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German-wide Malaise trap metabarcoding estimates over 33,000 insect species

Authors :
Buchner, D.
Beermann, A.
Hörren, T.
Enss, J.
Frenzel, Mark ; orcid:0000-0003-1068-2394
Li, Y.
Müller, J.
Pauls, S.U.
Sorg, M.
Haase, P.
Leese, F.
Buchner, D.
Beermann, A.
Hörren, T.
Enss, J.
Frenzel, Mark ; orcid:0000-0003-1068-2394
Li, Y.
Müller, J.
Pauls, S.U.
Sorg, M.
Haase, P.
Leese, F.
Publication Year :
2023

Abstract

Insects are unique in terms of their high species diversity and deliver key ecological functions. Despite this importance, we know little about true species numbers and biodiversity trends for most insect orders. A key limitation is a lack of time, funding and taxonomic expertise needed to identify the huge number of often small species, of which many remain undescribed as “dark taxa”. We here present a holistic, scalable and affordable insect diversity monitoring approach using DNA metabarcoding of the mitochondrial COI gene. Using data from the German Malaise trap program we analyzed 1,815 samples obtained from 2019 and 2020 through 75 traps across Germany. We uncovered 10,803 plausible insect species of which the majority (83.9%) was represented by a single OTU. We estimated another 22,500 potential insect species, which lack reference data or represent undescribed species. The overall number of >33,000 insect species reported here is almost as high as the total number of insect species known for Germany (∼35,500). As Malaise traps capture only a certain fraction of insect species, we argue that many species recorded here are unknown from Germany or new to science in general. Our approach uses robotics and replicated analysis with on average 1.4 M sequence reads per sample for less than 50 € including supply, labor and maintenance. Our up-scalable analysis of 141 samples within two weeks with one person provides a blueprint for large-scale insect monitoring in almost real time.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1399411108
Document Type :
Electronic Resource