Beschreibung
Meta-barcoding approaches are increasingly being used for characterization and monitoring of species assemblages. Yet reliable data on species detection rates in meta-barcoding approaches are rare as the actual species composition present in the samples is usually unknown. We employed a nested calibration approach to obtain reliable data on species detection rates and investigate potential taxonomic bias. For this purpose we used five light trap samples collected in the Danube National Park, Austria. All individuals of macrolepidoptera in our samples were manually determined to species level in order to serve as an internal calibration of species detection rates. Five samples with different complexity in a seasonal succession from early spring to summer were sequenced on the Illumina MiSeqv3 600 cycles platform. We employed two commonly used amplicons of different length for arthropod meta-barcoding, amplicon length was 205 bp and 313 bp respectively. Detection rates of manually determined species ranged from 46 to 69 percent for the shorter amplicon, and from 37 to 72 percent with the longer amplicon, depending on the sample and primer combination. Overall the shorter amplicon performed better and more consistently compared to the longer amplicon. Singleton species had a considerably lower chance of being detected as they are the most affected by sample homogeneity. Taxonomy was the strongest predictor for sequencing success. Species of the superfamilies Geometroidea and Pyraloidea were less likely to be detected than species of Noctuoidea. Biomass of individual moths was only a weak predictor for the probability for a species to be detected. This indicates that both primer combinations show a pronounced taxonomic bias. Our results demonstrate the need for studies on species detection rates in real world samples and investigation of potential bias in the affinity of commonly used primer combinations.| Zeitraum | 18 Nov. 2022 |
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| Ereignistitel | 9. Abol Tagung 2022 |
| Veranstaltungstyp | Konferenz |
| Ort | St. Pölten, ÖsterreichAuf Karte anzeigen |
| Bekanntheitsgrad | International |