Morphological variation in homo erectus and the origins of developmental plasticity

Homo erectus was the first hominin to exhibit extensive range expansion. This extraordinary departure from Africa, especially into more temperate climates of Eurasia, has been variously related to technological, energetic and foraging shifts. The temporal and regional anatomical variation in H. erectus suggests that a high level of developmental plasticity, a key factor in the ability of H. sapiens to occupy a variety of habitats, may also have been present in H. erectus. Developmental plasticity, the ability to modify development in response to environmental conditions, results in differences in size, shape and dimorphism across populations that relate in part to levels of resource sufficiency and extrinsic mortality. These differences predict not only regional variations but also overall smaller adult sizes and lower levels of dimorphism in instances of resource scarcity and high predator load. We consider the metric variation in 35 human and non-human primate ‘populations’ from known environmental contexts and 14 time-and space-restricted paleodemes of H. erectus and other fossil Homo. Human and non-human primates exhibit more similar patterns of variation than expected, with plasticity evident, but in differing patterns by sex across populations. The fossil samples show less evidence of variation than expected, although H. erectus varies more than Neandertals. To begin to address the above inter-related issues, we compile a fossil and an extant dataset designed to consider the variation in both somatometric and osteometric (cranial and postcranial) data. For Questions 1 and 2, we set out to assess how human and non-human primate populations vary across environments using matched datasets of osteometric and somatometric variables. We define environment broadly to include differences in climate, resource base and any aspect of extrinsic mortality (including predation, parasite loads, etc.). We purposefully limit our comparisons to intraspecific populations in closely circumscribed geographic areas in an attempt to control for similarities in ancestry and adaptation to overall climate (e.g. Bergmann’s and Allen’s rules). This is intended as a conservative approach minimizing differences between populations. Matched datasets are, however, challenging to assemble, and as a consequence, we consider this a preliminary effort and a call for the necessity and usefulness of detailed demic level environmental and somatic data collection from living primates. Because most of the H. erectus remains are craniodental, we have prioritized datasets with at least some cranial measures (see Methods section). For Question 3, we compare these to fossil hominin paleodemes across four species (table 2). All paleodemes represent adult individuals with localities/samples chosen to maximize sample size and limit temporal and geographic distribution. However, the geographic and temporal spread differs between them. Samples by taxon (sample size). Question 1 addresses variability in living humans, and we stress that our aim was not to replicate the abundant work that has established the extensive geographic and climatic variation of recent human populations across the globe [68,69]. Instead we ask whether closely related populations in different environments yield different body sizes (as would be predicted from differing conditions) and whether the degree of variation (CV) differs across these populations. We pay close attention to sex-specific changes within and between populations and whether mixed-sex samples yield similar results, and we assess the signals from somatometric and osteometric data. To accomplish this, we compare amongst living samples and between living and skeletal samples matched for ancestry or geography. We compare skeletal and somatometric data for six recent and one archaeological Arctic population (figure 1; table 3, electronic supplementary material, tables S1 and S2). Comparisons between these populations control for differences due to ancestry and thermal stress but vary on nutritional base and extrinsic mortality. The Point Hope assemblage represents a pre-contact, coastal group living about 200 km north of the Arctic Circle. We focus on remains from the Old Tigara cemetery at Point Hope that dates from AD 1200 to 1700. The archaeological evidence, confirmed by dental microwear, suggests a subsistence base primarily oriented around marine mammals, particularly whale hunting [71,72]. Thus these individuals were leading a completely traditional coastal lifestyle. From the archaeological assemblage at the site, this lifestyle and diet were similar to those of the coastal Inuit at the time of European contact. The diet at contact in this area consisted of 35–65% protein, 30–60% fat and very little carbohydrate [73]. We compare this Point Hope sample to a Wainwright Inuit somatometric dataset collected in the late 1960s and five other indigenous Alaskan samples collected in the earliest 1900s. The individuals sampled for the Wainwright study included all the indigenous individuals living in Wainwright Alaska in 1967–1968 [74]. These individuals were permanently