles, and the

population of H. fischeri from Sibuyan is fixed for one unique

allele (Appendix S1). Further, the genetic distances between

populations evident in Fig. 3 are greater between Pleistocene

islands than within them, and are typically greatest to the small

oceanic islands. Whether this genetic distinctiveness is due to

selective or neutral factors is not evident from our data;

certainly, it is conceivable that the differing biotic and abiotic

environmental conditions on these small oceanic islands may

impose different selective pressures on these populations.

However, the rate of fixation of genes due to genetic drift is a

function of the inverse of effective population size (Kimura,

1983) and it may be that these small oceanic island populations

are sufficiently small to have accelerated rates of fixation of

new alleles relative to the large island populations.

It is unlikely that the genetic distinctiveness of small isolated

island populations is solely a reflection of the phylogenetic

history of these populations. Peterson & Heaney (1993)

discussed the importance of establishing population-level

phylogenies for understanding the biogeographic history of

these taxa in the Philippines. They objected to interpreting

UPGMA dendrograms, which are the results of cluster analyses

of distance data utilizing mid-point rooting, as representations

of phylogeny, preferring that estimates of phylogenetic

relationships be based on parsimony analyses of character

data using outgroup comparisons. Additional objections to the

use of allozymes in phylogenetic analyses are that allozyme

frequencies are temporally unstable (Gaines et al., 1978;

Crother, 1990) and that transitions between electromorphs

Figure 3 UPGMA dendrograms of island populations based on

genetic distance (Cavalli-Sforza & Edwards (1967) arc distance).

Abbreviations are: BAR, Barit; BIL, Biliran; CAT, Catanduanes;

DAL, Dalupiri; FUG, Fuga; LEY, Leyte; LUZ, Luzon; MRO,

Mindoro; NEG, Negros; POL, Polillo; SIB, Sibuyan. All

dendrograms drawn to same scale.

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 241

cannot be reliably ordered (Lewontin, 1991). As noted by

Peterson & Heaney (1993), the distinctive small oceanic island

populations are very unlikely to represent basal divisions vs.

other populations in a phylogenetic sense due to their

geographic setting (well away from likely avenues of coloniza-

tion) and to the fact that they are among the geologically most

recent of the Philippine islands (Steppan et al., 2003). This

implies, for example, that the long branches associated with

Sibuyan Island (Fig. 3) are due to rapid evolution on Sibuyan,

not to earlier isolation than other populations. Our interpret-

ation could be tested by use of intraspecific phylogenies

generated from DNA sequences, as currently being developed

by T. Roberts (pers. comm.).

Gene flow: endemism or habitat requirements?

This report yields two additional insights particularly relevant

to our understanding of mammals and the Philippine biota.

First, it seems an intuitively obvious expectation that a non-

volant mammal should have rates of dispersal across water

barriers orders of magnitude lower than those of a volant

mammal. It is therefore remarkable that the endemic rodent

R. everetti shows levels of gene flow between Pleistocene islands

comparable to that of the endemic fruit bat H. fischeri. One

likely explanation for this unanticipated result is that the

tolerance for disturbed, open habitat by H. fischeri is far less

than that of R. everetti (Rickart et al., 1993; Heaney et al., 1998,

1999): although it is far more effective for small mammals to

fly over water barriers than to swim across them, some bat

species may cross-water gaps less often than some rodents.

This inference suggests the hypothesis that habitat affinity may

be as important as mode of dispersal in accounting for

variation in levels of gene flow across different taxa.

Second, the pattern of variation within and between

populations exhibited by P. jagori highlights distinctive aspects

of its historical and ecological traits. It is an endemic species

that is common in good quality rain forest habitat, and it

displays low levels of within-population variation. However, it

also persists well in degraded forest and often flies in cleared

areas, and it displays high gene flow and little variation

between populations. This combination of low within- and

between-population variability is often considered to be the

earmark of a recent colonizer. It is possible that P. jagori was

formerly more restricted in distribution, perhaps on a single

Pleistocene island like its sister-taxon, P. minor, and has only

recently spread throughout the Philippine archipelago. The

data presented here cannot resolve this question, and even if

the colonization of the whole of the Philippine archipelago by

P. jagori has been a relatively recent event, some differentiation

between populations has occurred. The Sibuyan population

appears relatively distinct based on the allozyme data presented

here (Fig. 2), and morphological data (Walsh, 1998) indicate

that on the islands of Greater Mindanao, where P. jagori is

sympatric with the smaller P. minor, P. jagori has evolved

much larger body size than is found in its other island

populations. Investigations currently underway on the

phylogenetic relationships of populations of Ptenochirus and

related cynopterine fruit bats by T. Roberts using DNA

sequencing (pers. comm.) may provide additional insight into

the historical association of genetic variation and geographic

distribution in these taxa.

