Dental and phylogeographic patterns of variation in gorillas

Journal of Human Evolution 59 (2010) 16e34

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Dental and phylogeographic patterns of variation in gorillas Varsha Pilbrow University of Melbourne Department of Anatomy and Cell Biology, Victoria 3010 Australia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 February 2009 Accepted 18 January 2010

Gorilla patterns of variation have great relevance for studies of human evolution. In this study, molar morphometrics were used to evaluate patterns of geographic variation in gorillas. Dental specimens of 323 adult individuals, drawn from the current distribution of gorillas in equatorial Africa were divided into 14 populations. Discriminant analyses and Mahalanobis distances were used to study population structure. Results reveal that: 1) the West and East African gorillas form distinct clusters, 2) the Cross River gorillas are well separated from the rest of the western populations, 3) gorillas from the Virunga mountains and the Bwindi Forest can be differentiated from the lowland gorillas of Utu and Mwenga-Fizi, 4) the Tshiaberimu gorillas are distinct from other eastern gorillas, and the Kahuzi-Biega gorillas are affiliated with them. These findings provide support for a species distinction between Gorilla gorilla and Gorilla beringei, with subspecies G. g. diehli, G. g. gorilla, G. b. graueri, G. b. beringei, and possibly, G. b. rex-pygmaeorum. Clear correspondence between dental and other patterns of taxonomic diversity demonstrates that dental data reveal underlying genetic patterns of differentiation. Dental distances increased predictably with altitude but not with geographic distances, indicating that altitudinal segregation explains gorilla patterns of population divergence better than isolation-bydistance. The phylogeographic pattern of gorilla dental metric variation supports the idea that Plio-Pleistocene climatic fluctuations and local mountain building activity in Africa affected gorilla phylogeography. I propose that West Africa comprised the historic center of gorilla distribution and experienced drift-gene flow equilibrium, whereas Nigeria and East Africa were at the periphery, where climatic instability and altitudinal variation promoted drift and genetic differentiation. This understanding of gorilla population structure has implications for gorilla conservation, and for understanding the distribution of sympatric chimpanzees and Plio-Pleistocene hominins. Ó 2010 Elsevier Ltd. All rights reserved.

Keywords: Gorilla Molar morphometrics Altitudinal variation Gene flow Drift Phylogeography Chimpanzees Hominins

Introduction Next to chimpanzees, gorillas are our closest evolutionary relatives. They are the largest living primates and exhibit a high degree of sexual dimorphism. They occur in sympatry with chimpanzees in equatorial Africa and, like chimpanzees, shared a long evolutionary history with early hominins in Africa. Being large-bodied apes it is likely that the present distribution and patterns of colonization, or phylogeography, of this closely related group was affected by the vicissitudes of Plio-Pleistocene climatic fluctuations in Africa. As such, gorillas are relevant for studying the ranges and patterns of variation among human ancestors, the phylogenetic relationships among fossil hominins and the environmental influences on early hominin distribution in Africa. Their sympatric relationship with chimpanzees is relevant for studying the dietary and niche-separation strategies of sympatric hominin groups. Despite this potential, many aspects of gorilla behavior, diet, morphology and genetic structure still remain E-mail address: [email protected] 0047-2484/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jhevol.2010.01.009

undocumented. In recent years, habitat destruction, disease and political turmoil have caused a decline in gorilla populations (Huijbregts et al., 2003; Leroy et al., 2004; Bermejo et al., 2006; McNeilage et al., 2006), resulting in a renewed urgency to gorilla studies. This paper focuses on patterns of dental diversity in gorillas with a view to documenting and interpreting the dental morphological structure of gorilla populations. The study follows from an earlier study on dental diversity in chimpanzee populations using molar morphometrics (Pilbrow, 2006). The aims of the study parallel the previous analysis, including to: 1) identify major divisions among gorilla populations in molar metrics, 2) map patterns of dental diversity onto the ecological patterns of gorilla distribution, 3) determine the concordance among dental and other morphological, molecular, ecological and behavioral patterns of diversity, 4) ascertain the dental affinities of isolated gorilla populations, and 5) comprehend the evolutionary and environmental influences on gorilla population structure. Molars are used to study population structure because of their relevance for paleontological systematics. They are preferentially

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

preserved in the fossil record and commonly used to delineate fossil species. It is useful to know how capable they are for reconstructing taxonomy (Pilbrow, 2006). A match between the taxonomic patterns revealed by molar morphometrics and non-dental types of data would indicate that dentally-identified paleospecies are likely to have exhibited differences in non-fossilizable morphological features, such as soft-tissue anatomy, behavior and molecular structure. While this is relevant for differentiating paleontological species, it is also relevant for extant species for conservation efforts because dental samples representing most wild populations are readily available in museums. If teeth preserve a taxonomic signal, they could verify the distinctiveness of small, endangered populations and help corroborate the findings of molecular systematics, which limited sample sizes often constrain. Furthermore, an underlying genetic structure to dental divergence patterns allows us to test predictions of population genetics, such as isolation-bydistance models and the role of Pleistocene climatic fluctuations in genetic and phylogeographic structuring in gorillas. What sets this study apart from previous gorilla dental studies is its substantively larger dataset, with the local population as the unit of analysis, providing a more comprehensive analysis of gorilla dental variation. Gorilla distribution and taxonomy Gorillas occur in two main centers in the west and east of equatorial Africa (Fig. 1). In the west their distribution begins at the Nigeria-Cameroon border in the Cross River region and continues through the western part of the Central African Republic to the Oubangi River and southward to the lower Congo River in Angola. In the east, they occupy areas from the eastern part of the Democratic Republic of Congo at the Lualaba River to the Albertine rift in southwestern Uganda and the Luama River in northwestern Rwanda (Sarmiento, 2003). A distance of about a 1000 km from 17
E to 28
E along the Congo River is devoid of gorillas. Even within the western and eastern regions, gorilla populations are distributed patchily at variable altitudes. Originally, many of the isolated populations received new species or subspecies designations (reviewed in Jenkins, 1990). Coolidge (1929) consolidated these into one species with two subspecies: G. g. gorilla from West Africa and G. g. beringei from East Africa. Later Groves (1967, 1970b) reinstated

17

G. g. graueri for the lowland east African gorillas, resulting in a three subspecies classification, widely substantiated by cranial, postcranial, mandibular and dental data (Vogel,1961; Casimir,1975; Inouye, 1992, 2003; Sarmiento, 1992, 1994; Uchida, 1998; Taylor, 2002, 2003; Leigh et al., 2003). This classification was common until recent revisions (cited below) revived previous species and subspecies. The most striking new proposal comes from mitochondrial DNA (mtDNA) sequence studies, arguing that there are greater mtDNA differences between East and West African gorillas than between the two recognized species of Pan, and therefore, that major gorilla groups should be recognized as distinct species, G. gorilla and G. beringei, with G. b. graueri as a subspecies of G. beringei (Ruvolo et al., 1994; Morell, 1994; Garner and Ryder, 1996: Saltonstall et al., 1998; JensenSeaman and Kidd, 2001; Jensen-Seaman et al., 2004). Groves (2001, 2003) supports the two species distinction on the strength of cranial and nasal differences. However, non-mtDNA studies do not largely adhere to the two species proposal, despite the fact that many molecular, craniodental and postcranial studies find a primary split between East and West African gorillas (Burrows and Ryder, 1997; Uchida, 1998; Altheide and Hammer, 1999, 2000; Jensen-Seamen et al., 2003; Stumpf et al., 2003; Taylor and Groves, 2003; Inouye, 2003; Clifford et al., 2004; Guillén et al, 2005). Specifically, Y-chromosome and nuclear DNA sequences do not corroborate the greater distinction of East and West African gorillas relative to the two species of Pan (Burrows and Ryder, 1997; Altheide and Hammer, 1999, 2000; Jensen-Seamen et al., 2003). As importantly, some artifactual integrations of nuclear DNA copies into mtDNA sequences may have compromised mtDNA studies supporting the split (Jensen-Seaman et al., 2004; Vigilant and Bradley, 2004a; Anthony et al., 2007). Other new taxonomic proposals concern isolated populations. The Cross River gorillas from southern Nigeria are separated from the other western gorillas by about 200 km and occur as impoverished populations in fragmented localities within rugged mountainous terrains of more than 2000 m above sea level and lowland forests of less than 200 m above sea level (Oates et al., 2003, 2004; Bergl and Vigilant, 2007). Sarmiento and Oates (2000) reinstated them as G. g. diehli (Matschie, 1904). The subspecies distinction is supported by several cranial and postcranial differences (Groves,1967, 1970b, 2001; Stumpf et al., 1998, 2003; Sarmiento and Oates, 2000), and some differences in mtDNA (Oates et al., 2003; but see Clifford et al., 2004).

Figure 1. Gorilla distribution in equatorial Africa shown in shaded areas. Altitude data taken from: Schaller, 1963; Hall et al., 1998; Omari et al., 1999; Sarmiento, 2003.

