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Background. Broad-scale monitoring of arthropods is often carried out with passive traps (e.g., Malaise traps) that can collect thousands of specimens per sample. The identification of individual specimens requires time and taxonomic expertise, limiting the geographical and temporal scale of research and monitoring studies. DNA metabarcoding of bulk-sample homogenates has been found to be faster, efficient and reliable, but the destruction of samples prevents a posteriori validation of species occurrences and relative abundances. Non-destructive metabarcoding of DNA extracted from collection medium has been applied in a limited number of studies, but further tests of efficiency are required with different trap types and collection media to assess the consistency of the method. Methods. We quantified the detection rate of arthropod species when applying nondestructive DNA metabarcoding with a short (127-bp) fragment of mitochondrial COI on two combinations of passive traps and collection media: (1) water with monopropylene glycol (H2O-MPG) used in window-flight traps (WFT, 53 in total); (2) ethanol with monopropylene glycol (EtOH-MPG) used in Malaise traps (MT, 27 in total). We then compared our results with those obtained for the same samples using morphological identification (for WFTs) or destructive metabarcoding of bulk homogenate (for MTs). This comparison was applied as part of a larger study of arthropod species richness in silver fir (Abies alba Mill., 1759) stands across a range of climate-induced tree dieback levels and forest management strategies. Results. Of the 53 H2O-MPG samples from WFTs, 16 produced no metabarcoding results, while the remaining 37 samples yielded 77 arthropod MOTUs in total, of [ABSTRACT FROM AUTHOR]

The current decline of wild bees puts important ecosystem services such as pollination at risk. Both inventory and monitoring programs are needed to understand the causes of wild bee decline. Effective insect monitoring relies on both mass-trapping methods coupled with rapid and accurate identifications. Identifying wild bees using only morphology can be challenging, in particular, specimens from mass-trapped samples which are often in poor condition. We generated DNA barcodes for 2931 specimens representing 157 species (156 named and one unnamed species) and 28 genera. Automated cluster delineation reveals 172 BINs (Barcodes Index Numbers). A total of 36 species (22.93%) were found in highly urbanized areas. The majority of specimens, representing 96.17% of the species barcoded form reciprocally exclusive groups, allowing their unambiguous identification. This includes several closely related species notoriously difficult to identify. A total of 137 species (87.26%) show a "one-to-one" match between a named species and the BIN assignment. Fourteen species (8.92%) show deep conspecific lineages with no apparent morphological differentiation. Only two species pairs shared the same BIN making their identification with DNA barcodes alone uncertain. Therefore, our DNA barcoding reference library allows reliable identification by non-experts for the vast majority of wild bee species in the Loire Valley. [ABSTRACT FROM AUTHOR]