Metabarcoding Analysis of Arthropod Pollinator Diversity: A Methodological Comparison of eDNA Derived From Flowers and DNA Derived From Bulk Samples of Insects

生物 节肢动物 环境DNA 传粉者 昆虫 生态学 动物 生物多样性 授粉 花粉
作者
Kara S. Jones,David S. Pilliod,Aaron W. Aunins
出处
期刊:Molecular Ecology [Wiley]
卷期号:34 (14): e70003-e70003 被引量:6
标识
DOI:10.1111/mec.70003
摘要

Limitations of traditional insect sampling methods have motivated the development and optimisation of new non-lethal methods capable of quantifying diverse arthropod communities. Environmental DNA (eDNA) metabarcoding using arthropod-specific primers has recently been investigated as a novel way to characterise arthropod communities from the DNA they deposit on the surface of plants. This sampling method has had demonstrated success, but pollinators-especially bees-are oddly underrepresented in these studies. To evaluate this inconsistency, we investigated the limitations of eDNA metabarcoding for bees and other pollinators. We compared pollinator diversity derived from eDNA extracted from flowers and DNA extracted from pulverised bulk samples of insects collected from vane traps deployed at the same sites using three metabarcoding primers, two of which target arthropods generally (COI-Jusino and 16S-Marquina) and one that targets bumblebees (Bombus spp., COI-Milam). Across methods, we detected 77 insect families from 9 orders. The COI-Jusino marker amplified the highest taxonomic diversity compared to 16S-Marquina and COI-Milam. More amplicon sequence variants (ASVs) were recovered from vane traps (blue: 1357, yellow: 1542) than flowers (245), but only 23% of families and 13% of genera were shared among methods, indicating that flowers and blue and yellow vane traps may each sample different parts of the available arthropod community. Of 29 flower samples with known bee visitations, only 10 samples had bee detections from eDNA, and incomplete reference databases hindered assignment to species. Although our study provides additional evidence for the usefulness of eDNA metabarcoding for characterising arthropod communities, significant challenges remain when using eDNA metabarcoding methods to identify and quantify pollinator communities, especially bees.
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