A simple geographical/ecological model of genetic

differentiation in oceanic archipelagos

The previous analyses suggest that patterns of genetic variation

in these Philippine mammals are strongly influenced by two

ecological variables, namely their vagility (especially the ability

to fly) and the ability to tolerate open habitats (which in the

Philippines are synonymous with heavily disturbed habitats).

These variables interact simultaneously in any given species to

largely determine its colonizing ability. These two variables, in

turn, are associated with varying levels of genetic differenti-

ation, as discussed further below.

Among our study species, C. brachyotis and M. minimus are

moderately strong fliers, and R. amplexicaudatus is a very

strong flier; all three prefer open habitat, and we characterize

them as having high colonizing ability. One of the endemic

bats (P. jagori) prefers closed-canopy, primary forest, but is a

strong flier and maintains populations in open, disturbed

forest well; we characterize it overall as having moderate

colonizing ability. Two species, H. fischeri and R. everetti, have

low colonizing ability, but for different reasons: H. fischeri can

fly, but is a relatively weak flier and rarely will fly out from

under good canopy cover, while R. everetti does well in

disturbed forest (although not in intensive agricultural areas)

but cannot fly. Ptenochirus minor prefers good canopy cover

but tolerates second growth, and so may have better colon-

izing ability overall than the prior two species, but its

restriction to a single Pleistocene island (Greater Mindanao)

implies limited abilities. We further note that C. brachyotis,

M. minimus, and R. amplexicaudatus occur on even the most

isolated of Philippine islands, whereas P. jagori and R. everetti

are absent from some of the most isolated islands (including

Barit, Batan, Dalupiri, and Fuga) and H. fischeri is absent from

those islands and also from less isolated Siquijor and

Camiguin (north of Mindanao; Lepiten 1997; Heaney et al.,

1998), providing direct empirical evidence of their limited

dispersal abilities.

We have found three categories of Philippine islands with

respect to geological history: (1) the current islands, many of

which aggregated during Pleistocene periods of low sea level

(as shown in Fig. 1); within such aggregates, these share very

similar faunas; (2) large Pleistocene islands that are surroun-

ded by deep water, which have been isolated continuously

throughout their existence but are not very distant from one

another; each has a very distinctive fauna, with 40–80%

endemism (Heaney, 1998, 2000); and (3) Pleistocene islands

that are especially small and isolated by great distance, some of

which are depauperate. The last two categories differ primarily

in degree, but in the Philippines, they are fairly discrete, as can

be seen in Fig. 1.

L. R. Heaney et al.

242 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

We summarize the two variables of colonizing ability and

geographic isolation for our seven study species along two axes

in Fig. 4. We present each as a categorical variable rather than

a continuous variable because, while conceptually each is

continuous, our data demonstrate that they appear to behave

in the Philippines in a discontinuous fashion because of

historical circumstances; in general, the world is often neither

homogeneous nor continuous with respect to these variables.

Our data (Table 2, Fig. 2) show C. brachyotis, M. minimus,

and R. amplexicaudatus to have consistently high gene flow both

within and between Pleistocene islands (Nm of 4–14), although

C. brachyotis has Nm as low as 1.2–1.7 on some isolated islands

(such as Sibuyan). P. jagori, as expected, hasNm at intermediate

levels (3–5.5), and H. fischeri and R. everetti have Nm values

always far less than 1.0 between Pleistocene islands.

The converse of gene flow, genetic differentiation, is

calculated from the same data set as gene flow, and is

effectively its inverse, so that species with high gene flow have

low differentiation (FST values), and the converse (Tables 2

and 4). In other words, in the absence of high levels of gene

flow (defined as Nm less than 1.0 by Wright, 1931), substantial

genetic differentiation takes place.

Our data demonstrate that these two variables have

combined to have a strong association with rates of genetic

differentiation, as we show in the third axis in Fig. 4. Within a

Pleistocene island (Fig. 4, bottom row), none of our study

species showed genetic differentiation. On separate but adja-

cent Pleistocene islands (Fig. 5, middle row), H. fischeri and

R. everetti show moderately high genetic differentiation, but

the other species very low differentiation. On distant oceanic

islands (Fig. 5, top row), H. fischeri and R. everetti again show

heightened differentiation due to low colonizing ability.

