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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 on 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 arthropods and plant species from pan trap water, and investigated 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 arthropod-plant interactions.

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 gui

Animal pollinators are vital for the reproduction of ~90% of flowering plants. However, many of these pollinating species are experiencing declines globally, making effective pollinator monitoring methods more important than ever before. Pollinators can leave DNA on the flowers they visit, and metabarcoding of these environmental DNA (eDNA) traces provides an opportunity to detect the presence of flower visitors. Our study, collecting flowers from seven plant species with diverse floral morphologies, for eDNA metabarcoding analysis, illustrated the value of this novel survey tool. eDNA metabarcoding using three assays, including one developed in this study to target common bush birds, recorded more animal species visiting flowers than visual surveys conducted concurrently, including birds, bees, and other species. We also recorded the presence of a flower visit from a western pygmy possum; to our knowledge this is the first eDNA metabarcoding study to simultaneously identify the interaction of insect, mammal, and bird species with flowers. The highest diversity of taxa was detected on large inflorescence flower types found on Banksia arborea and Grevillea georgeana. The study demonstrates that the ease of sample collection and the robustness of the metabarcoding methodology has profound implications for future management of biodiversity, allowing us to monitor both plants and their attendant cohort of potential pollinators. This opens avenues for rapid and efficient comparison of biodiversity and ecosystem health between different sites and may provide insights into surrogate pollinators in the event of pollinator declines.

Animal pollinators are vital for the reproduction of ~90% of flowering plants. However, many of these pollinating species are experiencing declines globally, making effective pollinator monitoring methods more important than ever before. Pollinators can leave DNA on the flowers they visit, and metabarcoding of these environmental DNA (eDNA) traces provides an opportunity to detect the presence of flower visitors. Our study, collecting flowers from seven plant species with diverse floral morphologies, for eDNA metabarcoding analysis, illustrated the value of this novel survey tool. eDNA metabarcoding using three assays, including one developed in this study to target common bush birds, recorded more animal species visiting flowers than visual surveys conducted concurrently, including birds, bees, and other species. We also recorded the presence of a flower visit from a western pygmy possum; to our knowledge this is the first eDNA metabarcoding study to simultaneously identify the interaction of insect, mammal, and bird species with flowers. The highest diversity of taxa was detected on large inflorescence flower types found on Banksia arborea and Grevillea georgeana. The study demonstrates that the ease of sample collection and the robustness of the metabarcoding methodology has profound implications for future management of biodiversity, allowing us to monitor both plants and their attendant cohort of potential pollinators. This opens avenues for rapid and efficient comparison of biodiversity and ecosystem health between different sites and may provide insights into surrogate pollinators in the event of pollinator declines.

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.

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 gui

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 opportun

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 opportun

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 oppor

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 oppor

Kestel, J. H., Phillips, R. D., Anthony, J., Davis, R. A., & Krauss, S. L. (2021). Unexpectedly low paternal diversity is associated with infrequent pollinator visitation for a bird-pollinated plant. Oecologia, 196(4), 937-950. https://doi.org/10.1007/s00442-021-04906-x