The potential of metabarcoding plant components of Malaise trap samples to enhance knowledge of plant-insect interactions

Abstract

The worldwide rapid declines in insect and plant abundance and diversity that have occurred in the past decades have gained public attention and demand for political actions to counteract these declines are growing. Rapid large-scale biomonitoring can aid in observing these changes and provide information for decisions for land management and species protection. Malaise traps have long been used for insect sampling and when insects are captured in these traps, they carry traces of plants they have visited on the body surface or as digested food material in the gut contents. Metabarcoding offers a promising method for identifying these plant traces, providing insight into the plants with which insects are directly interacting at a given time. To test the efficacy of DNA metabarcoding with these sample types, 79 samples from 21 sites across Germany were analysed with the ITS2 barcode. This study, to our knowledge, is the first examination of metabarcoding plant DNA traces from Malaise trap samples. Here, we report on the feasibility of sequencing these sample types, analysis of the resulting taxa, the usage of cultivated plants by insects near nature conservancy areas and the detection of rare and neophyte species. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. Metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen and is the only possible identification method for the other plant traces from Malaise traps and could provide a broad utility for future studies of plant-insect interactions.

Improving insect conservation management through insect monitoring and stakeholder involvement

“…Within the framework of DINA, we were able to demonstrate that Malaise trap samples can be used not only for studies on insect species richness and biomass, but also to examine traces carried into the traps by insects to analyse plant species richness through metabarcoding (Swenson et al 2022) and pesticide residues in ethanol (Brühl et al 2021). Results from our Malaise trap transect studies for the analysed sampling intervals show a clear positive correlation between insect species richness and insect biomass, confirming previous observations in Europe among certain insect taxa such as hoverflies (Diptera: Syrphidae; Hallmann et al 2021a).…”

“…Sequencing data were processed with USEARCH (Edgar 2010) and DADA2 (Callahan et al 2016) using R (R Core Team 2019). The resulting ASVs were identified by implementing the SINTAX algorithm (Edgar 2016) using a custom Plantae reference database (Swenson et al 2022) (for full outline see Online Resource 2, Plant metabarcoding).…”

“…2021). To enable an evidence-based optimisation of protected area management, we assess species composition at selected sites, unprecedented in its completeness for flying insects due to the use of DNA metabarcoding and relate it to floral (Swenson et al 2022) and spatial characteristics of the nature reserves and potential pesticide residues. By drawing on a complete set of biodiversity monitoring data, ecotoxicology data (Brühl et al 2021) as well as spatial data on agricultural land-use (Eichler et al 2022), this study presents a comprehensive analysis of impacts on insect biodiversity in nature reserves.…”

Insect biomass of protected habitats under the impact of arable farming in Germany

“…The DINA project (Diversity of Insects in Nature protected Areas), a comprehensive interdisciplinary research project involving eight institutions (Lehmann et al, 2021), investigates the influence on insect populations in nature reserves as part of SAC and within the European Natura 2000 network (Brühl et al, 2021; Eichler et al, 2022; Köthe et al, 2023a; Lehmann et al, 2021; Swenson et al, 2022). Based on the original model to study the main drivers for the decline in insect biomass (Hallmann et al 2017), we focused on the already identified covariates: the influence of arable land and the chemical inputs such as nitrogen and pesticides associated with intensive land use.…”

“…Moreover, due to the comparability in methodology, the data can be collated with those of Hallmann et al (2017). In addition to insect data, landscape elements and their spatial distribution pattern (Eichler et al, 2022), vegetation (Köthe et al, 2023b; Swenson et al, 2022), and pesticide residues were measured (Brühl et al, 2021) accompanied by exchange with local stakeholders for developing solutions for improved insect protection (Fickel et al, 2020; Köthe et al, 2023a; Lehmann et al, 2021).…”