domiciled in Wainwright and include only those individuals who trace both their maternal and paternal ancestry to indigenous people of the immediate area. This area of ancestry includes the coastal region north of Point Hope. The Wainwright sample had the most seasonally consistent resource base of the non-archaeological samples; at the time of data collection, there were two stores for a 40 house village. The dietary percentages were measured for Wainwright in 1971 and include 25% protein, 43.1% fat and 31.9% carbohydrates [75]. The Wainwright population diet will thus have been more consistently available through all seasons and have included substantially greater proportions of carbohydrates than the traditional Point Hope diet. The Wainwright individuals also benefited from year-round presence of medical facilities/treatment although they were certainly more sedentary and so will not have benefited from the frame size increases in stature associated with extensive exercise [76]. The five other indigenous populations were living Alaskan natives from whom data were collected by V. Steffanson between 1906 and 1912 [70]. The populations sampled include an area surrounding Wainwright (the Barrow sample) and north of Point Hope, an area immediately inland from Wainwright and inland and north of Point Hope (Nunatagamiut), and three more eastern coastal populations from MacKenzie Valley, Victoria Island and Coronation Gulf ([70,74,77,78]; figure 1). These populations were sampled over a broader area than the Wainwright sample, and while experiencing the same general thermal stress as the Wainwright individuals and benefitting from some food stores at various outposts the individuals were not, as a rule, permanently domiciled at the outposts. They, thus, lived a more traditional lifestyle and subsistence pattern than at Wainwright, although they were all embedded into a market economy at some level, specifically seeking food resources such as flour and other staples and routinely working on whaling ships [70]. Among the samples, four are coastal samples and one (Nunagiamit) is a more inland population that also came in to the coastal areas seasonally for whale hunting and to find work on ships [70]. The inland population diet was likely to have been more seasonal than the more coastal populations and to have included more protein from terrestrial than marine mammals. At the time of Steffanson’s data collection, the Barrow region was the most integrated into the market economy and likely integrated individuals from the same area as Wainwright (the outpost of which was established in 1904 [74] just before Steffanson’s data collection). The MacKenzie and, especially, the Victoria Island and Coronation Gulf groups to the east were the most isolated at the time of Steffanson’s visits. Steffanson and colleagues [70,79] note that Western medical treatment was available at more distant outposts just once a year. Given these parameters, we anticipate that the Wainwright sample should show relatively large size but the least dimorphism of the living samples given its more recent date, more seasonally consistent resource base and greater access to medical services. We expect that the other five populations will be more similar in size to Wainwright than to Point Hope given greater similarities in resource base. However, we expect dimorphism to be greater in these populations than in Wainwright given greater mortality risks, particularly from predation and accident. The geographic distribution of Arctic human populations used in this study. Adapted and redrawn from Seltzer and Stefansson [70]. Point Hope archaeological sample from AD 1200 to 1700. Wainwright population measured in 1967–1968. All other populations measured between 1906 and 1912 in the specified regions. Sexual dimorphism values (male/female) and means by sex for Alaskan samples. Mean values that do not significantly differ between the living populations and the Point Hope sample (at the 0.05 level with Benjamini–Yekutieli adjustment for multiple comparisons) are indicated by ‘ns’. Significant differences within populations between the sexes are in bold italics. Stature is in cm, and all other dimensions are in mm. To further consider the influence of changing environments, we use data for four populations from Boas’ immigrant studies in the early 1900s ([80]; electronic supplementary material, tables S3 and S4). We matched populations for country of ancestral origin and compared between birth countries. The four populations are Central Italians born in Italy and the USA as well as Scottish individuals born in Scotland and in the USA. We chose these populations for their geographically restricted origin of the foreign-born cohorts and because they possessed relatively large US-born cohorts (>40). Boas was not concerned specifically with resource base but with the overall change in environment from foreign to USA. He used ‘congested areas’ of US cities, principally New York, as his locus of study and included emigres from Europe in the mid- to late 1800s and US born individuals ancestrally from those same countries. Although the immigrant areas of New York City were not particularly bountiful