18

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Gorillas from the south of the Sanaga River to the mouth of the Congo River and east of the Sangha River (Fig. 1) have a wide distribution across southern Cameroon, southwest Central African Republic, Equatorial Guinea, Gabon and Congo and mostly inhabit lowland closed-canopy forests at altitudes ranging from sea level to about 800 m above sea level (Sarmiento, 2003). They are traditionally included in the subspecies G. g. gorilla, but higher population densities (Wolfheim, 1983; Doran and McNeilage, 1998; Vigilant and Bradley, 2004b), greater diversity in locomotor repertoire, behavioral strategies and dietary preferences (Williamson et al.,1990; Tutin et al.,1991; Kuroda et al.,1996; Remis,1997), and higher variability in mtDNA than in the eastern gorillas all indicate that there could be further substructure within this region (Garner and Ryder,1996; Clifford et al., 2004; Guillén et al., 2005). Clifford et al. (2004) found three genetic subgroups in this region, in Equatorial Guinea, Central African Republic and Gabon including adjacent Congo, although nuclear integrations of mtDNA appear to have influenced this to some extent (Jensen-Seaman et al., 2004). Groves (1967) also previously recognized three demes in the coastal area, inland plateau and the Sangha River region, but did not consider the distinctions great enough to warrant subspecies designations. In East Africa an isolated population believed to be present near Bondo on the Uele River in the northeastern part of the Democratic Republic of Congo was originally described as G. g. uellensis (noted by Schouteden in Schwarz, 1927). The population is known only from museum specimens and could not be differentiated in cranial measurements from G. g. gorilla (Groves, 1970b). Recent mtDNA studies of a single specimen aligned it with the western populations of Nigeria, Cameroon and northern Gabon (Hofreiter et al., 2003; Clifford et al., 2004). In the Virunga region of Rwanda in East Africa, a small secluded population from a high altitude montane forest at 3900 m (Schaller, 1963) has been recognized as G. g. beringei in the traditional three subspecies classification. The new classfication elevates it to the species-level, G. beringei, which is distinct from eastern and western lowland gorillas in morphology, diet and behavior (Coolidge, 1929; Schaller, 1963; Groves, 1970a, b). Another small population from the Bwindi Impenetrable Forest in Uganda, about 25 km from Virunga (Sarmiento et al., 1996), but at a lower altitude of about 1160e2600 m (Jensen-Seaman and Kidd, 2001), is often allocated to this group (Groves and Stott, 1979; Butynski and Kalina, 1993) and bears genetic similarity to it (Garner and Ryder, 1996; Jensen-Seaman and Kidd, 2001). Sarmiento et al. (1996) noted a few morphological and behavioral differences between the Bwindi and Virunga gorillas and suggested that they do not belong to the same subspecies. They did not provide an alternative name (no prior name is available). Gorillas from the Itombwe Massif of Lake Tanganyika (Fig. 1), and Utu and Mwenga-Fizi region of the Democratic Republic of Congo fall midway between the eastern mountain and western lowland gorillas in cranial morphology, and have been placed in G. g. graueri (Groves, 1967, 1970b). They occupy lowland forests at altitudes from about 1000 to 1500 m (Omari et al., 1999). The Kahuzi-Biega and Tshiaberimu mountain gorillas from eastern Congo were provisionally placed in G. g. graueri (Groves and Stott, 1979). They are intermediate in morphology between G. g. graueri and G. g. beringei, and occur at intermediate altitudes of up to 3300 m (Hall et al., 1998). In mtDNA D-loop haplotypes the populations from KahuziBiega and Tshiaberimu are more similar to each other than either is to the Virunga gorillas (Saltonstall et al., 1998; Jensen-Seaman and Kidd, 2001). Sarmiento and Butynski (1996) suggest reviving the nomen G. g. rex-pygmaeorum (Schwarz, 1927) for the Tshiaberimu gorillas. If revived, Jensen-Seaman and Kidd (2001) suggest allocating the Kahuzi-Biega gorillas to this subspecies. Several new morphological, eco-behavioral and genetic lines of evidence suggest that the three subspecies classification is no longer

viable for gorillas. A consensus summary of the studies offer predictions to be tested in this paper: 1) the main separation in gorilla populations is between the western and eastern gorillas, 2) within the western clade, the Cross River gorillas are distinguishable from the other western gorillas, 3) high levels of diversity characterize other western gorillas, with possible subdivisions in Equatorial Guinea, Central African Republic and Gabon, including Congo, 4) gorillas from the Uele River region are similar to the western lowland gorillas, 5) within the eastern region the lowland gorillas and mountain gorillas form distinct groups, 6) the Utu and Mwenga-Fizi gorillas resemble each other and are morphologically distinct from the western lowland and eastern mountain gorillas, 7) the Kahuzi and Tshiaberimu gorillas resemble each other and appear intermediate between the Utu, Mwenga Fizi and the Virunga gorillas, 8) the Virunga gorillas are distinct from the Kahuzi and Tshiaberimu groups and 9) the Bwindi (or Kayonza) gorillas are most similar to the Virunga gorillas. Pleistocene climatic fluctuation and gorilla phylogeography The current distribution of gorillas into isolated pockets may be a reflection of Pleistocene climatic fluctuations (Jensen-Seaman and Kidd, 2001; Clifford et al., 2004). Evidence from aeolian dust deposits (deMenocal, 1995; Maley, 1996), lake sediments (Talbot et al., 1984), ancient sand dunes (Nichol, 1999), deep-sea cores (Hamilton, 1992; Livingstone, 1993), and fossil pollen (Maley, 1996), indicate that after about 2.8 million years the climate in Africa became dependent on the glacial and interglacial cycles of the northern hemisphere. In response to advancing and retreating ice sheets in the upper latitudes, local climate in Africa went through cooler and arid, and warmer and wetter periods, respectively. The arid periods led to shrinkage of tropical and montane forests into refugia (Livingstone, 1975, 1993; Bonnefille et al., 1990; Maley, 1991, 1996; Hamilton, 1992; deMenocal and Rind, 1993; deMenocal, 1995; Partridge et al., 1995; Nichol, 1999). Taxa adapted to tropical climates, including gorillas, redistributed themselves into the climatically stable refugia. Extended periods of isolation resulted in a high level of endemism within refugia (Haffer, 1982; Vrba, 1992). When the climatic crisis ceased migration and dispersal recommenced linking previous refugia. Evidence for past refugia has been asserted in the endemic distribution of African mammals (Grubb, 1982, 1990) and the phylogeography of gorillas (Avise et al., 1998; Jensen-Seaman and Kidd, 2001; Eggert et al., 2002). Whether the patterns of dental diversity in gorillas fit with isolation-by-distance models (dental distances reflecting geographical distances) or are consistent with the evidence for Pleistocene refugia is addressed in this study. Materials and methods Samples The study sample includes 323 dental specimens from museums in the United States of America and Europe (see Pilbrow, 2003 for a listing of museums). Only adult individuals with third molars in place, relatively unworn teeth, and verifiable provenience were selected. The sample represents all known wild gorilla populations, and particular care was taken to include individuals from populations with contested affinities. The dental samples were divided into 14 populations (Table 1) based on locality allocations from previous studies (Groves, 1970b; Braga, 1995 and others reviewed above). Small sample sizes for populations from Bwindi forest, Mt. Kahuzi and the Uele River region reflect the numbers present in museums. Larger samples were available for West African gorillas. These were divided into seven populations, preserving the distinctions recognized by Groves (1970b) and Clifford et al. (2004). The East African gorillas were divided into six populations, separating the highland,

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

19

Table 1 Samples and population divisions. Number

Population

Localities included

1 2

Cross River Coastal Cameroon

3 4

7

Coastal Gabon Southern Gabon, Congo and Angola Sangha River Upper reaches of Sangha and Sanaga Rivers Inland Cameroon

Cross River localities in Nigeria Localities south of Sanaga River, including Bipindi, Campo, Lolodorf, Kribi Ogooue River region, Sangatanga, Cap Lopez, Libreville Sette Gamma, Fernan Vaz, Mayombe, Mambili, Opa, Bade, Zalangoye Ouesso, Nola, Youkadouma, Ziendi, Kadei, M’Bimou Batouri

8 9 10 11 12 13 14

Utu Mweng-Fizi Tshiaberimu Virunga Kayonza Kahuzi-Biega Uele River

5 6

N

Lomie, Abong Mbang, Metet, Ebolowa, Acam, Djaposten, Obala, Meyoss, Lobomouth, Akonolinga, Northeast Rio Muni Lowland localities in eastern Democratic Republic of Congo Wabembe, Baraka, Itombwe Lubero, Luofo, Alimbongo, Butembo Virunga volcano localities Kayonza, Bwindi, Kumbi Montane section including Lake Kivu, Kabare, Bukavu Uele River

