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Does Allen's rule rule? : a reanalysis of ecogeographic variation in modern human limb proportions Dembo, Mana 2007

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DOES A L L E N ' S R U L E R U L E ? A R E A N A L Y S I S OF E C O G E O G R A P H I C V A R I A T I O N IN M O D E R N H U M A N L I M B PROPORTIONS by Mana Dembo H o n . B . S c , The University of Toronto, 2005  A THESIS S U B M I T T E D IN P A R T I A L F U L F I L L M E N T OF T H E R E Q U I R E M E N T S FOR T H E D E G R E E OF  M A S T E R OF A R T S  in  T H E F A C U L T Y OF G R A D U A T E STUDIES  (Anthropology)  T H E U N I V E R S I T Y OF BRITISH C O L U M B I A August 2007  © Mana Dembo, 2007  Abstract In the late 1970s Derek Roberts presented the first systematic analyses o f the impact o f climate on human morphological variability. One o f his key findings was that humans follow A l l e n ' s Rule, which holds that there is a positive correlation between peripheral body part size and temperature in homeothermic species.  Roberts' conclusions regarding the applicability o f A l l e n ' s Rule to humans have been widely accepted. However, three features o f his analyses are potentially problematic. First, he used a sample that is strongly biased towards warm climates. Second, he maximized sample size o f each limb segment at the expense o f among-segment comparability. Third, he ignored the confounding effects o f phylogeny.  In this study the reliability o f Roberts' conclusions were evaluated i n relation to the aforementioned problems. In the first set o f analyses, Roberts' analyses were replicated to ensure the dataset is comparable to his. In the second, the impact o f sampling was investigated by examining the range o f variation present especially among the warm climate populations. In the third, the impact o f over-representation o f warm temperature populations was evaluated by stratifying random samples by temperature. In the fourth, stratified analyses were conducted using populations with data for all limb segments. In the  last  set  o f analyses,  the  influence  o f phylogeny  was  investigated  through  phylogenetically-controlled correlation analyses.  ii  The first set o f analyses was consistent with Roberts' conclusions indicating that the dataset is appropriate. In the second, the slope o f the regression line was variable such that both positive and negative correlations were obtained for many segments, which emphasizes the impact o f sample selection. The third set supported the idea that overrepresentation o f warm climates is problematic as only two segments yielded statistically significant correlations. In the fourth, the pattern o f limb proportion variation did not support previous analyses, suggesting that Roberts' decision to maximize sample size at the expense o f among-segment comparability is problematic. The fifth set o f analyses indicated that phylogeny has a significant impact on the results o f the correlation analyses.  Together, the results o f the analyses reported here cast doubt on the claim that humans follow A l l e n ' s Rule.  iii  Table of Contents Abstract Table of Contents List of Tables List of Figures Acknowledgements  ii iv v vi vii  Chapter 1 Introduction 1.1 Ecogeographical rules 1.2 Bergmann's and A l l e n ' s Rules in Anthropology 1.3 Problems with Roberts' analyses of modern human ecogeographic variation 1.4 A i m s of this study  1 5 7 9  Chapter 2 Materials and Methods 3.1 Data 2.2 Analyses  11 13  Chapter 3 Results 3.1 Replicating Roberts' study 3.2 Analyses of minimum and maximum correlation coefficient samples 3.3 Segment specific stratified analyses 3.4 Multi-segment stratified analyses 3.5 Phylogenetically-controlled analyses  22 22 23 24 25  Chapter 4 Discussion 4.1 Summary of the results 4.2 Reliability of the study 4.3 Implication of the results 4.3.1 Explanations for the observed morphological variation 4.3.2 Other ways of adapting to the environment  27 28 31 31 34  Chapter 5 Conclusion  39  References  42  Appendix I Anthropometric data  49  Appendix II Sources of data  59  iv  List of Tables Table 1 Anthropometric variables used in this study  12  Table 2 Results of the first set of analyses  22  Table 3 Results of the second set of analyses  23  Table 4 Results o f the third set of analyses  24  Table 5 Results of the fourth set of analyses  25  Table 6 Results of the fifth set of analyses  26  v  List of Figures Figure 1 Phylogenetic tree of lower arm random sample 1  17  Figure 2 Phylogenetic tree of lower arm random sample 2  17  Figure 3 Phylogenetic tree of lower arm random sample 3  18  Figure 4 Phylogenetic tree of lower arm random sample 4  18  Figure 5 Phylogenetic tree of lower arm random sample 5  19  Figure 6 Phylogenetic tree of foot length random sample 1  19  Figure 7 Phylogenetic tree of foot length random sample 2  20  Figure 8 Phylogenetic tree of foot length random sample 3  20  Figure 9 Phylogenetic tree of foot length random sample 4  21  Figure 10 Phylogenetic tree of foot length random sample 5  21  vi  Acknowledgements This research would not have materialized without invaluable contributions o f many people whom I would like to thank. First, I would like to thank my supervisor, Dr. Mark Collard for his guidance, support, and advice from the very beginning. I am very fortunate to have a supervisor who often goes above and beyond his call o f duty for his students.  I also wish to thank my committee advisor, Dr. David Potokylo for juggling his unbelievably hectic schedule to meet with me throughout the M A program. I am truly grateful to him for introducing me to the wonderful world of SPSS.  I am lucky to be surrounded by great minds and wonderful people. Many thanks are due to the past and present members of the Laboratory o f Biological Anthropology for their advice and help in keeping my sanity: Marina Elliott, Briggs Buchanan, Hartley Odwak, Harald Yurk, Michael Kemery, and Kimberly Casey. I would especially like to thank A l a n Cross for his advice and for making this project possible. In addition, I need to send a million emails to thank Pauline Shou and K e v i n Quan for their expertise in computer programming that made the climate data less of a nightmare.  Lastly, I would like to thank my family who has given me endless encouragement and support from half way across the country. Also many thanks are due to Anna Oh, Tom Porawski, Bobo L u i , Denise Edwards, Eric Burling, Shaun Deonarine, and Mariam Nargolwalla whose support and friendship made the life of a graduate student worthwhile.  vii  1. Introduction  1. Introduction The study reported here focused on what has become a widely accepted idea within the discipline o f anthropology, namely that the limb proportions o f modern humans follow Allen's Rule. This rule states that, i n homeothermic species, the size o f peripheral body parts correlates with temperature such that populations living i n colder climates have smaller peripheral body parts than populations living in warmer climates. The aim o f the study was to evaluate the impact o f several analytical shortcomings o f the work that underpins the consensus that modern human limb proportions follow A l l e n ' s Rule—the second edition o f Derek Roberts' 'Climate and Human Variability', published in 1978. The remainder o f this chapter provides some background to A l l e n ' s Rule and the other main ecogeographical rule, Bergmann's Rule, and anthropological work dealing with the impact o f climate on human morphological variation. The second chapter describes the data used and the analyses conducted in this study. The results o f the analyses are presented in the third chapter. The fourth chapter discusses the reliability o f results and their implications. The conclusions o f the study are presented i n chapter five.  1.1 Ecogeographical rules Ecogeographical rules are empirical generalizations that describe the correlation between aspects o f organismal morphology and features o f the physical environment. Bergmann's Rule and A l l e n ' s Rule are perhaps the best known ecogeographical rules. Bergmann's Rule states that body size o f homeothermic organisms increases as mean annual ambient temperature decreases (Bergmann 1847). A l l e n ' s Rule is an extension o f Bergmann's Rule. A s noted above, it states that in homeothermic species the size o f peripheral body parts such as limbs, ears and tails correlates positively with temperature (Allen 1877).  1  1. Introduction  Many studies have assessed the applicability o f Bergmann's Rule i n a variety o f vertebrate and invertebrate species since the appearance o f Bergmann's (1847) study (e.g. Ray 1960; Lindsey 1966; James 1970; M c N a b 1971; Zink & Remsen 1986; Geist 1987; Paterson 1990; Blackburn & Gaston 1996; Ashton et al. 2000; Ashton 2002; Y o m - T o v et al. 2002; M e i r i & Dayan 2003; Freckleton et al. 2003; Blackburn & Hawkins 2004; Y o m Tov & Y o m - T o v 2005; Rodriguez et al. 2006). Collectively, these studies suggest that Bergmann's Rules holds for the majority o f mammalian and avian species. For example, Rensch (1938) noted that upwards o f 70% o f North American bird species conformed to the predictions o f Bergmann's Rule. More recently, a meta-analysis conducted by M e i r i and Dayan (2003) found that 68 o f 94 avian species and 97 o f 149 mammalian species follow Bergmann's Rule. Fewer studies  have  assessed the applicability o f A l l e n ' s  Rule in natural  populations (e.g. Niles 1973; Stevenson 1986; Y o m - T o v & N i x 1986; Lindsay 1987; Rasmussen 1994; Fooden & Albrecht 1999; Laiolo & Rolando 2001; Cartar & Morrison 2005). These studies provide evidence that variation in the size o f peripheral body parts of some mammalian and avian species conform to the predictions o f A l l e n ' s Rule. For example, the lengths o f ear, foot and tail in five mammalian species from Australia, beak length o f Imperial Shags from South America, bill and tarsus lengths o f Chough species, and the tail length in Macaques followed the trends expected by A l l e n ' s Rule (Yom-Tov & N i x 1986; Rasmussen 1994; Laiolo & Rolando 2001; Fooden & Albrecht 1999). However, other species do not follow the rule. For example, Stevenson (1986) found that the ear and tail lengths o f hares and the hind limb lengths o f hares and rabbits o f North America do not vary i n the manner predicted by the rule.  2  1. Introduction  Thermoregulation is usually cited as the mechanism producing the patterns described by Bergmann's and A l l e n ' s Rules (e.g. Weaver & Ingram 1969; Riesenfeld 1973; Baker 1988; Frisancho 1993). In homeothermic species, the maintenance o f body heat is vital for proper organ function (Baker 1988; Frisancho 1993; Parsons 2003). The maintenance o f body heat equilibrium involves basal metabolic rate, mechanical work done by the body and heat transferred into and out o f the body v i a conduction, convection, radiation and evaporation through the skin surface (Frisancho 1993; Parsons 2003). Since body heat is generated through the process o f metabolic energy conversion needed to support the mechanical work done by the muscles o f the body, heat production is proportional to the amount o f muscle and fat within the body (Baker 1988; Frisancho 1993; Parsons 2003). Therefore, heat production is largely a function o f body mass (Baker 1988; Frisancho 1993; Parsons 2003). In contrast, heat loss is largely dependent on the surface area o f the skin (Baker 1988; Frisancho 1993; Parsons 2003). The relationship between surface area and volume is such that increasing body size and reducing limb length results in a reduction in relative surface area, while decreasing body size and increasing limb length has the opposite effect. Hence, individuals who live in cold environments are expected to have been selected to have larger bodies and shorter limbs than conspecifics living i n warmer environments. Not all researchers accept the idea that thermoregulation drives Bergmann's and A l l e n ' s Rules. It has been argued that there are other ways to maintain body heat that are more efficient than altering body sizes and proportions, including increasing body insulation and altering vascular controls (Scholander 1955, 1956; Irving 1957; M c N a b 1971; Geist 1987). Skeptics o f the thermoregulation hypothesis have also pointed out that  3  1. Introduction many ectothermic species such as insects, fish, and lizards, also exhibit patterns of body size variation