environments, historical data from Scotland suggest that at least the foreign-born Scots likely came from less favourable nutritional and disease conditions; the rapid industrialization of Scotland in the 1800s led by 1840 to extremely negative nutritional conditions across the country such that the 1840s were known as the ‘hungry 40s’, cities were particularly hard hit [81]. We expect then that the direction of change, particularly for the Scottish sample, will be that US-born cohorts of each population will be bigger than their foreign-born cohort and sexual dimorphism will be greater in US-born cohorts due to improved resources. Finally, we compare between twentieth century skeletal samples of similar ancestry, the Hamann-Todd (H-T) collection ‘Whites’ and the Erie County, NY Poorhouse Collection (electronic supplementary material, tables S4 and S5). These comparisons control for area of ancestry, climate and general living conditions. While both the Hammann-Todd and the Erie County Poorhouse include individuals of lower socio-economic status [82,83] and presumably resource base, the poorhouses of the turn of the century were particularly nutritionally challenged, and likely carried a higher parasite and disease load [83]. The Erie County Poorhouse operated in Buffalo, New York from 1851 to 1926 as an almshouse, an insane asylum, and a hospital with maternity and consumptive wards with over 171 000 individuals receiving care and over 11 000 deaths occurring at the institution [84]. By the 1850s nearly all of the countries’ poorhouses were failing, exposing the poor to conditions that negatively affected their occupants’ health [83]. In general, these institutions were marked by poor construction, poor ventilation, poor heating, overcrowding, inadequate medical care and poor-quality food [85]. Food sources of both the institutionalized and non-institutionalized poor who may have sought care at the facility were generally considered to be low cost, high carbohydrate and highly cariogenic foods [86]. In 1856, the New York State Senate issued a statement, indicating that good health within the poorhouses was an ‘impossibility’ [83]. The H-T collection individuals were largely poor, working-class labourers, who were mostly first-generation US citizens from the Northern States [82]. The most frequent causes of death among these individuals were diseases of poverty and exposure (e.g. [82]). While it is not necessarily clear which group encountered worse conditions, and we expect the two groups to be largely similar, we anticipate that the Erie sample will be somewhat smaller than the H-T and show moderate dimorphism. To compare the relationship between skeletal and somatic signals, we compare skeletal and somatometric data for the H-T medical collection ‘White’ sample. Question 2 focuses on plasticity in non-human primates, and as with the human sample, we emphasize localized sub-populations of broadly dispersed species, in this case Macaca and Chlorocebus. We consider this to be a conservative approach based on the logic that broadly dispersed genera may be expected to have inherently higher levels of variability and would thus be less likely to yield a signal of remarkability compared with either humans or H. erectus. Indeed, both macaques and vervets are so adaptable as to often be classified as ‘pest species’ [87]. Future work is needed to address patterns in less widely dispersed genera. To closely assess the intra-specific variation across living populations, we use raw somatometric data from four populations of Kenyan vervets (Chlorocebus aethiops pygerythrus) whose environments differ in terms of elevation, rainfall and resource availability ([88]; figure 2a; table 4 and electronic supplementary material, tables S6–S8). The vervets sample a species that is found in both East and South Africa, but we focus on a restricted part of its range in Kenya. The animals include groups from two highland (Naivasha and Mosiro) and two lowland (Kimana and Samburu) sites; the highland sites are colder and wetter than the lowland sites. Each pair of sites also differ in resource base with cultivated crops, which vervets are known to raid, available at Naivasha and Kimana. Thus, between sites we expect overall larger body size should ensue for Naivasha (the highest elevation) both because of climatic adaptation and because of greater nutritional sufficiency due to the greater availability of cultivated crops. The Kimana animals are expected to be somewhat larger than their lowland counterparts. We also expect greater dimorphism in both of these populations compared to their environmental counterparts due to relatively greater nutritional sufficiency. To assess the relationship between skeletal and somatometric signals, we compare these data with skeletal data from Kenyan vervets housed in the National Museum of Natural History, USA, and we compare across wild and captive skeletal samples. Comparative CV values for (a) postcranial somatometrics for male, Kenyan vervets from Naivasha (open circle), M. mulatta from Cayo Santiago (filled square) and M. fuscata from Wakasa (open square) and (b) femur length for fossil paleodemes and postcranial human samples including