Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology, Trondheim, NO-7491, Norway.
Zoology Department, Stockholm University, Stockholm, 106 91, Sweden.
BMC Biol. 2024 Sep 27;22(1):215. doi: 10.1186/s12915-024-02010-z.
Zoology's dark matter comprises hyperdiverse, poorly known taxa that are numerically dominant but largely unstudied, even in temperate regions where charismatic taxa are well understood. Dark taxa are everywhere, but high diversity, abundance, and small size have historically stymied their study. We demonstrate how entomological dark matter can be elucidated using high-throughput DNA barcoding ("megabarcoding"). We reveal the high abundance and diversity of scuttle flies (Diptera: Phoridae) in Sweden using 31,800 specimens from 37 sites across four seasonal periods. We investigate the number of scuttle fly species in Sweden and the environmental factors driving community changes across time and space.
Swedish scuttle fly diversity is much higher than previously known, with 549 putative specie) detected, compared to 374 previously recorded species. Hierarchical Modelling of Species Communities reveals that scuttle fly communities are highly structured by latitude and strongly driven by climatic factors. Large dissimilarities between sites and seasons are driven by turnover rather than nestedness. Climate change is predicted to significantly affect the 47% of species that show significant responses to mean annual temperature. Results were robust regardless of whether haplotype diversity or species-proxies were used as response variables. Additionally, species-level models of common taxa adequately predict overall species richness.
Understanding the bulk of the diversity around us is imperative during an era of biodiversity change. We show that dark insect taxa can be efficiently characterised and surveyed with megabarcoding. Undersampling of rare taxa and choice of operational taxonomic units do not alter the main ecological inferences, making it an opportune time to tackle zoology's dark matter.
动物学的暗物质包括高度多样化、知之甚少的分类群,它们在数量上占优势,但在温带地区,尽管魅力分类群得到了很好的理解,但它们在很大程度上仍未被研究。暗分类群无处不在,但由于多样性高、数量多、体型小,历史上一直阻碍着它们的研究。我们展示了如何使用高通量 DNA 条形码(“宏条形码”)阐明昆虫学的暗物质。我们使用来自瑞典四个季节的 37 个地点的 31800 个标本,揭示了瑞典的粪蝇(双翅目:粪蝇科)的高丰度和多样性。我们研究了瑞典粪蝇物种的数量以及驱动时间和空间上群落变化的环境因素。
与以前记录的 374 种相比,瑞典粪蝇的多样性要高得多,检测到了 549 种可能的种。物种群落的层次模型揭示了粪蝇群落受纬度的高度结构化,并受气候因素的强烈驱动。站点和季节之间的巨大差异是由周转率而不是嵌套性驱动的。气候变化预计会对 47%对年平均温度有显著反应的物种产生重大影响。无论使用单倍型多样性还是物种代理作为响应变量,结果都是稳健的。此外,常见类群的物种水平模型可以很好地预测总体物种丰富度。
在生物多样性变化的时代,了解我们周围大部分的多样性是至关重要的。我们表明,宏条形码可以有效地描述和调查暗昆虫类群。稀有类群的抽样不足和操作分类单元的选择不会改变主要的生态推论,因此现在是解决动物学暗物质的恰当时机。