consistent with Bergmann's Rule (Ray 1960; Lindsey 1966; Cushman et al. 1993; Van Voorhies 1996; Mousseau 1997). These researchers contend that thermoregulation cannot explain the pattern observed in ectotherms since the maintenance of internal body heat equilibrium is not as vital in cold-blooded organisms as it is in warm-blooded species. Therefore, the pattern observed in homeotherms is unlikely to be due to heat conservation and dissipation. Several alternative mechanisms have been proposed to explain Bergmann's Rule. Rosenzweig (1968) and Kolb (1978) have suggested that body size correlates better with food availability in the environment than temperature. Fewer species are capable of surviving in the harsher environmental conditions of higher latitudes. Therefore, there are greater opportunities for niche exploitation in such environments. Although the amount of primary productivity may be lower in higher latitudes, there are fewer species to exploit it. Thus, those that are able to persist in the environment have access to more resources, which may lead to the attainment of larger body sizes as observed. There may be another advantage to large body size in harsher environments, namely larger body mass increases starvation resistance (Calder 1984; Lindstedt & Boyce 1985). This would favour selection for larger body sizes in higher latitudes where resources are seasonally scarce and unpredictable year to year. A further possibility is that the pattern of body size variation may reflect the dispersal ability of organisms. Large body mass is associated with higher dispersal ability (Blackburn et al. 1999). Therefore, small bodied species are under-represented in the higher latitudes because they cannot disperse to exploit those niches as frequently as larger bodied species. A fourth possibility is that higher latitude  4  1. Introduction  populations may have larger body masses because their ancestors happened to be larger by chance (Blackburn et al. 1999). These ancestral populations could have subsequently given rise to generations o f organisms that are larger simply by descent. Lastly, it is possible that Bergmann's Rule could be due to linkage disequilibrium. That is, the pattern could be due to natural selection acting not on body size but on a trait that is linked to it (Blackburn et al. 1999). It has been argued that there need not be a single mechanism that applies to all taxa (Blackburn et al. 1999). There could be one mechanism for ectotherms and another for homeotherms. Moreover, various mechanisms could possibly interact to produce the pattern predicted. A certain mechanism, such as altering body sizes and proportions, may not necessarily be the most efficient in terms o f thermoregulation. However, as long as it confers a slight advantage, natural selection could potentially favour that unique trait. Therefore, even i f body insulation and altered vascular controls are more efficient for thermoregulation, an organism with thick fur, decreased peripheral circulation, and larger body size with relatively shorter limbs could have higher fitness than the one with only thick fur, and decreased peripheral circulation (Mayr 1956: emphasis added). The cause o f the patterns described by Bergmann's and A l l e n ' s Rules could potentially be a complex interplay o f various factors o f phylogeny, physiology and ecology.  1.2 Bergmann's and Allen's Rules in Anthropology The first person to propose that Bergmann's and A l l e n ' s Rules might apply to modern humans appears to have been W i l l i a m Ridgeway. In his presidential address at the 1908 meeting o f British Association for the Advancement o f Science, Ridgeway argued that Homo sapiens can be expected to follow ecogeographical rules like the rest o f the animal  5  1. Introduction  kingdom. Given that humans are the most widely distributed species in the animal kingdom, H. sapiens has been subjected to greater extremes o f temperature than any other mammalian species. Subsequent to Ridgeway's lecture, many studies have been conducted in which the morphology o f humans and their fossil relatives has been analyzed with respect to climate. Several researchers have focused on body weight and its correlation with ambient temperature to demonstrate Bergmann's Rule in human populations (Schreider 1950, 1957, 1964; Roberts 1953; Katzmarzyk & Leonard 1998). Others have studied limb proportions and climate to provide evidence for A l l e n ' s Rule in humans and other hominins (e.g. Newman 1953; Hiernaux & Froment 1976; Roberts 1978; Trinkaus 1981; Macho & Freedman 1987; Ruff 1991, 1993, 1994, 2002; Holliday 1997a, 1997b, 2006; Weinstein 2005). Today, these ecogeographical rules are widely considered to be supported by robust empirical evidence. This consensus is so wide spread among anthropologists that they are routinely taught in introductory biological anthropology classes as examples o f climatic adaptation in human evolution (Boaz & Almquist 1999; Jurmain et al. 2003; Jurmain et al. 2004; Stanford et al. 2006). These rules are often demonstrated in a photograph o f an Inuit alongside an equatorial African to show the marked differences in human body morphology (Jurmain et al. 2003; Jurmain et al. 2004; Stanford et al. 2006). O f the numerous  studies  dealing with the  impact o f climate on  human  morphology, by far the most influential are Derek Roberts' 1953 article ' B o d y weight, race, and climate' and his 1978 book 'Climate and Human Variability'. In the former, Roberts reported analyses that he interpreted as demonstrating that modern humans follow Bergmann's Rule. Colder climate populations had relatively larger body weights  6  1. Introduction than warmer climate populations that generally had relatively lower body weights. In his 1978 volume, Roberts analyzed numerous anthropometric variables from globally distributed populations and studied bivariate correlations with mean annual temperature. Roberts found strong positive correlations with the limb segment lengths and mean annual temperature.  Populations from colder climates had relatively shorter  limb  segments and conversely, populations from warmer climates had relatively longer limbs. Roberts concluded from these findings that modern humans follow A l l e n ' s Rule as well as Bergmann's Rule. Together, Roberts' (1953, 1978) works established the consensus that human morphology has been selected with respect to climate. In the last 30 years, numerous authors have referenced Roberts' works in the discussion o f Bergmann's and A l l e n ' s Rules to modern humans and fossil hominins (e.g. Trinkaus 1981; Austin & Lansing 1986; Macho & Freedman 1987; Hanna et al. 1989; Stinson 1990; Ruff & Walker 1993; Ruff 1991, 1993, 1994, 2002; Shea & Bailey 1996; Holliday 1997a, 1997b, 2006; Katzmarzyk & Leonard 1998; Bogin & Rios 2003; Jurmain et al. 2003; Stanford et al. 2006). More recently, Katzmarzyk and Leonard (1998)'s study has confirmed Roberts' conclusions and the validity o f these rules.  1.3 Problems with Roberts' analyses of modern human ecogeographic variation Notwithstanding the fact that Roberts' (1978) conclusions have been widely accepted within anthropology, there are several reasons to be skeptical about his conclusions. First, the samples he used are dominated by warm-climate populations. It is possible that the skewed distribution in favour o f one climatic region over others may have biased the  7  1. Introduction results o f his correlation analyses. Although the issue o f over-representation in such correlation analyses has been raised by some (e.g. Hiernaux & Froment 1976), no study to date has corrected for this problem. Second, the range o f variation within Roberts' warm-climate populations is almost as great as the range o f variation in the entire sample. A s it was reported in Roberts' (1978), some populations between 70-80°F fall well below the regression line. In fact, there are warm-climate populations with shorter relative span than some coldclimate populations. The wide range o f variation in warm climates in and o f itself indicates that human limb proportion variation cannot be explained by temperature differences alone. A third problem with Robert's (1978) study is that he maximized sample size o f each limb segment by using different subsets o f populations for each segment. Roberts (1978) recognized that this sampling practice is problematic. He warned that only the pattern o f correlation, not the actual values o f the correlations, is significant since the correlation coefficients for the various segments cannot be compared. However, the notion that he used different samples for different segments, comparing the patterns of correlation is no more appropriate than comparing the correlation coefficients. More problematical still, it is possible that the significant correlations are i n fact artifacts o f the sampling procedure. If populations adapted differently to the same climatic regime (e.g. one population may have evolved relatively long lower limb segments while another has evolved relatively long upper limb segments), the use o f different subsamples may produce spurious correlations. The current study does not address this possibility. However, it would be an interesting topic to investigate in the future.  8  1. Introduction A fourth problem with Roberts' (1978) study is that he did not address the potentially confounding effects o f phylogeny in his comparative analyses. Comparative studies o f limb length using simple correlation analysis assume that data points are independent o f one another (Felsenstein 1985; Harvey & Pagel 1991). However, because all organisms are related to one another, this is a potentially major flaw. Phylogenetic relationships lead to non-independence o f data points. When data points o f closely related populations are treated as independent data points, it may lead to a pseudoreplication o f data. Pseudoreplication is more likely to produce statistically significant results because the degrees o f freedom w i l l inevitably be larger than when the phylogenetic relationship between data points is considered (Felsenstein 1985). Thus, population history must be considered when investigating morphological variations with respect to climate. The underlying premise is that closely related populations tend to be more similar than distantly related populations due to the more recently shared ancestry. Therefore, this may give rise to the morphological pattern observed, which could be driven by genetic propinquity, not by climatic adaptation.  1.4 Aims of this study With the foregoing i n mind, this study reinvestigates the validity o f Roberts' (1978) conclusion that A l l e n ' s Rule is applicable to modern human populations. The impact o f sample choice w i l l be assessed by employing various sampling strategies. The impact o f Roberts' failure to correct for phylogeny w i l l be investigated by carrying out correlation analyses in which the phylogenetic relationships among populations are taken into  9  1. Introduction account. If humans do indeed follow A l l e n ' s Rule, then all o f the analyses should return correlations between temperature and limb segment size that are positive and significant.  10  2. Materials and Methods  2. Materials and Methods 2.1 Data The morphological data were compiled from published anthropometric  studies o f  populations in Africa, Eurasia, Oceania and the Americas. Populations were limited to the groups discussed i n Outline of World Cultures (Murdock 1976), History and Geography of Human Genes (Cavalli-Sforza et al. 1994) American Indian Languages (Campbell 1997) and Ethnologue (Gordon 2005). To be included in the sample, groups had to be distinguished by dialectical differences. Comparisons o f first and second generation migrants indicate that environment can have a major impact on morphology via phenotypic plasticity as well as by means o f natural selection (Boas 1912; Shapiro & Hulse 1939; Harrison 1988). Thus, i n order to avoid introducing another source o f variability, only populations that have existed in their current location since 1492 were used. Individuals reported i n the original studies to be o f mixed ancestry were excluded from the dataset. Since Roberts (1978) used males in his study investigating limb proportions, only adult males were considered here. A n individual was considered to be adult i f they were 17 or older at the time o f the data collection. Data were used i f the sample size o f the population exceeded 10 individuals, and the sex o f the individuals was stated. Variables for which values were collected include: stature, upper arm length, lower arm length, hand length and width, upper leg length, lower leg length, and foot length and width. Definitions o f these variables are presented in Table 1. Descriptions o f the landmarks and methods o f measurement can be found in standard anthropometric texts (e.g. Hrdlicka 1947; Weiner & Lourie 1969). In order to counter the confounding  11  2. Materials and Methods  effects o f body size differences, relative segment measurements were used in all o f the statistical analyses. These were obtained by dividing each o f the segment values by the stature o f the individuals i n question.  