Total

lowland and intermediate altitude populations. The Uele River gorillas were allocated to an additional population in the East. There is a bias toward male gorilla skulls in museum collections. How this affected the study is addressed below. Measurements Dental measurements were taken on digital images of the occlusal surface of molars. The traits measured include: mesiodistal length taken along the longitudinal developmental groove; buccolingual breadths measured at the tips of the mesial and distal cusps; lengths of molar crests measured from the tips of the cusps to the fissures dividing the cusps at the cemento-enamel junction; position of mesiobuccal and mesiolingual cusps measured as angles between the lines connecting the tips of the cusps to the longitudinal groove; position of hypoconid formed by the angle between the tips of hypoconulid, hypoconid and entoconid; and position of cristid obliqua formed by the angle connecting cristid obliqua to the tips of hypoconid and entoconid (Fig. 2). Inter-observer error studies, datascreening tests, and protocols for selecting teeth, verifying provenience, and photographing and measuring the occlusal surface are described in detail in previous publications (Pilbrow, 2003, 2006, 2007; Bailey et al., 2004). Data analysis All measurements were divided by the Geometric Mean (GM) to produce scale-free shape variables (Mosimann and James, 1979; Darroch and Mosimann, 1985; James and McCulloch, 1990; Falsetti et al., 1993). Statistical analyses were carried out using both raw and shape variables, thus permitting an assessment of the role of size and shape versus shape alone in discrimination. Molar positions are abbreviated to L for lower, U for upper, and 1, 2, 3 for mesial to distal positions. A step-wise discriminant analysis was used to assess the likelihood that individuals will segregate into predetermined populations. Discriminant functions analysis is commonly used for population systematics studies because the discriminant functions, which are linear combinations of variables in the analysis, are designed to maximize inter-group separation at the expense of intra-group variation, and thus classify individuals into groups (Groves, 1970b; Groves et al., 1992). The first two discriminant functions explained 70% to 80% of the variance in the populations and were used in scatter plots to show the pattern of clustering.

% Male, Female

33 20

73, 27 80, 20

37 38

46, 54 87, 13

18 33

61, 39 42, 58

51

61, 39

31 9 17 29 2 4 2

64, 36 67, 33 35, 65 55, 45 50, 50 100, 0 50, 50

323

62, 38

An independent samples t-test (p < 0.05) showed that gorilla male and female molar dimensions differ significantly, but not when they are indexed against the GM, indicating that size, not shape of molars separates male and female gorillas. Bearing in mind that sexual dimorphism is a necessary component of intra-group variation in gorillas, the sexes were combined in the analysis, despite the disparate representation of males in the samples. Sample sizes differed for molar positions because several specimens had teeth missing and only relatively unworn teeth were selected for study. Only 50% of the sample (163 specimens) presented all six molars. A single discriminant analysis using all six molars would result in smaller sample sizes per population, with a greater number of variables relative to samples, leading to singular covariance matrices. To ensure non-singular covariance matrices, and non-zero discriminant functions (Manly, 1994), separate analyses were carried out for each molar type, thus maximizing sample sizes while using a subset of the variables. A step-wise variable selection procedure ensured that only variables contributing significantly to the discriminant functions were selected. Bwindi, Kahuzi and Uele were not included as populations in the analysis, but their affiliations were tested post-hoc using the discriminant functions from the other 11 populations. All groups were assumed to have equal prior probabilities of classification so as not to bias classification accuracy through unequal sample sizes. Classification accuracy helped to assess population discrimination, but the likelihood of individuals being classified into presumed species and subspecies was also examined by aggregating individuals assigned to these units. Mahalanobis generalized squared distances (D2) were used to study the phenetic distances between groups. The results of each molar position were assessed independently, but pair-wise distances across the maxillary and mandibular molars were also averaged to get an overall phenetic distance between groups. Sample sizes did not differ greatly at these tooth positions justifying the average. F-statistics were used to verify the significance of pair-wise Mahalanobis distances. The pattern of phenetic distances, the accuracy of classification, and two-dimensional scatter plots were used to study population structure. Canonical coefficients of the discriminant functions were used to identify the variables separating groups and a one-way ANOVA provided the significance levels of the separating variables. Pearson’s correlations between the discriminant function scores and the geometric mean were used to study the role of size (allometry) in

20

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Figure 2. Gorilla molars showing dental measurements taken. Top row upper molars; bottom row lower molars. A: Linear dimensions. 1) Mesiodistal length, 2) Buccolingual width at mesial cusps, 3) Buccolingual width at distal cusps. B: Crest/ cristid lengths. Upper molar: 1) Preparacrista, 2) Postparacrista, 3) Premetacrista, 4) Postmetacrista, 5) Preprotocrista, 6) Postprotocrista, 7) Prehypocrista, 8) Posthypocrista. Lower molar: 1) Preprotocristid, 2) Postprotocristid, 3) Prehypoconid cristid, 4) Posthypoconid cristid, 5) Prehypoconulid cristid, 6) Posthypoconulid cristid, 7) Premetaconid cristid, 8) Postmetaconid cristid, 9) Preentoconid cristid, 10) Postentoconid cristid. C: Angles. Upper molar: 1) Position of mesiobuccal cusp, 2) Position of mesiolingual cusp. Lower molar: 1) Position of mesiobuccal cusp, 2) Position of mesiolingual cusp, 3) Position of cristid obliqua, 4) Position of hypoconulid.

discriminating groups. Finally, Mantel’s Spearman matrix correlations were used to determine the relationship between ecological variables, such as geographical distance and altitude, and Mahalanobis distances. Results The average Mahalanobis (D2) distances for the upper and lower molars between 11 population pairs are shown in Table 2, along with the statistical significance of the distances (Supplementary Online Material Table 1 shows the inter-population Mahalanobis distances at each molar position). Table 3 records classification accuracy for raw and shape variables for 11 populations, along with the most likely membership for Bwindi, Kahuzi and Uele, and the probability of individuals being correctly assigned to larger subgroups (presumed Gorilla species and subspecies). The variables driving the dispersion are shown in Table 4, along with correlations of the variables with the first two canonical discriminant functions, and the GM. A comparison of the results from the raw and shape variables reveals that adjusting molar size by indexing against GM does not greatly alter the discriminatory power of gorilla molar metrics. The phenetic distances differ in both analyses, but relative inter-population distances are similar, so that the closest affiliate of a population is often the same (shown in bold in Table 2 and Supplementary Online Material Table 1). The accuracy of classifying populations into larger subgroups is also largely similar (Table 3). The variables responsible for causing the dispersion are mostly similar in both analyses, as are their correlations with the discriminant functions (Table 4). The variances explained by the first two discriminant functions are also similar. The correlations of the discriminant scores on the first two functions with the GM, a proxy for overall size, are fairly high and statistically significant for both functions, with a few notable exceptions in the second function of lower molars. For the

UM1, for example, the correlations are the same for both variables (Table 4, Fig. 3). As seen by the regression line, the size difference between East African (closed symbols) and West African (open symbols) gorillas accounts for most of the correlations, with the size difference between males and females in each group contributing somewhat to the correlations. When shape variables are used, the groups occupy reversed positions, thus there are negative correlations between discriminant scores and size, with male eastern gorillas having the lowest discriminant scores relative to the GM. This indicates that isometric size accounts for some variance among gorillas. However, similarity in phenetic distances, classification accuracy, variables causing dispersion and correlations of the discriminant scores with GM suggest that the separation is not driven by isometric size alone, but by size and shape. Figure 4 shows the relative placement of gorilla populations on scatter plots of the first two discriminant functions averaged for maxillary and mandibular molars (scatter plots for individuals molars are shown in Supplementary Online Material Figure 1). These two functions are responsible for 70% to 80% of the variance. The third function accounts for 6% to 10% of variance, but was not included in the scatter plots, as it did not enhance population dispersion. Only plots for the raw variables are included, as the plots for the shape variables did not differ from these. Numerous general observations emerge from these analyses through careful inspection of population relations (Figs. 1,4, Tables 2e4, and Supplementary Online Material). In general, gorilla populations fall into two main clusters. Populations from Cross River to Inland Cameroon and the Uele River, shown as open symbols in the plots, belong in one cluster; while populations from Utu to Kahuzi, shown as closed symbols, fall in the second cluster. The clusters correspond with the geographical division of gorillas in West and East Africa. The East African gorillas fall at the positive end of the axis for the first two molars, and the negative end for the third molars. Inter-group distances within the

Table 2 Average maxillary and mandibular molar generalized square distances between gorilla populations using raw metrics (first row) and shape metrics (second row). Cross R. UM1-UM3 Cross R. Coastal Cameroon Coastal Gabon Southern Gabon Sangha R Upper Sangha and Sanaga

Utu Mwenga-Fizi Tshiaberimu Virunga LM1-LM3 Cross R. Coastal Cameroon Coastal Gabon Southern Gabon Sangha R Upper Sangha and Sanaga Inland Cameroon Utu Mwenga-Fizi Tshiaberimu Virunga

Coastal Gabon

Southern Gabon

* *

* *

* *

1.20 1.31 0.75 0.99 0.91 0.84 0.97 0.99 0.63 0.58 5.37 5.38 10.09 9.45 8.60 7.77 4.66 4.58 * *

4.26 5.16 3.98 3.86 2.91 2.93 2.56 2.96 3.83 4.60 3.24 3.41 7.71 7.69 7.06 6.88 9.92 8.96 7.76 6.59

1.39 1.66 1.60 2.03 1.45 2.01 0.92 1.14 1.28 1.64 9.36 8.74 7.28 6.57 14.43 12.39 6.99 5.86

Sangha R.

