eDNA metabarcoding of avocado flowers: 'Hass' it got potential to survey arthropods in food production systems?

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.

Aquatic environmental DNA: A review of the macro-organismal biomonitoring revolution

Environmental DNA (eDNA) is the fastest growing biomonitoring tool fuelled by two key features: time efficiency and sensitivity. Technological advancements allow rapid biodiversity detection at both species and community levels with increasing accuracy. Concurrently, there has been a global demand to standardise eDNA methods, but this is only possible with an in-depth overview of the technological advancements and a discussion of the pros and cons of available methods. We therefore conducted a systematic literature review of 407 peer-reviewed papers on aquatic eDNA published between 2012 and 2021. We observed a gradual increase in the annual number of publications from four (2012) to 28 (2018), followed by a rapid growth to 124 publications in 2021. This was mirrored by a tremendous diversification of methods in all aspects of the eDNA workflow. For example, in 2012 only freezing was applied to preserve filter samples, whereas we recorded 12 different preservation methods in the 2021 literature. Despite an ongoing standardisation debate in the eDNA community, the field is seemingly moving fast in the opposite direction and we discuss the reasons and implications. Moreover, by compiling the largest PCR-primer database to date, we provide information on 522 and 141 published species-specific and metabarcoding primers targeting a wide range of aquatic organisms. This works as a user-friendly 'distillation' of primer information that was hitherto scattered across hundreds of papers, but the list also reflects which taxa are commonly studied with eDNA technology in aquatic environments such as fish and amphibians, and reveals that groups such as corals, plankton and algae are under-studied. Efforts to improve sampling and extraction methods, primer specificity and reference databases are crucial to capture these ecologically important taxa in future eDNA biomonitoring surveys. In a rapidly diversifying field, this review synthetises aquatic eDNA procedures and can guide eDNA users towards best practice.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.