Assessing Biodiversity in Agricultural Landscapes Through Drone-Based Environmental DNA Sampling

As agricultural intensification expands globally, there is an increasing concern about the impact of food production on global biodiversity. Biodiversity decline is problematic as species provide a wealth of benefits, including pollination, soil fertility, and protection against pests, within agrosystems. Many countries, especially across Europe, have implemented incentives for farmers to introduce biodiversity-friendly land management practices, from building hedgerows to planting pollinator fields. Quantifying the impacts of these measures on biodiversity at the farm scale is technically challenging. Here, we developed a method involving the collection of environmental DNA (eDNA) samples with drones from crops, demonstrated in a case study on rapeseed fields under three management types: conventional, biological, and IP Suisse. We analyzed swabbed material through metabarcoding of a 16S amplicon to detect the composition of hexapod in the field. After cleaning and taxonomic assignment, we obtained a total of 75 taxa assigned to 19 families, 23 genera, and 33 species. We found that the variance in recovered diversity was significantly higher for replicates between fields than for replicates within a field, suggesting that eDNA swabbing replicates provided consistent local results. We did not detect significant differences between treatments, possibly because of a landscape effect which causes spillover of species from neighboring seminatural habitats. Our results provide a direction for developing a toolbox for biodiversity measurements in agricultural fields, highlighting the potential for expanding these methodologies to suit the needs of scientists, farmers, and other stakeholders in understanding and fostering farm-scale biodiversity.