Upper Sangha and Sanaga

1.11 0.96 1.12 1.24 0.91 1.02 6.01 5.94 10.26 9.70 9.21 8.63 3.92 4.17

0.99 0.96 0.78 0.73 6.11 5.36 10.62 8.95 9.46 8.29 5.73 5.08

* *

Utu

MwengaFizi

Tshiaberimu

Virunga

N

* *

* * * * * * * * * * * * * *

* * * * * * * * * * * * * *

* * * * * * * * * * * * * *

* * * * * * *

25

* * * *

* 0.78 0.94 1.81 1.81 0.93 1.00 1.55 1.60 4.89 5.09 8.16 7.65 7.24 6.56 3.30 3.35

Inland Cameroon

0.72 0.74 5.59 5.37 8.29 7.61 7.07 6.37 4.44 4.30 * *

5.52 5.14 10.24 9.20 8.13 7.35 4.91 4.58

*

* * 1.52 1.49 1.50 1.41 1.05 1.46 1.17 1.34 7.50 7.67 5.68 5.89 11.43 10.48 4.15 3.85

0.66 1.00 1.82 2.28 1.60 1.97 6.91 6.71 5.30 5.04 11.15 9.52 5.00 4.48

1.36 1.77 1.21 1.48 6.59 6.97 5.13 5.10 10.95 10.07 5.47 5.07

0.53 0.68 7.23 7.15 5.80 5.27 11.61 10.73 5.23 4.71

6.81 6.58 4.90 4.61 10.65 9.40 4.87 4.21

3.74 3.42 2.90 2.44 2.49 2.65 * * * * * * * * * * * * * *

2.83 2.14 2.79 2.30 3.49 3.44

3.69 2.86 4.72 4.22 * * * *

* *

* * * * * * * * * * * *

4.34 3.44 * * * * * * * * * * * * * *

19 33 33 15 29 46 26 8 13 25

* * * * * * * * * * * * * * * *

10 19 30 30

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Inland Cameroon

1.89 2.50 1.93 2.63 2.32 2.85 1.60 1.75 1.51 1.92 2.02 2.54 6.52 6.72 9.90 9.82 8.84 8.65 5.63 6.30

Coastal Cameroon

15 27 41 24 8

4.40 3.79 2.92 2.54

* * 4.60 3.81

13 27

Shortest distances between populations are marked in bold. Asterisk shows population pairs with statistically significant (p < 0.05) D2 values.

21

22

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Table 3 Percent classification accuracy and predicted memberships.

Cross R. Coastal Cameroon Coastal Gabon Southern Gabon Sangha R Upper Sangha and Sanaga Inland Cameroon Utu Mwenga-Fizi Tshiaberimu Virunga 11 populations Nigerian Western lowland Eastern lowland Eastern intermediate Eastern highland Western Eastern Predicted membership Bwindi Kahuzi Uele

UM1

UM2

UM3

LM1

LM2

LM3

50 58 22 11 38 41 19 35 14 14 15 19 32 32 55 59 75 75 55 36 50 46 36 37 50 58 79 80 72 72 44 35 75 23 92 94 95 94

61 61 10 25 32 30 32 32 18 12 44 38 26 30 59 62 75 75 75 69 56 52 41 41 61 61 77 77 69 70 54 51 78 76 89 88 93 94

52 52 21 21 35 38 11 17 13 20 21 10 19 17 50 39 29 43 33 42 28 36 28 28 52 52 72 74 61 64 50 54 14 18 81 82 71 72

78 67 44 33 39 43 41 50 23 46 33 38 17 26 59 45 50 50 80 80 65 58 44 45 78 67 65 67 68 63 65 65 83 54 74 75 82 79

60 70 26 47 39 39 27 36 38 44 23 37 26 33 52 72 38 38 80 80 54 57 38 47 60 70 79 87 67 63 40 40 27 29 89 91 73 81

45 64 42 47 43 40 15 21 13 31 0 19 12 16 54 54 14 29 57 64 38 35 28 34 45 64 62 64 46 51 29 45 19 67 90 88 86 85

Eastern gorillas (Virunga) Eastern gorillas (Virunga) Eastern gorillas (Tshiaberimu or Utu) Eastern gorillas (Tshiaberimu) Western gorillas (Sangha R.) Western gorillas (Sangha R.)

Percentage of cases correctly classified into 11 gorilla populations, along with the best predicted memberships for unassigned populations (Bwindi, Kahuzi and Uele), and aggregate classification accuracy for 2 main groups and 5 subgroups (see text). First row shows results from raw variables, second row shows shape variables.

clusters are lower than distances between clusters, with the distances between clusters being statistically significant (p < 0.05). The likelihood of individuals being accurately classified into each cluster ranges from 71% to 95%, depending on molar position and whether raw or shape variables are used. Turning to western populations, it is clear that gorillas from the Uele River region unequivocally fall within the western gorilla clade. This result is consistent at all molar positions (seen in scatter plots) and when the metrics are adjusted for size. The exact affiliation of the two specimens within the western cluster cannot be determined accurately, but the strongest ties are with the Sangha River population. Within the West African cluster, the Cross River population is more distinct from other western populations than those populations are from each other. The classification accuracy for this population is higher and the distances separating it from other populations are statistically significant. Of the western populations, the Cross River gorillas are more closely affiliated with the inland populations of Cameroon, Central African Republic and Congo, than with the coastal populations. Overall, western gorillas

lack clear population substructure. Pair-wise distances separating populations from Coastal Cameroon to Inland Cameroon are low and on the whole non-significant. However, the scatter of specimens for the upper molars shows slight separation of the coastal Cameroon, Gabon and southern Gabon populations (open green symbols in charts) from the inland populations of Cameroon and upper Sangha and Sanaga (open red symbols). The Sangha River population (open black symbols) lies between the two groups. For the eastern populations, results indicate relatively greater morphometric distances among East African populations than among populations from West Africa. Moreover, the accuracy of classification is higher among eastern populations. In particular, statistically significant Mahalanobis distances separate the Virunga gorillas from all East and West African populations. In addition, Tshiaberimu gorillas are removed from the other East African populations. This is apparent in scatter plots, particularly for the first two molar positions. In phenetic distances they are more closely affiliated with the Utu gorillas than with the Virunga population. The Kahuzi-Biega gorillas, for which only males were studied, most often fall with the Tshiaberimu gorillas in post-hoc analyses. This is seen in scatter plots (green closed symbols), particularly for the UM1, UM2 and LM3. Gorillas from the Bwindi/ Kayonza region share greatest similarity with the Virunga population in post-hoc analyses, shown in the scatter plots as closed orange symbols. Populations from Utu and Mwenga-Fizi have high discrimination rates and are distinct from other eastern populations. They are affiliated with each other (red closed symbols in the plots) but are also close to the Tshiaberimu gorillas in phenetic distances. The likelihood of individuals’ classification into their predetermined populations is low (between 28% and 47%, depending on molar type), indicating high overlap among populations (Table 3). By aggregating populations that fall into the two main clusters in East and West Africa we get up to 95% classification accuracy (Table 3). Additional population clusters are identified in the Cross River region of Nigeria; the western lowland regions of Cameroon, Gabon, Equatorial Guinea, Republic of Congo, Central African Republic and the Uele River in northeastern Democratic Republic of Congo; eastern lowland regions of Utu and Mwenga-Fizi in eastern Democratic Republic of Congo; and eastern highland areas of Virunga and Bwindi in Rwanda and Uganda. The population from Tshiaberimu has high classification accuracy and falls away from the others in scatter plots (Table 3, Fig. 3). The Kahuzi-Biega population is affiliated with it, although this relationship, based on 4 male specimens, needs to be substantiated with more data. Together these populations make an additional cluster of intermediate altitude gorillas in eastern Democratic Republic of Congo. Classification rates for the western and eastern lowland gorillas are consistently high, while those for the Nigerian and eastern intermediate altitude populations are lower. The UM3 and LM2 are poor classifiers of the eastern highland gorillas, whereas the unadjusted UM1, UM2 and LM1 have higher classificatory power. The dental dimensions characterizing the eastern and western gorillas and the subgroups within these regions are shown in Supplementary Online Material Table 2. Several dimensions differ significantly between the groups (one-way ANOVA, p < 0.05), even when adjusted for overall dental size. These are also the dimensions with high correlations on the first two discriminant functions (Table 4). Eastern gorillas differ from western gorillas in having longer molars that are splayed out distally and mesiolingual cusps placed distal to the mesiobuccal cusps (Fig. 5). The eastern gorillas also have longer premetaconid cristids and postentoconid cristids, but shorter postmetaconid cristids on the lower molars compared to the western gorillas. The proportion of differences for the subgroups within the two main geographical groups is smaller, yet a few traits can be found to

