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At least 65 aquatic plant species have been identified as part of a surveillance list of non-native species that pose a threat to biodiversity and ecosystem services in the Laurentian Great Lakes. Early detection of these potentially invasive aquatic plants (IAP) could minimize impacts of novel incursions and facilitate successful eradication. We developed, implemented, and then adaptively refined a probabilistic boat-based sampling design that aimed to maximize the likelihood of detecting novel IAP incursions in large (400+ hectares) Great Lakes coastal areas. Surveys were conducted from 2017 to 2019 at five Great Lakes locations - St Joseph River (MI), Saginaw River (MI), Milwaukee (WI), Cleveland (OH), and the Detroit River (MI). Aquatic plant communities were characterized across the five sites, with a total of 61 aquatic plant species detected. One-fifth of the species detected in our surveys were non-native to the Great Lakes basin. Sample-based species rarefaction curves, constructed from detection data from all surveys combined at each location, show that the estimated sample effort required for high confidence (> 95%) detection of all aquatic plants at a site, including potentially invasive species, varies (< 100 sample units for Detroit River; > 300 sample units for Milwaukee, roughly equivalent to 6 to 18 days sampling effort, respectively). At least 70% of the estimated species pool was detected at each site during initial 3-day surveys. Leveraging information on detection patterns from initial surveys, including depth and species richness strata, improved survey efficiency and completeness at some sites, with detection of at least 80% of the estimated species pool during subsequent surveys. Based on a forest-based classification and regression method, a combination of just five variables explained 70% or more of the variation in observed richness at all sites (depth, fetch, percent littoral, distance to boat ramps and distance to marinas). We discuss how the model outcomes can be used to inform survey design for other Great Lakes coastal areas. The survey design we describe provides a useful template that could be adaptively improved for early detection of IAP in the Great Lakes. [ABSTRACT FROM AUTHOR]

High densities of invasive rusty crayfish on critical spawning reefs present a potential impediment to the recovery of native fish in the Laurentian Great Lakes. Suppression of rusty crayfish on spawning reefs to protect fall spawning native fishes in the Great Lakes is hampered by regular storm events and ambient weather conditions, limiting the number of practical days traps can be checked, cleared, and re-baited. The Gee minnow trap design is the most common gear for sampling and managing crayfish, yet design constraints of the standard Gee minnow trap manifest as tradeoffs between capture efficiency and retention for users. In this study, we compared catch rates from a semi-controlled field experiment and escapement probabilities from laboratory controlled trials for a Gee minnow trap, a modified Gee minnow trap with intention to reduce escapement, and an experimental flat-bottomed pyramid design which showed potential promise during prototype-stage development. Bayesian parameter estimation of generalized linear models applied to catch data suggested that standard Gee minnow traps performed at least as well and often better than both novel trap designs in catch rate and escapement probability. Escapement during laboratory controlled trials was high for all trap designs, demonstrating that retention of trapped individuals is a persistent problem for crayfish monitoring and management. We conclude from our data that standard Gee minnow traps are a sensible gear choice for monitoring and/or potential suppression efforts for invasive rusty crayfish on nearshore spawning reefs in the Great Lakes. However, modifications to its design to improve retention should yet be pursued. [ABSTRACT FROM AUTHOR]

