A N N A L E S H I S T O R I C O - N A T U R A L E S M U S E I N A T I O N A L I S H U N G A R I C I Volume 92 Budapest, 2000 pp. 455-476.

Biological distance among six population samples excavated in the environs around Székesfehérvár, Hungary, as derived by

non-metric trait variation

M. FlNNEGAN1 & K. ERY2

'Osteology Laboratory, Department of Sociology, Anthropology and Social Work Kansas State University, Manhattan, Kansas, USA

2H-1031 Budapest, Amfiteátrum u. 29, Hungary

FlNNEGAN, M.& É R Y , K. (2000): Biological distance among six population samples excavated in the environs around Székesfehérvár, Hungary, as derived by non-metric trait variation. - Annls hist.-nat. Mus. natn. hung. 92 : 455^-76.

Abstract - Non-metric analysis of 376 crania housed at the King St. Stephen Museum, Székesfehér­vár, Hungary, representing six 4th through the 13th century populations, was conducted to ascertain the separation among the samples studied. Standard biological distance statistics were employed to elucidate the divergence among these groups and numerical taxonomy computer programs were used to display relevant associations within and among these populations. Several samples generated no significant differences, suggesting that they are simply different samples drawn from the same, larger populations. However, most sample pairs generated significant differences showing good biological separation. In these samples, biological distance appears to follow temporal rathed than spatial sepa­ration. With 6 figures and 10 tables.

I N T R O D U C T I O N

During the last decade a number of papers have been published dealing with population distance of earlier human populations from the Carpathian Basin and Transdanubia (FlNNEGAN & MARCSIK, 1979, 1989a,b, FlNNEGAN et al. 1991, FlNNEGAN & SZÁLAI 1992). During the summer of 1990 the authors had the op­portunity to study non-metric traits on a number of populations housed in the King St. Stephen Museum in Székesfehérvár. The present paper reports on the materials studied and gives a preliminary descriptive analysis of these materials and the re­sults of the study.

M A T E R I A L S A N D METHODS

Of the vast holdings of cranial material held at the Museum, we looked at six samples which ranged in age from Roman period to the 13th Century. Inasmuch as non-metric data was present on many Avar aged samples, we decided that earlier and later samples would help complete our knowledge of population distance using samples from Central Hungary. The samples chosen were based on our general interest in the populations, the completeness and preservation of the materials and the sample sizes themselves. Geographic location of the cemetery sites, while important, did not take priority for the sample of choice. Those samples chosen, along with some limited demographic considerations, are summarized in Table 1. The sample from the cemetery at Tác is a late Roman (4th-5th century) population which has been elaborated, with respect to the stature, by BOCQUET-APPEL & ERY (1988), and, with respect to the osteoarcheological data, by ERY (2000). This cemetery is located approximately 12.8 km south of Székesfehérvár and provides 39 males, 50 females and 29 unsexed crania. Two samples come from the area of Dunaújváros: Dunaújváros-Táborkerülct, a 4th-5th century Late Roman aged cemetery with 36 males and 16 females, Dunaújváros-Csetény an 11th-13th century cemetery of the Arpádian time period is represented by 27 males, 19 females and 2 unsexed individuals. These cemeteries are located approximately 50 km east southeast of Székesfehérvár. A fourth cemetery, Rácalmás, is located approximately 45 km east southeast of Székesfehérvár and represents a 10th-11 th century cemetery of the Árpádian time period. In this sample we studied 38 males, 22 females and 2 unsexed crania. The cemetery sample from Sárbogárd, located approximately 40 km southeast of Székesfehérvár, is represented by 34 male and 16 female individuals from the 10th century of the Hungarian Conquest period. This material is elaborated by ERY (1968). The final cemetery sample comes from Csákvár, located 24 km north-northeast of Székesfehérvár and is represented by 33 males, 21 females and one unsexed crania, dated to the Late Roman 4th-5th century.

In total, our sample represents 207 males, 144 females and 35 individuals whose sex remains unknown. Al l crania were scored for 42 cranial non-metric traits as described by FlNNEGAN (1972) and FlNNEGAN & MARCSIK (1979) except where breakage, damage, or fusion of sutures or local pathology did not allow an observation to be made.

The frequencies recorded for these non-metric traits in each of the six population samples can be seen in Table 2. Inasmuch as the number of individuals in each sample population scored for a particular trait varies, depending on breakage and pathology in the area of that trait, the sample size is variable for each trait. The actual number for each trait is recorded in Table 3. Note here that for some traits, 2N (twice the sample size due to the bilateral traits) is presented as ultimately left and right sides were pooled. Table 4 displays the minimum and maximum frequency and the range in frequency of each trait across the six population samples.

In that we arc interested in the biological distance between these population samples, we utilized FlNNEGAN & COOPRIDER (1978) for determining which statistic to use. We settled on the statistic developed by C. A. B. S M I T H , which was first used by G R E W A L (1962). This is the statistic of choice in that it is easily computed and has been used in research concerning other regions of Hungary (FlNNEGAN & MARCSIK 1979, 1989a).