Table 4 Correlations between dental variables and first and second discriminant functions, variance explained and correlations with GM. UM1

UM2 F1

Angles Mesiobuccal cusp Mesiolingual cusp Hypoconid Cristid obliqua Percent of variance explained Pearson’s correlation with GM

F2

F1

R 0.43 0.23

S 0.29

R 0.52 0.32

S 0.09

0.62

0.65

0.54

0.38

0.26 0.39 0.22

0.43

0.12 0.30 0.54 0.61 0.33 0.25 0.31 0.23 0.41

R 0.20 0.44

S 0.05 0.33

0.30

0.68

0.37

0.50

0.21 0.04 0.34 0.21

0.19 0.57 0.31 0.60 0.39 0.23 0.10

0.45

0.45

F2

S 0.45 0.02

R 0.34 0.54

F1

F2

LM3 F1

F2

F1

S R 0.20 0.46 0.38 0.34

S 0.14 0.20

R 0.08 0.07

S 0.07 0.06

R 0.49 0.37

S 0.43

R 0.09 0.04

S 0.26

0.55

0.51

0.12

0.14

0.37

0.26

0.10

0.07

13.7 0.45

0.13 0.07 0.17 0.24

0.11

0.11

0.49

R 0.60

F2 S 0.55

R 0.02

S 0.60

0.35 0.49 0.32 0.77

0.12 0.26 0.21

0.34 0.10 0.42 0.31

0.36 0.39 0.10 0.39 0.59 0.04 0.01 0.16 0.38 0.70 0.71 0.51 0.49 0.04 0.07 0.01 0.15 0.39 0.48

0.07 0.59

0.16 0.62

0.17 0.15

0.44 0.06

0.48 0.50

0.29 0.40 0.22

0.01

0.16

60.5

R 0.67 0.41

0.29

0.27

0.44

62.4

F1

R S 0.65 0.57 0.34 0.09

LM2

0.17 0.16

0.11

F2

LM1

13.3 0.31

62.1 0.57

0.28 0.42

59.6 0.56

0.32

11.5 0.41

0.55 0.27

12.1 0.50

0.53

0.65

61.9

58.4

0.57

0.62

0.46

19.8 0.48

0.11

0.03

0.11 58.4

0.18 0.02 48.5

0.46 19.1

0.04 0.37 21.0

0.41

0.21

0.18

0.52

24.3 0.43

0.05*

0.28 0.38 0.22 0.19 0.30 0 0.71 0.67 0.02 0.21 0.09 0.29 0.19 0.10 0.10 0.01 0.12 0.23 0.07 0.02 0.01 0.05

0.28 0.33 0.01 0.21 0.02 0.78 0.32 0.17 0.23 0.19 0.21 0.06 0.08

0.21

0.32

0.07

0.20

0.05 61.7

0.13 61.5

0.52 13.2

0.41 11.8

0.15 73.4

0.43

0.40

0.03*

0.28

0.48

0.13

72.1 0.34

0.59 0.36

0.07

0.61 10.4

12.4

0.15

0.01*

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Lengths Mesiodistal Buccolingual at mesial cusps Buccolingual at distal cusps Preparacrista Postparacrista Premetacrista(id) Postmetacrista(id) Preentoconidcristid Postentoconidcristid Preprotocrista(id) Postprotocrista(id) Prehypocrista(id) Posthypocrista(id) Prehypoconulidcristid Posthypoconulidcristid

UM3

Only variables included in the step-wise discriminant analysis are shown. * Correlation not significant (p > 0.05). R: Raw variables, S: Shape variables.

23

24

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Figure 3. Plot of first discriminant function against the Geometric Mean for UM1 raw and shape variables. A: UM1 Raw Variables, B: UM1 Shape Variables.

differentiate each cluster from the other. The Nigerian population is the smallest of the subgroups, and differs from other western gorillas in having smaller linear dimensions, but relatively longer postprotocrista on the upper molars (Fig. 6). The eastern intermediate altitude population (Tshiaberimu and Mt. Kahuzi) is the largest dentally and has significantly longer mesiodistal molar dimensions than the other eastern populations. The eastern mountain gorillas from Virunga and Bwindi have the smallest linear dimensions of the eastern subgroups and differ from the lowland (Utu and Mwenga Fizi) and intermediate altitude (Tshiaberimu and Mt. Kahuzi) populations, particularly in the buccal placement of the cristid obliqua (Fig. 7).

The pair-wise Mahalanobis distances between populations are strongly correlated with pair-wise geographical distances measured linearly on a map of gorilla distribution (Mantel’s Spearman rank order correlation ¼ 0.73; r2 ¼ 0.53; p ¼ 0.01). Although this suggests that an isolation-by-distance model explains gorilla population structure, a plot of the inter-population D2 values against interpopulation geographical distances (Fig. 8) reveals that the wide geographic and dental distances between the East and West African gorillas account for most of the strong correlations. Within each of the two clusters, correlations between the two pair-wise distances are non-significant and not strong (r2 ¼ 0.13; p ¼ 0.09 for the West African populations; r2 ¼ 0.14; p ¼ 0.35 for the eastern populations).

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

25

Figure 4. Scatter plot of first two discriminant functions in the analysis of raw variables. A: Upper molar average, B: Lower molar average.

When the West African populations are considered exclusively, however, without including the Cross River population, correlations are significant (p ¼ 0.02) and stronger (r2 ¼ 0.27). Gorilla populations inhabit areas at different altitudes in Central Africa, possibly contributing to higher inter-population D2 values among the East African populations than among the West African populations (Table 2 and Supplementary Online Material Table 1). To test for the effect of altitude in the patterning of gorilla population structure, the median altitude for the 11 populations was taken from the literature (Schaller, 1963; Garner and Ryder, 1996; Hall et al., 1998; Omari et al., 1999; Sarmiento, 2003) and pairwise midpoint altitudes were compared with pairwise D2 values. Mantel’s Spearman rank order correlations are strong (r ¼ 0.59; r2 ¼ 0.35) and significant (p ¼ 0.02). A two-dimensional plot of the midpoint altitude against D2 values in the eastern and western

gorillas (Fig. 9) shows that D2 values increase with altitude. The lowest D2 values occur among populations of low altitude western gorillas. Distances separating the higher altitude Nigerian population from the rest of the western populations are intermediate. The phenetic distances among higher altitudes East African populations are mostly high. Discussion This study supports the conclusions of previous molecular and morphological studies (Ruvolo et al., 1994; Morell, 1994; Garner and Ryder, 1996; Sarmiento and Butynski, 1996; Burrows and Ryder, 1997; Saltonstall et al., 1998; Uchida, 1998; Jensen-Seaman and Kidd, 2001; Groves, 2001; Stumpf et al., 2003; Taylor and Groves, 2003; Inouye, 2003; Clifford et al., 2004; Jensen-Seaman

26

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Figure 5. Dental morphological differences between western and eastern gorillas. All images at same scale, with isolated second molars magnified six times further to show morphological details. The small scale (in mm) is for the isolated molars.

et al., 2004; Guillén et al., 2005) in suggesting that the main split in gorillas lies between the western and eastern gorillas. Gorilla populations from west of about 17
E in the Central African Republic are distributed over a large geographical area, but they are similar to each other in dental morphology and distinct from the East African populations. Gorilla populations east of about 28
E in the Democratic Republic of Congo are much more patchily distributed, found at variable altitudes and do not share such close dental affinity, yet they are all clearly separable from the West African populations. In addition, dental morphometrics support the division of the Cross River gorillas at the Nigeria-Cameroon border from the lowland gorillas in Cameroon, Gabon, Equatorial Guinea, Republic of Congo and Central African Republic (Groves, 1967, 1970b; Stumpf et al., 1998, 2003; Sarmiento and Oates, 2000; Groves, 2001; Oates et al., 2003). Gorillas, supposedly from the

Uele River region about 400 miles east of the western gorilla distribution, cluster with western gorillas, confirming previous studies (Groves, 1970b; Hofreiter et al., 2003; Clifford et al., 2004). In East Africa, dental data strengthen previous results, showing that the Virunga gorillas form a distinct group (Coolidge, 1929; Schaller, 1963; Groves, 1970a, b) and that the Bwindi gorillas are aligned with them (Sarmiento et al., 1996; Garner and Ryder, 1996; JensenSeaman and Kidd, 2001), the Tshiaberimu gorillas are morphologically transitional between the Virunga and Utu gorillas (Groves and Stott, 1979; Sarmiento and Butynski, 1996), while the Mt. Biega gorillas could be associated with them (Saltonstall et al., 1998; Jensen-Seaman and Kidd, 2001), and the lowland gorillas from Utu and Mwenga-Fizi are distinct from the higher altitude groups (Groves, 1967, 1970b; Saltonstall et al., 1998). Thus, both major and minor aspects of gorilla population structure can be deduced from

