Monitoring insects across space and time is challenging, due to their vast taxonomic and functional diversity. This study demonstrates how nets mounted on rooftops of cars (car nets) and DNA metabarcoding can be applied to sample flying insect richness and diversity across large spatial scales within a limited time period. During June 2018, 365 car net samples were collected by 151 volunteers during two daily time intervals on 218 routes in Denmark. Insect bulk samples were processed with a DNA metabarcoding protocol to estimate taxonomic composition, and the results were compared to known flying insect richness and occurrence data. Insect and hoverfly richness and diversity were assessed across biogeographic regions and dominant land cover types. We detected 15 out of 19 flying insect orders present in Denmark, with high proportions of especially Diptera compared to Danish estimates, and lower insect richness and diversity in urbanised areas. We found 319 species not known for Denmark and 174 species assessed in the Danish Red List. Our results indicate that the methodology can assess the flying insect fauna at large spatial scales to a wide extent, but may be, like other methods, biased towards certain insect orders.

Flying insects were collected with car nets during June 2018 in Denmark. Citizen scientists drove back and forth on 5 km routes and the insects were shipped to the Natural History Museum of Denmark in 96% EtOH. The insects were size sorted in two size fractions prior to DNA extraction with a non-destructive DNA lysis buffer and further processing with a DNA metabarcoding protocol. The full laboratory protocol for the research project 'InsectMobile' can be accessed here: https://dx.doi.org/10.17504/protocols.io.bmunk6ve. Only the output of fwh primer pair is used in this study.

Statistical analyses were carried out in RStudio on the original samples (size sorted samples were merged prior to analysis). Scripts can be found here: https://github.com/CecSve/InsectMobile_CarNet. The data in this Dryad repository are the data used in script 02.