RESULTS

One of the advantages of the statistic used, and non-metric trait analysis in general, is for bilateral traits information may be gathered from each side of the

cranium. We tested for side asymmetry using the chi square statistic based on theta values as presented in FlNNEGAN (1972). This chi square test was used in analyz­ing side asymmetry in crania assessed as male for the 42 non-metric traits. Four­teen traits were significant at or above the .05 level. At this level of significance, we would expect, in this case, 10.5 significant differences due to chance alone. Here, we slightly exceed the chance expectation at the .05 level. While two traits were significantly different at the .01 level, this does not exceed the chance expec­tation of 2.1 traits. Three traits generated significant side asymmetry in more than one population (Pterion Form, Frontal Foramen Present, and Mylohyoid Grove Closed). The number of significant side asymmetries varied from one to three traits in each population. Of those traits, where a significant side asymmetry was gener­ated, four instances showed the left side to have the higher incident frequency, while 10 traits showed the right side to have the higher incident frequency. On those traits where a significant difference was found in more than one population sample, two samples had the higher frequency on the left, while one other sample had the highest incident frequency on the right. In one case, Mylohyoid Groove Closed, the higher incident was on the right side in the two samples which showed a significant side asymmetry. In each of these samples the sample size was suffi­ciently high to discount the significant difference due to small sample size. In gen­eral, it can be said that the significant differences generated in this study are rela­tively random among the population samples studied and in only a few instances specific to a particular trait under analysis. We feel that these borderline significant differences, as a whole, do not present a need to control for side asymmetry in the male sample.

In the female sample, 14 traits were significant at or above the .05 level of confidence. Again, we would expect only 10.5 significant differences due to chance alone at the .05 level. Therefore, the female samples slightly exceeded the chance expectation at the .05 level of confidence. Two traits developed significant side asymmetiy at the .01 level of confidence, but this does not exceed the number of significant differences at the .01 level due to chance expectation. As well, 7 of the 14 significant differences were generated where one or both of the sides tested had a sample size less than 12, which we believe adversely affects the chi square statistic used here. The number of significant side asymmetries vary from 1 to 3 traits within a population sample. These were randomly distributed with respect to the traits in that the same trait did not show a significant difference in more than one population. As well , in seven of these significant side asymmetries, the higher frequency was seen on the left side and in seven instances, the higher frequency was seen on the right side. Of the 14 traits significant at or above the .05 level, 7 of these traits had sample sizes below 12 on one or both sides, which raises some

doubt as to the validity of the significance generated for that particular trait. In gen­eral, the results for females, as with the males, is marginal with respect to signifi­cant side asymmetries. In that this is a preliminary descriptive report, we chose to overlook the few significant side asymmetries above those expected due to chance alone. We realize that in a final study of population divergence, some minor cor­rections would have to be made either by omitting certain traits or in generating samples where the number of sides are equal.

The same chi square analysis was used to test for sex dimorphism, keeping left and right sides separate so that the minor side asymmetry (observed above) would not be reflected in the chi square analysis for sex. The chi square values gen­erated in comparing male and females on the left side only are presented in Table 5. Here we find 21 significant differences at or above the .05 level whereas we would expect, due to chance alone, only 16 significant differences. Therefore, at this level of significance, chance expectation was exceeded. As well , at the .01 level of sig­nificance, we found 5 differences where chance expectation alone would suggest but 2.5. While this discrepancy is real and some significant sex differences are found, we note that in seven traits where significant differences were generated, the sample size of one or both samples involved was equal or less than 15 which al­lows a consideration for the sample size being, in part, responsible for the genera­tion of significant difference. Nonetheless, three traits, Frontal Foramen Present, Mandibular Torus Present and Foramen of Vesalius Present, showed a significant difference in more than one population sample. Aside from these, the significant differences generated are randomly distributed among both the population samples and the traits. Presence of the Frontal Foramen on the left side showed a significant difference at the .01 level in the populations samples from Sárbogárd and Dunaúj­város-Táborkerület . In each of these cases, the highest frequency was found in fe­male individuals. In the other two cases where a trait showed a significant difference in more than one sample, the male frequency was higher. The Rácalmás population dis­played the greatest number of significant differences with five, while the Dunaúj-város-Csetény population had but one significant difference between the sexes.

Looking at sex dimorphism on the right side (see Table 6), 23 significant dif­ferences were generated at the .05 level where only 12.6 are suggested due to chance alone. Five significant differences were found at the .01 level where only 2.5 significant differences could be due to chance expectation. Nine of these cases had a sample size of 15 or less in one or both samples being tested, which may have generated a significant difference due to the small sample size. The sample with the lowest number of significant differences was Tác with two significant differ­ences at the .05 level while the Rácalmás sample had five significant differences again, all at the .05 level. No one non-metric trait had more than two significant

differences while six traits had more than one significant difference: Highest Nuchal Line, Asterionic Bone, Mandibular Torus, Accessory Lesser Palatine Fo­ramen, Foramen of Vesalius, and Anterior Ethmoid Foramen Exsutural. In the Mandibular Torus trait, one significant difference had the higher frequency in the female sample, while the other significant difference had the higher frequency in the male sample. The Anterior Ethmoid Foramen Exsutural had the higher incident frequency in females in both cases, while the other four traits showed a higher inci­dence in males.

In this study we are pooling males and females even though the number of significant differences generated exceed chance expectation. We are doing this be­cause this study is preliminary in nature and while individual samples may exceed a 60/40 male/female split, the overall sample does not exceed a 60/40 split which falls in the range suggested by FlNNEGAN & MARCSIK (1979) and F l N N E G A N & SZÁLAI ( 1991 ). In other instances, we would argue for some correction due to sex dimorphic traits as suggested in FlNNEGAN (1972, 1978) using the methodology of GAHERTY ( 1974), JANTZ ( 1970) or FlNNEGAN ( 1978).

A G E DEPENDENCY

KOREY (1970) suggested that non-metric traits displayed significant age de­pendency. He tested this assumption using correlation statistics which showed a slight increase in trait frequency with age, and in many cases, significantly so. However, this is probably not the statistic of choice when looking for age-trait de­pendency. While the present data was not checked for age dependency, we rely on the work of FlNNEGAN (1972, 1978) which showed by chi square analysis, that from youngest to oldest age samples, little significance was found. Indeed, fewer significant differences were found at the .05 level than chance expectation when comparing the 20-29 year old age group to the 60-69 year old age group ( 1978). As well, other individuals have suggested either mild age dependency or have stated that the age dependent nature of non-metric traits is negligible i f adult crania are utilized (OSSENBERG 1970, BUIKSTRA 1972, CORRUCCINI 1974).