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

27

Figure 6. Dental morphological differences between Nigerian and western lowland gorillas. All images at same scale, with isolated second molars magnified six times further to show morphological details. The small scale (in mm) is for the isolated molars.

dental morphological features. The close correspondence between the dental and other morphological and molecular patterns of population differentiation indicates that dental data demonstrate a genetic pattern of population divergence and are worthwhile for reconstructing events of evolutionary significance in gorillas. Gorilla taxonomy and implications for paleoanthropology The eastern and western gorillas are lately being recognized as distinct species, G. gorilla and G. beringei (Ruvolo et al., 1994; Morell, 1994; Garner and Ryder, 1996; Saltonstall et al., 1998; JensenSeaman and Kidd, 2001; Groves, 2001, 2003; Jensen-Seaman et al., 2004). The Nigerian gorillas have been revived as G. g. diehli

(Sarmiento and Oates, 2000), distinct from G. g. gorilla in West Africa. In East Africa, G. b. rex-pygmaeorum has been proposed for the Tshiaberimu, Mt. Biega gorillas (Sarmiento and Butynski, 1996; Jensen-Seaman and Kidd, 2001), distinguishing them from G. b. graueri and G. b. beringei. The present study supports these distinctions. Whether the revised species and subspecies designations will find common usage will no doubt depend on one’s systematic philosophy and conservation priorities, but will finally rest on disparate datasets displaying these distinctions. Ultimately, it is concordance among datasets that demonstrates underlying historic and genetic patterns of divergence. If the East African and West African gorillas find acceptance as distinct species, their level of differentiation can be used in distinguishing species of fossil hominids by offering a counter

28

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Figure 7. Dental morphological differences between eastern highland, eastern lowland and eastern intermediate altitude gorillas. All images at same scale, with isolated second molars magnified six times further to show morphological details. The small scale (in mm) is for the isolated molars.

perspective to the chimpanzee patterns of variation. At present the two species of chimpanzees provide the sole comparison for fossil hominid species, although differences in patterns of variation between chimpanzees and gorillas (Pilbrow, 2007) are likely to offer different interpretations of fossil hominid taxonomy.

Difference between chimpanzees and gorillas in patterns of diversification Chimpanzees and gorillas occur in sympatry throughout much of Equatorial Africa and share a close evolutionary history. It is expected that patterns of speciation and evolutionary divergence

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Figure 8. Correlation between geographical and Mahalanobis distances. Spearman rank order correlation ¼ 0.73, r2 ¼ 0.53, p < 0.05.

will differ between them as distinctions in niche exploitation, including differences in diet, locomotion, habitat preferences, social organization and dispersal patterns are necessary for their sympatric coexistence. Dental morphometric distances between chimpanzee populations are highly correlated with geographic distances, suggestive of isolation-by-distance models of population dispersal, with rivers forming effective barriers to dispersal (Pilbrow, 2006). In gorillas, on the other hand, isolation-by-distance fails to provide a complete explanation for population dispersal patterns. The correlation between geographical and morphometric distance between the eastern and western groups is specious and easily accounted for by the large phenetic and linear distances between the two clusters. In the West, the Cross River gorillas are separated from other populations by high Mahalanobis distances, but these do not increase linearly with geographical distances. In East Africa, morphometric distances among populations are high although geographical distances are comparable to those in West Africa. The West African lowland gorillas are the only subgroup of gorillas displaying significant correlations between morphometric and linear distances.

Phylogeography and altitudinal variation Altitudinal variation has a more significant correlation with dental metric distances than latitude and longitude. This suggests

Figure 9. Correlation between altitude and Mahalanobis distances. Spearman rank order correlation ¼ 0.59, r2 ¼ 0.35, p < 0.05.

29

a niche differentiation strategy with phylogeographic and evolutionary consequences for gorillas. Low phenetic distances among lowland western gorillas indicate higher levels of gene flow in this region, whereas greater distances in the intermediate to high altitude Cross River area and East Africa probably indicate genetic discontinuity. This pattern of altitudinal and genetic structuring could be the consequence of habitat fragmentation, isolation and subsequent reconnection during Pleistocene climatic fluctuations in Africa (Jensen-Seaman and Kidd, 2001; Clifford et al., 2003, 2004). During periods of aridity and lowered temperatures, gorillas and other animals with a close relationship with their habitat redistributed themselves into stable refugia. Over time, a level of endemism developed in these isolated pockets. When the climate improved during warmer and wetter periods, the isolates could have made secondary contact, leaving signatures of the historical events in their genetic structure (Hewitt, 1996; JensenSeaman and Kidd, 2001). Many such areas of species richness and endemism have been recognized in Africa (Grubb, 1982, 1990), and provide circumstantial evidence for past refugia. These can be used to test hypotheses of gorilla phylogeography. A possible refugium occurs between the Niger River or Dahomey Gap in western Nigeria and the Sanaga River in northern Cameroon. The region is a “hotspot” of biodiversity with a high level of endemism in mammals, invertebrates, birds, and plant species (Oates et al., 2004). The Cross River gorillas, G. g. diehli (Sarmiento and Oates, 2000), a newly reinstated chimpanzee subspecies, P. t. ellioti (Oates et al., 2009; previously P. t. vellerosus, Gonder et al., 1997), and 22 other endemic primate taxa (Oates et al., 2004) fall within this biozone. The gorilla distribution is fragmented over lowland and montane regions. Autosomal microsatellite loci show distinct geographical substructuring, separating east and west montane inhabited gorillas from the central lowland gorillas (Bergl and Vigilant, 2007). The fragmentation appears to be the recent influence of human pressure and habitat destruction (Oates et al., 2003, 2004), but nonetheless points to an altitudinal pattern of segregation. The gorillas, chimpanzees and other endemic taxa, appear to have diverged from their congeners during an episode of Pleistocene cooling. The mountainous landscape at the Nigeria-Cameroon border could have caused further substructuring in gorillas. The Sanaga River, which is considered a major biogeographic barrier for chimpanzee distribution (Gonder et al., 1997), evidently does not hinder gorilla dispersal as gorillas from the north of the Sanaga River share similarities in cranial morphology and mtDNA haplotypes with gorillas south of the river in southeast Cameroon and northeast Gabon (Clifford et al., 2004; Oates et al., 2004; Groves, 2005). The Cross River specimens in this study come from intermediate altitude localities. They are easily distinguished from other gorillas, but are most closely affiliated with south Sanaga River populations in inland Cameroon, Central African Republic and Congo. Thus, while the distinction of the Cross River gorillas is supported, it does not indicate complete reciprocal monophyly between the Cross River and other western gorillas, which accords well with a subspecies designation. Several other major forest refugia have been identified in Cameroon, Gabon, Equatorial Guinea, Congo and the Central African Republic (Maley, 1996), all in the area of distribution for the rest of the western gorillas, G. g. gorilla. Genetic variability is considerably higher in western than in eastern gorillas (Gagneux et al., 1999; Clifford et al., 2003, 2004), and a study of genetic structure revealed partitioning among the Sangha/Dja, Equatorial Guinea and southern Gabon/Congo gorillas (Clifford et al., 2003, 2004). Groves’ (1967) craniometric analysis also identified three demes of western gorillas in the Sangha River valley, including Cameroon plateau, and coastal areas of Cameroon, Gabon and