Variable  Definition  Stature  the superior point of the head to the ground  Upper arm length  the humeral head to the olecranon process of the ulna  Lower arm length  the olecranon process to the distal ulnar stylus  Hand length Hand width  the midline connecting the proximal limits of the hypothenar and thenar eminences of the palm to the tip of the third digit across the distal ends of the metacarpals  Upper leg length  the greater trochanter of the femur to the tibial plateau  Lower leg length  the tibial plateau to the distal malleolus of the tibia  Foot length  the back of the heel to the longest toe  Foot width  the maximum horizontal distance perpendicular to its longest axis wherever it is found across the foot  Table 1. Anthropometric variables used in this study Geospatial coordinates were obtained from the original sources i f provided by the investigators. In most cases, however, only the location o f the study site was reported. In such cases, any information given on the location (e.g. topographic description o f the site of study, village names or maps) was used to obtain latitude and longitude from Geographic and Geospatial Information (Borseth 2006). If the data were compiled from populations sampled from multiple locations, the arithmetic means o f the latitude and longitude o f all o f the sites were calculated and taken as the geospatial coordinates. In a few cases where the national mean measurements were used, such as for the Italians or  12  2. Materials and Methods  Czechs, no information on specific sites o f investigation was given. In these cases, the geospatial coordinates for the capital city o f that country were used. Mean annual temperature data was obtained from the Climate Research Unit's Global Climate Database (New et al. 1999). This database contains the mean monthly temperature from the period o f 1961 to 1990 for 12,092 locations worldwide. The closest meteorological station to the site o f investigation was determined based on the geospatial information. Mean annual temperature was calculated from the mean monthly data given for the meteorological station. Given that the mean monthly temperature data from the meteorological station is the average o f a thirty year period, the climatic data and the geospatial coordinates should not be potential sources o f error. The anthropometric and temperature data are provided i n Appendix I. A list o f relevant sources is presented in Appendix II.  2.2 Analyses Five sets o f analyses were conducted. The aim o f the first set was to confirm that the sample is suitable to evaluate the potential shortcomings o f Roberts' (1978) study. In this analysis, only groups with sample sizes greater than 20 individuals were included. The sampled groups did not necessarily have all o f the limb segment data. Bivariate correlations were calculated for all o f the limb segments and mean annual temperature. The analyses were conducted in SPSS version 12.0 (SPSS Inc, Chicago I L L ) . The goal o f the second set o f analyses was to examine the range o f variation in limb segment lengths and widths among the sampled populations. The minimum and maximum correlation coefficients for each segment were generated by selecting a maximum o f three populations from every 2.5°C increment in mean annual temperature  13  2. Materials and Methods  to either minimize or maximize the slope o f the regression line. For the minimum coefficient, the slope o f the regression line was minimized by selecting populations with the longest relative segment lengths from the colder climates, and the populations with the shortest relative segment  lengths from the warmer climates. Conversely, the  maximum coefficient was calculated by selecting populations with the shortest relative segment lengths from the colder climates and populations with the longest relative segment lengths from the warmer climates. The colder climate represents areas with mean annual temperature below 15 °C and the warmer climate represents areas with mean annual temperature equal to and above 15 °C. Again, the analyses were conducted in SPSS. The third set o f analyses investigated the impact o f the over-representation o f warm-climate populations. This was accomplished by stratifying samples on the basis o f mean annual temperature. Each anthropometric variable was analyzed separately to maximize the size o f the samples. Sample sizes ranged from 28 populations (upper leg length) to 45 populations (hand length). Mean annual temperature was divided into 2.5°C increments and a maximum o f three populations were randomly selected from each temperature category. Five random stratified samples were drawn for each limb segment. In order to maximize sample size, the minimum number o f individuals per sample was reduced to 10 individuals. These analyses were also conducted i n S P S S . The fourth set o f analyses assessed the impact o f Roberts' decision to maximize sample size at the expense o f among-segment comparability. Only populations with all o f the anthropometric variables were used. T o ensure equal representation from all o f the temperature ranges, five stratified samples were randomly generated according to mean  14  2. Materials and Methods annual temperature. In order to maximize sample size, the mean annual temperature was divided into 5°C categories. From each mean annual temperature category, a maximum o f three groups were randomly sampled. The stratified samples consisted o f 14 populations each. Using the mean annual temperature and the relative segment lengths and widths, correlation coefficients were calculated in SPSS. The  fifth  set o f analyses investigated the potential confounding effects o f  phylogeny. The populations were stratified based on mean annual temperature for every 2.5 °C and a maximum o f three populations were selected from each temperature category. Five random samples were generated and then analyzed using the program Comparative Analysis by Independent Contrast ( C A I C ) version 2.6.9 (Purvis & Rambaut 1995). C A I C was used to calculate 'independent contrasts'  at every node o f the  phylogeny. Independent contrasts measure the change in limb segmental lengths and widths along each branch o f the phylogenetic tree. The contrasts are calculated as the differences i n trait X between two sister taxa divided by the variances i n the trait X o f these taxa and the time elapsed since the divergence o f these two sister taxa (Felsenstein 1985). Each contrast is divided by its standard deviation. B y performing the above calculations, these contrasts are drawn independently from a bivariate normal distribution (Felsenstein 1985). Thus, even when the taxa analyzed are part o f a nested hierarchy, these independent contrasts can be calculated from a known phylogeny and used in correlation and regression analyses. C A I C requires a fully resolved cladogram. The primary phylogenetic tree used i n these analyses is the average linkage tree published in Cavalli-Sforza et al. (1994:78).  15  2. Materials and Methods This is a phylogenetic tree based on genetic distances (F T ) calculated from 120 allele S  frequencies o f 42 populations worldwide. Not all groups used in the analyses were included i n Cavalli-Sforza et al.'s (1994) study. The missing groups were included by using subsets o f regionally specific genetic analyses as reported by Cavalli-Sforza et al. (1994), and the linguistic associations reported in Campbell (1997) and Gordon (2005) to produce fully resolved trees. The resulting trees are depicted in Figures 2-11, and were drawn using Mesquite 1.06 (Maddison & Maddison 2005). C M C offers two models o f data analysis: ' C R U N C H ' and ' B R U N C H ' . These models differ on the assumptions made in the evolutionary model used to estimate evolutionary change. C R U N C H uses each value entered for a taxon to calculate an independent contrast between two sister taxa and in turn, uses those values to estimate the values for higher nodes. In contrast, B R U N C H uses the values only once, and thus calculates only half as many contrasts as the number o f taxa (Purvis & Rambaut 1995). The B R U N C H algorithm is designed for use in studies in which a continuous variable is regressed against a discrete variable (Purvis & Webster 1999). The authors o f C A I C recommend that C R U N C H should be used for continuous data (Purvis & Rambaut 1995). Therefore, since this study involves only continuous variables, the C R U N C H model was used. Furthermore, it was assumed that all branches were o f equal lengths. The results o f the second set o f analyses, segment-specific stratified samples indicated that lower arm length and relative foot length correlate significantly with mean annual temperature i n all o f their respective five random samples. Thus, the influence o f phylogeny was investigated using these samples. Regression analyses were performed and the R , R and P values were obtained using C A I C .  16  2. Materials and Methods  Figure 1. Phylogenetic tree of random sample 1 used in the analysis of lower arm segment  T  Figure 2. Phylogenetic tree of random sample 2 used in the analysis of lower arm segment  17  2. Materials and Methods  Figure 3. Phylogenetic tree of random sample 3 used in the analysis of lower arm segment m to  ~  ra  <a  Figure 4. Phylogenetic tree of random sample 4 used in the analysis of lower arm segment  18  2. Materials and Methods  Figure 5. Phylogenetic tree of random sample 5 used in the analysis of lower arm segment  Figure 6. Phylogenetic tree of random sample 1 used in the analysis of foot length  *. I  9> £ 8 o o O 0 c n> <» 2 f 2. 5 -g I a _ a I 5 o § | S "5 2 o1 3 to s 3 m £ .2 co < o a ce t « s << 3^ g 3> <* Q a i < ? _ j u j O ^ : h - u - t o oo >oi < < J 2 ' s w x z o S 5 N S o c f l _ ) O X O Q . o s  ffl  c  ;  _LJJ  11 I  UL] I^JLJ jLLjJ  19  a o> m  2. Materials and Methods  Figure 7. Phylogenetic tree of random sample 2 used in the analysis of foot length co ~  -o IB  a.  5 .._ ow  S a £  o^ a  ra .2 cu » a o  uuu u  TO w  5 X 5 » S « c a -2 o ^ til r  § § X z to a.  >*  r£  Jr  -KJ  < o o >-  u Ul S  TO  Figure 8. Phylogenetic tree of random sample 3 used in the analysis of foot length  20  CQ  <  2. Materials and Methods Figure 9. Phylogenetic tree of random sample 4 used in the analysis of foot length  Figure 10. Phylogenetic tree of random sample 5 used in the analysis of foot length  8 !»*  co  a = c  1  § -  m m j  I 15 8 €  2 I  3 B  - - a o  Jd 3  <u — 2  3  O  ^ o £  W  1 <  oS ~  § 5 « » * o « i z O < Q . X ( °» o5 5&z Sw x a 3 Z  3 § c _i §- -g 8 2 05  UJUULJLJJ |LLJJUUJ  5  e  UJ U  3  21  3. Results  3. Results 3.1 Replicating Roberts' analyses The results o f the first set o f analyses are summarized in Table 2. Most o f the variables show a trend o f increasing lengths in warmer climates, as predicted by A l l e n ' s Rule. Relative upper arm, lower arm, upper leg, and foot lengths all correlate positively with mean annual temperature at a significance level o f  P=0.01. Relative foot width also  shows a positive correlation with mean annual temperature,  with the correlation  significant at the P=0.05 level. However, two variables—hand length and width—do not show a trend o f increasing lengths in warmer climates. Thus, the results o f the first set o f analyses are generally consistent with those obtained by Roberts (1978), although there are some differences like the hand length and width.  Variable Upper arm length Lower arm length Hand length Hand width Upper leg length Lower leg length Foot length Foot width  Sample size 130 132 204 157 69 70 125 111  Pearson's r .246 (**) .435 (**) -.097 -.114 .342 (**) .157 .458 (**) .216 (*)  Table 2. Results of the first set of analyses. Single asterix (*) indicates statistical significance at 0.05 level (two-tailed). Double asterix (**) indicates statistical significance at 0.01 level (two-tailed). 