In the present analysis we have not been concerned about age dependency with the non-metric traits we are using since the samples are composed of predom­inantly adult crania which offers little for age dependency. Only seven individuals in the combined sample of 376 individuals were under the age of 18 years. This represents approximately 1.8% of the sample and it can be further noted that these 7 individuals are more or less evenly distributed among the population samples. We therefore conclude that in this particular analysis, age dependency does not pose a problem.

D A T A A N A L Y S I S

The frequencies presented in Table 2 were transformed to theta values using the arcsine (sin-1) transformation. These transformed frequencies were then applied to the G R E W A L - S M I T H statistic ( G R E W A L 1962) and used to calculate the mean measure of divergence ( M M D ) among all sample pairs as presented in Table 7. The M M D values are written above with italicized estimates of the variance writ­ten below. As noted in Table 7, seven of these interpopulation distances are signifi­cant at the .05 level, while 8 distances are not significant at the .05 level. It is inter­esting to note that the lowest population distance is between population samples Csákvár and Dunaújváros-Táborkerület at 0.004. The next lowest are the distances between Tác and Csákvár and Dunaújváros-Táborkerület at a level of 0.007 each. It is interesting that all of these are of the same time period, late Roman age. How­ever, none of these population pairings have generated a significant M M D . As such, these populations must be viewed as different samples drawn from the same population, and should not be further analyzed at this level.

In order to reduce these population samples, which logically are different samples of the same population, we have used the distances presented in Table 7 and the statistical package of R O H L F et al. (1974) to generate a general distance phenogram, a bivariate plot and a phenogram of cophenetic relationships in order to help us determine how the samples should be pooled. The statistic used is a se­quential agglomerative, hierarchical cluster analysis where the unweighted pair-group method using arithmetic averages was used. We decided that the lowest values were to be considered for similarity. The phenogram which resulted is pre­sented in Fig. 1. Cophenetic values for each element in the matrix were generated and compared to the original matrix for congruence ( S O K A L & S N E A T H 1963). The bivariate scatter diagram shown in Fig. 2 was developed by comparing ele­ments of the first matrix plotted against corresponding elements of the cophenetic matrix. The phenogram of the cophenetic matrix is presented in Fig. 3 and in com­paring this to Fig. 1, we see little distortion in the groupings based on cluster analy­sis techniques. This gives us additional confidence in the original matrix, and the correlation between the original and cophenetic matrices is 0.804. The significance of the cophenetic relationships which also shows the integrity of this plot has been determined by D E R I S H & S O K A L ( 1988) to be in the neighborhood of 0.85 in order to be highly significant. We have not attained this level in this particular plot. While the groupings of the phenogram presented in Fig. 1 meet our expectation, the correlation itself is not highly significant which probably reflects the number of population pairings from the matrix in Table 7 which are also not significant.

In order to adjust for the lack of significance seen in the matrix of Table 7, and in order to heighten the cophenetic correlation, we decided to group a number of population samples into higher groupings. As such, Tác and Dunaújváros-Csetény were coalesced as one sample which can be justified in that the M M D between these two samples was not significant, suggesting they were different samples from the same larger population. Similarly, samples Csákvár and Dunaújváros-Táborkerület were also coalesced into one sample. These reductions are supported in Fig. 1, particularly for the reductions of Csákvár and Dunaújváros-Táborkerület; less so for the reduction between Tác and Dunaújváros-Csetény which jo in later in the phenogram (Fig. 1) at a relatively low, insignificant, level (0.010 from Table 7).

The new populations can be called T á c — Dunaújváros-Csetény which is made up of populations Tác and Dunaújváros-Csetény. The other new grouping, Csákvár—Dunaújváros-Táborkerület is the coalescence of samples Csákvár and Dunaűjváros-Táborkerület. Once these samples were brought together, the trait frequencies and sample sizes were re-established for each trait in each new sample. These are presented in Table 8 and 9 respectively. Theta transformations were again conducted and the G R E W A L - S M I T H statistic was utilized in developing new M M D ' s (F lNNEGAN 1972). The resultant distance matrix is presented in Table 10. The figures underwritten in italics are estimates of the variance and note that in this case, all of the samples are significant at or above the .05 level with one sample generating significance at the .01 level.

In this case, our reduction of samples, making larger population samples, ap­pears to be correct. Again, the M M D ' s from this Table were submitted to T A X O N and M X C O M P , which develops a phenogram (Fig. 4) based on the raw data, cre­ates the cophenetic matrix with resultant phenogram (Fig. 6) and generates another bivariate scatter diagram (Fig. 5). The results from the sample reduction are quite evident in Table 10 and Figures 4, 5 and 6. In Fig. 4, the arbitrary line of signifi­cance shows that, in pairs, all samples are now significantly different. Table 10 shows all sample pair M M D ' s to be significant at or above the .05 level and the new resultant cophenetic correlation is now 0.902 which is highly significant based on the criteria of SOKAL & D E R I S H (1988).

The small number of samples which remain in the analysis do not cluster into groups. Rather, they join into one large grouping at nearly equal intervals with Tác-Dunaújváros-Cse tény joining Csákvár-Dunaújváros-Táborkerüle t at the 0.007 level. Sample Rácalmás joins this group at a level of 0.0145 and then sample Sárbogárd joins the group at a level of 0.0257. This suggests relatively equal place­ment of these three samples in the total matrix.

