ORIGINAL PAPER

Morphometric variations of the skull in the Gray Wolf(Canis lupus) in Iran

R. Khosravi & M. Kaboli & J. Imani & E. Nourani

Received: 13 May 2012 /Accepted: 12 July 2012 /Published online: 3 August 2012# Mammal Research Institute, Polish Academy of Sciences, Białowieża, Poland 2012

Abstract The Gray Wolf is a wide ranging carnivore in Iran,absent only in the central deserts and Dasht-e Lut. This studywas carried out to verify whether, despite their high mobility,individual wolves belonging to different populations showmorphological variations in the skull. We collected 48 skullsfrom various regions of Iran and measured 24 variables on thecranium. These primary variables were then used to generatesix indices to examine any variations in the shape of the skullscollected in different regions of the country. Although thelargest skulls collected for this study originated in the moun-tainous regions of the northwest, northeast, and west, principlecomponent analysis (PCA) did not result in a meaningfuldifference in the size and shape of wolf skulls in differentregions of Iran. Our results confirm that the minor morpho-logical variations of the skull in wolves of Iran are not anevidence for the separation of wolf populations in differentregions or the existence of various subspecies in the country.This uniformity can be explained by the strong gene flowamong populations as well as high mobility of the wolf thatfacilitates movement of individuals between populations.

Keywords Canis lupus . Cranium . Principal componentanalysis . Iran . Morphometry

Introduction

The Gray Wolf (Canis lupus) is a carnivore with a vastdistribution range, occupying habitats in North Americaas well as in Europe and Asia (Mech 1970). Varioussubspecies of the gray wolf are identified due to mor-phological differences in color, size of body and bones,especially the skull, and behavior (Wozencraft 2005).Wolves in Iran, nominative subspecies C. lupus pallipes(Sykes 1831), occupy a wide range of habitats and areabsent only in the central deserts and Dasht-e Lut. Thesubspecies shows high diversity in color pattern (Ziaei2009). This might be due to the great diversity ofhabitats in Iran which is caused by the existence oftwo large water bodies in the north and south and thevast mountain ranges expanding in the north and west.However, habitat fragmentation, due to construction ofcities, villages, and roads could have lead to the isola-tion of wolf populations and a decrease in genetic exchange(wayne 1992).

Wolves in Iran are considered one (Mech and Boitani2004) or two subspecies (International Wolf Center(2012) http://www.wolf.org), with populations in thesouth Caspian region belonging to the Caucasian sub-species (C. lupus cubanensis), populations in the north-east belonging to European subspecies (C. lupus lupus)of Europe, and wolves in other regions of Iran belong-ing to the Indian/Iranian subspecies, C. lupus pallipes.

The speed of gene flow between different populationsversus adaptation to local conditions, suggest the theo-ries of intraspeciefic or clinal variation. Intraspecificvariation has been tested against clinal variation forwolves in various parts of the world. Milenković et al.(2010) showed that Carpathian wolves had larger skullthan Dinaric–Balkan wolves and males were larger thanfemales in both populations and Dinaric–Balkan wolves

Communicated by: Mieczyslaw Wolsan

R. Khosravi :M. Kaboli (*) : J. Imani : E. NouraniDepartment of Environmental Sciences,Faculty of Natural Resources, University of Tehran,Karaj, Irane-mail: mkaboli@ut.ac.ir

R. Khosravie-mail: Khosravi65@ut.ac.ir

J. Imanie-mail: jalil.imani@ut.ac.ir

E. Nouranie-mail: enourani@ut.ac.ir

Acta Theriol (2012) 57:361–369DOI 10.1007/s13364-012-0089-6

had a more elevated snout and sagittal crest thanCarpathian wolves. Nowak and Federoff (2002) foundthat wolf skulls in the Italian peninsula have relativelynarrow palate between P1s, broad frontal shield, andshallow jugal, sharply different from other Eurasian C.lupus. Milenković (1997) studied wolf skulls fromYugoslavia and distinguished two different phenotypes:Dinaric-Balkan wolves that have relatively short andbroad skulls with concave foreheads and curved man-dibles and Carpathian wolves that have long and narrowskulls with flat foreheads and mandibles. Okarma andBuchalczyk (1993) studied mountain and lowland wolfpopulations and found significant differences in cranio-metrical characteristics between these two regions andnoticed that males were larger than females.

