Edith Cowan University, Research Online, Perth, Western Australia
Doi
Abstract
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 of these managed and unmanaged taxa. 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 h 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. Environmental DNA metabarcoding from flowers revealed potential arthropod pollinators, as well as plant pests and parasites. 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. eDNA metabarcoding of flowers has the potential to revolutionize the way arthropod communities are monitored in natural and agro-ecosystems, potentially detecting the response of pollinators and pests to climate change, diseases, habitat loss and other disturbances