DISCUSSION

The mean measure of divergence ( M M D ) seen in Tables 7 and 10, with result­ing phenograms, Figs 4 and 6, should be taken as group data with each population joining at roughly equal intervals. In Fig. 1, a somewhat arbitrary line can be drawn at 0.0120, which is the level of lowest significant difference as seen in Table 7. In the phenogram in Fig. 1, a number of populations are grouped to the right side or below the arbitrary significance level in that phenogram. As a result, some samples were coalesced into larger samples which we felt depicted single populations. These results, shown in Table 10 and in the phenogram in Fig. 4, suggest another arbitrary level of significance at 0.007. In this case, groups no longer form below the significance level and as larger groups are created, population samples arrive in the grouping at nearly normal intervals; each interval is approximately the numeri­cal size of the minimum generated significance level.

It is of interest here that the 4th and 5th century samples now coalesce wi th an 11-13th century sample which was dictated from the M M D ' s in Table 7. It is prob­ably of less interest to notice that the Rácalmás sample, a 10th century sample and the Sárbogárd sample, another 10th century sample, are about equal distance from each other as they are from the 4th-5th century and 11th-13th century combined samples. This type of phenogram development, particularly from Table 7, may suggest that populations from a geographical locale are more stable over time, sug­gesting the similarity in frequencies of non-metric variables, and thence possibly genetic distance, rather than the spatial separation between these and some other samples. While the M M D ' s presented in Table 7 and their cophenetic correlation (0.804) was not highly significant, by the time the population samples were co­alesced into significant sample groupings, the cophenetic correlation was in­creased to 0.902, a highly significant figure (SOKAL & DERISH 1988).

This is the first analysis of these samples strictly by non-metric trait variation. As we continue research on these samples, in the direction of adding cultural and spatial differences as well as including other samples from similar and later times in Transdanubia as well as the larger Carpathian Basin, we w i l l try to elaborate more closely on the differences between these and other earlier human popula­tions.

Acknowledgements - The authors arc indebted to the staff of the King St.Stephen Museum in Székesfehérvár for their assistance in the course of data collecting during July and August of 1990. We thank Kansas State University for providing computer facilities used in this analysis.

REFERENCES

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Table 1 . Some limited demographic considerations and references for further elaboration of the cemetery samples reported in this study

Cemetery Sample

Males Females Unsexed Total Age

73 Tác (Bocquet-Appel & Éry 1983, Éry 2000) 39 50 19 236 4- -5th

74 Dunaújváros-Csetény (Éry) 27 19 i 96 1 1 -13th

75 Rácalmás (Éry) 38 22 2 124 10--1 Ith

76 Sárbogárd (Éry 1968) 34 16 1 102 1 0th

77 Csákvár(Éry) 33 21 1 1 10 4- -5th

78 Dunaújváros-Táborkeriilet I. (Éry) 36 16 0 104 4- -5th

Note: Total is twice the sum of M+F+US as we score each side separately.

Table 2 . Frequencies of non-metric traits for the six populations studied in Székesfehérvár during the summer of 1990

Cranial non-metric traits Tác Duna-C Rácalmás Sárbogárd Csákvár Duna-T 1. Highest nuchal line 0.242 0.152 0.213 0.176 0.100 0.094 2. Coronal ossicles 0.036 0.047 0.036 0.033 0.031 0.032 3. Ossicle at bregma 0.000 0.000 0.037 0.000 0.000 0.000 4. Sagittal ossicles 0.073 0.075 0.043 0.179 0.095 0.118 5. Ossicle at lambda 0.164 0.261 0.214 0.275 0.235 0.238 6. Lambdoid ossicles 0.448 0.500 0.535 0.520 0.505 0.610 7. Os inca 0.009 0.021 0.016 0.000 0.000 0.000 8. Parietal for. 0.424 0.406 0.379 0.461 0.361 0.436 9. Parietal notch bone 0.105 0.093 0.065 0.096 0.118 0.056

10. Asterionic bone 0.095 0.143 0.049 0.105 0.050 0.091 11. Auditory torus 0.000 0.000 0.000 0.000 0.010 0.000 12. Malar tubercle 0.064 0.044 0.031 0.000 0.061 0.049 13. Os japon 0.000 0.000 0.016 0.011 0.000 0.000 14. Pterion form 0.034 0.025 0.016 0.022 0.020 0.011 15. Epiteric bone 0.135 0.232 0.179 0.211 0.169 0.197 16. Infra-orbital for. 0.054 0.015 0.108 0.036 0.141 0.076 17. Supra-orbital for. 0.209 0.174 0.323 0.274 0.269 0.245 18. Frontal for. present 0.096 0.120 0.048 0.105 0.120 0.108 19. Metopic suture 0.077 0.043 0.049 0.140 0.019 0.115 20. Mandibular torus 0.075 0.040 0.042 0.111 0.158 0.067 21. Mylohyoid groove 0.055 0.053 0.042 0.010 0.061 0.105 22. Mandibular torus 0.029 0.076 0.000 0.043 0.000 0.000 23. Mental foramen 0.020 0.026 0.067 0.010 0.000 0.012 24. Palatine torus 0.295 0.385 0.393 0.235 0.346 0.225 25. Acc. les palate for. 0.125 0.161 0.119 0.125 0.140 0.063 26. For. of Vesalius 0.130 0.108 0.144 0.125 0.131 0.086 27. For. ovale 0.025 0.000 0.008 0.024 0.000 0.032 28. For. spinosum 0.043 0.051 0.049 0.062 0.067 0.048 29. For. of huschke 0.065 0.054 0.137 0.219 0.067 0.022 30. Condylar facet 0.023 0.000 0.026 0.014 0.014 0.016 31. Post, condy for. 0.468 0.329 0.395 0.318 0.459 0.582 32. Precondy. tubercle 0.063 0.051 0.033 0.000 0.048 0.097 33. Anterior condy for. 0.186 0.147 0.225 0.244 0.202 0.224 34. Mastoid for. 0.812 0.894 0.860 0.907 0.844 0.814 35. Mastoid for. exsut. 0.380 0.235 0.273 0.326 0.378 0.267 36. Paramastoid process 0.214 0.131 0.278 0.254 0.205 0.105 37. Digastric groove 0.259 0.184 0.293 0.256 0.170 0.195 38. Stylomastoid for. 0.004 0.000 0.016 0.000 0.010 0.000 39. Zygo-max tuberös. 0.364 0.278 0.320 0.425 0.408 0.456 40. Zygo-facial for. 0.251 0.192 0.260 0.205 0.262 0.202 41. Ant. eth. for. ex. 0.734 0.840 0.816 0.929 0.766 0.644 42. Post ethmoid for. 0.066 0.208 0.150 0.191 0.110 0.100

Table 3. Numbers of non-metric traits for the populations studied in Székesfehérvár during the summer of 1990.