3.2 Analyses of minimum and maximum correlation coefficient samples The maximum correlation coefficients yielded strongly positive correlations with mean annual temperature for all segments (see Table 3). With the exception o f hand width and upper leg length, all o f the variables achieved statistical significance at P=0.01. Upper leg  22  3. Results length achieved statistical significance at P=0.05. Hand width did not yield a statistically significant positive correlation i n the maximum coefficient analysis. In the minimum coefficient analysis, a negative trend resulted i n six o f the eight segments. Hand length and hand width were negatively correlated at P=0.01 and upper arm length and foot width achieved negative correlations significant at P=0.05.  Variable Upper arm length Lower arm length Hand length Hand width Upper leg length Lower leg length Foot length Foot width  Sample size 36 37 45 41 28 33 41 36  Minimum R -.355(*) .104 -.604(**) -.729 (**) -.157 -.201 .032 -.404 (*)  Maximum R .561 (**) .785(**) .505 (**) .222 .446(*) .453(**) .627(**) .556(**)  Table 3. Results of the second set of analyses. Single asterix (*) indicates statistical significance at 0.05 level (two-tailed). Double asterix (**) indicates statistical significance at 0.01 level (two-tailed).  3.3 Segment specific stratified analyses The third set o f analyses investigated the potential problem o f over-representation o f warm-temperature populations, the results o f which are presented i n Table 4. When the samples were stratified, a significant correlation was observed only i n the relative lower arm length and relative foot length i n all five random samples at the P=0.01 level. A positive correlation between relative foot width with mean annual temperature was significant i n four o f the five random samples at the P=0.01 level. A positive trend following A l l e n ' s Rule was observed i n relative upper arm, relative upper leg and relative lower leg lengths, but none o f these correlations were statistically significant even at  23  3. Results  P=0.05. The correlation coefficients o f the relative lower leg lengths were only slightly positive in three analyses. Relative hand length and width were negatively correlated with mean annual temperature, and i n one sample the correlation was statistically significant at the P=0.05 level.  Sample 1  Sample 2  Sample 3  Sample 4  Sample 5  Upper arm length  Sample size 36  .210  .212  .160  .201  .052  Lower arm length  37  .638 (**)  .466 (**)  .518 (**)  .572 (**)  .588 (**)  Hand length  45  -.142  -.218  -.336 (*)  -.090  -.210  Hand width  41  -.271  -.208  -.337 (*)  -.167  -.256  Upper leg length  28  .149  .223  .243  .293  .222  Lower leg length  33  .078  .098  .080  .247  .292  Foot length  41  .531 (**)  .469 (**)  .467 (**)  .443 (**)  .455 (**)  Foot width  36  .435 (**)  .402 (*)  .351 (*)  .215  .343 (*)  Variable  Table 4. Results of the third set of analyses. Single asterix (*) indicates statistical significance at 0.05 level (two-tailed). Double asterix (**) indicates statistical significance at 0.01 level (two-tailed).  3.4 Multi-segment stratified analyses The results o f the correlation analyses using the populations with data for all eight variables are presented in Table 5. In all five random samples, relative upper leg length and relative foot width followed the patterns predicted by A l l e n ' s Rule. However, these patterns were not all statistically significant. The correlation for relative foot length was significant at P=0.05 level in two o f the five samples.  Relative lower arm length, hand 24  3. Results  width, lower leg length and foot length were even more sensitive to the composition o f the random samples, as the correlations were both negative and positive in the five random samples. Relative upper arm length, hand length and hand width were always negatively correlated with mean annual temperature, which opposes the pattern predicted by A l l e n ' s Rule. Hand length was statistically significant at P=0.05 in one o f the five samples. Thus, the results o f this set o f analyses were not compatible with Roberts' (1978) findings.  Variable Upper arm length Lower arm length Hand length Hand width Upper leg length Lower leg length Foot length Foot width  N 13 13 13 13 13 13 13 13  Sample 1 -.144 -.022 -.336 -.317 .384 .007 -.159 .254  Sample 2 -.246 .089 -.291 -.002 .430 -.092 .045 .566 (*)  Sample 3 -.083 .032 -.420 -.269 .456 -.098 .112 .447  Sample 4 -.006 -.078 -.442 -.070 .415 -.049 .087 .673(*)  Sample 5 -.166 .193 -.630(*) -.364 .518 .148 .081 .172  Table 5. Results of the fourth set of analyses. Single asterix (*) indicates statistical significance at 0.05 level (two-tailed). 3.5 Phylogenetically-controlled analyses Regression analyses on relative lower arm and relative foot lengths were conducted using independent contrasts with mean annual temperature using C A I C . To reiterate, these segments were selected because they were significantly correlated with mean annual temperature at P=0.01 i n all random samples in the third set o f analyses. The correlation coefficients, R and P values from SPSS and C A I C for relative lower arm length and 2  relative foot length are presented in Table 5. When the phylogenetic relationships were  25  3. Results  taken into account, the correlations became insignificant i n a l l five o f the foot length samples and three o f the five lower arm length samples.  Lower arm length  Foot length  Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample  1 2 3 4 5 1 2 3 4 5  R  Standard R  P  0.638 0.466 0.518 0.572 0.588 0.531 0.469 0.467 0.443 0.455  0.407 0.217 0.269 0.327 0.346 0.282 0.220 0.218 0.196 0.207  0.000 0.004 0.001 0.000 0.000 0.000 0.002 0.002 0.004 0.003  2  Independent Contrasts R P R 0.188 0.230 0.202 0.511 0.445 0.178 0.075 0.058 0.079 0.297  0.035 0.053 0.041 0.261 0.198 0.032 0.006 0.003 0.006 0.088  0.295 0.183 0.260 0.002 0.009 0.299 0.651 0.729 0.633 0.079  Table 6. Results offifthset of analyses. Standard = correlation coefficients produced by regular analyses. Independent contrasts = correlation coefficients produced by independent contrasts. Single asterix (*) indicates statistical significance at 0.05 level (two-tailed). Double asterix (**) indicates statistical significance at 0.01 level (twotailed).  26  4. Discussion  4. Discussion 4.1 Summary of results The results o f the first set o f analyses were generally consistent with those obtained by Roberts (1978). They indicate that the size o f most limb segments is positively and significantly correlated with mean annual temperature. This suggests that the dataset is suitable to evaluate the impact o f the shortcomings o f Roberts' analyses. The results o f the second set o f analyses indicated that variation among the populations is so great that the strength o f correlation, the pattern o f correlation, and the statistical significance o f the correlations are all dependent on which populations are chosen for analysis. This suggests that Roberts' finding o f a positive correlation between limb length and temperature is sample specific. The results o f the third set o f analyses indicate that Roberts' finding o f a positive correlation between limb length and temperature is largely due to the overrepresentation o f warm-climate populations in his sample. When the data for each segment were stratified by mean annual temperature, only two limb segments produced statistically significant positive correlations. The results o f the fourth set o f analyses also suggest that Roberts'  finding  o f a positive correlation between limb length and  temperature is due in large part to the over-representation o f warm-climate populations in his sample. When only populations with data for all limb segments were analyzed and the warm-climate bias was taken into account, only two o f the eight variables yielded positive correlations with temperature,  and none  consistently achieved statistical  significance. The results o f the fifth set o f analyses suggest that Roberts' findings are not only sample specific, but also undermined by data point interdependence.  When  phylogenetic effects were removed, the correlation remained significant in only two o f  27  4. Discussion  the 10 random samples. Overall, the results o f the study strongly suggest that Roberts' findings are invalid. This i n turn casts doubt on the idea that modern humans follow A l l e n ' s Rule.  4.2 Reliability of the study One o f the potential shortcomings o f this study concerns the size o f the samples used in the third and fourth sets o f analyses. In order to correct for the problem o f overrepresentation o f warm-climate populations, the samples were stratified on the basis o f mean annual temperature. Due to a shortage o f data for cold-climate populations, the stratified sampling reduced sample sizes to 28-45 in the third set o f analyses. The sample size was further reduced to 13 populations in the fourth set o f analyses. However, as the results o f the third set o f analyses indicated, the problem o f over-representation o f warmclimate populations is significant. Thus, stratified sampling o f populations at the expense of reduced sample size was necessary. Furthermore, in a study reported by Trinkaus (1981), limb length variability was analyzed using only 13 populations. Given that Trinkaus (1981) is often cited as a reliable source regarding hominin morphological variation and climate (e.g. Ruff 1991, 1994; Holliday 1997a, 1997b), the small sample size used in the third and fourth sets o f analyses should not undermine the results o f this present study. A second potential shortcoming o f this study is the use o f anthropometric data only from male individuals. Froment and Hiernaux (1984) suggest that there may be a differential response i n morphology to climatic variation between the sexes. These authors investigated morphological variation among 10 African populations living along  28  4. Discussion  the Niger River i n two ecological zones. Some populations were classified as Sahelian, and others as Sudanian. The Sahelian populations live in the dry environment o f the Sahel Desert, while the Sudanian populations live in environments with greater moisture content south o f the Niger River bend. Various anthropometric measurements such as limb segment lengths and facial dimensions were taken on male and female subjects. Although this study was limited in geographical scope, the authors reported that the Sahelian populations had significantly longer lower limbs, lower arms, larger hands and narrower faces (Froment & Hiernaux 1984). These were hypothesized to be adaptations to the drier environments characterized by higher peaks o f heat than their Sudanian neighbours. However, this pattern was only observed in the female subjects. The limb proportion variation i n males did not produce a significant correlation with climatic variables. A m o n g the males, the only significant correlation was in the dimensions o f the ear. Thus, it is possible that different results would have been obtained i f values for females had been included. However, given that all o f the correlations related to limb segments reported by Roberts (1978) were based on males, the exclusion o f female individuals from this study should not undermine the results presented here. Another potential criticism also concerns the dataset used i n this study. Since Roberts did not provide a list o f the sources o f anthropometric data he employed, it was not possible to use exactly the same sample o f populations. However, as the results o f the first set o f analyses indicate, most o f the limb segments produced correlation coefficients and P-values comparable to those obtained by Roberts. This suggests that the dataset used here is comparable to his. However, unlike Roberts' study, relative hand length and width yielded negative correlations, albeit they were statistically insignificant. One likely  29  4. Discussion  explanation for this difference is that this study incorporated more data on the dimensions of the hand than did Roberts. In addition, the bulk o f the data were published after Roberts' study. A s Katzmarzyk and Leonard (1998) have noted, it is possible that more recent data could reflect the secular changes that have been documented in various populations. However, it seems unlikely that the impact o f secular changes in the last 30 years would be great enough to mask