Somewhat to our surprise, C. brachyotis shows moderate

differentiation on isolated islands, perhaps indicating that our

estimates of colonizing ability are too high. We found the

species with the highest colonizing ability (R. amplexicaudatus)

to show virtually no genetic differentiation on distant Pleis-

tocene islands, one that is smaller and a somewhat weaker flier

(M. minimus) to show slightly more, and a species with

medium colonizing ability (P. jagori) to show somewhat

greater genetic differentiation on the same islands.

Most crucially for the study of diversification, a comparison

of species on a given set of isolated oceanic islands shows

that species with high colonizing ability (R. amplexicaudatus

and M. minimus) exhibit little genetic differentiation, species

with moderate colonizing ability (P. jagori and apparently

C. brachyotis) exhibit a moderate amount of genetic

differentiation, and species with little colonizing ability

(H. fischeri, R. everetti) on the same islands exhibit high

genetic differentiation. In other words, the likelihood of any

given species developing substantial genetic differentiation

increases as it reaches progressively more isolated islands, but a

species with ecological traits that reduce its colonizing ability

(e.g. an aversion to flying out from beneath the canopy or an

inability to fly) will differentiate on less isolated islands than a

species with ecological traits that increase the rate of gene flow.

This simple description of patterns of interaction between

colonization ability and isolation, and the degree of genetic

differentiation that is associated, may be used as a model to

make predictions for other Philippine mammals, for other

Philippine organisms, and for organisms in other oceanic

archipelagos. For example, we predict that insectivorous bats in

the Philippines will show similar patterns: widespread species

that do well in disturbed habitats, such as those in the genera

Taphozous, Miniopterus, Myotis, Pipistrellus, and Scotophilus

should be very similar to C. brachyotis, M. minimus, and

R. amplexicaudatus, but Philippine endemic species in the

genera Rhinolophus and some Hipposideros that live in primary

forest should be similar to Haplonycteris and Ptenochirus. If

there are animals with still less dispersal ability than H. fischeri

and R. everetti, perhaps such as the many native shrews and

mice, or frogs with very low dispersal, we predict that they will

show even lower levels of colonizing ability and higher rates of

genetic differentiation; this prediction is at least generally

supported by the findings of Brown & Guttman (2002) and

Steppan et al. (2003). We predict that Philippine birds will

show very similar patterns to these bats overall, with widespread

species that favour disturbed habitats having genetic patterns

that resemble those of C. brachyotis, M. minimus, and

R. amplexicaudatus, whereas those that require primary forest

and/or that have limited flight will have genetic patterns that

resemble those of H. fischeri. In this study, we found all species

to have high colonizing ability and low differentiation within

Pleistocene islands, but we note that some other taxa may have

Figure 4 Graphical model of the interaction of colonizing ability

and degree of isolation on the extent of genetic differentiation by

six species of fruit bats and one murid rodent in the oceanic

Philippines. Isolation is low (within islands that merged during

Pleistocene periods of low sea level), medium (between islands

separated continuously by deep water, but by channels that are

narrow), or high (between islands separated continuously by deep

water and broad channels). Cb, Cynopterus brachyotis, Hf, Hapl-

onycteris fischeri, Mm, Macroglossus minimus, Pj, Ptenochirus

jagori, Pm, Ptenochirus minor, Ra, Rousettus amplexicaudatus,

Re, Rattus everetti.

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 243

far lower dispersal abilities and be influenced by more subtle

isolating barriers (such as different types of forest), and

therefore show higher rates of genetic differentiation within a

given modern island (perhaps including frogs and some

montane non-volant small mammals, flightless montane inver-

tebrates, etc. that live in montane and mossy forest; Heaney &

Rickart, 1990; Heaney, 2001). We predict their relative levels of

gene flow and differentiation will be structured similarly to the

bats but on a smaller geographic scale, with equivalent

ecological correlates regarding habitat fidelity and vagility.

Finally, we predict that species on the oceanic islands of

Wallacea as a whole, and in other oceanic archipelagos, will

show similar patterns of association between colonizing ability,

isolation, and differentiation. Ideal test cases would include the

birds (Lack, 1976; Ricklefs & Bermingham, 2001) and lizards

(Losos & Schluter, 2000; Harmon et al., 2003) of the Caribbean,

and the fauna of the Sea of Cortez (Case et al., 2002).