Cranial non-metric traits Tác Duna-C Rácalmás Sárbogárd Csákvár Duna-T 1. Highest nuchal line 227. 92. 122. 102. 110. 96. 2. Coronal ossicles 225. 85. 112. 90. 98. 95. 3. Ossicle at bregma 111. 44. 54. 48. 51. 42. 4. Sagittal ossicles 96. 40. 47. 39. 42. 34. 5. Ossicle at lambda 110. 46. 56. 51. 51. 42. 6. Lambdoid ossicles 221. 90. 114. 100. 97. 82. 7. Os inca 116. 47. 62. 51. 55. 50. 8. Parietal for. 229. 96. 124. 102. 108. 101. 9. Parietal notch bone 228. 86. 123. 94. 102. 89.

10. Asterionic bone 220. 84. 123. 95. 101. 88. 11. Auditory torus 234. 93. 124. 96. 103. 98. 12. Malar tubercle 204. 68. 97. 64. 99. 81. 13. Os japon 221. 76. 123. 88. 107. 90. 14. Pterion form 232. 81. 123. 90. 98. 93. 15. Epiteric bone 192. 69. 106. 71. 83. 66.

16. Infra-orbital for. 221. 68. 111. 55. 99. 79. 17. Supra-orbital for. 235. 92. 124. 95. 108. 98. 18. Frontal for. present 230. 92. 124. 95. 108. 102. 19. Metopic suture 117. 47. 61. 50. 54. 52. 20. Mandibular torus 200. 75. 119. 90. 95. 75. 21. Mylohyoid groove 199. 76. 119. 99. 98. 76. 22. Mandibular torus 209. 79. 115. 94. 104. 79. 23. Mental foramen 204. 78. 120. 101. 105. 80. 24. Palatine torus 105. 39. 61. 34. 52. 40. 25. Acc. les palate for. 176. 56. 109. 48. 93. 64. 26. For. of Vesalius 184. 65. 111. 64. 84. 58. 27. For. ovale 201. 77. 121. 82. 86. 62. 28. For. spinosum 208. 78. 122. 81. 90. 62. 29. For. of huschke 216. 92. 124. 96. 104. 93. 30. Condylar facet 175. 70. 116. 71. 74. 64. 31. Post, condy for. 186. 70. 114. 66. 74. 67. 32. Precondy. tubercle 95. 39. 61. 44. 42. 31. 33. Anterior condy for. 188. 75. 120. 86. 84. 67. 34. Mastoid for. 213. 85. 121. 86. 90. 86. 35. Mastoid for. exsut. 213. 85. 121. 86. 90. 86,

36. Paramastoid process 192. 61. 115. 59. 78. 57. 37. Digastric groove 220. 87. 116. 82. 94. 87. 38. Stylomastoid for. 232. 93. 124. 94. 103. 96. 39. Zygo-max tuberös. 225. 79. 122. 80. 103. 90. 40. Zygo-facial for. 223. 73. 123. 88. 107. 89.

41. Ant. eth. for. ex. 188. 50. 76. 28. 64. 45. 42. Post ethmoid for. 183. 53. 100. 47. 73. 50.

Table 4 . Minimum and maximum frequencies and ranges of fre­quency for traits used in this study of the samples studied in

Székesfehérvár during the summer of 1990

Cranial non-metric traits Minimum Maximum Range 1. Highest nuchal line 0.097 0.216 0.119 2. Coronal ossicles 0.031 0.039 0.008 3. Ossicle at bregma 0.000 0.037 0.037 4 Sagittal ossicles 0.043 0.179 0.136 5. Ossicle at lambda 0.192 0.275 0.083 6. Lambdoid ossicles 0.463 0.553 0.090 7. Os inca 0.000 0.016 0.016 8. Parietal for. 0.379 0.461 0.082 9. Parietal notch bone 0.065 0.102 0.037

10. Asterionic bone 0.049 0.109 0.060 11. Auditory torus 0.000 0.005 0.005 12. Malar tubercle 0.000 0.059 0.059 13. Os japon 0.000 0.016 0.016 14. Pterion form 0.016 0.032 0.016 15. Epiteric bone 0.161 0.211 0.050 16. Infra-orbital for. 0.036 0.112 0.076 17. Supra-orbital for. 0.199 0.323 0.124 18. Frontal for. present 0.048 0.114 0.066 19. Metopic suture 0.049 0.140 0.091 20. Mandibular torus 0.042 0.118 0.076 21. Mylohyoid groove 0.010 0.080 0.070 22. Mandibular torus 0.000 0.043 0.043 23. Mental foramen 0.005 0.067 0.062 24. Palatine torus 0.235 0.393 0.158 25. Acc. les palate for. 0.108 0.134 0.026 26. For. of Vesalius 0.113 0.144 0.031 27. For. ovale 0.008 0.024 0.016 28. For. spinosum 0.045 0.062 0.017 29. For. of huschke 0.046 0.219 0.173 30. Condylar facet 0.014 0.026 0.012 31. Post, condy for. 0.318 0.518 0.200 32. Precondy. tubercle 0.000 0.068 0.068 33. Anterior condy for. 0.175 0.244 0.069 34. Mastoid for. 0.830 0.907 0.077 35. Mastoid for. exsut. 0.273 0.339 0.066 36. Paramastoid process 0.163 0.278 0.115 37. Digastric groove 0.182 0.293 0.111 38. Stylomastoid for. 0.000 0.016 0.016 39. Zygo-max tuberös. 0.320 0.430 0.110 40. Zygo-facial for. 0.205 0.260 0.055 41. Ant. eth. for. ex. 0.716 0.929 0.213 42. Post ethmoid for. 0.097 0.191 0.094