Due to the unavailability of suitable wolf specimens inIran, no study has been done on the differences of subspe-cies in this part of the world. The present study focuses onthe morphological variations of this species for the first timein Iran.

Material and methods

Specimens collected

Since the skulls of wolf carcasses found in nature are notcollected and preserved on a regular basis in Iran and skullsin natural history museums are mostly lacking accurate infor-mation about sex of the specimen and sampling area, we faceddifficulties in collecting the specimens to carry out this mor-phometric study. A total of 48 skulls (28 known and 20 un-known localities; Appendix 1) from different regions in Iranwere obtained and examined for their morphological features(Fig. 1). Adults were identified on the basis of fused sphenooc-cipital suture, degree of ossification of the cranial sutures,zygomatic breadth, and tooth wear (Gipson et al. 2000).

Variables measured

For cranial evaluation, 24 craniometric measurementswere taken following the methodology of Onar et al.(2005) and Milenković et al. (2006). All measurementswere obtained to the nearest 0.01 mm by a digitalcaliper (Table 1; Fig. 2). Also, in order to carry outshape analysis, craniometric measurements were used tocalculate the following six indices (Onar et al. 2005;Onar et al. 2001): skull index (zygomatic width×100/

Fig. 1 Locations where wolf skulls were collected (see Appendix I forgeographic names and locality abbreviations). The darker areas indi-cate mountainous regions

Table 1 Variables measured on the cranium in the Gray Wolf (C. lupus)

Variable Variable

1 Skull length GL 13 Condylobasal length CBL

2 Greatest length of the nasals MAIN 14 Basal length BPL

3 Cranial length LON 15 Maximum width of occipital condyles BOC

4 Least length of the nasals MIIN 16 Greatest diameter of the auditory bulla LBO

5 Upper neurocranium length LOB 17 Least diameter of the auditory bulla HBO

6 Maximum zygomatic width ZYB 18 Upper carnassial length LP4

7 Cranial width LBR 19 Height of upper canine HCC

8 Postorbital breadth LBS 20 Greatest breadth of the palatine GBP

9 Frontal breadth FRB 21 Length of p2 to m2 LP2M2

10 Interorbital breadth LBBO 22 Length of the cheektooth row LUTM

11 Distance between infraorbital foramina BIF 23 Length of upper tooth row LUT

12 Rostrum width ROB 24 Height of skull HOC

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skull length), skull index-1 (frontal breadth×100/skulllength), cranial index (cranial width×100/cranial length),basal index (zygomatic width×100/basal length), basalindex-1 (cranial width×100/basal length), and length-width index (skull length/zygomatic width).

Data analysis

All measurements were log-transformed to allow for normaldistributions. In morphometric analyses, allometric growth(i.e., heterogeneity in body size among samples) can

Fig. 2 Skull measurements ofthe Gray Wolf (C. lupus); adorsal view and b ventral viewof the cranium

