Estimating sexual size dimorphism in fossil species from posterior probability densities.
Estimating sexual size dimorphism in fossil species from posterior probability densities.
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从后验概率密度估计化石物种中性别大小二态性。
DOI：
10.1073/pnas.2113943118
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Suwa G
中科院分区：
文献类型：
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作者：
Sasaki T;Semaw S;Rogers M;Simpson S;Beyene Y;Asfaw B;White T;Suwa G
在进化生物学中，准确刻画性别二型性是至关重要的，因为它对于理解涉及物种生殖和资源利用策略的现在和过去的适应具有重要意义。然而，推断化石组合中的二形性是困难的，特别是在二形性相对较低的情况下。估计化石二态程度的常用方法有平均法、二项式二态指数法和变异系数法。据报道，这些方法高估了低水平的二态现象，这在研究灵长类动物的犬类体型二态及其与生殖策略的关系等问题时是有问题的。在这里，我们介绍了后验密度峰值(PdPeak)方法，该方法利用贝叶斯推断来提供二态水平和性别内方差的后验概率密度。后方密度最高的点称为pdPeak。我们研究了pdPeak方法的性能，并与上述传统方法进行了比较，1)计算机生成的样本模拟了一系列条件，2)应用于现有已知性别类人猿的犬冠直径数据集。结果表明，与其他方法相比，pdPeak方法能够在更宽的二态水平范围内无偏估计，并且唯一地提供可靠的区间估计。虽然当一些分布假设被违反时，需要注意它的低估趋势，但我们证明了pdPeak方法能够在比以前更低的二态水平上实现更准确的二态估计，这对于阐明人类进化是重要的。
Accurate characterization of sexual dimorphism is crucial in evolutionary biology because of its significance in understanding present and past adaptations involving reproductive and resource use strategies of species. However, inferring dimorphism in fossil assemblages is difficult, particularly with relatively low dimorphism. Commonly used methods of estimating dimorphism levels in fossils include the mean method, the binomial dimorphism index, and the coefficient of variation method. These methods have been reported to overestimate low levels of dimorphism, which is problematic when investigating issues such as canine size dimorphism in primates and its relation to reproductive strategies. Here, we introduce the posterior density peak (pdPeak) method that utilizes the Bayesian inference to provide posterior probability densities of dimorphism levels and within-sex variance. The highest posterior density point is termed the pdPeak. We investigated performance of the pdPeak method and made comparisons with the above-mentioned conventional methods via 1) computer-generated samples simulating a range of conditions and 2) application to canine crown-diameter datasets of extant known-sex anthropoids. Results showed that the pdPeak method is capable of unbiased estimates in a broader range of dimorphism levels than the other methods and uniquely provides reliable interval estimates. Although attention is required to its underestimation tendency when some of the distributional assumptions are violated, we demonstrate that the pdPeak method enables a more accurate dimorphism estimate at lower dimorphism levels than previously possible, which is important to illuminating human evolution.