Tab le 5. Chi-square values for each trait in each population comparing males and females on left sides. *=p<0.05; * * =p<0.01. m and f indicate the sex o f the higher f requency

Non-metric trait/ Sample Tác Duna-C Ráca lmás Sárbogárd Csákvár Duna-T

1. Highest nuchal line 0.866 0.013 2.743 0.145 11.753**m 0.722

2. Coronal ossicles 0.706 0.628 1.491 0.192 3.244 1.250

3. Ossicle at bregma 0.000 0.000 0.163 0.000 0.000 0.000

4. Sagittal ossicles 2.222 5.286*m 3.472 0.125 0.065 0.365

5. Ossicle at lambda 2.061 0.406 0.157 0.107 1.712 0.068

6. Lambdoid ossicles 0.751 1.892 9.378**m 0.010 0.009 0.196

7. Os inca 2.299 1.690 1.462 0.000 0.000 0.000

8. Parietal for. 0.966 1.322 0.018 0.030 0.425 0.981

9. Parietal notch bone 1.061 1.118 0.024 0.066 2.170 0.001

10. Asterionic bone 3.594 0.217 3.035 5.817* 0.146 0.368

11. Auditory torus 0.000 0.000 0.000 0.000 2.504 0.000

12. Malar tubercle 0.150 0.191 0.000 0.000 5.000*f 1.294

13. Os japon 0.000 0.000 2.640 0.000 0.000 0.000

14. Pterion form 0.641 3.384 5.234*f 0.000 0.000 1.162

15. Epiteric bone 4.843 * f 1.736 1.308 0.661 0.890 0.755

16. Infra-orbital for. 2.002 0.000 1.962 0.000 1.492 0.040

17. Supra-orbital for. 2.043 0.134 2.997 0.087 0.133 0.320

18. Frontal for. present 3.374 0.024 0.306 8.599**f 0.209 8.026**f

19. Metopic suture 0.588 3.472 4.596*m 2.033 1.589 0.021

20. Mandibular torus 0.232 1.630 4.531*m 0.047 5.788*m 0.250

21. Mylohyoid groove 3.544 3.350 1.500 0.000 2.502 0.517

22. Mandibular torus 0.173 1.029 0.000 2.508 0.000 0.000

23. Mental foramen 4.524*m 1.573 2.947 1.274 0.000 1.294

24. Palatine torus 0.365 0.122 0.743 7.899*f 0.124 0.191

25. Acc . les palate for. 0.051 0.268 0.588 3.190 2.311 3.134

26. For. of Vesalius 1.142 1.644 3.322 4.253*m 4.692*m 2.452

27. For. ovale 0.000 0.000 2.640 2.775 0.000 3.342

28. For. spinosum 4.663*m 2.354 0.044 0.269 2.678 0.705

29. For. of huschke 0.149 1.751 1.354 1.503 1.219 2.834

30. Condylar facet 2.463 0.000 3.197 1.299 0.000 1.409

31. Post, condy for. 0.573 0.117 5.649*m 0.979 3.756 0.000

32. Precondy. tubercle 0.003 2.630 0.001 0.000 0.012 0.161

33. Anterior condy for. 0.103 0.749 0.417 0.324 0.006 2.293

34. Mastoid for. 4.800*m 0.596 1.354 0.225 0.751 1.229

35. Mastoid for. exsut. 3.584 0.005 0.036 3.029 3.687 0.211

36. Paramastoid process 2.379 0.050 0.429 1.836 0.450 2.769

37. Digastric groove 0.402 2.438 3.338 0.353 2.276 0.458

38. Stylomastoid for. 0.000 0.000 2.547 0.000 0.000 0.000

39. Zygo-max tuberös. 2.110 2.983 0.055 0.439 2.032 1.105

40. Zygo-facial for. 0.040 1.769 0.561 0.140 1.566 0.513

41. Ant. eth. for. ex. 1.681 9.081 0.025 0.000 0.213 43954*m

42. Post ethmoid for. 0.580 1.263 0.031 0.261 0.227 8.075**f

Table 6. Chi-square values for each trait in each population comparing males and females on right sides only. *=p<0.05; **=p<0.01. m and f indicate sex of the higher frequency

Non-metric trait/ Sample Tác Duna-C Rácalmás Sárbogárd Csákvár Duna-T

1. Highest nuchal line 0.030 0.013 4.353*m 0.045 0.376 3.967*m

2. Coronal ossicles 0.121 1.696 4.212*m 1.299 1.701 2.630

3. Ossicle at bregma 0.000 0.000 0.163 0.000 0.000 0.000

4. Sagittal ossicles 2.222 5.286*m 3.472 0.125 0.065 0.365

5. Ossicle at lambda 2.061 0.406 0.157 0.107 1.712 0.068

6. Lambdoid ossicles 0.061 0.354 0.193 1.362 0.085 1.079

7. Os inca 2.299 1.690 1.462 0.000 0.000 0.000 8. Parietal for. 2.070 1.333 1.494 0.370 0.713 0.865

9. Parietal notch bone 0.000 0.148 0.282 5.087*m 2.356 0.437

10. Asterionic bone 0.023 0.701 0.282 8.216**m 4.405*m 0.091 11. Auditory torus 0.000 0.000 0.000 0.000 0.000 0.000

12. Malar tubercle 0.112 1.356 0.003 0.000 10.178**f 0.108

13. Os japon 0.000 0.000 2.547 1.360 0.000 0.000

14. Pterion form 0.020 0.000 0.000 2.742 0.000 0.000

15. Epiteric bone 0.058 0.003 0.386 0.641 0.542 0.833

16. Infra-orbital for. 3.560 1.257 0.487 2.967 0.831 0.653

17. Supra-orbital for. 2.301 1.763 1.663 1.739 0.143 1.597 18. Frontal for. present 1.100 1.387 5.234*f 0.085 1.013 0.158

