Departamento de Biología, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
TRAGSATEC, Madrid, Spain.
Sci Rep. 2024 Feb 28;14(1):4876. doi: 10.1038/s41598-024-54735-0.
The digitization of natural history specimens and the popularization of citizen science are creating an unprecedented availability of large amounts of biodiversity data. These biodiversity inventories can be severely affected by species misidentification, a source of taxonomic uncertainty that is rarely acknowledged in biodiversity data management. For these reasons, taxonomists debate the use of online repositories to address biological questions at the species level. Hedera L. (ivies) provides an excellent case study as it is well represented in both herbaria and online repositories with thousands of records likely to be affected by high taxonomic uncertainty. We analyze the sources and extent of taxonomic errors in the identification of the European ivy species by reviewing herbarium specimens and find a high misidentification rate (18% on average), which varies between species (maximized in H. hibernica: 55%; H. azorica: 48%; H. iberica: 36%) and regions (maximized in the UK: 38% and Spain: 27%). We find a systematic misidentification of all European ivies with H. helix behind the high misidentification rates in herbaria and warn of even higher rates in online records. We compile a spatial database to overcome the large discrepancies we observed in species distributions between online and morphologically reviewed records.
自然历史标本的数字化和公民科学的普及正在创造前所未有的大量生物多样性数据的可用性。这些生物多样性清单可能会受到物种误识别的严重影响,而这种分类学不确定性是生物多样性数据管理中很少被承认的一个来源。出于这些原因,分类学家就在线存储库是否可用于解决物种层面的生物学问题展开了辩论。常春藤属(常春藤)就是一个很好的案例研究,因为它在标本馆和在线存储库中都有很好的代表,有数千条记录可能受到高度分类学不确定性的影响。我们通过审查标本馆标本来分析鉴定欧洲常春藤物种时分类错误的来源和程度,并发现高错误识别率(平均为 18%),在不同物种之间存在差异(在 H. hibernica 中最高:55%;在 H. azorica 和 H. iberica 中最高:48%)和地区(在英国和西班牙最高:38%和 27%)。我们发现所有欧洲常春藤都存在系统的误识别,而 H. helix 在标本馆中的高错误识别率背后,我们警告在线记录中的错误识别率甚至更高。我们编制了一个空间数据库,以克服我们在在线和形态学审查记录之间观察到的物种分布的巨大差异。