twentieth-century skeletal samples from the USA (CMNH, Erie) and an archaeological Arctic sample from Point Hope; 95% confidence intervals included. Note that the relative fossil CV values follow the prediction that shortest interval paleodemes (Atapuerca/Trinil) will have the lowest values. However, differences are not significant and both values seem artificially low compared to extant values. (c) Comparative mean values across fossil paleodemes for cranial length (GOL) with 95% confidence intervals. Sexual dimorphism values (male/female) and means by sex for adult vervet samples for six of 12 variables used in the study. Bold italic values differ significantly between males and females of the same sample. Non-significant values for Mosiro may be due to small sample sizes. Weight is in kg, and all other dimensions are in mm. To assess a more temperate climatic scope, we use somatometric data for 1 captive and 12 wild populations of Japanese macaques (M. fuscata) distributed across the geographic range of Japan ([89]; electronic supplementary material, tables S9 and S10; figure 2a). These comparisons allow for a limited variation in climate and resource base while controlling for predator load. These are compared amongst themselves and with raw skeletal data from a single troop of wild macaques from Chiba Prefecture (Takagoyama Troop T-1; [90–92]). The populations vary in terms of mean annual temperature, with the more northern populations experiencing the lowest temperatures. Populations also differ in terms of rainfall and experience different levels of seasonality (as based on the number of dry versus wet months) and live in different types of forests that are known to differ in energy availability of diets [93]. Deciduous forests have lower secondary productivity and thus are less energy dense seasonally. Environmental details and mean values are presented in the electronic supplementary material, but in brief, the Shiga group (Nagano Prefecture), lives in a deciduous forest, experiences the most seasonality in food sources, and the deepest snow and thus a reduced resource base, suggesting that we should see greater differentiation in size and the least dimorphism compared even to their climate-matched neighbours (Nikko) living under similar thermal stress. Of the Japanese macaques, the closest climate match for our skeletal sample is the Wakasa group. The Japanese macaques have no natural predators. We use raw data from the rhesus macaques (M. mulatta) from Cayo Santiago, Puerto Rico to consider patterns of variation between somatometric data collected in the early 1980s and skeletal metric data from individuals who died during that time and between the Cayo animals and Indian M. mulatta ([89,90,94]; figure 2a; electronic supplementary material, table S11). These data allow for comparison between groups of different predator load and nutritional sufficiency. The founding individuals of the Cayo Santiago colony were M. mulatta collected in Northern India in the 1930s whose descendants continue as a free-ranging but provisioned population on Cayo Santiago Island, Puerto Rico [95]. During the early years of the colony the animals were undernourished, but the cohort included here are animals who died in the 1970s and 1980s who had been reliably provisioned with a high protein (24–26%) monkey chow diet in addition to freely foraging on tropical plants for many generations and thus can be considered to have experienced high nutritional sufficiency [96]. At the same time, the parasite load in the Cayo animals, while apparently asymptomatic, is reported to be as high as laboratory animals who would be symptomatic and treated for parasites [97,97]. Their predator load, however, is very low as there are no natural predators on the island. Additionally, their age at first reproduction (AFR), as would be expected from both high nutritional sufficiency and moderate extrinsic mortality, does not seem delayed (AFR = 4.27; [98]) compared to other populations (AFR = 3, 4.19, 4.5 from three populations reported in [99]). Given their region of origin, we compare a limited number of Indian-derived, wild-shot M. mulatta skeletons with these Cayo Santiago skeletal data. We also compare Cayo Santiago somatic data with similar data from living Indian macaques. We expect Cayo animals will be larger due to resource sufficiency and low predation, but that their size might be somewhat negatively affected by parasite load. We therefore expect a moderate amount of sexual dimorphism. To approximate the close population approach taken above, for Question 3 we apply a narrower lens to the fossil record than previous studies and attempt to construct and assess paleodemes (electronic supplementary material, tables S12–S15). Because we are interested in variation, paleodemes must contain at least two individuals in a somewhat circumscribed temporal span and geographic region. To consider the intraspecific variation across populations we require at least two, and preferably three, paleodemes per fossil taxon. These criteria severely limit our choices of fossil comparators. We consider paleodemes of H. erectus and, to provide a comparative framework, we also look at Neandertal and other