Estimating stature in fossil hominids: which regression model and reference sample to use?

coResearchers have long appreciated the significant relationship between body size and an animal's overall adaptive strategy and life history. However, much more emphasis has been placed on interpreting body size than on the actual calculation of it. One measure of size that is especially important for human evolutionary studies is stature. Despite a long history of investigation, stature estimation remains plagued by two methodological problems: (1) the choice of the statistical estimator, and (2) the choice of the reference population from which to derive the parameters.This work addresses both of these problems in estimating stature for fossil hominids, with special reference to A.L. 288-1 (Australopithecus afarensis) and WT 15000 (Homo erectus). Three reference samples of known stature with maximum humerus and femur lengths are used in this study: a large (n=2209) human sample from North America, a smaller sample of modern human pygmies (n=19) from Africa, and a sample of wild-collected African great apes (n=85). Five regression techniques are used to estimate stature in the fossil hominids using both univariate and multivariate parameters derived from the reference samples: classical calibration, inverse calibration, major axis, reduced major axis and the zero-intercept ratio model. We also explore a new diagnostic to test extrapolation and allometric differences with multivariate data, and we calculate 95% confidence intervals to examine the range of variation in estimates for A.L. 288-1, WT 15000 and the new Bouri hominid (contemporary with [corrected] Australopithecus garhi). Results frequently vary depending on whether the data are univariate or multivariate. Unique limb proportions and fragmented remains complicate the choice of estimator. We are usually left in the end with the classical calibrator as the best choice. It is the maximum likelihood estimator that performs best overall, especially in scenarios where extrapolation occurs away from the mean of the reference sample. The new diagnostic appears to be a quick and efficient way to determine at the outset whether extrapolation exists in size and/or shape of the long bones between the reference sample and the target specimen.     

Lessons from the size efficiency hypothesis II. The mire of complexity

Over the years, models and concepts developed to explain the behaviour of lake plankton have been generalized and extended to most parts of the limnetic community. This development has now fused with parallel research programs into stream and marine benthos and fish, to yield an imposing literature dealing with complex interactions in aquatic communities. Although the size of this literature has grown, its basic elements, i.e. the allometries of organismal capacity and environmental opportunity, remain those associated with the seminal size efficiency hypothesis. Unfortunately, the difficulties that eventually buried that hypothesis in a welter of detail and special cases were not resolved, so the newer, broader concepts associated with complex interactions remain difficult or impossible to test. Those concepts are so subjective, poorly defined, and variably interpreted that they are more effective in explaining our observations after the fact than in predicting them before-hand. Despite predictive failure, such explanatory models have achieved wide acceptance. Once accepted as substitutes for predictive theory, they mire the advance of science by hiding its deficiencies. One solution to this cloying complexity is insistence that the theories of ecology specify simple, observable response variables so that theories may be evaluated by their predictive power. Components of a general refuge concept illustrate the point. This policy has implications for environmental science well beyond the confines of plankton ecology.Dedicated to Dr Karl Banse, School of Oceanography, University of Washington on his 60th Birthday.     

Phyletic size change and brain/body allometry: A consideration based on the African pongids and other primates

A problematic aspect of brain/body allometry is the frequency of interspecific series which exhibit allometry coefficients of approximately 0.33. This coefficient is significantly lower than the 0.66 value which is usually taken to be the interspecific norm. A number of explanations have been forwarded to account for this finding. These include (1) intraspecificallometry explanations, (2) nonallometric explanations, and (3) Jerison’s “extraneurons” hypothesis, among others. The African apes, which exhibit a lowered interspecific allometry coefficient, are used here to consider previous explanations. These are found to be inadequate in a number of ways, and an alternative explanation is proposed. This explanation is based on patterns of brain and body size change during ontogeny and phytogeny. It is argued that the interspecific allometry coefficient in African apes parallels the intraspecific one because similar ontogenetic modifications of body growth separate large and small forms along each curve. In both cases, body size differences are produced primarily by growth in later postnatal periods, during which little brain growth occurs. Data on body growth, neonatal scaling, and various lifehistory traits support this explanation. This work extends previous warnings that sizecorrected estimates of relative brain size may not correspond very closely to our understanding of the behavioral capacities of certain species in lineages characterized by rapid change in body size.     

Why get big in the cold? Size–fecundity relationships explain the temperature‐size rule in a pulmonate snail (Physa)

Most ectotherms follow a pattern of size plasticity known as the temperature‐size rule where individuals reared in cold environments are larger at maturation than those reared in warm environments. This pattern seems maladaptive because growth is slower in the cold so it takes longer to reach a large size. However, it may be adaptive if reaching a large size has a greater benefit in a cold than in a warm environment such as when size‐dependent mortality or size‐dependent fecundity depends on temperature. I present a theoretical model showing how a correlation between temperature and the size–fecundity relationship affects optimal size at maturation. I parameterize the model using data from a freshwater pulmonate snail from the genus Physa. Nine families were reared from hatching in one of three temperature regimes (daytime temperature of 22, 25 or 28 °C, night‐time temperature of 22 °C, under a 12L : 12D light cycle). Eight of the nine families followed the temperature‐size rule indicating genetic variation for this plasticity. As predicted, the size–fecundity relationship depended upon temperature; fecundity increases steeply with size in the coldest treatment, less steeply in the intermediate treatment, and shows no relationship with size in the warmest treatment. Thus, following the temperature‐size rule is adaptive for this species. Although rarely measured under multiple conditions, size–fecundity relationships seem to be sensitive to a number of environmental conditions in addition to temperature including local productivity, competition and predation. If this form of plasticity is as widespread as it appears to be, this model shows that such plasticity has the potential to greatly modify current life‐history theory.     

Test of the Optimal Body Size Model for Strepsirhines

We determined if data on strepsirhine body and home range sizes support an optimal body size (OBS) model of 100 g, as predicted from studies of energetics in terrestrial mammals. We also tested the following predictions of the OBS model: 1) relationships between body and home range sizes will change slope and sign above and below the OBS threshold of 100 g and 2) best-fit lines for OBS regression models (above and below the 100-g threshold) will intersect at ca. 100 g (range of 80–250 g). We collected data on body mass, home range size, and vertical ranging behavior for 37 strepsirhines from the literature. Linear regression analyses and phylogenetic independent contrasts methods revealed that body size is a significant determinant of both 2-dimensional (ha) and 3-dimensional (km³) home range sizes only in taxa weighing >100 g. There were consistent changes in the sign of the slopes above and below the OBS threshold. The intersections of the best-fit lines were within the OBS range for the body size to 3-dimensional home range comparisons. Thus, the data provide some support for the OBS model in strepsirhines. However, no regression model was statistically significant for the taxa below the OBS threshold, which may reflect small sample sizes. Also, no slope differed significantly between taxa above and below the OBS. Significant correlations between body and home range sizes for the complete data sets refute the √-shaped constraint space predicted via the OBS model.     

Body size estimators in primate skeletal material

A series of twenty-three skeletal variables are tested for their utility as estimators of body size, measured as partial skeletal weight, over 286 Old World anthropoids. Several variables proved to be consistently accurate in this for the present sample: bizygomatic breadth, bicondylar femoral width, skull length, orbital width, basioninion, femoral circumference and vertebral area. The only reasonably acceptable mandibular measurement was mandibular breadth. Other variables that have been used as size estimators in previous studies proved to be less accurate.