CONCLUSION

For much of the last three decades, most studies of biological

diversity in island ecosystems have approached the topic from

either an ecological or an historical/geological perspective,

typified by the ecologically-oriented equilibrium model of

MacArthur & Wilson (1967) and by the historically-oriented

vicariance model (e.g. Rosen, 1975). Moreover, there is

generally a tendency for biological research to be deliberately

conducted in very simple systems so that the impact of specific

processes may be finely parsed. This study has been useful in

demonstrating that the question of ‘geological history or

ecology’ is based on a false premise that only one or the other

is a significant factor; in this case, both are highly important, and

we predict that both will be found to be equally important in all

other oceanic archipelagos. In this case, current genetic patterns

are profoundly influenced by historical (geological) factors, but

ecological features of the various species, such as habitat

association and vagility, strongly affect rates of gene flow and,

therefore, degree of divergence among populations. Indeed, we

found that habitat association may in some cases be even more

important in determining patterns of genetic variation within

species than whether a species is volant or non-volant.

Few of our findings could have been derived from studying

any single one of the seven species, and few could have been

derived had we worked in a simpler set of islands. While very

specific and narrowly-oriented studies of simple island systems

or single species may be useful and often necessary in adding

clarity, studies that emphasize broad contexts, multiple species,

and complex regions are likely to be essential for discovering

broad patterns and processes. Indeed, this study would have

been strengthened by including even more species and islands.

The complexity of global biological diversity will best be

understood by combining historical and ecological questions

and perspectives, and considering them for many species

simultaneously; the challenge is not to determine which single

model or process predominates, but rather to determine how

the processes interact under varying circumstances, and how

narrow/focused models can be integrated into comprehensive

models that accurately portray the very real complexity of

living systems (Case & Cody, 1982; Heaney, 1986, 2000;

Whittaker, 1998; Zink et al., 2000; Hewitt, 2001; Arbogast &

Kenagy, 2002; Riddle & Hafner, in press).

ACKNOWLEDGEMENTS

We gratefully acknowledge the assistance of many colleagues

and institutions with the field portion of this study, especially

A. C. Alcala, D. S. Balete, C. Catibog-Sinha, R. I. Crombie,

C. Custodio, R. Fernandez, P. C. Gonzales, P. D. Heideman,

J. S. H. Klompen, M. Laranjo, M. V. Lepiten-Tabao,W. Pollisco,

E. A. Rickart, C. A. Ross, B. R. Tabaranza, Jr, R. C. B. Utzurrum,

the Protected Areas and Wildlife Bureau of the Philippines, the

Department of Environment and Natural Resources of the

Philippines, Silliman University, the Haribon Foundation, and

the Philippine National Museum. Permits were provided by the

Philippine Department of Natural Resources. We thank E. A.

Rickart, P. D. Heideman, T. J. McIntyre, R. S. Thorington, Jr,

R. S. Hoffmann, M. J. Carleton, J. H. Brown, G. G. Musser,

J. M. Bates, and S. J. Hackett, who have all played important

roles in the development of the ideas presented here. We thank

John Bates, Shannon Hackett, Trina Roberts, and two anony-

mous reviewers for their helpful comments on earlier drafts of

the manuscript. These studies were supported in part by the US

National Science Foundation (BSR-8514223), the Smithsonian

Institution Office of Fellowships and Grants, the Ellen Thorne

Smith and Barbara Brown Funds of the Field Museum, and the

John D. and Catherine T. MacArthur Foundation’s World

Environment and Resources Program (90-9272A).

SUPPLEMENTARY MATERIAL

The following material is available from http://www.blackwell

publishing.com/products/journals/suppmat/JBI/JBI1120/

JBI1120sm.htm

Appendix S1 Allele frequencies for Philippine mammals.

Appendix S2 Genetic distance matrices.

Appendix S3 Matrix of geographic distances between islands.

REFERENCES

Arbogast, B.S. & Kenagy, G.J. (2001) Comparative phylogeo-

graphy as an integrative approach to historical biogeo-

graphy. Journal of Biogeography, 28, 819–825.

Avise, J.C. (2000) Phylogeography, the history and formation of

species. Harvard University Press, Cambridge.

Bermingham, E. & Moritz, C. (1998) Comparative phylogeo-

graphy: concepts and applications. Molecular Ecology, 7,

367–369.

Berry, R.J. (1986) Genetics of insular populations of mammals,

with particular reference to differentiation and founder

effects in British small mammals. Biological Journal of the

Linnean Society, 28, 205–230.

L. R. Heaney et al.

244 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

Berry, R.J. (1998) Evolution of small mammals. Evolution on

islands (ed. by P.R. Grant), pp. 35–50. Oxford University

Press, Oxford.

Brown, R.M. & Guttman, S.I. (2002) Phylogenetic systematics

of the Rana signata complex of Philippine and Bornean

stream frogs: reconsideration of Huxley’s modification of

Wallace’s Line at the Oriental-Australian faunal zone inter-

face. Biological Journal of the Linnean Society, 76, 393–461.