30

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

Congo. Groves’ subdivisions differ quite markedly from Clifford’s, but they concur in recognizing that the Sangha River gorillas form a distinct deme. In this study, six western gorilla populations formed a close cluster to the exclusion of the Cross River and eastern gorillas. No major subdivisions were apparent in the pattern of Mahalanobis distances. But scatter plots showed slight differentiation of the coastal, inland and Sangha River gorillas. Groves and Clifford did not argue for taxonomic designations for the subdivisions, but recognize that more work needs to be done to understand the genetic configuration of western gorillas. Secondary contact between Plio-Pleistocene refugia could explain the pattern of broad substructuring and genetic admixture in western lowland gorillas. The exact pattern of refugia formation in the region is complex (Livingstone, 1982). No major mountain building activity took place in this region (Guiraud et al., 2005) and no mountain refugia are known. Grubb (1982) postulated a West Central center of species endemism, White’s (2001a, b) GuineoCongolian center of endemism overlaps with that and there is some indication that a fluvial refuge existed in the Sangha River region (Colyn, 1991). It is conceivable that without the marked topographic detail in this region, Pleistocene refugia, formed during cool, arid periods would have reconnected during warmer periods and formed zones of secondary contact, contributing to the complex pattern of present-day genetic diversity in these gorillas. Analyses of specimens from Bondo in the Uele River region of the Democratic Republic of Congo suggests that they have been transported there from the western gorilla range. In molar morphometrics they clustered with western gorilla specimens, providing support for G. g. gorilla. Other morphological (Coolidge, 1929; Groves, 1970b) and genetic analyses (Hofreiter et al., 2003; Clifford et al., 2004) showed the same relationship. The specimens studied here were blackened and burnt, probably as a result of cooking. It is possible that they got transported nearly 400 km out of their range by the bush-meat trade, which must have been prevalent even in the 1890s, when the specimens arrived at the Royal Museum of Central Africa in Tervuren. In East Africa, Grubb (1982) recognizes an East Central center (west of Lakes Edward and Kivu) and an Eastern center (East of the Rift valley) of species endemism. Several minor refuges are also recognized (Grubb, 1982). More than 80 percent of the fauna in these centers is endemic. The mammals in the region are divided into lowland and montane adapted taxa (Grubb, 1982). It is possible that the faunal distribution is due to fragmentation and formation of refugia from Pleistocene climatic fluctuations, but this would be superimposed on the topographic relief caused by the Miocene and later tectonic activity in the African Rift (Livingstone, 1982). Paleoenvironmental evidence suggests that as volcanic mountains rose and temperatures dropped due to glaciation, montane forest replaced riverine forest (Coetzee, 1964; van Zinderen Bakker and Coetzee, 1972; Bonnefille et al., 1990; Colyn et al., 1991; Maley 1996). These factors would have caused dispersal of lowland adapted taxa (Colyn et al., 1991). It is not clear how taxa such as gorillas adapted to such severe changes in climate and habitat, but the presence of minor refuges in the East Central region suggests to Colyn et al. (1991) that taxa did not conglomerate in major refugia but dispersed into several nuclei around the main river systems. Goldberg (1998) surmised that chimpanzees lived both in and out of refugia during periods when tropical forests were confined to refugia. Kingdon (1989) suggests that the highlands provided an important retreat for the gorillas because gorillas were able to exploit the vast quantities of low-level herbage available within the changed highland habitat. Eastern gorillas differ from the western gorillas in this study in having longer and wider molars with longer occlusal crests. These traits are associated with a folivorous diet (Kay, 1975, 1977; Hylander,

1975a, b; Kay and Hylander, 1978), and fits with the proportional reduction in fruit availability in the eastern distribution. The lowland eastern gorilla diet consists of fruit when available, but includes a wide range of leaves, plants, stems and bark (Yamagiwa et al., 1994). In the montane regions where fruit availability is further reduced, the gorilla diet consists of tough and bulky herbs, bamboo shoots, bark and pith (Schaller, 1963; Watts, 1996). In the western regions fruit is more abundant and when available it constitutes most of the gorilla diet (Remis, 1997; Rogers et al., 2004). When scarce, herbaceous vegetation, bark, shoots and young leaves are eaten. The diversity in the gorilla diet and flexibility in the consumption of fibrous foods when fruit is scarce probably allowed them to adapt to fragmented, impoverished and high altitude habitats in East Africa. There is a correlation between dietary diversity, including frugivory and population density, including mobility patterns and day ranges in gorillas (Rogers et al., 2004). With a higher proportion of herbaceous foods in East Africa, population densities are lower, and gorilla groups are less mobile (Caldecott and Miles, 2005). There is also less genetic diversity, with evidence for population bottlenecks in the area (Jensen-Seaman and Kidd, 2001). Dental phenetic distances separating populations of gorillas in East Africa are high in this study, and particularly striking in relation to the small geographic area the gorillas are confined to. The Utu/Walikale/ Kasese specimens and the Mwenga-Fizi/Wabembe/Baraka specimens come from lowland habitats (although at higher altitude than the western lowland localities), yet they are quite distinct from one another. Populations from Tshiaberimu and the Virunga mountains are also distinctive. The Kayonza/Bwindi specimens clustered with the Virunga gorillas, whereas the Kahuzi-Biega specimens were closest to the Tshiaberimu gorillas. There is some amount of overlap between populations, but this study supports the presence of a lowland gorilla group, increasingly referred to as G. b. graueri, a mountain gorilla group, G. b. beringei, and a Tshiaberimu/Kahuzi-Biega group, which is proposed as G. b. rex-pygmaeorum (Sarmiento and Butynski,1996). The latter group in particular, cannot be overemphasized as it is based on smaller samples. Higher dental distances imply a history of isolation and interrupted gene flow in East Africa and are consistent with the biogeographic history of fragmentation and the tectonic activity associated with volcanism in the region. Influence of genetic drift, gene flow and the abundant center distribution model Overall, an isolation-by-distance model cannot be invoked to explain patterns of population structure within the main centers of gorilla distribution in this study. A model of genetic drift primarily acting on peripheral, altitudinally variable isolates in Nigeria and East Africa, with drift-gene flow equilibrium working in the West African region may be a better explanation. This fits with Darwin’s (1859) “abundant center distribution” pattern, wherein the density of individuals in a population and density of populations in an area decreases from the center of a species’ range towards the periphery (Hengeveld and Haeck, 1982; Brown, 1984). The model suggests that environmental conditions are optimal at the species’ center, and predicts that in the absence of extrinsic barriers there will be continuous gene flow between the center and periphery, which will limit adaptation or speciation even if there is intense directional selection at the periphery (García -Ramos and Kirkpatrick, 1997; Kirkpatrick and Barton, 1997). If ecological or topographic barriers isolate peripheral populations, however, selection and drift will work to differentiate the peripheral populations rapidly (see Herrera and Bazaga, 2008, for a recent application of this model). Correlations between geographical and dental distances are fairly high for the western group of gorillas (not including the Cross

V. Pilbrow / Journal of Human Evolution 59 (2010) 16e34

River gorillas), indicating that isolation-by-distance and gene flow may play a significant role in maintaining dental morphological similarity in this region. Genetic diversity and population densities are also high (Wolfheim, 1983; Doran and McNeilage, 1998; Clifford et al., 2003, 2004; Vigilant and Bradley, 2004b; Thalmann et al., 2007), suggesting that the West African region may have been at the historical center of gorilla distribution. Fruit trees are more abundant, providing gorillas with a greater opportunity to acquire their preferred food, although their diet also includes a diverse range of fibrous plant fallback foods (Remis, 1997; Doran et al., 2002; Cippolletta, 2004; Rogers et al., 2004), additionally suggesting that the western region could have provided the optimal foraging conditions for gorilla survival and niche differentiation from chimpanzees (Stanford, 2006). Cranial, dental and genetic substructuring is evident in the region (Groves, 1967; Clifford et al., 2003, 2004), but as outlined above, it is probably a signature of past climate related fragmentation events and provides some evidence for drift. Without extrinsic barriers separating previously divided populations, gene flow would have resumed, resulting in the present day drift-gene flow equilibrium. In both Nigeria and East Africa, high dental distances relative to geographic distances, low genetic diversity (at least for the Eastern gorillas – Gagneux et al., 1999; Jensen-Seaman and Kidd, 2001, Jensen-Seaman et al., 2003), and low population densities (Oates et al., 2003; Sarmiento, 2003) support the premise that the Nigerian and East African gorillas fall at the periphery of gorilla distribution. A greater reliance on lower quality herbaceous foods with a reduced fruit component, despite a preference for fruit (Oates et al., 2003; Ganas et al., 2004; Nkurunungi et al., 2004) once again points to their marginal status. A historically diverse dietary regime, along with folivorous fallback options would have allowed gorillas to adapt to impoverished ecological conditions at higher altitudes. The abundant center distribution model predicts that barriers imposed by Pleistocene refugia and especially the altitudinal pattern of segregation resulting from mountain building in East Africa and Nigeria promoted isolation and genetic drift in these peripheral areas even though gorillas are large, terrestrial, vagile animals and are likely to have resumed genetic contact when the ecological barriers were less stringent. Thalmann et al. (2007) state that there was male-mediated gene flow predominantly from the eastern to the western region until about 80e200 ka. This model of gorilla population structure has important implications for conservation. It implies that conservation efforts should be directed towards peripheral populations, where low population density, pauperized genetic diversity, and ecological isolation put gorillas at greater risk of extinction. It also suggests that corridors of genetic contact should be kept open to allow continued genetic exchange between isolated populations. Finally, it demonstrates the immense evolutionary resilience and adaptability of peripheral gorilla isolates, which is an encouraging prospect for conservation efforts. Similar environmental and ecological influences can be envisaged for chimpanzees and early hominins in Plio-Pleistocene Africa. Chimpanzee population structure does not conform to a climate refugia pattern. Goldberg (1998) found little evidence for PlioPleistocene refugia in the genetic structure of chimpanzees in East Africa. Pilbrow (2006) supported an isolation-by-distance model, with strong correlation between dental morphometric distances and geographical distances, and rivers presenting barriers for dispersal. Gagneux et al. (2001) and Goldberg (1998) suggest, based on elevated levels of genetic diversity and panmixia, that chimpanzees are extremely vagile and capable of maintaining high levels of genetic contact across varied habitats. The highest levels of genetic diversity are detected in central African chimpanzees (Kaessmann et al., 1999; Yu et al., 2003; Fischer et al., 2004, 2006),