Table 2 Craniometric charac-teristics of 48 Iranianwolves

Minimum Maximum Mean Std. deviationStatistic Statistic Statistic Statistic

Skull length 213.00 270.02 235.65 12.94

Greatest length of the nasals 76.84 100.46 86.81 5.92

Cranial length 110.90 140.24 124.99 7.23

Least length of the nasals 65.90 89.90 76.69 5.95

Upper neurocranium length 59.02 91.65 74.21 8.91

Maximum zygomatic width 100.28 142.82 125.18 9.79

Cranial width 65.88 86.55 75.71 3.94

Postorbital constriction 33.95 51.24 42.01 4.49

Frontal breadth 45.59 71.72 58.56 5.99

Interorbital constriction 32.70 47.30 41.32 3.52

Distance between infraorbital foramina 35.42 55.86 47.92 3.64

Rostrum width 36.00 55.86 43.08 4.02

Condylobasal length 195.10 250.76 215.76 12.22

Basal length 185.04 240.24 206.79 11.13

Maximum width of occipital condyles 36.12 47.90 43.13 2.79

Greatest diameter of the auditory bulla 23.22 38.38 29.99 3.18

Least diameter of the auditory bulla 20.96 30.80 24.53 2.13

Upper carnassial length 17.88 25.80 22.94 1.80

Height of upper canine 14.80 36.42 25.65 4.36

Greatest breadth of the palatine 31.52 42.42 37.67 2.63

Length of p2 to m2 57.86 78.95 69.65 4.68

Length of the cheektooth row 64.20 85.85 77.67 4.48

Length of upper tooth row 75.68 110.20 95.86 6.33

Height of skull 62.20 95.28 70.29 7.05

Skull index 43.98 63.28 53.13 3.35

Cranial index 54.66 68.41 60.66 2.94

Basal index 49.99 71.01 60.56 3.99

Basal index-1 32.84 40.95 36.65 1.59

Skull index-1 21.01 29.87 24.85 2.14

Length-width index 1.58 2.27 1.88 0.12

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result in heterogeneity of shape without providing infor-mation on differences in body proportions among pop-ulations (Reist 1985). In the present study, there weresignificant correlations between skull length and the othermorphometric characters. Therefore, transformation of abso-lute measurements to size-independent shape variables wasthe first step of the analyses. Size-dependent variation formorphometric characters was removed using geometric mean(Darroch and Mosimann 1985; Mosimann 1987). Usinglog transformed data, geometric mean was computedas the average of the logged variables. Correlation coef-ficients between transformed variables and standardlength were calculated to check if the data transforma-tion was effective in removing the effect of size.

PCA was carried out for analyzing the morphometricdata to identify the combination of variables that best

separate skull samples. PCA produces a set of princi-pal components (PCs) that are not correlated. Smallsubsets of principal components (PCs) account for themajority of the variation, and therefore PCA is a veryeffective method for data reduction (Klingenberg andMcIntyre 1998; Klingenberg 2009). PCA was per-formed in two methods. In the first method, we used24 transformed measured variables for analyzing mor-phometric variations throughout Iran. We also calculat-ed six skull indices for shape analysis among samplesin different regions. The average size and shape vari-able for each individual were also calculated using thematrices of the Mahalanobis distance from mean val-ues of the 24 primary variables plus the six indices.PCA was performed using ADE-4 (Thioulouse et al.2001).

Table 3 Simple regression equations for the prediction of different unknown parameters (Y) of the skull in Iranian wolves

Predicted parameters (Y) Known parameters X0skull width Known parameters X0skull length

Correlation coefficient Regression equation Correlation coefficient Regression equation

Skull index 0.721 Y021.91+0.249X* −0.095 Y058.93−0.025X

Skull index-1 −0.358 Y037.35−0.099X* −0.452 Y047.19−0.094X*

Cranial index 0.026 Y059.67+0.008X −0.290 Y076.24−0.066X

Basal index 0.735 Y023.03+0.300X* −0.018 Y061.86−0.006X

Basal index-1 0.035 Y035.94+0.006X −0.316 Y045.84−0.039X*

Length-width index −0.737 Y03.04−0.009X* 0.073 Y01.727+0.002X

Fig. 3 Means, standard deviations, and standard errors for the six indices in Iranian wolves

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Results

Analysis of skull variations

Macroanatomical study was conducted on the skulls of 48wolves. Some descriptive statistics of different skull meas-urements is presented in Table 2. The largest and smallestskulls belonged to Tabriz and Kerman provinces respective-ly (SLT0270.02, LONT086.55 and BPLT0240.24; SLK0213, LONK0110.9, BPLK0187.96). Six indices were cal-culated from skull measurements. The mean of skull index,skull index-1, cranial index, basal index, basal index-1, andlength-width index were 53.13, 25.00, 60.66, 60.56, 36.65,and 1.89, respectively (Fig. 3). The correlation analyses ofthe features examined in this study are presented in Table 3.A strong negative correlation between skull index-1 andlength and width of the skull was determined in the wolves.A very strong negative correlation was found betweenlength-width index and skull width while a very weakpositive correlation was found between skull-width indexand skull length.