19. Metopic suture 0.588 3.472 4.596*m 2.033 1.589 0.021 20. Mandibular torus 0.057 5.316*f 2.947 0.775 8.125**m 1.473 21. Mylohyoid groove 0.397 0.107 0.246 1.306 0.860 0.123

22. Mandibular torus 0.216 0.908 0.000 2.508 0.000 0.000

23. Mental foramen 2.236 2.399 1.259 0.000 0.000 0.000

24. Palatine torus 0.365 0.122 0.743 7.899**f 0.124 0.191

25. Acc . les palate for. 0.778 4.078*m 0.056 0.488 0.020 3.923*m

26. For. of Vesalius 1.142 1.644 3.322 4.253*m 4.692*m 2.452

27. For. ovale 0.000 0.000 2.640 2.775 0.000 3.342

28. For. spinosum 4.663*m 2.354 0.044 0.269 2.678 0.705

29. For. of huschke 0.149 1.751 1.354 1.503 1.219 2.834

30. Condylar facet 2.463 0.000 3.197 1.299 0.000 1.409

31. Post, condy for. 0.573 0.117 5.649*m 0.979 3.756 0.000 32. Precondy. tubercle 2.135 3.805 0.131 0.000 0.060 0.002

33. Anterior condy for. 0.103 0.749 0.417 0.324 0.006 2.293 34. Mastoid for. 4.800*m 0.596 1.354 0.225 0.751 1.229 35. Mastoid for. exsut. 3.584 0.005 0.036 3.029 3.687 0.211

36. Paramastoid process 2.379 0.050 0.429 1.836 0.450 2.769 37. Digastric groove 0.402 2.438 3.338 0.353 2.276 0.458 38. Stylomastoid for. 0.000 0.000 2.547 0.000 0.000 0.000

39. Zygo-max tuberös. 2.110 2.983 0.055 0.439 2.032 1.105 40. Zygo-facial for. 0.040 1.769 0.561 0.140 1.566 0.513

41. Ant. eth. for. ex. 1.681 9.081**f 0.025 0.000 0.213 4.954*f

42. Post ethmoid for. 0.580 1.263 0.031 0.261 0.227 8.075*f

Table 7 . Measures of divergence (biological distance) between population samples used in this study. Underwritten figures in italics are estimates of the variance deviation. + represents significant at p<.05; * represents significant at p< 0.01

Tác Duna-C Rácalmás Sárbogárd Csákvár

Dunaújváros C 0.010

0.005

Rácalmás 0.012+

0.004

0.018+

0.006

Sárbogárd 0.027+

0.005

0.018

0.007

0.022+

0.006

Csákvár 0.007 0.017 0.013 0.029+

0.004 0.006 0.005 0.006

Dunaújváros T 0.007 0.021+ 0.026 0.041 + 0.004

0.005 0.007 0.006 0.007 0.006

Table 8. Frequencies of non-metric traits for the four coalesced populations studied in Székesfehérvár during the summer of 1990

Cranial non-metric traits Tác-DunaC Rácalmás Sárbogárd Csákvár-Duna' 1. Highest nuchal line 0.216 0.213 0.176 0.097 2. Coronal ossicles 0.039 0.036 0.033 0.031 3. Ossicle at bregma 0.000 0.037 0.000 0.000 4. Sagittal ossicles 0.074 0.043 0.179 0.105 5. Ossicle at lambda 0.192 0.214 0.275 0.237 6. Lambdoid ossicles 0.463 0.535 0.520 0.553 7. Os inca 0.012 0.016 0.000 0.000 8. Parietal for. 0.418 0.379 0.461 0.397 9. Parietal notch bone 0.102 0.065 0.096 0.089

10. Asterionic bone 0.109 0.049 0.105 0.069 11. Auditory torus 0.000 0.000 0.000 0.005 12. Malar tubercle 0.059 0.031 0.000 0.056 13. Os japon 0.000 0.016 0.011 0.000 14. Pterion form 0.032 0.016 0.022 0.016 15. Epiteric bone 0.161 0.179 0.211 0.181 16. Infra-orbital for. 0.045 0.108 0.036 0.112 17. Supra-orbital for. 0.199 0.323 0.274 0.257 18. Frontal for. present 0.102 0.048 0.105 0.114 19. Metopic suture 0.067 0.049 0.140 0.066 20. Mandibular torus 0.065 0.042 0.1 11 0.118 21. Mylohyoid groove 0.055 0.042 0.010 0.080 22. Mandibular torus 0.042 0.000 0.043 0.000 23. Mental foramen 0.021 0.067 0.010 0.005 24. Palatine torus 0.319 0.393 0.235 0.293 25. Acc. les palate for. 0.134 0.119 0.125 0.108 26. For. of Vesalius 0.124 0.144 0.125 0.113 27. For. ovale 0.018 0.008 0.024 0.014 28. For. spinosum 0.045 0.049 0.062 0.059 29. For. of huschke 0.062 0.137 0.219 0.046 30. Condylar facet 0.016 0.026 0.014 0.014 31. Post, condy for. 0.430 0.395 0.318 0.518 32. Precondy. tubercle 0.060 0.033 0.000 0.068 33. Anterior condy for. 0.175 0.225 0.244 0.212 34. Mastoid for. 0.836 0.860 0.907 0.830 35. Mastoid for. exsut. 0.339 0.273 0.326 0.324 36. Paramastoid process 0.194 0.278 0.254 0.163 37. Digastric groove 0.238 0.293 0.256 0.182 38. Stylomastoid for. 0.003 0.016 0.000 0.005 39. Zygo-max tuberös. 0.342 0.320 0.425 0.430 40. Zygo-facial for. 0.236 0.260 0.205 0.235 41. Ant. ethfor. ex. 0.756 0.816 0.929 0.716 42. Post ethmoid for. 0.097 0.150 0.191 0.106