Middle Pleistocene samples. Only Neandertals have a sufficient number of paleodemes for intraspecific comparisons and small sample sizes and preservation preclude us from considering the variation in paleodemes of earliest Homo at all. Each paleodeme was constructed to sample as little time as possible, although apart from Ngandong and Sima de los Huesos localities, most are more time transgressive than the extant samples. Temporal duration is unequal across samples. The fossil samples are by necessity mixed-sex and we thus limit ourselves to sampling from just genus Homo among the hominins. Homo erectus as defined here ranges in age from about 1.9 Ma to at least 250 000 years ago or younger and from Africa to Southeast Asia (figure 2b,c; electronic supplementary material, tables S12 and S14). Within this broad swath, we assess two samples that are thought to be of short or even single depositional events: Dmanisi, Georgia and Ngandong, Indonesia. The Dmanisi assemblage is dated to about 1.77 Ma and has been argued to have been deposited over no more than about 10 000 years [42]. The Ngandong assemblage, although of contested absolute age (possibly ∼550 000 or 50 000 years old), is argued on all accounts to be a catastrophic depositional assemblage [100,101]. To expand the comparison, we include five potentially more time transgressive units: Zhoukoudian, China; Sangiran and Trinil, Indonesia; Daka, Ethiopia; and Koobi Fora, Kenya. We limit the Zhoukoudian assemblage to just those hominins from layers 7 to 11 (about 750 000 years old, with a youngest age of 670 000 years; [102]), which may be comparable to the age distribution of the Neandertal cohorts (see below). The Zhoukoudian femoral specimens are restricted to layers 8–9 and should, therefore, be more time constrained. The Koobi Fora H. erectus specimens cover about 130 000 years of time ranging in age from about 1.5 to 1.63 Ma (for KNM-ER 3733; [103]). The Sangiran specimens are more time transgressive and include about a half million years of time from about 1.1 to 1.6 Ma [104]. The Trinil and Daka femoral assemblages (∼900 000 and 960 000 years old, respectively) are each of unknown depositional span; while they could be tightly time constrained, strictly speaking, the time between specimens is unknown and there is no close capping age in either context (see [104,105]). It should be noted that the requirement to constrain time and locality and maximize individuals per sample excludes some notable cranial fossils from the analyses. The exclusions include sites with single crania (e.g. Olorgesalie, Daka and Trinil), as well as those with too great a time span between individuals (e.g. Olduvai Gorge where OH 9 and OH 12 are separated by more than a half million years) or a time span that would be greatly expanded by including the entire assemblage (e.g. we exclude the upper Bapang Formation specimens from Sangiran and specimens from level 6 and higher at Zhoukoudian). The total H. erectus sample includes 50 fossil specimens. Of these paleodemes, the Dmanisi sample provides the best evidence of extrinsic mortality and nutritional sufficiency signals. The Dmanisi site and hominin remains show evidence of carnivore activity and accumulation [106], suggesting predator load (and extrinsic mortality) was high. A few individuals also show signs of generalized stress as indicated by enamel hypoplasia [107], potentially also an indicator of issues related to high extrinsic mortality. The temperate and seasonal climatic zone of the site has also been used to infer less resource abundance or at least a more challenging resource environment compared to that of East Africa [106]. The Zhoukoudian remains are latitudinally similarly placed and should have the same seasonality and resource signal as Dmanisi. However, their direct evidence of predator load is not as great as at Dmanisi. Thus we would predict smaller size (based on resources and extrinsic mortality due to disease) in Dmanisi and moderate dimorphism. To provide a comparative context we sample Neandertals, Sima de los Huesos and H. naledi (figure 2c; electronic supplementary material, tables S13 and S15). Each of these species is geographically more restricted than H. erectus. For H. neanderthalensis, we compare five samples: three from single localities (El Sidrón, Spain, Shanidar, Iraq, and Krapina, Croatia); and two from broader regions (Europe (40–80 ka) and the Near East (50–130 ka); [108–110]). While the Shanidar remains are more geographically restricted than the European sample, they span many, poorly dated metres of section that likely comprise some 30–60 000 years of time [110]. Owing to small numbers of individuals and few overlapping variables among them, the Shanidar sample is not subdivided further. The temporal range for Shanidar is thus potentially comparable to that of the European sample. Owing to fragmentation, the Krapina remains offer a more limited set of mandibular comparisons from about 130 000 years ago. Our El Sidrón sample is also limited to mandibular data and offers a more time-restricted comparison of likely about 46 000 years ago and perhaps of a single depositional event [111]. The Near Eastern Neandertals are fewer