Brumfield, R.T. & Capparella, A.P. (1996) Historical diversi-

fication of birds in northwestern South America: a mole-

cular perspective on the role of vicariant events. Evolution,

50, 1607–1624.

Caccone, A. (1985) Gene flow in cave arthropods: a qualitative

and quantitative approach. Evolution, 39, 1223–1235.

Case, T.J. & Cody, M.L. (1982) Synthesis: pattern and process

in island biogeography. Island biogeography in the Sea of

Cortez (ed. by T.J. Case and M.L. Cody), pp. 307–341.

University of California Press, Berkeley.

Case, T.J., Cody, M.L. & Ezcurra, E. (eds) (2002) A new island

biogeography of the Sea of Cortez. Oxford University Press,

Oxford.

Cavalli-Sforza, L.L. & Edwards, A.W.F. (1967) Phylogenetic

analysis: models and estimation procedures. Evolution, 21,

550–570.

Cockerham, C.C. (1969) Variance of gene frequencies. Evolu-

tion, 23, 72–84.

Cockerham, C.C. (1973) Analysis of gene frequencies. Genetics,

74, 679–700.

Crother, B.I. (1990) Is ‘some better than none’ or do allele

frequencies contain phylogenetically useful information?

Cladistics, 6, 277–281.

Dietz, E.J. (1983) Permutation tests for association between

distance matrices. Systematic Zoology, 32, 21–26.

Esselstyn, J.A., Widmann, P. & Heaney, L.R. (in press) The

mammals of Palawan Island, Philippines. Proceedings of the

Biological Society of Washington, in press.

Fairbanks, R.G. (1989) A 17,000-year glacio-eustatic sea level

record: influence of glacial melting rates in the Younger Dryas

event and deep-ocean circulation. Science, 342, 637–642.

Farris, J.S. (1972) Estimating phylogenetic trees from distance

data. American Naturalist, 106, 645–668.

Felsenstein, J. (1989) PHYLIP (phylogeny inference package),

Version 3.2 manual. University of Washington, Seattle, WA.

Fisher, R.A. (1954) Statistical methods for research workers, 12th

edn. Oliver and Boyd, Edinburgh.

Fitch, W.M. & Margoliash, E. (1967) Construction of phylo-

genetic trees. Science, 155, 279–284.

Frankham, R. (1995) Inbreeding and extinction: a threshold

effect. Conservation Biology, 9, 792–799.

Frankham, R. (1996) Relationship of genetic variation to

population size in wildlife. Conservation Biology, 10, 1500–

1508.

Gaines, M.S., McClenaghan, L.R., Jr & Rose, R.K. (1978)

Temporal patterns of allozymic variation in fluctuating

populations of Microtus ochrogaster. Evolution, 32, 723–739.

Grant, P.R. (1998) Evolution on islands. Oxford University

Press, Oxford.

Gurevitch, J., Morrow, L.L., Wallace, A. & Walsh, J.S. 1992. A

meta-analysis of competition in field experiments. American

Naturalist, 140, 539–572.

Haldane, J.B.S. (1954) A test for randomness of mating.

Journal of Genetics, 52, 631–635.

Hall, R. (1998) The plate tectonics of Cenozoic SE Asia and the

distribution of land and sea. Biogeography and geological

evolution of SE Asia (ed. by R. Hall and J.D. Holloway).

Backhuys Publishers, Leiden.

Hall, R. (2002) Cenozoic geological and plate tectonic evolu-

tion of SE Asia and the SW Pacific: computer-based

reconstructions, model and animations. Journal of Asian

Earth Sciences, 20, 353–431.

Hall, R. & Holloway, J.D. (eds) (1998) Biogeography and geo-

logical evolution of SE Asia. Backhuys Publishers, Leiden.

Harmon, L.J., Schulte, J.A., II, Larson, A. & Losos, J.B. 2003.

Tempo and mode of evolutionary radiation in Iguanian

lizards. Science, 301, 961–964.

Harris, H. & Hopkinson, D.A. (1978) Handbook of enzyme

electrophoresis in human genetics. North Holland Publishing

Co., Amsterdam.

Heaney, L.R. (1986) Biogeography of mammals in SE Asia:

estimates of rates of colonization, extinction, and speciation.

Biological Journal of the Linnean Society, 28, 127–165.

Heaney, L.R. (1991a) An analysis of patterns of distribution

and species richness among Philippine fruit bats (Pteropo-

didae). Bulletin of the American Museum of Natural History,

206, 145–167.

