We are far from knowing all species living on the planet. Understanding biodiversity is demanding and requires time and expertise. Most groups are understudied given problems of identifying and delimiting species. DNA barcoding emerged to overcome some of the difficulties in identifying species. Its limitations derive from incomplete taxonomic knowledge and the lack of comprehensive DNA barcode libraries for so many taxonomic groups. Here, we evaluate how useful barcoding is for identifying arthropods from highly diverse leaf litter communities in the southern Appalachian Mountains (USA). We used three reference databases and several automated classification methods on a data set including several arthropod groups. Acari, Araneae, Collembola, Coleoptera, Diptera, and Hymenoptera were well represented, showing different performances across methods and databases. Spiders performed the best, with correct identifications rates to species and genus levels of ~50% across databases. Springtails performed poorly, no barcodes were identified to species or genus. Other groups showed poor to mediocre performance, from around 3% (mites) to 20% (beetles) correctly identified barcodes to species, but also with some false identifications. In general, BOLD-based identification offered the best identification results but, in all cases except spiders, performance is poor, with less than a fifth of specimens correctly identified to genus or species. Our results indicate that the soil arthropod fauna is still insufficiently documented, with many species unrepresented in DNA barcode libraries. More effort toward integrative taxonomic characterization is needed to complete our reference libraries before we can rely on DNA barcoding as a universally applicable identification method.

中文翻译：

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根据当前的 DNA 条形码参考库，大多数土壤和凋落物节肢动物都无法识别

我们远未了解地球上生活的所有物种。了解生物多样性是一项艰巨的任务，需要时间和专业知识。由于识别和界定物种的问题，大多数群体都没有得到充分研究。DNA条形码的出现是为了克服物种识别中的一些困难。其局限性源于分类学知识不完整以及缺乏针对众多分类群的综合 DNA 条形码库。在这里，我们评估了条形码对于识别来自阿巴拉契亚山脉南部（美国）高度多样化的落叶群落中的节肢动物的有用性。我们在包括几个节肢动物群的数据集上使用了三个参考数据库和几种自动分类方法。蜱螨目、蜘蛛目、跳虫目、鞘翅目、双翅目和膜翅目都有很好的代表性，在不同方法和数据库中表现出不同的表现。蜘蛛表现最好，在整个数据库中物种和属水平的正确识别率约为 50%。跳尾鱼表现不佳，没有识别出物种或属的条形码。其他群体的表现较差甚至中等，大约 3%（螨虫）到 20%（甲虫）正确识别了物种条形码，但也有一些错误识别。一般来说，基于粗体的识别提供了最好的识别结果，但在除蜘蛛之外的所有情况下，性能都很差，只有不到五分之一的标本被正确识别为属或种。我们的结果表明，土壤节肢动物区系的记录仍然不足，许多物种在 DNA 条形码文库中没有代表性。在我们可以依赖 DNA 条形码作为普遍适用的识别方法之前，需要付出更多的努力来完成我们的参考库的综合分类学表征。