Skulls in the morphospace of primary Variables

The first and second axes of the PCA plane (24×48 matrix)demonstrate 23 and 13 % of morphological variationscaused by the primary variables (Fig. 4, Table 4). Thefirst axis mostly represents body size, although becauseof a reduction in effect of size on measurements, it ismostly affected by shape of the skull. Figure 4 indicatesthat according to the variables used in this study, thereis no significant discrimination between skulls collectedin different regions. As shown in Fig. 4, most speci-mens are concentrated at the center of the diagram.

Fig. 4 PC1–PC2 plane of thePCA performed on 24morphological characteristics ofthe wolves. See Appendix 1 forsample abbreviations

Table 4 Eigenvalues, percentages of explained variance, cumulativepercentage of explained variance, and contribution of the variables tothe first three principal components of a PCA of Iranian wolf skullsmeasurements

N048 PC1 PC2 PC3

Eigenvalues 5.53 3.09 2.29

Percentages of explained variance 23.1 12.8 9.1

Cumulative percentages of variance 23.1 35.9 45

Contribution of the variables (/10,000)

GL 1,346 38 53

CBL 1,346 38 53

BPL 1,403 9 237

LP2M2 14 50 79

LUTM 79 1,000 505

HCC 850 463 193

LP4 710 398 6

HOC 327 18 525

BOC 140 89 370

ZYB 80 125 1,261

FRB 280 700 709

GBP 6 526 888

ROB 98 220 62

BIF 292 444 448

MIIN 366 175 230

LON 1 366 1,886

LOB 534 1,340 109

LBR 534 1,340 109

MAIN 648 229 634

LBBO 30 931 1,098

LBS 137 18 364

LUT 19 1,334 164

HBO 307 116 0

LBO 444 20 0

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Considering the circle of variables, it can be seen thatvariables regarding length are located at quadrants 2 and3, with the main skull length variables (GL, BPL, andCBL) being concentrated in quadrant 2. Variables rep-resenting the width at the back of the skull (LBR,BOC) are located in quadrant 2 while the two variablesshowing the width of the frontal part (BIF, ROB) arelocated in quadrant 1. The third and fourth axes of the

PCA (24×48 matrix) include 10 % and 9 % of mor-phological variations caused by the primary variables(not shown here). No major discrimination exists alongthese axes.

The results of the PCA show that the divergence ofthe specimens based on the 24 measured variables isnot enough to separate the specimens collected in dif-ferent regions. Therefore, the wolf populations in differ-ent parts of Iran are not morphologically discriminated(Fig. 5).

Skulls in the morphospace of index variables

The first and second axes of PCA on the six indicescalculated from primary variables (6×48 matrix) dem-onstrate 15 % and 25 % of morphological variationscaused by the six indices (Fig. 6, Table 5). Since the sixindices represent variations in shape of the skull, thedifferences in shapes of skulls collected in differentregions are noticeable on the first and second axes.Results of grouping the specimens on the first andsecond axes, like in the case with primary variables,suggest no discrimination among skulls collected indifferent regions with most specimens located at thecenter of the plane. As shown in Fig. 6, except forindex LWI, the other five indices show an increase fromright to left, with Ke5 and Ha5 showing the largest valuesamong the specimens.

The third and fourth axes of the PCA (24×48 matrix)demonstrate 17 % and 6 % of morphological variationscaused by primary variables respectively (not shownhere). No evident discrimination can be seen along theseaxes.

Fig. 5 Dendrogram based on morphometrical distances. Numbers inparentheses indicate the locations where wolf skulls were collected(see Fig. 1)

Fig. 6 PC1–PC2 plane of thePCA performed on 6morphological indices of thewolves. See Appendix 1 forsample abbreviations

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Discussion

Results of our analyses indicate no difference among wolfskulls collected in different regions of Iran. However, resultsof PCA point to the fact that skulls collected in Tabriz,Khorasan, and western Iran are generally larger (Fig. 7).Since these regions are located in mountain ranges of Alborzand Zagros, the large size of the skulls here seems to agreewith findings of Okarma and Buchalczyk (1993) whoreported larger skulls in mountainous regions than inplains.