Table 9. Numbers of non-metric traits for the four coalesced populations studied in Székesfehérvár during the summer of 1990

Cranial non-metric traits Tác-DunaC Rácalmás Sárbogárd Csákvár-DunaT 1. Highest nuchal line 319. 122. 102. 206. 2. Coronal ossicles 310. 112. 90. 193. 3. Ossicle at bregma 155. 54. 48. 93. 4. Sagittal ossicles 136. 47. 39. 76. 5. Ossicle at lambda 156. 56. 51. 93. 6. Lambdoid ossicles 311. 114. 100. 179. 7. Os inca 163. 62. 51. 105. 8. Parietal for. 325. 124. 102. 209. 9. Parietal notch bone 314. 123. 94. 191.

10. Asterionic bone 304. 123. 95. 189. 11. Auditory torus 327. 124. 96. 201. 12. Malar tubercle 272. 97. 64. 180. 13. Os japon 297. 123. 88. 197. 14. Pterion form 313. 123. 90. 191. 15. Epiteric bone 261. 106. 71. 149. 16. Infra-orbital for. 289. 111. 55. 178. 17. Supra-orbital for. 327. 124. 95. 206. IX. Frontal for. present 322. 124. 95. 210. 19. Metopic suture 164. 61. 50. 106. 20. Mandibular torus 275. 119. 90. 170. 21. Mylohyoid groove 275. 119. 99. 174. 22. Mandibular torus 288. 115. 94. 183. 23. Mental foramen 282. 120. 101. 185. 24. Palatine torus 144. 61. 34. 92. 25. Acc. les palate for. 232. 109. 48. 157. 26. For. of Vesalius 249. 111. 64. 142. 27. For. ovale 278. 121. 82. 148. 28. For. spinosum 286. 122. 81. 152. 29. For. of huschke 308. 124. 96. 197. 30. Condylar facet 245. 116. 71. 138. 31. Post, condy for. 256. 114. 66. 141. 32. Precondy. tubercle 134. 61. 44. 73. 33. Anterior condy for. 263. 120. 86. 151. 34. Mastoid for. 298. 121. 86. 176. 35. Mastoid for. exsut. 298. 121. 86. 176. 36. Paramastoid process 253. 115. 59 135. 37. Digastric groove 307. 116. 82. 181. 38. Stylomastoid for. 325. 124. 94. 199. 39. Zygo-max tuberös. 304. 122. 80. 193. 40. Zygo-facial for. 296. 123. 88. 196. 41. Ant. eth. for. ex. 238. 76. 28. 109. 42. Post ethmoid for. 236. 100. 47. 123.

Table 10. Measures of divergence (biological distance) between secondary population samples used in this study. Underwritten figures in italics are estimates of the variance. Al l are significant (p<.05)+ and some are very significant (p<.01 )*. Note that in the first run a number of population sample pairs

were not significant and had to be coalesced in this matrix

Samples Tác-DunaC Rácalmás Sárbogárd

Rácalmás 0.012+

0.003

Sárbogárd 0.023+

0.004

0.022+

0.006

Csákvár-DunaT 0.007+ 0.017+ 0.032*

0.002 0.004 0.005

Fig. 1. A phenogram based on the clustered distance matrix (males and females; left and right sides pooled) using the unweighted pair-group method with arithmetic averages. Low values were speci­fied to indicate corresponding distance similarities. Abscissa is scaled in relative population dis­tances

0.004 0.009 0.013 0.018 0.022 0.027 0.031 0.036 0.040

0.028 _ _

0.023

0.018

0.013

0.008 - -

0.003

0.004 0.009 0.013 0.018 0.022 0.027 0.031 0.036 0.040

Fig . 2. A stereogram of the distance value matrix plotted against the cophenetic value matrix deter­mined by arithmetic averages and the unweighted pair-group method. This cluster is done in order to test for the amount of distortion present in the cluster analysis. Correlation = 0.804

Fig. 3. A phenogram derived from the matrix of cophenetic values. When comparing with Fig. 1 , we find little distortion in this phenogram, which produces little distortion in the cluster analysis seen in Fig. 2. Abscissa is scaled in relative population distances

Fig. 4. A phenogram based on the clustered distance matrix from the coalesced samples presented in Table 10. As with Fig. 1, males and females and sides were pooled using the unweighted pair-group method with arithmetic averages. The abscissa is scaled in relative population distances

0.007 0.010 0.013 0.016 0.019 0.022 0.025 0.028 0.031

0.026 __

0.022

0.018

0.014 - -

0.010

0.006

0.007 0.010 0.013 0.016 0.019 0.022 0.025 0.028 0.031

Fig. 5 . A stereogram of the distance value matrix plotted against the cophenetic value matrix deter­mined by arithmetic averages and the unweighted pair-group method. This cluster is done in order to test for the amount of distortion present in the analysis. The correlation = 0.902

Fig. 6. A phenogram derived from the matrix of cophenetic values of the coalesced samples. When comparing this with Fig. 4, we find little distortion. The abscissa is scaled in relative population dis­tances