https://ipt.gbif.org/resource?r=dsub578
timtimtim
DNA metabarcoding data of arthropods from lower mountain range regions in southwest Germany
Lara
Hoffmann
University of Duisburg-Essen
Author
Duisburg
DE
lara.hoffmann2@stud.uni-due.de
Stefan
Stoll
University of Applied Sciences Trier
PI
Trier
DE
s.stoll@umwelt-campus.de
Birgit
Rach
Leibniz institute for the Analysis of Biodiversity Change - LIB
Data Curator
Bonn
DE
b.rach@leibniz-lib.de
Birgit
Rach
LIB - Leibniz Institute for the Analysis of Biodiversity Change
Data curator
Bonn
DE
b.rach@leibniz-lib.de
publisher
University of Applied Sciences Trier
Owner institute
DE
owner
University of Duisburg-Essen
DE
owner
2026-04-21
eng
The dataset comprises presence data on arthropods, but also on the groups 'Annelida', 'Ascomycota', 'Basidiomycota', 'Mollusca', 'Mucoromycota', 'Nematoda' and 'Proteobacteria'. For each detection of an Observational Taxonomic Unit (OTU), the number of reads is also given, as well as further information about the species assigned. The species information was derived from a comparison of the detected DNA sequences with the BOLD database and the database of the National Center for Biotechnology Information (NCBI). Further, the Ribosomal Database Project (RDP) classifier was used to identify species. A consensus taxonomy compiles the species information dervied from the different databases and ranks the results according to their validity by using labels from A to C (Information on A, B, and C given at the description of the variables). The DNA metabarcoding process is decribed in detail in Uhler et al (2021): Relationship of insect biomass and richness with land use along a climate gradient (https://www.nature.com/articles/s41467-021-26181-3#Sec10 ). Since the samples were devided into large and small subsamples to improve the metabarcoding results, the data is given for each of the subsamples separately. The samples that went through DNA metabarcoding were derived from a Malaise trap experiment, for which five different types of Malaise traps were placed on a meadow and a forest clearing site each in three regions of southwest Germany (Nationalpark Hunsrück-Hochwald, Rhine-Main-Observatory, Steigerwald). The sites in the Hunsrück and the Rhine-Main-Observatory are part of the Long-term Ecological Research Network Germany (LTER-D).
Samplingevent
GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type_2015-07-10.xml
This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.
Creative Commons Attribution 4.0 International
https://spdx.org/licenses/CC-BY-4.0.html
CC-BY-4.0
https://doi.org/10.20363/zc0n-5a36
three regions of southwest Germany: Nationalpark Hunsrück-Hochwald, Rhine-Main-Observatory, Steigerwald
-180
180
90
-90
2020-05-22
2020-08-14
All arthropods were identified by metabarcoding to different level.
order
Symphypleona
order
Psocoptera
order
Rickettsiales
order
Hemiptera
order
Tylenchida
order
Sarcoptiformes
order
Opiliones
order
Megaloptera
order
Gigartinales
order
Julida
order
Raphidioptera
order
Blattodea
order
Thysanoptera
order
Neuroptera
order
Dermaptera
order
Ephemeroptera
order
Microstromatales
order
Araneae
order
Mucorales
order
Mesostigmata
order
Plecoptera
order
Lepidoptera
order
Diptera
order
Entomobryomorpha
order
Trichoptera
kingdom
Animalia
order
Haplotaxida
order
Sporidiobolales
order
Lithobiomorpha
order
Eurotiales
order
Orthoptera
order
Rhabditida
order
Hypocreales
order
Coleoptera
order
Chaetothyriales
order
Mecoptera
order
Hymenoptera
order
Psocodea
order
Trombidiformes
order
Stylommatophora
order
Poduromorpha
order
Isopoda
daily
Lara
Hoffmann
University of Duisburg-Essen
Author
Duisburg
DE
lara.hoffmann2@stud.uni-due.de
For each detection of an Observational Taxonomic Unit (OTU), the number of reads is also given, as well as further information about the species assigned.
