AUTHORS: Michael Spear, Illinois Natural History Survey, Illinois River Biological Station (IRBS); Brandon Harris, IRBS; Levi Solomon, IRBS; Kris Maxson, IRBS; Andrya Whitten Harris, IRBS; Andrew Mathis, IRBS; Sam Schaick, IRBS; Jesse Williams, IRBS; Jason DeBoer, IRBS; Eric Hine, Illinois Natural History Survey, Great Rivers Field Station (GRFS); John Chick, GRFS; Jim Lamer, IRBS
ABSTRACT: The upper reaches of the Illinois Waterway are a critical containment threshold for invasive carps as they threaten to invade the Laurentian Great Lakes. Monitoring these carps – and evaluating the success of management efforts – has become the new focus of the Multi-Agency Monitoring program, a collaborative effort across state, federal, and partner agencies (discussed earlier in this session) originally designed for community-wide monitoring but recently adapted for invasive species management. Through careful analysis of the data, intentional re-allocation of resources, and effective communication across partner agencies, the MAM program has repositioned itself as a quantitative resource for evaluating the success of management efforts to contain invasive carps and prevent their entry into Lake Michigan. Here, we explore the first five years of MAM data and touch on fisheries topics including hyperstability, density-dependence, food web dynamics, and imperfect detection. A large, latitudinal gradient in carp density along the river allows for powerful space-for-time comparisons. Intense invasive carp removal efforts highlight stark contrasts between fisheries-dependent and fisheries-independent data sources. Clues from the health of the native community may offer complementary evidence for the trajectory of the invasive carp population, placing renewed value on maintaining the original community-wide sampling approach of MAM. As MAM answers this call to serve the short-term invasive species management goals, preserving the long-term integrity of its standardized sampling framework remains a priority that will require thoughtful, intentional, and iterative changes to the design and protocols of the program. Early results indicate that community-wide, fisheries-independent data such as MAM can flexibly serve shifting management priorities while maintaining long-term perspectives, a successful example of “adaptive monitoring.”