in number and cover a greater span of time (∼60 000 years) than the European individuals. We include data from the Sima de los Huesos assemblage which has been argued to be of short duration and perhaps even a catastrophic event [112]. Given their close genetic relationship to later Neandertals [113] as well as their restricted geographic and abbreviated temporal range, we believe these to be a relevant comparison. Finally, we consider a large number of H. naledi individuals (n = 8) whose geological age and duration of deposition are unknown [114]. Although the published raw data are limited to sub-trochanteric femoral dimensions, these dimensions are also available for a number of other fossil paleodemes and provide a means of estimating body weight in these samples as well. As we are interested in the variation in body size, their inclusion seems warranted. Because we are interested in patterns of variation within and among taxa, rather than differentiating between taxa, we explicitly avoid using variables that show relatively little inherent variation and purposefully include those with greater variation (we would do the opposite if we were interested in circumscribing species groups). Dental variation, especially of the M1, is low relative to other variables [115], presumably due to high heritability, and we therefore exclude these variables. We include variables from both high stress (facial and joint surfaces) and low stress (neurocranial and other postcranial) environments when possible, as the former may be more variable than the latter [115]. We are further limited by the kinds of data typically collected in extant studies, and we attempt to proxy these data from skeletal samples by matching somatometric individual bone elements (e.g. thigh length to femur length; head length to glabello-occipital length (GOL)). We are similarly limited by the fragmentary nature of the fossil record and so include variables that have the highest representation in H. erectus samples (e.g. GOL, cranial capacity and mandibular heights and breadths). While stature and body weight estimates are seemingly easily made from skeletal remains, they require a suite of inferences about body proportions and scaling that because of compounding error estimates may obscure variation between groups. For this reason, we focus more on direct skeletal measures using directly measured stature or weight for comparisons among living groups. The result of high developmental plasticity is variation in size across populations and so we compare adult means for each measure across samples as described above. However, because developmental plasticity works on a species’ inherent ability to vary (i.e. its variability) there is also the question of whether a different measure within a single population might also be a useful proxy for assessing variability of a species. That is, should we expect species with a greater ability to vary to also show more variation within each population? If so, should each population of the species show higher CVs for any given measure than do less variable species? As variation is size dependent, we use the CV to compare the variation adjusted for relative size across measures, and we adjust CVs for small sample size as necessary [116,117]. Arguably, the absolute size variation across demes is itself more important for understanding variability within a taxon than is CV. However, it would be ideal were CV to prove to be a good proxy for variability as that would allow us to measure species variability from just one paleodeme. Such an event would greatly increase the number of taxa available for inclusion. For the purposes of this initial evaluation we use univariate comparisons. The primary reason for this approach is the desire to contextualize the variation across H. erectus populations with other fossil samples and the resulting dearth of overlapping variables across all potential samples. Multivariate rank-order processes are not possible given the lack of overlapping variables across all samples. However, these may prove useful in future for more restricted samples. Additionally, while we have individual raw data measurements for our main comparative samples (vervets, M. mulatta, M. fuscata skeletal sample, Boas, H-T, Erie and Point Hope H. sapiens samples and the fossil samples), in order to expand potential comparisons we also use summary data from the literature for some living groups (M. fuscata somatometrics, Arctic H. sapiens). These latter studies provide only means and standard deviations, and so Fligner-Killen (sensu [118,119]) or resampling methods (sensu [120]) are not feasible for these datasets. We therefore compare between means and CVs following Lewontin [121]. To protect our alpha values due to multiple comparisons we use the Benjamini and Yekutieli method [122] for mean values to avoid false negatives in the more conservative Bonferroni correction. Analyses were run with Bonferroni as a comparison and very few differences resulted between the two. While recognizing the inherent limits of these tests (see [118] especially for the CV ratio test), they offer an initial assessment of the question given our very small fossil sample sizes.