The inconsistency in regulated species lists across the shared waters of the Great Lakes undermines the collective prevention efforts of the region, resulting in a "weakest link" problem; some jurisdictions regulate more than 100 species, others fewer than 20. We examine progress over the last twelve years toward more consistent regulated species lists within the 10 Great Lakes jurisdictions. Using a risk assessment framework, we assess a suite of regulated and unregulated organisms that have been identified as having the potential for introduction. Using these species assessments, we determine how sufficient current regulated species lists are in protecting against high-risk species. We also use these species assessments to transparently identify potential high-risk candidates for regional regulatory consideration. A total of 136 aquatic species were regulated by at least one jurisdiction (69 plant species and 67 animal species). The number of species regulated by 5 or more jurisdictions has gone from 10 in 2008 to 44 in 2020. However, the majority (68%) of the currently regulated species are listed in less than half of the Great Lakes jurisdictions. The number of regulated species varies widely across jurisdictions for both taxonomic groups. Wisconsin regulates the largest number of plant and animal species (104 in total), followed by Minnesota (71), New York (59), Illinois/Indiana/Michigan/Ohio (45), Pennsylvania (34), Ontario (23) and Québec (19). We observed only a weak positive correlation between impact score and regulation status. Many of the most-regulated species have impact scores in the low or low-moderate categories, and several species with high impact scores are regulated by less than half of jurisdictions. Twenty-one species (17 plant and 4 animal) are identified as priorities for future regulatory listing. [ABSTRACT FROM AUTHOR]

Risk-based prioritization for early detection monitoring is of utmost importance to prevent and mitigate invasive species impacts and is especially needed for large ecosystems where management resources are not sufficient to survey all locations susceptible to invasion. In this paper we describe a spatially-explicit and quantitative approach for identifying the highest risk sites for aquatic invasive species (AIS) introduction into the United States' waters of the Laurentian Great Lakes, a vast inland sea with a surface area of 246,049 square km and a shoreline length of 16,431 km. We compiled data from geospatial metrics available across all of the US waters of the Great Lakes as surrogates for propagule pressure from the dominant AIS pathways. Surrogates were weighted based on the observed or expected contribution of each pathway to past (historic) and predicted future invasions. Weighted surrogate data were combined to generate "invasion risk" scores for plants, invertebrates, fish, and all taxa combined at 3,487 management units (9 km × 9 km). The number of sites with invasion risk scores > 0 is: for plants (490), for invertebrates (220), for fish (436), and for all taxa (403). The rank order of sites with the highest risk scores varies by taxa, but in general the top thirty highest risk sites are the same across all groups. For all taxonomic groups, we show that the "top 30" sites account for at least 50% of predicted propagule pressure to the basin from all pathways. Many of the highest risk sites are located in western Lake Erie, southern Lake Michigan, and the St. Clair-Detroit River System. This framework provides a starting point for objective surveillance planning and implementation that can be adaptively improved. [ABSTRACT FROM AUTHOR]

Aim In clear, cold-water lakes, ultraviolet radiation ( UV) and temperature are two important stressors that may prevent the establishment of aquatic invasive species by inhibiting the survival of sensitive early life history stages. In this study, we develop a UV-temperature response model to predict the establishment potential of a warmwater fish, largemouth bass ( Micropterus salmoides), in a large subalpine lake based on the ability of bass larvae to tolerate UV and temperature stress along a UV-temperature stress gradient. Location Lake Tahoe ( California/ Nevada, USA). Methods We compared the UV tolerance of largemouth bass larvae to that of the native redside minnow ( Richardsonius egregius) in outdoor UV exposure-response experiments. A UV-temperature response model for larval bass was developed that combined the experimentally derived UV exposure response from our outdoor experiments with a temperature response curve derived from the literature. We used the UV-temperature response model to predict reproductive success (i.e. larval survival) over the range of UV exposure and temperature conditions in nearshore Lake Tahoe. The model predictions were validated with in situ incubation experiments at nearshore locations. Results Non-native bass were significantly less UV tolerant than native redside minnows. The UV-temperature response model predicted that larval bass survival varies seasonally, spatially and over depth gradients in nearshore Lake Tahoe and is constrained by UV and temperature conditions. In situ incubation experiments confirmed model predictions. Main conclusions Our findings provide important insights into the potential for species invasion in clear, cold-water lakes that are experiencing significant changes in both temperature and transparency. The conceptual model and approach that we employ is a potentially powerful tool for exploring unanswered questions in invasion biology, including the role of alternate stable states in facilitating invasion and the potential for invasive species to promote 'invasional meltdown' through their impacts on water clarity and temperature. [ABSTRACT FROM AUTHOR]