the effects o f thousands o f years o f climatic adaptation. A s a case in point, consider Katzmarzyk and Leonard's (1998) study. Their analyses still supported Bergmann's Rule even though they found evidence o f secular changes. Thus, it seems reasonable to conclude that the dataset is appropriate for the purposes o f this study and that discrepancies between the two sets o f results are mainly due to the problems with Roberts' study. The fourth potentially problematic issue is the phylogenetic trees used in the last set o f analyses. The trees in question were primarily based on genetic distance tree published by Cavalli-Sforza et al. (1994). However, the resolution o f the genetic tree was not good enough to accommodate all o f the populations used in the analyses. Thus, modifications to the genetic distance tree were made by incorporating information on the linguistic affinities o f various populations (Murdock 1976; Greenberg 1987; Campbell 1997; Gordon 2005). Unfortunately, there is considerable debate surrounding linguistic affiliations in some regions o f the world. The use o f molecular genetics has helped resolve some problematic cases (Renfrew 2000). For example, molecular data have supported the validity o f the existence o f various suggested linguistic phyla such as the existence o f Hokan and Penutian linguistic phyla in North A m e r i c a (Eshleman et al. 2004). However, i n other cases there is still some uncertainty (e.g Ruhlen 2000; Torroni  30  4. Discussion  2000). W i t h this i n mind, I chose to incorporate interpretations that seem to be accepted by the majority o f researchers, such as the recognition o f the Hokan linguistic group as a valid and distinct group from the Penutian family i n the Amerind linguistic phylum (e.g. Greenberg 1987; Campbell 1997; Eshleman et al. 2004). While it is possible that my combined genetic/linguistic phylogenetic trees may not be entirely accurate, it seems unlikely that the errors are sufficiently numerous to undercut the results. Thus, the results of the phylogenetically-controlled analyses should not be undermined by the uncertainties of the phylogenetic trees used.  4.3 Implications of the results The results o f the present study suggest that, contrary to what Roberts (1978) concluded, variation in limb proportions in modern humans does not correspond to changes in mean annual temperature as predicted by A l l e n ' s Rule. This raises two questions. First, i f variation in modern human limb proportions is not linked to thermoregulation, what drives it? Second, i f not through changing limb proportions, how do humans respond to various climates?  4.3.1 Explanations for the observed morphological variation The only climatic factor addressed i n this study was mean annual temperature. This variable was chosen because it was used by Roberts (1978). However, it is possible that the human morphology has been selected in relation to other environmental factors. Froment and Hiernaux's (1984) study suggests that moisture content o f the air may be important. It has been noted that the perspiration is the most effective method o f lowering body temperature in hot, dry environments (Baker 1988). Thus, it would be valuable to  31  4. Discussion  further investigate the relationship between human limb proportion variation and other factors o f the environment such as aridity, precipitation, and available net primary and secondary productivity to infer diet. These environmental factors may have stronger explanatory power for human limb proportion variation than temperature. The fifth set o f analyses indicated that phylogeny, which has heretofore never been investigated in relation to limb proportion variation and climate, has a significant impact on human morphology. This suggests that modern human limb proportions may simply reflect the population history o f H. sapiens. Some support for this hypothesis comes from analyses o f mitochondrial D N A . Europeans, Asians and the indigenous inhabitants o f the Americas exhibit much less m t D N A variability than Africans (Cann et al. 1987). This pattern is thought to be the result o f founder effect (Cann et al. 1987). A s a type o f genetic drift, founder effect involves changes in allele frequencies occurring as a result o f a non-selective process. In this case, the change in allele frequencies occurs due to a daughter population being a small non-representative sample o f its parent population (Mayr 1963). Recent studies by Manica et al. (2007) and Weaver et al. (2007) suggest that the founder effect has played a role in shaping human cranial diversity. With this in mind, it is worth considering the possibility that founder effect has shaped the variability in limb proportions among human populations. It is possible that as groups migrated out o f Africa to inhabit various parts o f the world, limb proportion variation became progressively more limited. The populations that migrated out o f Africa and settled in A s i a would represent the initial reduction in limb proportion diversity. A s groups moved from A s i a into the Americas and the Pacific, the variation in limb proportion would be further reduced due to founder effect. Thus, it is possible that the repeated impact o f the  32  4. Discussion  founder effect in various parts o f the world such as Eurasia, Oceania, and the Americas may underlie the observed limb proportion variability in modern humans. Another possibility is that the limb proportion variation reflects the phenotypic plasticity o f modern humans. Phenotypic plasticity refers to the ability o f a genotype to produce various phenotypes in response to different environmental conditions (Futuyma 1998). The limb proportion variation could be the result o f phenotypic plasticity as individuals respond to various environmental conditions. These responses may occur as a result o f changes i n developmental processes and growth rates, which may eventually lead to changes i n morphology. However, these morphological changes are not heritable; they are adjustments made by the individuals to the environment (Agrawal 2001). One example o f phenotypic plasticity in modern humans is the so-called secular changes documented in the last century. Such changes have often been attributed to improved nutrition, health care and environmental conditions (Tanner 1988). In Katzmarzyk and Leonard's (1998) study, the correlation coefficients between body weight and mean annual temperature and relative sitting height and mean annual temperature obtained were smaller than the reported values o f Roberts' 1953 study. They attributed this to secular changes, especially among tropical populations. If secular changes play an important role in determining body shape and proportions o f modern humans, this could potentially be reflected in the variations recorded in the present study. It has been observed that secular changes have been most significant in the length o f the lower limb (Shapiro & Hulse 1938; Bogin & Rios 2003). Thus, it is possible that the populations from more recent studies possess relatively longer lower limb than ancestral populations in the same geographical locations i n the late 19 century. If this is the case, then the th  33  4. Discussion  morphological pattern observed i n this present study may reflect the improvement in r nutrition and health care, especially i n developing parts o f the world where major changes have taken place i n the last century. Thus, human limb proportion variation may be responding to these non-climatic factors.  4.3.2 Other ways of adapting to the environment A s mentioned i n the Introduction, many scholars have questioned the thermoregulatory explanation for Bergmann's and A l l e n ' s Rules (e.g. Scholander 1955, 1956; Irving 1957; M c N a b 1971; Geist 1987). Most notably for present purposes, Steegmann (2007:224) has recently  suggested  that  there  are  so  many  unanswered  questions  regarding  thermoregulatory explanations for human morphological variation that such explanations should be considered no more than "folklore". It has been argued that other ways o f maintaining body heat equilibrium, such as increasing body insulation and altering vascular controls, are more efficient than altering body sizes and proportions (Scholander 1955; 1956). The corollary o f this is that, relative to such physiological factors, limb proportion changes may only play a minor role in temperature tolerance in modern humans (Hanna et al. 1989). Physiological responses to climatic factors have been investigated by various researchers (see Hanna et al. 1989 for a review). Human physiology is able to cope with considerable differences i n environmental conditions. With highly efficient sweat glands and sparsely haired surface, heat dissipation occurs well in hot, dry environments (Rowell 1977; Baker 1988). Evaporation o f sweat requires heat to convert water from liquid into gaseous phase o f the molecules (Parsons 2003). Thus, in theory, evaporation o f one litre of sweat uses up 25,000 kilo-joules o f heat (Baker 1988). A s such, the loss o f body heat  34  4. Discussion  occurs efficiently through evaporative cooling in environments where water evaporation can be induced readily. However, this relationship changes in a hot, humid environment where the air is so saturated that evaporation does not occur. It has been observed that the effectiveness o f evaporative cooling depends on the percentage o f active sweat glands (Baker 1988). The percentage o f active sweat glands in turn depends on the exposure o f high heat loads during an individual's childhood (Kuno 1956). Thus, it is possible that the key factor i n warm, dry climates is the percentage o f active sweat glands o f an individual, not the amount o f skin surface area. Therefore, even i f the limb length o f a warmer population is the equivalent to that o f a colder population, i f the percentage o f active glands is greater i n the warmer population, the limb is more effective at dissipating body heat. If this is the case, then the limb proportional variation among modern humans need not produce a pattern predicted by A l l e n ' s Rule. Vasoconstriction is a response to cold temperatures. It involves reducing skin blood flow by reducing the diameter o f the blood vessels, thereby minimizing heat loss (Wade et al. 1979; Baker 1988). In a laboratory experiment conducted by Wade et al. (1979), the amount o f blood flow to various body parts was measured after the subjects were immersed in 25°C water for 30 minutes. They reported that during the immersion experiment, average heat loss from different body segments varied. The upper torso lost 24 W , the head 17 W , the calf 17W, the hands 1.5 W each and the feet 1.5 W each (Wade et al. 1979). Compared to the torso, limb segments became so vasoconstricted that little heat was lost through the skin surface during immersion. If little heat is lost through the limbs because blood flow to these structures is reduced, then it may not be necessary for these structures to become shorter in colder environments.  35  4. Discussion  In addition to vasoconstriction, heat loss can be reduced i n colder environments by rerouting blood circulation i n the extremities from the superficial to deep veins (Frisancho 1993). A s blood circulates through the arms and legs back into the heart, the blood in deep veins absorbs heat from nearby arteries that are pumping warm blood from the heart to the periphery in a process called countercurrent heat exchange (Frisancho 1993; Parsons 2003). When blood leaves the heart, it has a temperature o f approximately 37°C. A s blood travels along the length o f the arm and reaches the hand, the temperature drops to 20°C (Frisancho 1993). However, as it circulates back to the heart through the deep veins, the blood warms up to 28°C (Frisancho 1993). The countercurrent heat exchange maintains blood flow to the limbs while reducing heat conductance to the extremities (Frisancho 1993). It is possible that this mechanism may also override the need for limb length variability as expected by A l l e n ' s Rule. Acclimatization may also be an important factor. Acclimatization to various heat conditions have been observed in experimental conditions (Hanna et al. 1989). Once the body acclimatizes to a higher heat load, the amount o f sweat production increases within several days, the sodium content o f sweat decreases, the body core temperature stabilizes at a lower point, and the heart rate lowers to reduce the cardiovascular strain in the new environment (Baker 1988). These physiological changes can be induced within a couple of days in order to optimize the body heat equilibrium in a new environment. Thus, even in the absence o f the theoretically optimal body shape and size, the body responds to ambient temperature in order to maintain proper functioning o f the vital organs. It is possible that these physiological acclimatization processes allow modern humans to  36  4. Discussion exploit various thermal environments without necessitating changes in the morphological structures o f the body. It has been noted, however, that the mechanisms o f acclimatization to colder temperatures are limited in humans (Baker 1988). This suggests that the efficiency and need for morphological changes as an adaptive response may be different i n colder and warmer environments.  