Globally, the diversity of arthropods and the plants upon which they rely are under increasing pressure due to a combination of biotic and abiotic anthropogenic stressors. Unfortunately, conventional survey methods used to monitor ecosystems are often challenging to conduct at large scales. Pan traps are a commonly used pollinator survey method and environmental DNA (eDNA) metabarcoding of pan-trap water may offer a high-throughput alternative to aid in the detection of both arthropods and the plant resources they rely on. Here, we examined if eDNA metabarcoding can be used to identify arthropod and plant species from pan-trap water, and invesitigated the effect of different DNA extraction methods. We then compared plant species identified by metabarcoding with observation-based floral surveys and also assessed the contribution of airborne plant DNA (plant DNA not carried by arthropods) using marble traps to reduce putative false positives in the pan trap dataset. Arthropod eDNA was only detected in 17% of pan trap samples and there was minimal overlap between the eDNA results and morphological identifications. In contrast, for plants, we detected 64 taxa, of which 53 were unique to the eDNA dataset, and no differences were identified between the two extraction kits. We were able to significantly reduce the contribution of airborne plant DNA to the final dataset using marble traps. This study demonstrates that eDNA metabarcoding of pan-trap water can detect plant resources used by arthropods and highlights the potential for eDNA metabarcoding to be applied to investigations of plant-animal interactions.

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection managed and unmanaged arthropod taxa (e.g. flower-visiting insects and potential pollinators). Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (Persea americana - ‘Hass’ avocado), with two conventional survey techniques; Digital Video Recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 hours of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. This study demonstrates that eDNA metabarcoding of flowers to detect visiting arthropods, although in a developmental stage, can complement traditional survey methods and increase the diversity of taxa detected with implications for both natural and agro-ecosystems.

Fauna biodiversity assessments often rely on traditional biomonitoring techniques such as camera traps, which may have biases that lead to gaps in biodiversity data. Environmental DNA (eDNA) has emerged as a new source of biodiversity data that may account for these gaps. However, eDNA biodiversity assessment remains relatively untested in terrestrial environments. We compared vertebrate detections using two independent monitoring methods: camera traps and eDNA (n = 160), across two sites in south-western Australia. We also investigated the suitability of tree hollow sediment as a source of eDNA, and the effect of other factors (visitation frequency and timing, animal size) on vertebrate species detectability. We detected 31 taxa with eDNA and 47 with camera traps of which 14 overlapped (12 mammals and 2 birds). Tree hollow sediment detected a wider range of biodiversity than did soil at the entrance of the hollow. By comparing camera trap data with eDNA sequence reads, we were able to detect animals with eDNA that had visited the area up to two months prior to sample collection, with a negative correlation between sequence read amount and days since last recorded detection via camera. “Large” animals (>3kg) detected via camera were associated with significantly higher sequence read amounts than smaller animals. Our results show the effect of substrate selection, frequency of sampling and animal size, on eDNA based surveys. If the aim is to detect broad taxon diversity eDNA based approaches need to be complemented by traditional vertebrate survey methods.