Hens S M, Konigsberg L W, Jungers W L
Department of Cell Biology and Anatomy, Johns Hopkins University School of Medicine, 725 North Wolfe Street, Baltimore, MD 21205, USA.
J Hum Evol. 2000 Jun;38(6):767-84. doi: 10.1006/jhev.1999.0382.
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.
长期以来，合作研究人员一直认识到体型与动物整体适应策略和生活史之间的重要关系。然而，人们更多地强调对体型的解读，而非对其实际计算。对于人类进化研究而言，一个特别重要的体型测量指标是身高。尽管有很长的研究历史，但身高估计仍然受到两个方法学问题的困扰：（1）统计估计量的选择，以及（2）用于推导参数的参考人群的选择。这项工作在估计化石原始人类的身高时解决了这两个问题，特别提及了A.L. 288 - 1（阿法南方古猿）和WT 15000（直立人）。本研究使用了三个已知身高且有肱骨和股骨最大长度的参考样本：一个来自北美的大型人类样本（n = 2209）、一个来自非洲的现代人类俾格米人较小样本（n = 19）以及一个野外采集的非洲大猩猩样本（n = 85）。使用从参考样本中得出的单变量和多变量参数，采用五种回归技术来估计化石原始人类的身高：经典校准、反向校准、主轴、简化主轴和零截距比率模型。我们还探索了一种新的诊断方法，以测试多变量数据的外推和异速生长差异，并计算95%置信区间，以检验对A.L. 288 - 1、WT 15000和新的布吕人原始人类（与[修正后的]加里南方古猿同时期）估计值的变化范围。结果常常因数据是单变量还是多变量而有所不同。独特的肢体比例和破碎的遗骸使估计量的选择变得复杂。最终，我们通常会认为经典校准器是最佳选择。它是总体表现最佳的最大似然估计量，尤其是在远离参考样本均值进行外推的情况下。这种新的诊断方法似乎是一种快速有效的方法，可在一开始就确定参考样本和目标标本之间长骨的大小和/或形状是否存在外推情况。
