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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.

A framework for aquatic invasive species surveillance site selection and prioritization in the US waters of the Laurentian Great Lakes