Following their introduction, invasive species management is most successful and cost-effective when new invaders are detected while still rare. Given the low capture probability for extremely rare species, early detection programs for aquatic invasive species (AIS) must maximize efficiencies to be successful. This study introduces the Rare Community Index (RCI) as a tool to determine sampling hotspots within locations to potentially increase efficiencies of AIS monitoring efforts.

The RCI evaluates species assemblages at individual sites within a given spatial extent based on the observed species rarity and species richness. We chose to leverage these two metrics to guide future site selection under the assumption that areas with high numbers of established species, and specifically established rare species, would also attract newly introduced AIS. We applied the RCI using 9 years of species capture data in a Hotspot Analysis to identify optimal sampling areas within a large freshwater bay with a high risk of AIS introductions in the Laurentian Great Lakes. Additionally, we demonstrate how the RCI could be used to evaluate the relative effectiveness of fisheries gear types.

Our findings demonstrate that the RCI coupled with Hotspot Analysis identified areas within a large bay to prioritize sampling with various gear types. Additionally, the RCI identified differences in the relative effectiveness of different gear types in AIS monitoring surveys. The results are consistent with the published literature on the locations and gear types that would be most efficient for surveying.

Practical implication: the RCI provides a potential framework for optimizing sampling efficiency for AIS monitoring on the basis of species rarity and species richness. By prioritizing rare communities and adapting sampling priorities over time, the RCI offers a dynamic approach to monitoring AIS to facilitate early detection and response to preserve biodiversity in aquatic systems.

Included here is the Maumee River System Fish Community Dataset, which contains date, gear type, location coordinates, and species captured for each of the 619 sites utilized in the following publication:

Huber, E.D., G. Wright, J. L. Fischer, J. Lajavic, and K. Towne. 2025. Optimized early detection of aquatic invasive species using a community rarity index. Ecological Solutions and Evidence.