In warm climates, the body can respond through various  acclimatization processes to optimize thermoregulation. However, since acclimation responses to colder temperatures are limited, morphological changes may be a more efficient means o f regulating body temperature specifically i n response to cold climates. This may explain the wider range o f variation observed among warmer climate populations i n comparison to the smaller range o f variation among the colder climate populations, as was reported i n Roberts (1978). In addition, behavioural responses may greatly enhance the heat and cold tolerance o f modern humans in the absence o f morphological changes. The use o f fire, protective shelter  and thermal clothing are obvious cultural adaptations  to  cold  environments. Anthropologists have observed numerous accounts o f such cultural adaptations by various populations like the construction o f semi-circular windbreaks o f grass and bough huts by the Bushmen o f the Kalahari Desert and the caribou fur clothing of the Inuit in the Canadian arctic (Frisancho 1993; Stenson 1991). Cree and Ojibway fishermen rely on the use their mouths to get fish off the nets during the winter possibly to minimize the exposure o f their hands to the cold (Steegmann 2007). Ethnographic reports o f such behavioural adaptations to the environment are numerous, as are  37  4. Discussion anecdotal accounts o f our own responses to the environmental conditions here and elsewhere. A s recently pointed out by Steegmann (2007), these physiological and biocultural aspects o f human climate-related adaptability have not been adequately addressed and have been largely ignored by human biologists since the 1970s. Over the last 30 years, the focus o f human biological research has shifted to molecular genetics and these issues have been left under explored (Steegmann 2007). However, the applicability o f ecogeographical rules to morphological variations in modern humans has been widely accepted in biological  anthropology despite these unanswered  physiological  and  biocultural questions. In light o f the results o f this study, perhaps the acceptance o f the applicability o f A l l e n ' s Rule to modern humans has indeed been insufficiently critical.  38  5. Conclusion  5. Conclusion The study reported here focused on the reliability o f the conclusion Roberts reached in his 1978 book 'Climate and Human Variability' that modern human limb proportion variation is consistent with A l l e n ' s Rule. It did so because 'Climate and Human Variability'  is  primarily responsible  for  establishing  the  current  consensus  in  anthropology that modern humans follow A l l e n ' s Rule. The impact o f a number o f the shortcomings o f Roberts' analyses was assessed. One problem that was examined is that the sample used i n Roberts' analyses is strongly biased towards warm climates. Another is that Roberts employed different subsamples for each limb segment, thereby making it impossible to compare the impact o f temperature on different limb segments. A third problem that was examined is that the potentially confounding effects o f population history were not addressed i n his correlation analyses. Five sets o f analyses were carried out. The first set o f analyses replicated Roberts' methodologies to evaluate the appropriateness o f the data used i n this study. The results o f these analyses generally supported the conclusions o f Roberts' (1978), which indicated that the sample is appropriate. The results o f maximum/minimum correlation coefficient analyses suggested that the range o f variation among populations is so great such that the results o f the correlation analyses were largely dependent on the composition o f the sampled populations. Segment-specific stratified analyses indicated that the overrepresentation o f warmer climate is problematic as only two limb segments yielded statistically significant correlations. In multi-segment stratified analyses, the pattern o f limb proportion variation did not support the findings o f previous three sets o f analyses. This underscores  the sensitivity o f the correlations to sample selection with the  39  5. Conclusion  implementation o f a more rigorous selection criterion. Phylogenetically-controlled analyses returned statistically significant associations consistent with A l l e n ' s Rule i n only two o f 10 correlation analyses. This highlights the importance o f Roberts' failure to control for phylogeny. Together, the results o f the analyses support the idea that Roberts' work on the impact o f temperature on modern human limb proportions is problematic, and call into question the notion that modern humans follow A l l e n ' s Rule. Several authors have highlighted species that do not follow Bergmann's and Allen's Rules i n body size and shape variations (Rensch 1938; M c N a b 1971; Riesenfeld 1980; Stevenson 1986; M e i r i & Dayan 2003). Therefore, it is not entirely surprising that modern human limb segment variability does not follow A l l e n ' s Rule. Given the numerous physiological and behavioural responses to heat and cold stresses that are available to humans, the traditional thermoregulation model for A l l e n ' s Rule may be limited to account for the morphological variability in modern humans. With regard to future research, one obvious course o f action would be to revisit the applicability o f Bergmann's Rule with the sampling strategies and analytical techniques used here. A s it has been pointed earlier i n this study, Katzmarzyk and Leonard (1998) recently conducted analyses investigating body size variation in different climates. They found that human body mass follows Bergmann's Rule. However, their study also suffers from the same problems as Roberts with respect to the overrepresentation o f warm-climate populations and the failure to control for phylogenetic relationships. It is possible that once the samples are stratified and the effects o f phylogeny are removed, the correlation between body size and temperature may not  40  5. Conclusion  conform to Bergmann's Rule and the findings o f Roberts (1953) and Katzmarzyk and Leonard (1998). Climatic factors have long been applied to explain morphological variation in modern humans. However, it may be necessary to seek explanations other than mean annual temperature to account for the observed variation. Exploring physiological and biocultural responses in various environmental conditions may lead to better insight regarding human climatic adaptation. There is also a need to study the entire scope o f modern human variation. M a n y populations have been excluded i n this study simply because the data were not available. The trend in anthropological research has moved away from anthropometric studies o f the early 2 0  th  century. 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Current Ornithology 4, 1-69.  49  OS  Beni Chaamba Mekhadma Reguibat Tuareg Bieno Chokwe Ginga Luimbe Muila  131.9  22.34  |  Rel low arm length  130.7 133.6 131.6 129.7  22.41 16.94 19.58 25.17 24.83 18.55 23.16 | 20.94 19.98 18.93 25.33  Rel up arm length  0.154 1640.0 0.190 1668.5 1630.8 1659.5 1750.0 1666.0 0.193 0.163 1599.0 | 0.191 | 0.161 0.162 1622.0 0.190 0.164 1681.0 0.190 1668.0 0.191 0.162 1655.0 0.190 0.161 1738.4 0.189 0.151 1684.0 0.189 0.163  Stature (mm)  1668.3 27.29 26.47 1700.5 0.191 0.164 17.60 1626.8 0.194 0.168 27.11 1692.9 1589.5 1596.0 1594.0 26.86 1684.2 0.196 0.162 29.36 0.192 0.159 27.65 1706.6 28.44 1 1720.4 1 0.195 | 0.159 0.194 29.36 1687.5 0.160 |  0.049 0.047 0.047 0.048  0.051 \ 0.050 0.050 0.050 0.051 0.050 0.049 0.046  0.051 0.051 0.052  Rel hand width 0.051 0.048 0.050 | 0.049 1 0.049  0.245 0.242  0.152 0.148  0.153 0.153 0.160 0.154  0.056  0.059 0.056  0.060 0.061 0.061  0.238  0.264  0.149 0.149  Rel foot width  0.062 0.062 0.063  Rel foot length  0.149 0.149 0.156  0.245 0.250  Rel low leg length  0.263 0.275  Rel up leg length  0.302 0.301 0.305 0.306  I xiptraddy  Group Central Melville & Bathurst Isles North South Victoria River Aymara Quechuas Wapisiana Bella Bwaba 1 Gurmanche Malebe  bo OS  Algeria Algeria Algeria Algeria Algeria Angola 1 Angola Angola Angola Angola Angola Argentina Australia Australia Australia Australia Australia Bolivia Bolivia Brazil Burkina Faso Burkina Faso I Burkina Faso Burkina Faso  so  Mean annual temp (°C) Ul so oo  <l SO  o o o o o o o © o o o o o o o o Ul Rel hand length OS os NJ oo o NJ Ul  1  1  o o o o o o o o SO SO o o o o o o  Longitude (180°E=-180) i Ul Ul © OS Ul bo U) b os  NJ ;-J OS O IK) 4^ SO b •  OS ^1 NJ  i i Os OS Os OS ^ ) O o NJ Ul bo •  t O © Ui  •  NJ NJ u> u> U) •  <l  SO  to Os 4^ 4^ NJ to SO Latitude (90°S=-90) so <1 os b Ul 4* bo  11 •  1  i i NJ Ul NJ UJ bo Os b  1i 1 • •  U) U) OS Ul NJ 4* U) SO bo bo © U) NJ NJ  O O 3 o' ss  N © OJ UJ u> SO 4^ SO 4^ o 00 o Ul  NJ o NJ © o o o o Ui O o o o o o 00 NJ U) Ul 00 NJ NJ U) U) NJ Ul  o Ul SO  Country  IS  Burkina Faso Burkina Faso Burkina Faso Cambodia Cameroon Canada 1 Canada Canada Canada Canada Chad Chad Chad Chile China China China China China China China China China China China -121.9 -109.5  103.7  1  27.97 28.14 29.36 27.49 23.71 Ul  Group Mossi of Donse Mossi of Kokologo Rimaibe Khmers Fang Beaver Chipewyan Cree Igloolik Inuits Labrador Inuits Goranes  Mean annual temp (°C) -14.23 24.18 27.44 21.94 14.73 14.89 16.19 14.89 14.89 14.89  1677.7 1689.3 1725.1 1610.5 1679.0 1683.0  Stature (mm) 1 1647.0 1715.0 1637.9 1584.8 1705.5 1739.2 1679.2 1571.3 1674.0 1555.5 1624.7 1594.8 1566.3 1601.0 1640.1 1558.8 1588.0 1561.0 1668.8  © UJ  ^t 4^. 4^.  14.73 14.89 14.73  0.184 0.172 0.179 0.181  0.192  0.190  0.201  0.200 0.195 0.194 0.190 0.198  Rel up arm length  0.153 0.148 0.150 0.156  0.155  0.160  0.138 0.148  0.166 0.163 0.161 0.153 0.162  Rel hand length  0.049 0.049 0.049 0.052 0.050 0.050 | 0.054 0.051  Rel hand width 0.045 0.052  0.050 0.050 0.050 0.050  o © o © © © © © © © © © © o o © © © o © © © o © © © o © © to © o © © Ul oo SO Os to UJ 4^ SO OS to UJ SO OS Ul © to Ul SO Ul  0.051 0.052 0.042 0.050 0.055 0.048 0.054 0.051  0.224 0.238  0.157 0.154  0.062 0.060  0.059  0.303 0.303 0.305 0.294 0.291  0.152  0.059  0.053 0.062  0.143  0.223  0.153 0.155 0.142 0.148  0.061 0.062  0.228  0.249  0.221 0.220 0.216 0.227  0.237  0.253 0.248 0.251 0.250  0.147 0.148  Rel foot width  0.064  Rel foot length  0.152  Rel low leg length  0.062  Rel up leg length  0.152  I xipuaddy  •  i  to bo  o  •  i  1  SO  Ul UJ Ul  k)  00 (a *-t P  Toubous Yahgans Black Lolo Bulang Setchuan Hani Jinuo Lu-jen Mongolians Pa Miao Pai-Y Shui-his Miao Changtang  o b  4^ •  i  1 ^1 Ul SO  to OS OO so to 4ib "o bo -O 1  © © © © © © Os © o © to SO to to to to 4^ to SO oo SO © © Ul © © © b u i b Ln SO  UJ UJ  © so to Longitude (180°E=- 180) k) Ul k)  i  Latitude (90°S=-90) 4=>  to -o to UJ UJ  to  bo i Ul Os Ul Ul Ul UJ UJ to UJ 4^ to to to UJ to UJ Ul to © IO Ul 4^ Ul Ul Ul OS SO 4^ Ul 4i. so OS © UJ Ul Ul OS 4^ Ul © b © © b b SO b b  N 4^ SO  to UJ to to 4^ Ul ^ 1 © to 4^ oo 4^ Ul 4^ 4^ UJ to Ul Os UJ Ul UJ SO SO © OS Ul Ul 4^ 4^ © oo ©  © © UJ  U l to UJ 4^ Ul 00  o © Ul o to to to OS  SO  Country  Rel low arm length  China China China Columbia Columbia Columbia Columbia Columbia | Columbia Columbia Congo Congo Cyprus Czech Rep D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo 1 D R Congo D R Congo D R Congo  Country  32.0 32.0 32.0  -11.7 34.7 50.1  1  1  Mean annual temp (°C)  Stature (mm)  -3.20 1664.3 -3.20 1648.9 -3.20 1650.9 18.63 1555.0 24.43 1576.0 13.27 1548.0 13.27 1583.0 14.95 1598.0 18.63 | 1568.0 1571.0 14.95 1441.9 22.67 20.22 1656.1 17.60 1649.0 1726.0 8.53 1444.1 24.87 1580.3 22.88 1612.3 22.59 24.16 1608.9 23.15 1618.6 1438.1 23.06 21.98 1590.6 16.91 1623.5 17.68 | 1577.8 18.18 1639.8 23.55 1585.6  0.051 0.049 0.050  0.288 0.297 0.272  0.279  0.234  0.232 0.236 0.224  0.220  0.051 0.051 0.051  0.048 0.048 0.046  0.272  0.228 0.297 0.225 0.303 0.304 0.224 0.299 0.226 0.303 0.232 | 0.297 j 0.221 0.291 0.225 0.233  0.046  u>  4^ U) OS  to  Longitude (180°E=- 180) 90.0 90.0 90.0 -76.3 -77.0 -76.0 -76.0 -76.4 -76.4J! -76.3 30.0 27.5 32.9 14.5 18.0 28.6 30.1 27.3 28.0 28.8 29.1 28.9 29.9 | 29.1 29.0  0.061 0.060. 