Heaney, L.R. (1991b) A synopsis of climatic and vegetational

change in Southeast Asia. Climatic Change, 19, 53–61.

Heaney, L.R. (1993) Biodiversity patterns and conservation of

mammals in the Philippines. Asia Life Sciences, 2, 261–274.

Heaney, L.R. (2000) Dynamic disequilibrium: a long-term,

large-scale perspective on the equilibrium model of island

biogeography. Global Ecology and Biogeography, 9, 59–74.

Heaney, L.R. (2001) Small mammal diversity along elevational

gradients in the Philippines: an assessment of patterns and

hypotheses. Global Ecology and Biogeography, 10, 15–39.

Heaney, L.R. (in press) Conservation in oceanic archipelagos.

Frontiers of biogeography, recent advances in the geography of

nature (ed. by M.V. Lomolino and L.R. Heaney). Sinauer

Associates, Sunderland.

Heaney, L.R., Heideman, P.D., Rickart, E.A., Utzurrum, R.B. &

Klompen, J.S.H. (1989) Elevational zonation of mammals in

the central Philippines. Journal of Tropical Ecology, 5, 259–

280.

Heaney, L.R. & Regalado, J.C. (1998) Vanishing treasures of the

Philippine rain forest. The Field Museum, Chicago, IL.

Heaney, L.R. & Rickart, E.A. (1990) Correlations of clades and

clines: geographic, elevational, and phylogenetic distribution

patterns among Philippine mammals. Vertebrates in the

tropics (ed. by G. Peters and R. Hutterer), pp. 321–332.

Museum Alexander Koenig, Bonn.

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 245

Heaney, L.R., Balete, D.S., Dolar, L., Alcala, A.C., Dans, A.,

Gonzales, P.C., Ingle, N., Lepiten, M.V., Oliver, W., Rickart,

E.A., Tabaranza, B.R., Jr & Utzurrum, R.C.B. (1998) A

synopsis of the mammalian fauna of the Philippine Islands.

Fieldiana Zoology New Series, 88, 1–61.

Heaney, L.R., Balete, D.S., Rickart, E.A., Utzurrum, R.C.B. &

Gonzales, P.C. (1999) Mammalian diversity on Mt. Isarog, a

threatened center of endemism on southern Luzon Island,

Philippines. Fieldiana New Series, 95, 1–62.

Heideman, P.D. & Heaney, L.R. (1989) Population biology and

estimates of abundance of fruit bats (Pteropodidae) in

Philippine submontane rainforest. Journal of Zoology (Lon-

don), 218, 565–586.

Hewitt, G.M. (2001) Speciation, hybrid zones and phyloge-

ography – or seeing genes in space and time. Molecular

Ecology, 10, 907–913.

Hisheh, S., Westerman, M. & Schmitt, L.H. (1998) Biogeo-

graphy of the Indonesian archipelago: mitochondrial DNA

variation in the fruit bat, Eonycteris spelaea. Biological

Journal of the Linnean Society, 65, 329–345.

Holloway, J.D. (2003) Biological images of geological history:

through a glass darkly or brightly face to face? Journal of

Biogeography, 30, 165–180.

International Union of Biochemistry and Molecular Biology

(1992) Enzyme nomenclature. Academic Press, SanDiego, CA.

Juste, J., Ibanez, C. & Machordom, A. 2000. Morphological

and allozyme variation of Eidolon helvum (Mammalia:

Megachiroptera) in the islands of the Gulf of Ghana. Bio-

logical Journal of the Linnean Society, 71, 359–378.

Kimura, M. (1983) The neutral theory of molecular evolution.

Cambridge University Press, Cambridge.

Lack, D. (1976) Island biology illustrated by the land birds of

Jamaica. University of California Press, Berkeley.

Lande, R. (1995) Mutation and conservation. Conservation

Biology, 9, 782–791.

Lande, R. & Barrowclough, G.F. (1987) Effective population

size, genetic variation, and their use in population man-

agement. Viable populations for conservation (ed. by Soule,

M.), pp. 87–123. Cambridge University Press, Cambridge.

Lepiten, M.V. (1997) The mammals of Siquijor Island, central

Philippines. Sylvatrop, 5, 1–17.

Levene, H. (1949) On a matching problem arising in genetics.

Annals of Mathematics and Statistics, 20, 91–94.

Lewontin, R. (1991) Twenty-five years ago in genetics: elec-

trophoresis in the development of evolutionary genetics:

milestone or millstone? Genetics, 128, 657–662.

Livshits, G., Sokal, R.R. & Kobyliansky, E. (1991) Genetic

affinities of Jewish populations. American Journal of Human

Genetics, 49, 131–146.