The species information was derived from a comparison of the detected DNA sequences with the BOLD database and the database of the National Center for Biotechnology Information (NCBI). Further, the Ribosomal Database Project (RDP) classifier was used to identify species. A consensus taxonomy compiles the species information dervied from the different databases and ranks the results according to their validity by using labels from A to C (Information on A, B, and C given at the description of the variables).
The DNA metabarcoding process is described in detail in Uhler et al (2021): Relationship of insect biomass and richness with land use along a climate gradient (https://www.nature.com/articles/s41467-021-26181-3#Sec10 ). Since the samples were devided into large and small subsamples to improve the metabarcoding results, the data is given for each of the subsamples separately.
The dataset comprises presence data on arthropods, but also on the groups 'Annelida', 'Ascomycota', 'Basidiomycota', 'Mollusca', 'Mucoromycota', 'Nematoda' and 'Proteobacteria'.
The samples were derived from a Malaise trap experiment, for which five different types of Malaise traps were placed on a meadow and a forest clearing site each in three regions of southwest Germany (Nationalpark Hunsrück-Hochwald, Rhine-Main-Observatory, Steigerwald). The sites in the Hunsrück and the Rhine-Main-Observatory are part of the Long-term Ecological Research Network Germany (LTER-D). The Malaise trap samples comprise insects captured over 14 days each. There is a detailled description of the study design available in Hoffmann et al (2025): Effects of species traits on the catchability of butterflies with different types of Malaise traps and implications for total catch biomass (DOI:10.1007/s10841-024-00645-5). The traps were operated from April to October, but only selected samples went to the DNA metabarcoding (data in this set).
DNA metabarcoding data of arthropods from lower mountain range regions in southwest Germany
Lara
Hoffmann
The dataset comprises presence data on arthropods, but also on the groups 'Annelida', 'Ascomycota', 'Basidiomycota', 'Mollusca', 'Mucoromycota', 'Nematoda' and 'Proteobacteria'. For each detection of an Observational Taxonomic Unit (OTU), the number of reads is also given, as well as further information about the species assigned. The species information was derived from a comparison of the detected DNA sequences with the BOLD database and the database of the National Center for Biotechnology Information (NCBI). Further, the Ribosomal Database Project (RDP) classifier was used to identify species.
Heinrich Böll foundation (P142690) and Trier University of Applied Sciences: Junior Researcher Fund
The samples were derived from a Malaise trap experiment, for which five different types of Malaise traps were placed on a meadow and a forest clearing site each in three regions of southwest Germany (Nationalpark Hunsrück-Hochwald, Rhine-Main-Observatory, Steigerwald). The sites in the Hunsrück and the Rhine-Main-Observatory are part of the Long-term Ecological Research Network Germany (LTER-D).
There is a detailled description of the study design available in Hoffmann et al (2025): Effects of species traits on the catchability of butterflies with different types of Malaise traps and implications for total catch biomass (DOI:10.1007/s10841-024-00645-5).
2025-10-07T09:29:13.325+00:00
dataset
Uhler et al (2021): Relationship of insect biomass and richness with land use along a climate gradient.
Hoffmann, Lara; Palt, Martin; Mignien, Lucas; Uhler, Johannes; Haase, Peter; Müller, Jörg; Stoll, Stefan (2024): Butterfly abundance data from lower mountain range regions in southwest Germany [dataset]. PANGAEA.
Hoffmann, Lara; Palt, Martin; Mignien, Lucas; Uhler, Johannes; Haase, Peter; Müller, Jörg; Stoll, Stefan (2024): Butterfly weight data from lower mountain range regions in southwest Germany [dataset]. PANGAEA.
Hoffmann et al (2025): Effects of species traits on the catchability of butterflies with different types of Malaise traps and implications for total catch biomass.
ASV-Registry
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Microsoft Excel
https://doi.org/10.20363/zc0n-5a36
https://ipt.gbif.org/resource?id=dsub578/v1.8.xml