Integrated Pest Management (IPM) provides a powerful framework for addressing threats to human well-being caused by nuisance species including invasives. We examined the hypothesis that adaptive management could erode barriers to IPM implementation by developing a decision-analytic adaptive management framework for invasive sea lamprey (Petromyzon marinus) IPM in the Laurentian Great Lakes of North America. The framework addressed objectives associated with coordinating multiple sea lamprey control actions at the regional scale and objectives associated with internal validity of control actions. We reduced the scope of possible management actions by orders of magnitude to the set of 6432 alternatives expected to be both socially acceptable and technically feasible. Using utility theory, we identified the management actions that optimized expected utility for all possible objective weighting schemes that considered tradeoffs between maximizing learning about control tactic efficacy and minimizing cost to the IPM program. Sensitivity analyses revealed that assumptions about the social acceptability of deploying electric weirs to control invasive sea lamprey influenced selection of the optimal control action, suggesting that resolving this source of uncertainty through iterative application of the framework may lead to improved sea lamprey control outcomes. Overall, we found that adaptive management enabled learning processes useful for overcoming barriers to IPM of invasive sea lamprey. It formalized learning about sea lamprey control tactic efficacy as an objective of the IPM institution, questioned previously held assumptions about what constitutes a viable control strategy, and enabled a management experiment with temporal and spatial replication.
Keywords: Adaptive management; Decision Analysis; Great Lakes; Integrated Pest Management; Invasive species management; sea lamprey.
Published by Elsevier Ltd.