Lomolino, M.V. (2000) A call for a new paradigm of island

biogeography. Global Ecology and Biogeography, 9, 1–6.

Losos, J.B. & Schluter, D. (2000) Analysis of an evolutionary

species-area relationship. Nature, 408, 847–850.

MacArthur, R.H. & Wilson, E.O. (1967) The theory of island

biogeography. Princeton University Press, Princeton.

Maharadatunkamsi, Hisheh, S., Kitchener, D.J. & Schmitt,

L.H. (2003) Relationships between morphology, genetics

and geography in the cave fruit bat Eonycteris spelaea

(Dobson, 1871) from Indonesia. Biological Journal of the

Linnean Society, 79, 511–522.

Mantel, N. (1967) The detection of disease clustering and a

generalized regression approach. Cancer Research, 27, 209–

220.

Mayr, E. (1963) Animal species and evolution. Belknap Press,

Cambridge, MA.

Mey, W. (2003) Insular radiation of the genus Hydropsyche

(Insecta, Trichoptera: Hydropsychidae) Pictet, 1834 in the

Philippines and its implications for the biogeography of

Southeast Asia. Journal of Biogeography, 30, 227–236.

Mitchell, A.H.G., Hernandez, F. & De La Cruz, A.P. (1986)

Cenozoic evolution of the Philippine archipelago. Journal of

Southeast Asian Earth Sciences, 1, 3–22.

Mittermeier, R.A., Myers, N. & Mittermeier, C.G. (1999)

Hotspots, earth’s biologically richest and most endangered

terrestrial ecoregions. CEMEX, Mexico City.

Myers, N. (1988) Environmental degradation and some eco-

nomic consequences in the Philippines. Environmental

Conservation, 15, 205–213.

Nei, M. (1973) Analysis of gene diversity in subdivided pop-

ulations. Proceedings of the National Academy of Science

USA, 70, 3321–3323.

Nei, M. (1977) F-statistics and analysis of gene diversity in

subdivided populations. Annals of Human Genetics, 41, 225–

233.

Nei, M. (1978) Estimation of average heterozygosity and genetic

distance from a small number of individuals. Genetics, 89,

583–590.

Packham, G. (1996) Cenozoic SE Asia: reconstructing its

aggregation and reorganization. Tectonic evolution of

Southeast Asia, Vol. 106 (ed. by R. Hall and D. Blundell),

123–152. Geological Society Special Publication, The Geo-

logical Society, London.

Peterson, A.T. & Heaney, L.R. (1993) Genetic differentiation

in Philippine bats of the genera Cynopterus and Haplo-

nycteris. Biological Journal of the Linnean Society, 49, 203–

218.

Powers, D.A., Lauerman, T., Crawford, D. & DiMichele, L.

(1991) Genetic mechanisms for adapting to a changing

environment. Annual Review of Genetics, 25, 629–659.

Rickart, E.A., Heaney, L.R. & Utzurrum, R.C.B. (1991) Dis-

tribution and ecology of small mammals along an elevational

transect in southeastern Luzon. Journal of Mammalogy, 72,

458–469.

Rickart, E.A., Heaney, L.R., Heideman, P.D. & Utzurrum,

R.C.B. (1993) The distribution and ecology of mammals on

Leyte, Biliran, and Maripipi Islands, Philippines. Fieldiana:

Zoology, New Series, 72, 1–62.

Ricklefs, R.E. & Bermingham, E. (2001) Nonequilibrium

diversity dynamics of the Lesser Antillean avifauna. Science,

294, 1522–1524.

L. R. Heaney et al.

246 Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd

Riddle, B.R. & Hafner, D.J. (in press) The past and future roles

of phylogeography in historical biogeography. Frontiers of

biogeography (ed. by M.V. Lomolino and L.R. Heaney).

Sinauer Associates, Sunderland.

Rosen, D.E. (1975) A vicariance model of Caribbean bioge-

ography. Systematic Zoology, 24, 431–464.

Schluter, D. (2000) The ecology of adaptive radiation. Oxford

University Press, Oxford.

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 Cynopterus. Evolution, 49, 399–412.

Shaw, C.R. & Prasad, R. (1970) Starch-gel electrophoresis of

enzymes: a compilation of recipes. Biochemical Genetics, 4,

297–320.

Siddall, M., Rohling, E.J., Almogi-Labin, A., Hemleben, C.,

Meischner, D., Schmelzer, I. & Smeed, D.A. (2003) Sea-level

fluctuations during the last glacial cycle. Nature, 423, 853–

858.

Slatkin, M. (1985) Rare alleles as indicators of gene flow.