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raising the likelihood that chimpanzees spread out from that central core (Groves et al., 1992; Kaessmann et al., 1999; Yu et al., 2003). Early hominin diversification, on the other hand, appears to have taken place from the eastern and southern part of Africa, as implied by abundant fossil material from the region. The lack of hominin fossil material should not be taken as evidence for the absence of hominins from elsewhere in Africa, but in a study extending over 40 years at Amboseli National Park, Kenya, Behrensmeyer found close fidelity between recent bone assemblages and density of parent vertebrate populations (Western and Behrensmeyer, 2009). This lends credence to the idea that hominin fossil density reflects original population density in the region. Genetic diversity of present day humans is also greatest in this region, as reported by studies on dental traits (Irish, 1998; Irish and Guatelli-Steinberg, 2003) and Y chromosome DNA (Chiaroni et al., 2009). By entertaining the possibility that chimpanzees, gorillas and humans had divergent centers of diversification in Plio-Pleistocene Africa we can understand the adaptive and niche differentiation strategies of these sympatric hominids. Genetic diversity in present-day humans is considerably reduced compared to chimpanzees and gorillas (Vigilant and Bradley, 2004b; Fischer et al., 2006). It is possible that cyclical climatic rhythms and local faulting caused genetic diversification and population dispersal of early hominins in East and South Africa. Conclusions This study reveals a primary split between the East and West African gorillas based on molar morphometrics, which may be used to support the distinction between G. gorilla and G. beringei. Two additional subgroups are recognized in West Africa, one in the Cross River area and the other encompassing southern Cameroon, Gabon, Equatorial Guinea, Republic of Congo and Central African Republic. These correspond with the subspecies, G. g. diehli and G. g. gorilla. In East Africa, a lowland gorilla subgroup, G. b. graueri, is recognized around the Itombwe and Mwenga-Fizi regions. This is distinct from the highland gorilla subgroup from Virunga and Bwindi, G. b. beringei. The Tshiaberimu gorillas are distinct from the other eastern gorilla subspecies, and together with the Kahuzi-Biega gorillas, provide preliminary support for G. b. rex-pygmaeorum. These patterns of molar differentiation match those recently revealed by other morphological and molecular data, suggesting that geographic patterning of dental variation reflects underlying genetic relationships among populations. There is little correlation between geographic and dental distances in the two main centers of gorilla distribution, but patterns of altitudinal variation provide a better explanation for gorilla patterns of segregation. This suggests that Pleistocene climatic fluctuations and mountain building activities in Nigeria and East Africa affected gorilla phylogeography. Thus, gorilla population structure most closely resembles an abundant center distribution pattern, with western gorillas at the historical center of gorilla distribution and altitudinally variable populations from Nigeria and East Africa at the periphery. The harsh climatic events in East Africa and Nigeria hastened the genetic differentiation of peripheral populations, primarily through the influence of drift. Acknowledgments I would like to thank the American Museum of Natural History, NY; Anthropologisches Institüt und Museum der Universität ZürichIrchel, Zürich; British Museum of Natural History, London; Field Museum of Natural History, Chicago; Museum of Comparative Zoology, Harvard; Muséum National d’Histoire Naturelle, Paris; Powell-Cotton Museum, Kent; Peabody Museum of Anthropology, Harvard; United States National Museum, Washington, D.C.; Musée

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Royal de l’Afrique Centrale, Tervuren; Zoologisches Museum, Berlin; Anthropologische und Zoologische Staassammlung, Münich for providing access to gorilla dental specimens. The project was funded by grants from the LSB Leakey Foundation, National Science Foundation (SBR-9815546), the Wenner-Gren Foundation and research support of the department of Anatomy and Cell Biology at the University of Melbourne. The comments of reviewers and editors greatly strengthened the paper. Appendix. Supplementary data Supplementary data associated with this article can be found in the online version, at doi:10.1016/j.jhevol.2010.01.009. References Altheide, T.K., Hammer, M.F., 1999. Y chromosome variation in the Hominoidea. Am. J. Phys. Anthropol. Suppl. 28, 83. Altheide, T.K., Hammer, M.F., 2000. Comparing patterns of Y chromosome and mitochondrial DNA variation in the Hominoidea. Am. J. Phys. Anthropol. Suppl. 30, 95. Anthony, N.M., Clifford, S.L., Bawe-Johnson, M., Abernethy, K.A., Bruford, M.W., Wickings, E.J., 2007. Distinguishing gorilla mitochondrial sequences from nuclear integrations and PCR recombinants: guidelines for their diagnosis in complex sequence databases. Mol. Phylogenet. Evol. 43, 553e566. Avise, J.C., Walker, D., Johns, G.C., 1998. Speciation durations and Pleistocene effects on vertebrate phylogeography. Proc. Roy. Soc. B 265, 1707e1712. Bailey, S.E., Pilbrow, V.C., Wood, B.A., 2004. Interobserver error involved in independent attempts to measure cusp base areas of Pan M1s. J. Anat. 205, 323e331. Bergl, R.A., Vigilant, L., 2007. Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli). Mol. Ecol. 16, 501e516. Bermejo, M., Rodriguez-Teijero, J.D., Illera, G., Barosso, A., Vila, C., Walsh, P.D., 2006. Ebola outbreak killed 5000 gorillas. Science 314, 1564. Bonnefille, R., Roeland, J.C., Guiot, J., 1990. Temperature and rainfall estimates for the past 40,000 years in equatorial Africa. Nature 346, 347e349. Braga, J.C., 1995. Définition de certains caractères discrets crâniens chez Pongo, Gorilla, et Pan. Perspectives taxonomiques et phylogénétiques. Ph.D. Dissertation, University of Bordeaux. Brown, J.H., 1984. On the relationship between abundance and distribution of species. Am. Nat. 124, 255e279. Burrows, W., Ryder, O.A., 1997. Y chromosome variation in great apes. Nature 385, 125e126. Butynski, T., Kalina, J., 1993. Three new mountain National Parks for Uganda. Oryx 27, 214e224. Caldecott, J., Miles, L., 2005. World Atlas of Great Apes and their Conservation. University of California Press, Berkeley. Casimir, M.J., 1975. Some data on the systematic position of the eastern gorilla population of the Mt. Kahuzi region (Republique du Zaire). Z. Morphol. Anthropol. 66, 188e201. Chiaroni, J., Underhill, P.A., Cavalli-Sforza, L.L., 2009. Y chromosome diversity, human expansion, drift, and cultural evolution. Proc. Natl. Acad. Sci. 106, 20174e20179. Cippolletta, C., 2004. Effects of group dynamics and diet on the ranging patterns of a western gorilla group (Gorilla gorilla gorilla) at Bai Hokou, Central African Republic. Am. J. Primatol. 64, 193e205. Coetzee, J.A., 1964. Evidence for a considerable depression of the vegetation belts during the Upper Pleistocene on the East African mountains. Nature 204, 564e566. Colyn, M., 1991. L'importance zoogeographique du basin du fleuve Zaire pour la speciation. Ann. Sci. Zool. 264, 180e185. Colyn, M., Gautier-Hion, A., Verheyen, W., 1991. A re-appraisal of paleaenvironmental history in central Africa: evidence for a major fluvial refuge in the Zaire basin. J. Biogeogr 18, 403e407. Coolidge, H.J., 1929. A revision of the genus Gorilla. Mem. Mus. Comparat. Zool. Harvard 50, 293e381. Clifford, S.L., Abernethy, K.A., White, L.J.T., Tutin, C.E.G., Bruford, M.W., Wickings, J.E., 2003. Genetic studies of western gorillas. In: Taylor, A.B., Goldsmith, M.L. (Eds.), Gorilla Biology: A Multidisciplinary Perspective. Cambridge University Press, Cambridge, pp. 269e292. Clifford, S.L., Anthony, N.M., Bawe-Johnson, M., Abernethy, K.A., Tutin, C.E.J., White, L.J.T., Bermejo, M., Goldsmith, M.L., McFarland, K., Jeffery, K.J., Bruford, M. W., Wickings, J.E., 2004. Mitochondrial DNA phylogeography of western lowland gorillas (Gorilla gorilla gorilla). Mol. Ecol. 13, 1551e1565. Darroch, J.N., Mosimann, J.E., 1985. Canonical and principal components of shape. Biometrika 72, 241e252. Darwin, C., 1859. On the Origin of Species by Means of Natural Selection. John Murray, London. deMenocal, P.B., 1995. Plio-Pleistocene African climate. Science 270, 53e59.

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