The pattern of genetic diversity and morphometric variationin species is due to genetic drift, gene flow, and natural selection(Allendorf 1983). Because the wolf is a highly mobile species,gene flow is expected among populations, leading to greatsimilarities among them (Forbes and Boyd 1997).

Studies on mtDNAmarkers and microsatellites reveal a highgenetic diversity among wolf populations occupying differentregions of Iran (Khosravi et al. 2012). This may be caused bystrong gene flow among different populations. Also, the phy-logenetic tree representing genetic distance indicates that noseparation exists among wolves in different regions of Iran(Khosravi et al. 2012). Since wolves are carnivores with highmobility, high gene flow among wolf populations is not sur-prising (Forbes and Boyd 1997). High heterozygosity and highgene flow among wolves in different habitats leads to a lack ofmorphological difference between populations.

Paquet and Carbyn (2003) stated that high genetic andmorphometric variation observed in wolves show that geneticdrift is not an important problem unless populations are smalland isolated. Since wolves are abundant in most habitats inIran, and high heterozygosity is observed in the populations, itcan be said that genetic drift is not likely to lead to genetic andmorphologic variations in wolves occupying different habitats.

This investigation is the first morphometric study of cranialvariation in the Iranian wolves. In view of limited sampling,however, the obtained results should be interpreted and gener-alized with some caution. Further investigations are needed forassessing the exact patterns of the Gray Wolf diversity in Iran.

Fig. 7 Dorsal (a) and ventral(b) views of cranium andventral view of mandible ofGray Wolf (C.lupus) fromnorthwest (Tabriz, left) and east(Kerman, right) of Iran

Table 5 Eigenvalues, percentage of explained variance, cumulativepercentage of explained variance, and contribution of the indices to thefirst three principal components of a PCA of Iranian wolf skullsmeasurement

PC1 PC2 PC3

Eigenvalues 3.05 1.54 9.99

Percentages of explained variance 50.8 25.6 16.7

Cumulative percentages of variance 50.8 76.4 93.1

Contribution of the variables (/10,000)

Skull index 3,078 267 24

Cranial index 113 5,144 149

Basal index 3,082 97 13

Basal index-1 590 4,212 34

Length-width index 3,077 269 26

Skull index-1 57 8 9,751

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Appendix 1

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Table 6 Locality, abbreviations,and examine location of 48 GrayWolf skulls

No Locality Collection

1 Semnan Se1 Garmsar, private collection

2 Semnan Se2 Semnan, Adibi

3 Semnan Se3 Semnan, Adibi

4 Semnan Se4 Semnan, Adibi

5 Esfahan Es1 Esfahan, private collection

6 Esfahan Es2 Faculty of environmental sciences, Karaj

7 Northern Khorasan Kh1 Tehran, Community of Land planning

8 Northern Khorasan Kh2 Bojnourd, private collection

9 Tehran Te1 Tehran, Community of Land planning

10 Tehran Te2 Tehran, Community of Land planning

11 Hamedan Ha1 University of Tehran, Karaj

12 Hamedan Ha2 University of Tehran, Karaj

13 Hamedan Ha3 University of Tehran, Karaj

14 Hamedan Ha4 Museum of College of Agriculture, Hamedan

15 Hamedan Ha5 Hamedan, Yalpanian

16 Kordestan Ko1 Karaj, Faculty of Environmental Sciences

17 Kerman Ke1 Department of Environment of Kerman

18 Kerman Ke2 Department of Environment of Kerman

19 Kerman Ke3 Kerman, private collection

20 Kerman Ke4 Kerman, private collection

21 Tabriz Ta1 Iranian Department of Environment (DOE)

22 Tabriz Ta2 Iranian Department of Environment (DOE)

23 Yazd Ya1 Iranian Department of Environment (DOE)

24 Yazd Ya2 Yazd, private collection

25 Yazd Ya3 Yazd, private collection

26 Sabzevar Sa1 Natural museum of DOE

27 Zanjan Za1 Natural museum of DOE

28 Hamedan Ha6 Natural museum of DOE

29–48 Unknown U01–U29 Natural museum of DOE

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