0.063  0.062  0.058  0.061  Rel foot width  | 0.062 |  I xtpuaddv  Ul  Ul  Ul  ©  Rel foot length  p  Ul  o  to  ^) 4^ SO Ul Ul  o  Rel low leg length  o o p  © © © © ©  o o O OS OS  oo  Ul  Ul  o o  o o  o  o o to  o  O  o  o o o O o O o  o  o O o O Os OS oo o  o  o o  © © o  o  Rel up leg length  © p o  Ul  o  Ul  Ul Ul  Rel hand length to  ©  Ul Ul  o o  Rel hand width  ©  Rel low arm length o  Ul  O  O  ©  O  o  o  o  Os 4*. U i U l U l U l 41. SO t o Os t o U i OS Os 4^ 4^ U ) U l Os IO 4*. Os OS U l Os U l SO o t o oo o o  oo  SO SO 4i.  oo  4*. U l  Ul  Rel up arm length 00 00 4^ o 4=. SO  © oo oo o o o o o to so SO o SO SO SO 00 41. 4^ o SO 4^ SO oo oo oo o SO U l ^4  O  o o o © © o © o o  o  o o o o o o o o  o  o o  to to to  Kam Tsang Ambalo Gaumbiano Kokonuko Paez Purace Quisgo Totoro Ituri Pygmy Luba Cypriotes Czech Aka Bira of rain forest Bira of savannah Bali Beyru Efe and Basua Fulero Havu 1 Humu Hunde Lese bo  o o o  Latitude (90°S=-90) bo ON  bo bo  to to  to to SO Os  o to OS 4^ 4^ 1  to to  bo 4^ 4*.  1 to  o •  tO  N t o 00 U l Ul t o U) SO OS t o =  oo o t o Os Os SO t o Ul  OS SO  oo oo to  to  o o oo U)  to to 00 OS U l  o © o o o o o o Os  C  Group  24.63 23.55 21.79 25.11 17.77 20.19 24.70 16.91 19.23 23.60 20.33 21.33 25.73  Mean annual temp (°C) 11.76 23.00 10.47 16.68 19.22 24.52 24.41 24.81 26.55 26.54 27.00  UJ  -179.0  167.0  to  N 1,084  bo bo bo  b  Longitude (180°E=-180) Ul  so bs UJ  bo "o SO bs to SO UJ  -o b Ul  o •  1  •  Mbuba Ndaka Nyanga Rega  Swaga Tembo Marsa Matrouh Salloum Sidi Barrany Siwah Lauans Finns Basque Lifu Islanders Normandie Greeks Mam Indians Guerze Kissi Toma Caribs Andamanese Car Nicobarese  1 •  •  SO to UJ  SO SO 00  oo ui  tO  D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo D R Congo Egypt Egypt Egypt Egypt Finland France France France Greece Guatemala Guinea Guinea Guinea Guyana India India  1580.8 1588.0 1601.8 1621.7 1638.8 1622.8 1616.5 1590.1 1670.2 1619.5 1645.9 1676.3 1729.1 1676.2 1691.0 1642.0  Stature (mm) 1705.1 1559.7 1681.0 1698.0 1697.0 1577.0 1489.9 1587.0  0.186 0.207 0.198 0.186 0.188 0.188 0.167 0.212 0.185  0.192 0.195  0.190  0.179 0.195 0.181 0.182 0.188 0.189 0.186 0.185 0.193  Rel up arm length  0.155 0.163 0.149 0.161 0.159 0.163 0.171 0.163 0.154  0.149 0.152  0.149  0.161 0.151 0.159 0.159 0.162 0.164 0.163 0.156 0.146  Rel low arm length  0.114 0.099 0.123 0.114 0.110 0.109 0.113 0.112 0.115 0.108 0.081 0.113  0.114  0.103 0.105 0.103 0.106 0.102 0.104 0.103 0.107 0.114  0.049  0.285  0.231  0.156  0.062  0.059 0.051 0.046  0.051  0.275 0.277 0.273  0.298 0.257  0.293 0.309  0.267 0.210  0.242 0.253 0.224 0.232 0.228 0.236  0.222 0.223  0.242  0.276  0.059 0.063  0.152  0.160 0.156 0.154 0.155  0.064  0.155 0.158 0.152  0.065  0.230  Rel foot width  0.060 0.061 0.060 0.058  Rel foot length  0.153 0.156 0.156 0.151  Rel low leg length 0.051 0.052 0.052 0.050 0.048  Rel up leg length 0.053  I xipusddv  bs  so  o  UJ  Ul Ul  oo UJ  to  1 • 1 • •  Ul  to to  to to to to to to to to oo 4^ SO 00 •o 00 oo Ul  SO  Ul Ul Ul  Latitude (90°S=-90) bs -o.  to •  to OS o to Os Ul to Ul so to bs to 4*. SO  UJ  U)  to u> to 1  4^ Os Ul UJ  4^  •  UJ  SO to -J 00 SO <i Ul 00 SO to k> Ui b Ul to bo u> b b b  c  o o OS to  00 00  Ul 4^  o o o o o o o © o oo o o 4^ to U J o Ul SO 4^ 4^ UJ  OS SO  oo o o o UJ to OS  oo to o to o Ul  Tl  Rel hand width  990 0  es  Country  Group  Rel hand length  0.159 0.148  26.82  0.189 0.204 25.57 25.57  0.209  0.204 0.203 0.191 0.188  0.146  0.163  0.153 0.153 0.160 0.157  0.049  0.052  0.054 0.051 0.052  0.050 0.050 0.052 0.052 0.048 0.052  0.272 0.269 0.281 0.282  0.277  0.236 0.240 0.197 0.208  0.204 0.233  Rel low leg length  0.249 0.259 0.198 0.256 0.204 0.202 0.202  Rel up leg length  0.267 0.270 0.229 0.287 0.220 0.233 0.220  o o o © o o o  0.052  0.067 0.058 0.056  0.060  0.153 0.059 0.154 0.061 0.155 1 0.061 1 0.155 0.059 0.155 0.061  0.148  0.056 0.056 0.063 0.065  0.052  LO  27.25  0.184  0.144 0.148 0.145  f  42.  0.169  1567.0 1598.0 1590.2 1654.0 1540.3 1618.0 1679.0  Rel low arm length 0.190 0.184 0.186  0.050 0.051 0.052 0.050 0.051  (JI  India India India India India India India  1,357  142.4 132.5 142.4 130.4 140.3 134.8  |  26.08 1720.0 26.08 1721.0 26.82 1614.0 26.82 1591.0 25.57 1696.0 14.98 1706.0 1622.0 14.70 1581.8 1671.0 14.54 1610.0 10.95 1571.9 12.67 1583.3 19.08 1738.1 19.24 1725.1 21.03 1 1697.9 19.08 1693.2 21.03 1698.9  OS 42. ui o SO oo  Rel foot width  42- OS U l SO  LO  ui  Group Chowrite Garhwali Kota Kulu Kanets Kurumba Lahaul Kanets Malavar Muhammadan Punjabis Sikh Punjabis Southern Nicobarese Terressan Toda Italians Ainu Hiroshima Hokkaido Fukuoka Fukushima Yamaguchi Ababukusu Abagushi | Abakisa Abalogoli | Abanyore  Rel up arm length  Ul  Rel foot length  Ul  to  Ul  Ul  (JI  Ul  (ji  to  India India India India India  Japan Japan Japan Japan Kenya Kenya | Kenya Kenya | Kenya  I xipuaddv  LO  to LO  42.  to  (ji  o o o to Rel hand length IO o 42.  o o o o o o o  o o oo OS SO o o o o 42. oo oo SO  O b  Rel hand width o o o o o o o o o o o o o o o o o o  00  Mean annual temp (°C) oo LO LO  LO  Ui  ON  jit 00  to  SO  ^1 LO  b  -J  LO  LO  LO  to  b  Longitude (180°E=-180) LO  ;-J  Ui  ^) •o. LO LO  ps (Jl  to  42. 42. b b SO SO LO  42. 42. 42. 42. 42bs 00 bs  to  NO OS  Latitude (90°S=-90) O 00 42. 42. (Jl  LO  LO  SO  LO  to bs 42. b  to to  CO  to  LO  N o LO  to  OS to L O to o Ul O Ul Ul  OS OS oo OS  (Jl  to to  00 LO LO 42- L O 42- 42. LO 42. L O to 00 O o 42. Lo 42. b b OS bo 42. bo © LO  •  3  LO LO  LO  o o o o (Jl as to "-j bs to (Jl O  05  Os 4^ oo  to to OS to LO  —1 (Jl SO  Os  (JI  (ji  42. OO ui  •a ET •<* 3 (a T3  Country  Stature (mm)  ss  Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Magascar Malawi Malaysia Mali Mexico Mexico Mexico Mexico Mexico Mexico Mexico Mexico Mexico  Abatirichi Abatsotso Abesukha Abetakho Akikuyu Iteso Ja-Luo Keiyo Marakwet Sabaot Wataita Antandroy Chewa Brunei Dogon Dogon Aztec Chamula Indians Choi Cora Maya Otomi 1 Tarahumare Tarasco Yaqui |  115.8  -105.0  -106.0 | -101.8 -110.7  0.189  0.191  0.202 0.160  Rel up arm length  0.153  0.160  0.162 0.146  0.049 0.052 0.051 0.049 0.050 0.050 0.050 0.049 0.049 0.048 0.051  0.300  0.207  Rel up leg length  0.203  to  Ul  Ul  Ul UJ  Ul  Rel hand width 0.049 0.051 0.050 0.052 0.050 0.058 0.052 | 0.051 0.050 0.051  Ul UJ  Mean annual temp (°C)  Stature (mm)  1712.9 17.43 21.03 1714.0 1706.2 21.03 1697.3 21.03 18.28 1678.1 19.08 1731.1 1751.5 22.23 1702.9 16.90 22.12 1700.5 1749.6 19.08 1646.3 22.66 1670.0 23.73 19.93 1660.6 22.73 1563.5 1685.0 28.61 1703.7 29.07 1608.5 17.92 1557.2 22.63 25.43 1585.5 1650.0 19.51 25.48 1551.1 21.88 1585.0 18.98 | 1642.0 1631.0 23.77 22.11 1748.0  0.061  0.059 0.061  0.061 0.059 0.057 0.060 0.058 0.060  Rel foot width  0.061 0.060 0.064 0.064 0.067 0.064 1 0.058 | 0.061 | 0.062 |  I xipuaddy  Rel foot length  Os to  Ul  Ul  Ul  SO to  to  SO U l  Ui  Rel hand length UJ UJ  to UJ UJ  to  ©  Ul  oo  ui  Ul  Ul UJ  bs  UJ Ul  UJ Ul  4 * 4^ U l  © © © © o ©  Ul  Ul  "o  bo  ©  Ul  © ©  Ul UJ  Ul  Ul  UJ  UJ  oo  © ©  © © ©  o © © © © © © © ©  UJ  UJ  Ul  ©  UJ  4^  Ul  "o U l  to  UJ UJ  UJ 1 1  • • i SO so SO to to SO 1  Ul  UJ UJ  4^ 4^  bo bo u>  ©  to  Longitude (180°E=-180) © bo  ©  sb oo SO SO  i UJ  •  UJ UJ  ©  UJ UJ  o © © © © © © © o © © © © ©  o o o © © © o © © © to o © © U> oo UJ © © 4^ o  UJ  4^ 4^ OS 4^. 4^ 4^ U l bs SO bo bo UJ  Latitude (90°S=-90) © © UJ  bs  ©  p to  © © bo © © UJ  i to 1  ©  © to  Ui  Ul Ul  Os 00 U i  to to  so  IO tO to SO SO 00 © U J to U l U l  to OS OS OS U l UJ SO Os ©  N Ul  to  OS OS  -J  to  © © © © to  oo  Ul  © ©  Ul  o ©  © oo  Ul Ul  U>  Ul  to  so o  2  Country  Group  Rel low arm length  Rel low leg length  9£  CP  CD  CI  s 2 2  Namibia Namibia Nicaragua Nicaragua Nicaragua Nicaragua Nicaragua Nicaragua 1 Norway Panama Panama Panama PNG PNG PNG PNG PNG PNG PNG  1 Peru Russia Russia  -o *o ••0  Country r  •8  •a  !Kung Kavango Miskito Rama Ramas Subtiava Sumo Sumus  O  Choco Cuna San Bias Auyana Awa Butam Gadsup New Ireland Ontenu Tairora Macheyenga  Quicha 1 Sipibo Ostiaks Samoyedes  y.  Group  Ul LO  Ui  OS U l  42.  ON  it  to  — i  • Ul  1  to  LO  l  i  O  LO to to Ul Ul to to  • •  LO  LO  Lo bo Lo  •  LO  SO  "-J  I  OS OS  i  •  LO  Os  to  LO  Ul  1 LO  42. 42- Lo 42. Lo  SO OS 0 0  •  OS Os OS b s  00 Ul  •  I  10  t o 10  00 Ul  00 Ul  42! 0  0  0  to to to to t o 0 U l U l ^1  11  LO  42!  N  11  OS  b  LO O  LO  LO  b  b  •  to to to to LO 42. t o t o so SO p  Lo  111  •  Latitude (90°S=-90)  1  00 0 0 0 0 00 •-4 42. 42. U i 42. U l 42. 42. 42. OS ^4 ^1 ; - J OS L O L O OS 0 0 0 0 42. SO 00 Ul Ui to Ul to Ui Ul © 00 42. !° os 42. b s bo b U l U l U i SO bo bo SO io ui U l Lo OS Lo bo bo bo © so b Lo  Longitude (180°E=- 180)  | 1614.4 0.188 0.158 21.00 0.164 21.90 1706.1 0.190 0.166 1640.3 0.196 21.83 24.34 1632.6 0.201 0.166 26.10 1661.0 0.153 27.56 1632.7 0.191 1586.4 0.199 0.160 25.48 25.48 1581.6 1 1581.0 | 0.195 | 0.152 1564.0 26.48 1549.0 26.48 1499.0 26.48 1536.8 24.36 24.36 1508.5 1580.8 23.90 24.45 1582.8 1610.7 23.90 1574.8 24.45 1559.7 24.45 1610.0 1613.0 23.62 1585.0 26.96 | 1568.0 1565.0 1568.0 Ui  42.  ©  o  oo bo  00  bo  to LO  LO  LO  o o o o o  OS OS 42. 00 OS SO 0 0 L O  o  LO  o o  o  O  O  Ul Ui - J 00 OS U l  o  o  to to 42. L O  ©  o  O  42.  Ul  ©  o o  oo oo  O  o ©  O O  SO  0  0  SO SO  o  o  0  o  o 00  o ^1  o  0  0  Ui Ul Ul SO OS 0  0  42!  0 00  Stature (mm)  Rel up arm length  0  Ul •0. 0  SO  0  0 0 SO  0  0  0  0  0  ~ J  0 00  0 42. 00  LO  0  0  0  0  0  0  Rel low arm length  0 0  42. 42. 0 0  Rel hand length  0.057 0.068 0.067 0.063  0.066 0.062  Rel foot length  0.058 0.062  0.153 0.048 1 0.052 | 0.264 | 0.217 | 0.155 0.151 0.053 0.156 0.054 0.153  0.066  0.212  1 0.213 | 0.152 | 0.063 |  Rel low leg length 0.150 0.157  0.162  0.066  0.047 0.050  0.215  0.159  Rel up leg length  0.061  0.269  0.221  Rel hand width  0.152  0.275  0.061 0.064  0.063 0.062 0.052 0.062 0.050 0.061 0.063 0.053 0.052  0.048  0.226 0.158 0.154 0.223 0.154 | 0.156 0.152  | 0.053 0.054 1 0.055  I xipusddv  Mean annual temp (°C)  0  SO 00 0 SO  OS OS OS U l OS U l Ul SO 42. oo O  0  SO 0 0 SO 42- OS 0  0900  ©  Rel foot width  Russia Rwanda Rwanda Rwanda Rwanda Rwanda Senegal Senegal Senegal Senegal Solomon Isl Solomon Isl Solomon Isl Solomon Isl Solomon Isl Solomon Isl Solomon Isl Solomon Isl South Africa Spain Sudan Tanzania 1 Tanzania Tanzania Tanzania  Vogouls Bahutu Batutsi Hutu Tutsi Twa pygmies Bedik Mandyago-Diola Ouolof Peuls ui © Ul to 00 to Ul o ^ 1 Ch 4*. SO Ch Ch -O Ul o oo  1  o ©  o o o o  p  o o  p  p  p  ©  o  o o o  i  1  1  p  p  •  p bo UJ  Rel up arm length oo oo oo SO so oo oo SO SO - J -o ^ 1 oo Ul OS -o 00 Os oo UJ  Longitude (180°E=-180) to to to to to OS Ul Ch Ch OS 4^ UJ UJ UJ UJ 1 UJ Ch Ul to OS OS Ul to SO SO SO SO SO oo U> U*l to to © to SO Ul Ul UJ UJ SO b b so 4^ bs SO bo SO bo Ul bs bs 'o. UJ UJ b ui b b b  Mean annual temp (°C)  Stature (mm)  1567.0 19.18 1643.7 16.65 1720.0 19.18 1674.3 16.65 1765.2 1577.4 16.65 28.51 1672.5 26.28 1712.0 25.69 1732.0 26.22 1700.0 0.216 26.95 1604.0 25.40 1613.0 0.213 25.40 1603.0 0.211 25.40 1625.0 0.220 0.216 22.18 1596.0 0.217 22.18 1621.0 1642.0 0.216 27.01 25.76 1616.0 0.213 18.49 0.194 11.22 1699.5 0.195 27.70 1723.8 21.27 1648.8 0.196 22.29 1 1628.5 | 0.204 0.187 18.45 1609.5 0.195 20.98 1655.9  0.123 0.112 0.108 0.103 0.099 0.116 0.113 0.113 0.112 0.112 0.118 0.116 0.115 0.116 0.117 0.117 0.113 0.114  Rel hand length  0.056 0.051 0.046  0.299  0.272 0.278  0.236 0.233 0.234  0.230  0.213 0.241 0.243  0.157 0.156  0.153  Rel foot length  0.059 0.059  0.064  Rel foot width 0.050 0.052 0.052 0.052 0.049 0.052 0.051 0.051  0.050 0.048  0.284 0.284 0.279  Rel low leg length  0.064 0.066 0.064 0.066 0.063 0.064 0.063 0.065  Rel up leg length  0.156 0.159 0.158 0.160 0.159 0.157 0.156 0.158  Rel hand width  0.220 0.100 0.305 0.111 0.047 0.275 0.246 0.270 0.240 0.117 | 0.117 | 0.049 1 0.273 | 0.241 0.106 0.047 0.235 0.113 0.051 0.274  I xxpuaddv  to UJ  Baegu Kwaio Nagovisi Nasioi Ontong Java Ulawa Venda Basque West Nile Nilotes Baziba 1 Bazinja Hadza Wanyamwezi  i  Latitude (90°S=-90) Ul • • • i 1 1 • 4*. to 1 i • 1 • 1 to Ul to UJ to UJ 4^ U) to oo UJ so Ul i s i s SO SO sb oo 4^ UJ OS bs b SO bs b b b b b SO 4^ ^o b UJ b 4^ b bo UJ  N o  © ~-4 Ul Ul  to  ^ 1 SO 42. o SO to SO  4^ UJ  Rel low arm length OS OS OS OS Ul Ul OS Ul OS Ul UJ UJ Ul o ^ 1 SO 4^ SO UJ OS  <l ^) 4^ -o o UJ o  o o o o o o  -J  o o  o  OS ui Os Ch 4^ o J> UJ to Ui SO  o o ©  o o o ©  &  to to UJ 4 *  Ul  o U>  > r c  Country  Group  85  Tanzania Timor Turkey Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Urundi Urundi  us us  US US US  us  US US US US  Country Zanzibar Arabs Timor Turks Acholi Baganda Bahima Bahiru Bakiga Banyoro Batoro Lubgwara North Uganda Bantu Teso Hutu Tusti Anaktuvuk Pass Apache Barrow Comanche Eastern Aleut Hano Hooper Bay Hopi Laguna Maricopa to  42. OS LO to © o SO o SO  Ul SO to ^ i  to  to o  SO OS  -  42. to 42- to 42. ^ 1 oo so Os 41.  ©  42. to bo so  b 42. 42.  1  O  i © O LO  to  39.9  68.1 33.9 71.3 34.4 53.4 35.8 61.5 35.8 35.0 33.1  i 1 to to to © LO LO  SO LO ^ 1 42. Ul 42. SO  1 t SO OS  to  39.2 124.9 32.8 33.2 31.7 30.2 31.4 31.2 31.8 30.0 31.2 33.2 33.8 29.4 29.4 -151.7 -105.7 -156.8 -98.0 -167.7 -110.4 -166.1 -110.4 -107.4 -112.0 • i to to to to to to to to i to |o IO SO to Os to SO 00 SO LO LO 42LO b os SO to OS 42. SO SO KJ SO 42- SO 42- b 00 to to SO os LO LO O LO ~ J OS 42. o oo oo o 00 LO  OS ^ 1 OS OS OS Os OS OS OS Os OS 41. LO 42- to to 42- oo OS so 42. Ul OS SO LA SO Ul © to to so b b b b b Ul SO b b b so 42-  OS ~ J Os OS SO LO oo LO © bo b SO SO  to to to to  OS Ul Os OS OS SO OO Ul oo Ul 00 SO to to SO LO OS SO •-'  p p O © © © p © © p © to to oo oo so SO SO SO SO SO SO © SO SO © Ul 42. Ul © 00 LO OS OS Os OS OS  ©  o o o o o o  ©  p p  ©  ©  ©  ©  ©  ©  SO LO  ©  Ul LO  OS OS OS Os OS OS Ul Os Ul OS OS OS OS OS LO 42. Ul © —1 SO © 42.  o o o o o o o  o o  O o  o  o o  O SO oo oo LO OS OS  o  o o o b b b LA Ui Ul to o  o o b b Ul Ul 42. o  O b  ©  b  o b  o ©  o  ©  O ©  o o  ©  LO LO LO to i o  p b  p b  Ul Ul Ul Ui Ul to to LO  o b Ul o  o b 42. ~J  o o  ©  o o ©  ©  ©  p © © © © © © b © © © © © © Ul 42. 42. 42. 42. 42. Ul ©  SO 00 SO SO Os ©  ©  ©  ©  o  ©  o  ©  ©  ©  ©  ©  © ©  ©  O  o o o o o o  Ln Ul 42. 42. 42. 42. Ul Ul Ul Ul tO 42. 42- LO 00 - J to  o b OS o  o b  O O o b b b  O o b b  ©  b  o b  o b  Ul Ul Ul Ul Ul OS OS Ul Ul oo SO Ul o to oo SO  I xipuaddy  Longitude (180°E=- 180)  Mean annual temp (°C)  Stature (mm)  Rel up arm length  Rel low arm length  ©  ©  ©  ©  ©  ©  ©  b © 42. Ul Ul oo oo  ©  ©  to to to to to to to to to to to Ul 42. 42. LO 42- 42. 4242. 42. to OS © © 42. to SO SO 42- to  o o  Latitude (90°S=-90)  Rel hand length  to to to to i o to to to to to ~J -o ^4 oo —1 ~J Ul to LO OO © LO © © 42- Os 42.  o o  ©  to LO LO  ©  N  to to  © LO © Ui Ul © os 42. LO LO LO bo 42- so LO 42. © SO  OS OS Os OS —1 Ul 42. SO 42. © Ul OS  Group  Rel hand width ©  to to  Rel up leg length  ©  to  LO ©  Rel low leg length  ©  Ui Ul  Rel foot length  © © OS ©  Rel foot width  65  Venezuela Venezuela Viet Nam Viet Nam Vietnam  C GO  d  oo  C oo  d  oo  C C 00 00  d  d  oo oo  d d d d d d 00 00 00 00 oo oo  Country Mohave Navaho Nunivak Island Papago Pima Point Hope Sioux Southern Ute St.Lawrence Island Wainwright Inuits Western Aleuts Yuma Zuni Choctaw Warao Yupa Mois Vietnamese Annamites u i -tk  o  to to •o U ) to  SO oo  to to Ul o SO to b b b b to  00 OS  o  SO  UJ  UJ  UJ  Ul Ul Ul  1  108.0 105.9 105.0  •  UJ  to  J>  •  OS SO  ~J  1  Ul Ul bo bs  Ul  -o  OS  UJ  bs bo  UJ  •  UJ  o  i  UJ  i  to  Ul Ui UJ  o  SO  so  o  1  •p* •p> to  -P.  Ui  Ul  b UJ  OS ON  00  •o SO  o  bo  1  1  SO OS  o  o -p. os •fc. b to 1  o  SO OS  so Ul bs  SO Ul  to  Longitude (180°E=-180)  Mean annual temp (°C)  1716.0 1699.0 1618.0 1709.0 1718.0 1638.0 1740.0 1669.0 1633.0 1662.8 1585.9 1731.0 1635.0 1708.0 1554.9 1537.8 1559.5 1573.0 1622.8  Stature (mm)  0.184 0.199 0.191 0.188  0.190  0.158 0.137 0.154 0.151  0.147  Rel low arm length  Rel hand length  0.052 0.052 0.054 0.050 0.050 0.052 0.054 0.052 0.053 0.052 0.056 0.051 0.051 0.053 0.052 0.049  0.051 0.048  Rel hand width  0.260 0.297 0.283  Rel up leg length  0.233 0.224 0.219  Rel low leg length  o o Ul Ul  to  o o o o © o o o o o o o o o o o Ul Ui Ui Ui Ul Ul .pi. Ul Ui -p- Ul Ul Ul Ui Rel foot length oo U J oo -pk to o o ^ i U J ^t to © 0.062 0.055 0.061 0.058 0.059 0.060 0.057 0.058 0.059 0.061 0.059 0.061 0.058 0.060 0.062 0.062  0.062 | 0.061 1  I xipuaddy  Latitude (90°S=-90)  Rel up arm length  o o o o o o o o o o o o o o o o o o o o o UJ o Ul o o -P- © Ul U J o o oo OS u> Ul  UJ  N  i  16.03  ©  Ul OS Ul  1  i  14.62 19.54  •  ;P*  to Ul  -p* Os to U J OS U J U J 00 OS OO so Os p Ul 4^  00 o bs UJ  o  •o. b  bs  o  o o  OS  -11.30  to  22.69  16.24 26.14 24.73 25.73 23.65 23.72  00  Ul  UJ  to to "o bs  o it oo  -p* OS  Group  Rel foot width  Appendix II  Country Algeria Algeria Algeria Algeria Algeria Angola Angola Angola Angola Angola Angola Argentina Australia Australia Australia Australia Australia Bolivia Bolivia Brazil Burkina Faso Burkina Faso Burkina Faso Burkina Faso Burkina Faso Burkina Faso Burkina Faso Cambodia Cameroon Canada Canada Canada Canada Canada Chad Chad Chad Chile China China China China China China  Group Beni Chaamba Mekhadma Reguibat Tuareg Bieno Chokwe Ginga Luimbe Muila Oio Ona Central M e l v i l l e & Bathurst Isles North South Victoria River Aymara Quechuas Wapisiana Bella Bwaba Gurmanche Malebe M o s s i of Donse M o s s i o f Kokologo Rimaibe Khmers Fang Beaver Chipewyan Cree Igloolik Inuits Labrador Inuits Goranes Sara Toubous o f Tibesti Yahgans Black L o l o Bulang Setchuan Hani Jinuo Lu-jen  Source Gessain&Lhote(1961) Coblentz(1968) Coblentz(1968) Coblentz(1968) Verneau(1916) Rosing (1977) Rosing (1977) Rosing (1977) Rosing (1977) Rosing (1977) Rosing (1977) Lehmann-Nitsche (1927) Abbie(1975) Howells (1937) Macho & Freedman (1987) Macho & Freedman (1987) Howells (1937) Chervin etal.(1907) Chervin et al. (1907) Farabee (1918) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Froment & Hiernaux (1984) Olivier & Moullec (1968) Lalouel(1957) Grant (1936) Grant (1936) Grant (1929) de Pena(1971) W e i l (1971) Coblentz(1968) Crognier (1972) Coblentz(1968) Hyades and Deniker (1891) Woo (1942) Zhongguo ren lei xue xue hui (1982) Legendre(1910) Zhongguo ren lei xue xue hui (1982) Zhongguo ren lei xue xue hui (1982) Woo (1942)  60  Appendix II  China China China China China (Tibet) China (Tibet) China (Tibet) China (Tibet) Columbia Columbia Columbia Columbia Columbia Columbia Columbia Congo Congo Cyprus Czech Republic Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Dem Rep Congo Egypt Egypt Egypt Egypt Fiji Finland France  Mongolians Pa M i a o Pai-Y Shui-hsi M i a o Changtang Kam Tsang U Ambalo Gaumbiano Kokonuko Paez Purace Quisgo Totoro Ituri Pygmy Luba Cypriotes Czech Aka B i r a o f rain forest B i r a o f savannah Bali Beyru Efe and Basua Fulero Havu Humu Hunde Lese Mbuba Ndaka Nyanga Rega Shi Shu Swaga Tembo Marsa Matrouh Salloum Sidi Barrany Siwah Lauans Finns Basque  Buxton (1926) Woo (1942) Woo (1942) Woo (1942) B u c h i e t a l . (1965) B u c h i e t a l . (1965) Buchi etal. (1965) Buchi et al. (1965) Lehmann & Marquer Lehmann & Marquer Lehmann & Marquer Lehmann & Marquer Lehmann & Marquer Lehmann & Marquer Lehmann & Marquer Cavalli-Sforza(1986) Hiernaux (1972) Angel (1972) Prokopec(1977) Gusinde(1948) Sporcq(1975) Sporcq (1975) Gusinde(1948) Gusinde(1948) Gusinde(1948) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Gusinde(1948) Hiernaux (1956) Gusinde (1948) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Hiernaux (1956) Godycki(1961) Godycki(1961) Godycki(1961) Godycki(1961) Lourie(1972) Kivalo(1957) Marquer (1963)  (1960) (1960) (1960) (1960) (1960) (1960) (1960)  61  Appendix II  France France Greece Guatemala Guinea Guinea Guinea Guyana India India India India India India India India India India India India India India Italy Japan Japan Japan Japan Japan Japan Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya Kenya  L i f u Islanders Normandie Greeks M a m Indians Guerze Kissi Toma Caribs Andamanese Car Nicobarese Chowrite Garhwali Kota K u l u Kanets Kurumba Lahaul Kanets Malavar Muhammadan Punjabis Sikh Punjabis Southern Nicobarese Terressan Toda Italians Ainu Hiroshima Hokkaido Fukuoka Fukushima Yamaguchi Ababukusu Abagushi Abakisa Abalogoli Abanyore Abatirichi Abatsotso Abesukha Abetakho Akikuyu Iteso Ja-Luo Keiyo Marakwet Sabaot Wataita  Ray (1917) Garnier-Mouronval (1913) Hertzberg et al. (1963) Goff(1948) Vallois(1941) Vallois (1941) Vallois(1941) Farabee (1924) M a n (1882) Ganguly (1976) Ganguly (1976) Eickstedt(1926) Kumar (2000) Holland (1902) Kumar (2000) Holland (1902) Fawcett(1903) Eickstedt(1923) Eickstedt(1923) Ganguly (1976) Ganguly (1976) Gates (1961) Hertzberg et al. (1963) Picon-Reategui et al. (1979) Shapiro & Hulse (1939) Picon-Reategui et al. (1979) Shapiro & Hulse (1939) Shapiro & Hulse (1939) Shapiro & Hulse (1939) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984) Winkler (1984)  62  Appendix II  Magascar Malawi Malaysia Mali Mali Mexico Mexico Mexico Mexico Mexico Mexico Mexico Mexico Mexico Namibia Namibia Nicaragua Nicaragua Nicaragua Nicaragua Nicaragua Nicaragua Norway Panama Panama Panama PNG PNG PNG PNG PNG PNG PNG Peru Peru Peru Peru Russia Russia Russia Rwanda Rwanda Rwanda Rwanda  Antandroy Chewa Brunei Dogon -Sanga Dogon Aztec Chamula Indians Choi Cora Maya Otomi Tarahumare Tarasco Yaqui !Kung Kavango Miskito Rama Ramas Subtiava Sumo Sumus Lapp Choco Cuna San Bias Auyana Awa Butam Gadsup N e w Ireland Ontenu Tairora Macheyenga Piro Quicha Sipibo Ostiaks Samoyedes Vogouls Bahutu Batutsi Hutu Tutsi  Rouquette (1914) Nurse (1972) Knocker (1907) Huizinga & Birnie-Tellier (1966) and Huizinga & de Vetten (1967) Froment & Hiernaux (1984) Hrdlicka(1935) Leche(1936) Gould (1946) Hrdlicka(1935) Steggerda(1932) Hrdlicka(1935) Hrdlicka(1935) Hrdlicka(1935) Hrdlicka(1935) Winkler & Christiansen (1991) Winkler & Christiansen (1991) De Stefano & Jenkins (1972) De Stefano & Jenkins (1972) Schultz(1926) De Stefano & Jenkins (1972) De Stefano & Jenkins (1972) Schultz(1926) Bryn(1932) Hrdlicka(1926) Hrdlicka(1926) Harris (1926) Littlewood(1972) Littlewood(1972) Schlaginhaufen (1964) Littlewood(1972) Schlaginhaufen (1964) Littlewood(1972) Littlewood(1972) Farabee(1922) Farabee(1922) Ferris (1916) Farabee (1922) Roudenko (1914) Roudenko(1914) Roudenko (1914) Oschinsky (1954) Oschinsky (1954) Hiernaux (1956) Hiernaux (1956)  63  Appendix II  Rwanda Senegal Senegal Senegal Senegal Solomon Islands Solomon Islands Solomon Islands Solomon Islands Solomon Islands Solomon Islands Solomon Islands Solomon Islands South Africa Spain Sudan Tanzania Tanzania Tanzania Tanzania Tanzania Timor Turkey Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Uganda Urundi Urundi US US US US US US US US US US  T w a pygmies Bedik Mandyago-Diola Ouolof Peuls Aita Baegu Kwaio Lau Nagovisi Nasioi Ontong Java Ulawa Venda Basque West N i l e Nilotes Baziba Bazinja Hadza Wanyamwezi Zanzibar Arabs Timor Turks Acholi Baganda Bahima Bahiru Bakiga Banyoro Batoro Lubgwara North Uganda Bantu Teso Hutu Tusti Anaktuvuk Pass Apache Barrow Comanche Eastern Aleut Hano Hooper Bay Hopi Laguna Maricopa  Desmarais (1977) Gomila(1971) Vallois (1941) Vallois (1941) Vallois (1941) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) Friedlaender (1987) de Villiers (1972) Marquer (1963) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Hiernaux & Boedhi Hartono (1980) Oschinsky (1954) Oschinsky (1954) Lammers (1963) Hertzberg et al. (1963) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Oschinsky (1954) Hiernaux (1956) Hiernaux (1956) Jamison (1978) Hrdlicka(1935) Jamison (1978) Goldstein (1934) Laughlin(1951) Hrdlicka(1935) Hrdlicka(1928) Hrdlicka(1935) Hrdlicka(1935) Hrdlicka(1935)  64  Appendix II  US us us us us us us us us us us us us us Venezuela Venezuela Viet N a m Viet N a m Vietnam  Mohave Navaho Nunivak Island Papago Pima Point Hope Sioux Southern Ute St. Lawrence Island Wainwright Inuits Western Aleuts Yuma Zuni Choctaw Warao Yupa Mois Vietnamese Annamites  Hrdlicka(1935) Hrdlicka(1935) Hrdlicka, 1928 Hrdlicka(1935) Hrdlicka (1935) Jamison (1978) Hrdlicka (1931) Hrdlicka (1935) Hrdlicka, 1928 Jamison & Zegura (1970) Laughlin(1951) Hrdlicka (1935) Hrdlicka (1935) Collins (1928) Fleischman(1980) Gusinde(1956) Oliver (1968) Oliver (1968) Roux (1905)  Sources of Data Abbie, A . 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