Archaeological and palaeontological excavations frequently produce large quantities of highly fragmentary bone. These bones can help to answer questions regarding past environments and human and animal lifeways via a number of analytical techniques but this potential is limited by the inability to distinguish individual animals and generate sufficiently large samples. Using stable carbon and nitrogen isotope values of bone collagen (δ¹³C, δ¹⁵N), we present a metric to identify the number of isotopically distinct specimens (NIDS) from highly fragmented faunal assemblages. We quantified the amount of intra-individual isotopic variation by generating isotopic data from multiple elements from individual animals representing a wide variety of taxa as well as multiple samples from the same skeletal element. The mean intra-individual variation (inter-bone) was 0.52‰ (σ = 0.45) (Euclidean distance between two points in isotopic bivariate space), while the mean intra-bone variation was 0.63‰ (σ = 0.06). Using archaeological data consisting of large numbers of individual taxa from single sites, the mean inter-individual isotopic variation was 1.45‰ (σ = 1.15). We suggest the use of 1.50‰ in bivariate (δ¹³C, δ¹⁵N) space as a metric to distinguish NIDS. Blind tests of modelled archaeological datasets of different size and isotopic variability resulted in a rate of misclassification (two or more elements from the same individual being classified as coming from different individuals) of < 5%.

考古和古生物学挖掘经常产生大量高度破碎的骨骼。这些骨骼可以通过多种分析技术帮助回答有关过去环境以及人类和动物生活方式的问题，但这种潜力受到无法区分个体动物和生成足够大样本的限制。使用稳定的骨胶原碳和氮同位素值 ( δ ¹³ C, δ ¹⁵N)，我们提出了一个度量来识别来自高度分散的动物群落的同位素不同标本 (NIDS) 的数量。我们通过从代表各种分类群的个体动物的多个元素以及来自同一骨骼元素的多个样本生成同位素数据来量化个体内同位素变异的数量。平均个体内变异（骨间）为 0.52‰（σ  = 0.45）（同位素二元空间中两点之间的欧几里德距离），而平均骨内变异为 0.63‰（σ  = 0.06）。使用由来自单个地点的大量个体分类群组成的考古数据，平均个体间同位素变异为 1.45‰ ( σ  = 1.15)。我们建议在双变量 (δ ¹³ C, δ ¹⁵ N) 空间作为区分 NIDS 的度量。对不同大小和同位素变异性的建模考古数据集的盲测导致错误分类率（来自同一个人的两个或多个元素被归类为来自不同个人）< 5%。