1. Clay model studies are a popular tool to identify predator–prey interactions that are challenging to observe directly in the field. But despite its wide use, the method's applicability is limited by its low taxonomic resolution. Attack marks on clay models are usually identified visually, which only allows classification into higher taxonomic levels of predators. Thus, the method is often biased, lacks proof and, above all, standardization.
2. Here, we tested whether precise identification of attackers can be provided by amplification and sequencing of mitochondrial DNA left in bite marks on clay models. We validated our approach in a controlled laboratory study as well as in a field experiment using clay models of a common European amphibian, the European fire salamander Salamandra salamandra. DNA‐based taxonomic assignments were additionally compared to visual assessments of bite marks.
3. We show that trace DNA of attackers can be routinely isolated and sequenced from bite marks, providing accurate species‐level classification. In contrast, visual identification alone yielded a high number of unassigned predator taxa. We also highlight the sensitivity of the method and show likely sources of contamination as well as probable cases of secondary and indirect predation.
4. Our standardized approach for species‐level attacker identification opens up new possibilities far beyond the standard use of clay models to date, including food web studies at unprecedented detail, invasive species monitoring as well as biodiversity inventories.

中文翻译：

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一种从人工猎物上留下的DNA痕迹识别攻击者的扩增子测序方案

1. 黏土模型研究是一种流行的工具，可用于识别捕食者与猎物之间的相互作用，这些挑战在现场很难直接观察到。但是，尽管使用广泛，但该方法的适用性受到其分类学分辨率低的限制。通常用肉眼识别粘土模型上的攻击痕迹，这只能将其分类为更高分类等级的食肉动物。因此，该方法经常有偏差，缺乏证据，尤其是标准化。
2. 在这里，我们测试了是否可以通过扩增和测序留在粘土模型上咬痕中的线粒体DNA来提供对攻击者的精确识别。我们在对照实验室研究以及使用常见的欧洲两栖动物，欧洲火sal Salamandra salamandra的黏土模型的野外实验中验证了我们的方法。此外，将基于DNA的分类分配与视觉评估咬痕进行了比较。
3. 我们表明，攻击者的痕量DNA可以常规地从咬痕中分离出来并进行测序，从而提供准确的物种级分类。相反，仅凭视觉识别就可产生大量未分配的捕食者类群。我们还强调了该方法的敏感性，并显示了可能的污染源以及可能发生的二次和间接捕食。
4. 我们用于物种级别攻击者识别的标准化方法为迄今为止的粘土模型标准使用提供了更多的可能性，包括对食物网络的前所未有的详细研究，入侵物种监测以及生物多样性清单。