Evolution, 39, 53–65.

Slatkin, M. (1993) Isolation by distance in equilibrium and

nonequilibrium populations. Evolution, 47, 264–279.

Slatkin, M. & Barton, N. (1989) A comparison of three indirect

methods for estimating average level of gene flow. Evolution,

43, 1349–1368.

Sneath, P.H.A. & Sokal, R.R. (1973) Numerical taxonomy.

W. H. Freeman, San Francisco.

Sokal, R.R. (1988) Genetic, geographic, and linguistic distances

in Europe. Proceedings of the National Academy of Science

USA, 85, 1722–1726.

Sokal, R.R. & Rohlf, F.J. (1981) Biometry, 2nd edn. W. H.

Freeman and Co., New York.

Sokal, R.R. & Wartenberg, D.E. (1983) A test of spatial auto-

correlation analysis using an isolation-by-distance model.

Genetics, 105, 219–237.

Soule, M.E. (1976) Allozyme variation, its determinants in

space and time. Molecular evolution (ed. by F.J. Ayala), pp.

60–77. Sinauer Associates, Sunderland.

Soule, M.E. (1987) Viable populations for conservation. Cam-

bridge University Press, Cambridge.

Steppan, S.J., Zawadski, C. & Heaney, L.R. (2003) Molecular

phylogenyof the endemicPhilippine rodentApomys (Muridae)

and the dynamics of diversification in an oceanic archipelago.

Biological Journal of the Linnean Society, 80, 699–715.

Swofford, D.L. & Berlocher, S.H. (1987) Inferring evolutionary

trees from gene frequency data under the principle of max-

imum parsimony. Systematic Zoology, 36, 293–325.

Swofford, D.L. & Selander, R.B. (1981) BIOSYS-1: A FOR-

TRAN program for the comprehensive analysis of electro-

phoretic data in population genetics and systematics. Journal

of Heredity, 72, 281–283.

Walsh, J.S., Jr (1998) Geographic variation in Philippine fruit

bats (Mammalia: Pteropodidae) and systematics of the

cynopterine section. Unpublished PhD Dissertation,

University of Chicago, Chicago, IL, 257pp.

Waples, R.S. (1987) A multispecies approach to the analysis of

gene flow in marine shore fishes. Evolution, 41, 385–400.

Weir, B.S. (1990) Genetic data analysis. Sinauer Associates, Inc.

Publishers, Sunderland.

Weir, B.S. & Cockerham, C.C. (1984) Estimating F-statistics for

the analysis of population structure.Evolution, 38, 1358–1370.

Whittaker, R.J. (1998) Island biogeography: ecology, evolution

and conservation. Oxford University Press, Oxford, 285pp.

Wildlife Conservation Society of the Philippines (1997)

Philippine red data book. Bookmark, Manila, Philippines,

240pp.

Wright, S. (1931) Evolution in Mendelian populations. Gen-

etics, 16, 97–159.

Wright, S. (1943) Isolation by distance. Genetics, 28, 114–138.

Wright, S. (1951) The genetical structure of populations. An-

nals of Eugenics, 15, 323–354.

Wright, S. (1965) The interpretation of population structure

by F-statistics with special regard to systems of mating.

Evolution, 19, 395–420.

Wright, S. (1978) Evolution and genetics of populations, Vol. 4.

Variability within and among natural populations. University

of Chicago Press, Chicago, IL.

Zink, R.M., Blackwell-Rago, R.C. & Ronquist, F. (2000) The

shifting roles of dispersal and vicariance in biogeography.

Proceedings of the Royal Society of London Series B – Biolo-

gical Sciences, 267, 497–503.

BIOSKETCHES

Lawrence Heaney is Curator and Head of the Division of Mammals at the Field Museum. His research is focused on the evolution,

ecology and conservation of mammal diversity in island and island-like ecosystems, especially in Southeast Asia and the western USA.

Joseph Walsh is a Lecturer in the Undergraduate Program in Biological Sciences at Northwestern University and a Research

Associate in Zoology at the Field Museum. He has worked on the systematics and biogeography of Southeast Asian fruit bats and is

currently involved in restoration of tallgrass prairie and oak savannas in northern Illinois.

Townsend Peterson is Associate Professor in Ecology & Evolutionary Biology, and Curator of Ornithology in the Natural History

Museum, University of Kansas. His research focuses on ecological and historical factors shaping species’ geographic distributions.

Editor: Philip Stott

Geology, ecology, and genetic differentiation in Philippine mammals

Journal of Biogeography 32, 229–247, ª 2005 Blackwell Publishing Ltd 247