Background: Detecting species at low abundance, including aquatic invasive species (AIS), is critical for making informed management decisions. Environmental DNA (eDNA) methods have become a powerful tool for rare or cryptic species detection; however, many eDNA assays offer limited utility for community-level analyses due to their use of species-specific (presence/absence) 'barcodes'. Metabarcoding methods provide information on entire communities based on sequencing of all taxon-specific barcodes within an eDNA sample.Aims: Evaluate measures of fish species detections, community diversity, and estimates of relative abundance based on eDNA metabarcoding and traditional fisheries sampling approaches in the context of fish community characterization and AIS survellience. Materials and Methods:In 2016, eight limnologically diverse lakes (surface area range: 13 -1,728 ha) in Michigan, USA were sampled using a variety of traditional fisheries gears to characterize fish community composition. Environmental DNAs from surface (33 ± 6, mean ± 1 SD) and benthic (14 ± 2) water samples from each lake were isolated and amplified for two metabarcoding markers (mitochondrial 12S and 16S rDNA loci) using fish-specific primers. Fish species detected within each lake were determined by comparing the sequencing data to a database of sequences from native Michigan fish species and 19 AIS on the Michigan's Watch List.Results: Analysis of species accumulation curves indicated multi-locus eDNA metabarcoding assays can enhance species detection capacities and characterize 95% of a fish community in fewer sampling efforts than traditional gear (range: 2 -62, median: 14). In addition, all AIS detected in traditional gear samples were also detected by eDNA, while some AIS detected by eDNA assays were absent from traditional gear samples. | 369SARD et Al.

Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1–10 cameras), and (2) by total season length (1–365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40–128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species.

Over 180 non-native species have been introduced in the Laurentian Great Lakes region, many posing threats to native species and ecosystem functioning. One potential pathway for introductions is the commercial bait trade; unknowing or unconcerned anglers commonly release unused bait into aquatic systems. Previous surveillance efforts of this pathway relied on visual inspection of bait stocks in retail shops, which can be time and cost prohibitive and requires a trained individual that can rapidly and accurately identify cryptic species. Environmental DNA (eDNA) surveillance, a molecular tool that has been used for surveillance in aquatic environments, can be used to efficiently detect species at low abundances. We collected and analyzed 576 eDNA samples from 525 retail bait shops throughout the Laurentian Great Lake states. We used eDNA techniques to screen samples for multiple aquatic invasive species (AIS) that could be transported in the bait trade, including bighead (Hypophthalmichthys nobilis) and silver carp (H. molitrix), round goby (Neogobius melanostomus), tubenose goby (Proterorhinus marmoratus), Eurasian rudd (Scardinius erythrophthalmus), and goldfish (Carassius auratus). Twenty-seven samples were positive for at least one target species (4.7% of samples), and all target species were found at least once, except bighead carp. Despite current regulations, the bait trade remains a potential pathway for invasive species introductions in the Great Lakes region. Alterations to existing management strategies regarding the collection, transportation, and use of live bait are warranted, including new and updated regulations, to prevent future introductions of invasive species in the Great Lakes via the bait trade.

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