Arthropods can strongly impact ecosystems through pollination, herbivory, predation, and parasitism. As such, characterizing arthropod biodiversity is vital to understanding ecosystem health, functions, and services. Emerging environmental DNA (eDNA) methods targeting trace arthropod eDNA left behind on flowers have the potential to track arthropod biodiversity and interactions. The goal of this study was to determine the extent to which eDNA metabarcoding can identify plant‐arthropod and arthropod‐arthropod interactions and assess eDNA metabarcoding compared to conventional sampling. We deployed camera traps to document arthropod activity on specific flowers, sampled eDNA from those same flowers, then performed a metabarcoding analysis that targets a partial fragment of the cytochrome c oxidase subunit I gene (COI) to determine all arthropod eDNA present. We found that our eDNA metabarcoding analysis detected small arthropod pollinators, plant pests, and parasites, and shed light on potential predator–prey interactions while detecting 55 species compared to just 21 species from conventional camera trapping. The camera trapping survey, however, detected larger, more conspicuous nectarivores more successfully. We also explored the ecology of residual arthropod eDNA, finding that rainfall had a significant negative effect on the ability to detect residual arthropod eDNA. Preliminary evidence also indicates flower species may impact the amount of arthropod eDNA that can be detected. We found that eDNA metabarcoding can provide clues to potential predator–prey interactions on flowers and highlights the potential insights that can be gained from future eDNA metabarcoding studies. We show that eDNA metabarcoding is a valuable tool for not only detecting pollinator communities but for revealing potential interactions among plants, pollinators, pests, parasites, and predators. Future research should focus on how to improve the detection of large pollinators/nectivores and studying the ecology of residual arthropod eDNA to further explore this method's utility.

Species detections often vary depending on the survey methods employed. Some species may go undetected when using only one approach in community‐level inventory and monitoring programs, which has management and conservation implications. We conducted a comparative study of terrestrial mammal and bird detections in the spring and summer of 2021 by placing camera traps at 30 locations across a large military installation in northern Michigan, USA and testing replicate soil samples from these sites for environmental DNA (eDNA) using an established vertebrate metabarcoding assay. We detected a total of 48 taxa from both survey methods: 26 mammalian taxa (excluding humans, 24 to species and two to genus) and 22 avian taxa (21 to species and one to genus). We detected a relatively even distribution of mammalian taxa on cameras (17) and via eDNA analysis (15), with seven taxa detected from both methods. Most medium‐to‐large carnivores were detected only on cameras, whereas semi‐fossorial small mammals were detected only via eDNA analysis. We detected higher bird diversity with camera traps (18 taxa) compared to eDNA analysis (eight taxa; four taxa were detected with both methods), but cameras alone were most effective at detecting smaller birds that frequently occupy arboreal environments. We also used Bayesian spatial occupancy models for two widely distributed game species (white‐tailed deer, Odocoileus virginianus, and ruffed grouse, Bonasa umbellus) that were moderately detected with both survey methods and found species‐specific site use (occupancy) estimates were similar between cameras and eDNA analysis. Concordant with similar studies, our findings suggest that a combination of camera trap and eDNA surveys could be most useful for assessing the composition of terrestrial mammal communities. Camera traps may be most efficient for assessing bird diversity but can be complemented with eDNA analysis, particularly for species that spend considerable time on the ground.

Analysis of environmental DNA (eDNA) has been successfully used across freshwater ecological parasitology to inform management of ecologically and economically important species. However, most studies have used species‐specific quantitative polymerase chain reaction (qPCR) assays to detect target taxa. While generally effective, this approach limits the amount of community and management‐supporting data that can be obtained from eDNA samples. If eDNA metabarcoding could be conducted with the same accuracy of a single species approach, researchers could simultaneously detect a target species while obtaining vast community data from eDNA samples. We sampled 38 freshwater sites on Fort McCoy, Wisconsin and compared qPCR to metabarcoding for eDNA detection of the ectoparasitic gill louse Salmincola edwardsii, an obligate parasite of Salvelinus fishes (chars). We found no evidence to suggest S. edwardsii occupancy or detection probabilities differed between qPCR and metabarcoding. Further, we found that the number of S. edwardsii reads from metabarcoding were negatively predictive of C_T values from qPCR (C_T value indicates cycle a significant amount of target eDNA is detected, with lower C_Ts indicative of more DNA), demonstrating that our metabarcoding reads positively predicted qPCR DNA quantities. However, the number of reads was not predictive of overall qPCR score (number of positive qPCR replicates). In addition to S. edwardsii, metabarcoding led to the detection of a vast community of over 2600 invertebrate taxa. We underscore the necessity for conducting similar analyses across environments and target species, as the ecology of eDNA will vary on a per‐study basis. Our results suggest that eDNA metabarcoding provides a highly sensitive and accurate method for detecting parasitic gill lice while also illuminating the broader biological community and co‐occurrence of species in the environment.

Head-starting is a conservation strategy that entails releasing captive-reared animals into nature at sizes large enough to better resist post-release predation. However, efforts to maximize growth in captivity may jeopardize development of beneficial behaviors. Environmental enrichment can encourage natural behaviors before release but potentially comes with a tradeoff of reduced growth in complex enclosures. We compared growth and behavior of enriched and unenriched captive-born juvenile box turtles (Terrapene carolina). Enriched turtles grew slower than unenriched turtles during the first eight months in captivity, although growth rates did not differ between treatments from 9–20 months old. After five months post-hatching, unenriched turtles became and remained larger overall than enriched turtles. During two foraging tasks, unenriched turtles consumed more novel prey than enriched turtles. In a predator recognition test, eight-month-old enriched turtles avoided raccoon (Procyon lotor) urine more than unenriched turtles of the same age, but this difference was not apparent one year later. The odds of turtles emerging from a shelter did not differ between treatments regardless of age. Although our results suggest turtles raised in unenriched environments initially grew faster and obtained larger overall sizes than those in enriched conditions, tradeoffs with ecologically-relevant behaviors were either absent or conditional.

Detecting environmental DNA (eDNA) of numerous organisms from the same samples has been revolutionized by metabarcoding. However, utilizing the vast amounts of data generated from metabarcoding to predict occupancy probabilities for co‐occurring species is currently rare. Here, we demonstrate how metabarcoding data can be used to advance community ecology research through a case study using replicate stream water samples and Bayesian occupancy models to test hypotheses of eDNA occurrence for a native fish (brook trout, Salvelinus fontinalis), its major ectoparasite (gill lice, Salmincola edwardsii), and an introduced potential competitor (brown trout, Salmo trutta). Gill lice DNA occupancy was positively associated with brook trout biomass determined via electrofishing conducted near eDNA sampling sites, suggesting gill lice occupancy is dependent on host density. Leveraging site‐specific molecular operational taxonomic units identified from metabarcoding, DNA occupancy of trout and gill lice was often positively predicted by species richness of aquatic insect orders trout commonly feed on, which are also environmental quality indicators. Thus, high‐quality habitats that environmentally sensitive salmonids and their primary prey rely on may promote higher fish occupancy rates, further facilitating the spread of fish parasites. An increasing amount of community‐level data is being generated from global metabarcoding efforts, and we suggest our framework could be broadly implemented to enhance understanding of factors impacting distributions of co‐occurring species, reveal new ecological phenomena, and support management and conservation efforts.