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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]

A thorough assessment of aquatic nonindigenous species' risk facilitates successful monitoring and prevention activities. However, species- and vector-specific information is often limited and difficult to synthesize across a single risk framework. To address this need, we developed an assessment framework capable of estimating the potential for introduction, establishment, and impact by aquatic nonindigenous species from diverse spatial origins and taxonomic classification, in novel environments. Our model builds on previous approaches, while taking on a new perspective for evaluation across species, vectors and stages to overcome the limitations imposed by single species and single vector assessments. We applied this globally-relevant framework to the Laurentian Great Lakes to determine its ability to evaluate risk across multiple taxa and vectors. This case study included 67 aquatic species, identified as “watchlist species" in NOAA's Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS). Vectors included shipping, hitchhiking/fouling, unauthorized intentional release, escape from recreational or commercial culture, and natural dispersal. We identified potential invaders from every continent but Africa and Antarctica. Of the 67 species, more than a fifth (21%) had a high potential for introduction and greater than 60% had a moderate potential for introduction. Shipping (72%) was the most common potential vector of introduction, followed by unauthorized intentional release (25%), hitchhiking/fouling (21%), dispersal (19%), stocking/planting/escape from recreational culture (13%), and escape from commercial culture. The ability to assess a variety of aquatic nonindigenous species from an array of potential vectors using a consistent methodology is essential for comparing likelihoods of introduction, establishment, and impact. The straightforward design of this framework will allow its application and modification according to policy priorities by natural resource managers. The ability to use a variety of information sources facilitates completion of assessments despite the paucity of data that often plagues aquatic nonindigenous species management. [ABSTRACT FROM AUTHOR]