Beetles are the most diverse group of animals and are crucial for ecosystem functioning. In many countries, they are well established for environmental impact assessment, but even in the well-studied Central European fauna, species identification can be very difficult. A comprehensive and taxonomically well-curated DNA barcode library could remedy this deficit and could also link hundreds of years of traditional knowledge with next generation sequencing technology. However, such a beetle library is missing to date. This study provides the globally largest DNA barcode reference library for Coleoptera for 15 948 individuals belonging to 3514 well-identified species (53% of the German fauna) with representatives from 97 of 103 families (94%). This study is the first comprehensive regional test of the efficiency of DNA barcoding for beetles with a focus on Germany. Sequences ≥500 bp were recovered from 63% of the specimens analysed (15 948 of 25 294) with short sequences from another 997 specimens. Whereas most specimens (92.2%) could be unambiguously assigned to a single known species by sequence diversity at CO1, 1089 specimens (6.8%) were assigned to more than one Barcode Index Number (BIN), creating 395 BINs which need further study to ascertain if they represent cryptic species, mitochondrial introgression, or simply regional variation in widespread species. We found 409 specimens (2.6%) that shared a BIN assignment with another species, most involving a pair of closely allied species as 43 BINs were involved. Most of these taxa were separated by barcodes although sequence divergences were low. Only 155 specimens (0.97%) show identical or overlapping clusters.

This study presents DNA barcode records for 4118 specimens representing 561 species of bees belonging to the six families of Apoidea (Andrenidae, Apidae, Colletidae, Halictidae, Megachilidae and Melittidae) found in Central Europe. These records provide fully compliant barcode sequences for 503 of the 571 bee species in the German fauna and partial sequences for 43 more. The barcode results are largely congruent with traditional taxonomy as only five closely allied pairs of species could not be discriminated by barcodes. As well, 90% of the species possessed sufficiently deep sequence divergence to be assigned to a different Barcode Index Number (BIN). In fact, 56 species (11%) were assigned to two or more BINs reflecting the high levels of intraspecific divergence among their component specimens. Fifty other species (9.7%) shared the same Barcode Index Number with one or more species, but most of these species belonged to a distinct barcode cluster within a particular BIN. The barcode data contributed to clarifying the status of nearly half the examined taxonomically problematic species of bees in the German fauna. Based on these results, the role of DNA barcoding as a tool for current and future taxonomic work is discussed.

The German Barcoding initiatives BFB and GBOL have generated a reference library of more than 16,000 metazoan species, which is now ready for applications concerning next generation molecular biodiversity assessments. To streamline the barcoding process, we have developed a meta-barcoding pipeline: We pre-sorted a single malaise trap sample (obtained during one week in August 2014, southern Germany) into 12 arthropod orders and extracted DNA from pooled individuals of each order separately, in order to facilitate DNA extraction and avoid time consuming single specimen selection. Aliquots of each ordinal-level DNA extract were combined to roughly simulate a DNA extract from a non-sorted malaise sample. Each DNA extract was amplified using four primer sets targeting the CO1-5’ fragment. The resulting PCR products (150-400bp) were sequenced separately on an Illumina Mi-SEQ platform, resulting in 1.5 million sequences and 5,500 clusters (coverage ≥10; CD-HIT-EST, 98%). Using a total of 120,000 DNA barcodes of identified, Central European Hymenoptera, Coleoptera, Diptera, and Lepidoptera downloaded from BOLD we established a reference sequence database for a local CUSTOM BLAST. This allowed us to identify 529 Barcode Index Numbers (BINs) from our sequence clusters derived from pooled Malaise trap samples. We introduce a scoring matrix based on the sequence match percentages of each amplicon in order to gain plausibility for each detected BIN, leading to 390 high score BINs in the sorted samples; whereas 268 of these high score BINs (69%) could be identified in the combined sample. The results indicate that a time consuming presorting process will yield approximately 30% more high score BINs compared to the non-sorted sample in our case. These promising results indicate that a fast, efficient and reliable analysis of next generation data from malaise trap samples can be achieved using this pipeline.

BackgroundBiodiversity patterns are inherently complex and difficult to comprehensively assess. Yet, deciphering shifts in species composition through time and space are crucial for efficient and successful management of ecosystem services, as well as for predicting change. To better understand species diversity patterns, Germany participated in the Global Malaise Trap Program, a world-wide collection program for arthropods using this sampling method followed by their DNA barcode analysis. Traps were deployed at two localities: “Nationalpark Bayerischer Wald” in Bavaria, the largest terrestrial Natura 2000 area in Germany, and the nature conservation area Landskrone, an EU habitats directive site in the Rhine Valley. Arthropods were collected from May to September to track shifts in the taxonomic composition and temporal succession at these locations.New informationIn total, 37,274 specimens were sorted and DNA barcoded, resulting in 5,301 different genetic clusters (BINs, Barcode Index Numbers, proxy for species) with just 7.6% of their BINs shared. Accumulation curves for the BIN count versus the number of specimens analyzed suggest that about 63% of the potential diversity at these sites was recovered with this single season of sampling. Diversity at both sites rose from May (496 & 565 BINs) to July (1,236 & 1,522 BINs) before decreasing in September (572 & 504 BINs). Unambiguous species names were assigned to 35% of the BINs (1,868) which represented 12,640 specimens. Another 7% of the BINs (386) with 1,988 specimens were assigned to genus, while 26% (1,390) with 12,092 specimens were only placed to a family. These results illustrate how a comprehensive DNA barcode reference library can identify unknown specimens, but also reveal how this potential is constrained by gaps in the quantity and quality of records in BOLD, especially for Hymenoptera and Diptera. As voucher specimens are available for morphological study, we invite taxonomic experts to assist in the identification of unnamed BINs.

This study summarizes results of a DNA barcoding campaign on German Diptera, involving analysis of 45,040 specimens. The resultant DNA barcode library includes records for 2,453 named species comprising a total of 5,200 barcode index numbers (BINs), including 2,700 COI haplotype clusters without species‐level assignment, so called “dark taxa.” Overall, 88 out of 117 families (75%) recorded from Germany were covered, representing more than 50% of the 9,544 known species of German Diptera. Until now, most of these families, especially the most diverse, have been taxonomically inaccessible. By contrast, within a few years this study provided an intermediate taxonomic system for half of the German Dipteran fauna, which will provide a useful foundation for subsequent detailed, integrative taxonomic studies. Using DNA extracts derived from bulk collections made by Malaise traps, we further demonstrate that species delineation using BINs and operational taxonomic units (OTUs) constitutes an effective method for biodiversity studies using DNA metabarcoding. As the reference libraries continue to grow, and gaps in the species catalogue are filled, BIN lists assembled by metabarcoding will provide greater taxonomic resolution. The present study has three main goals: (a) to provide a DNA barcode library for 5,200 BINs of Diptera; (b) to demonstrate, based on the example of bulk extractions from a Malaise trap experiment, that DNA barcode clusters, labelled with globally unique identifiers (such as OTUs and/or BINs), provide a pragmatic, accurate solution to the “taxonomic impediment”; and (c) to demonstrate that interim names based on BINs and OTUs obtained through metabarcoding provide an effective method for studies on species‐rich groups that are usually neglected in biodiversity research projects because of their unresolved taxonomy.