Cooperative Fish and Wildlife Research Units Program: Georgia
Education, Research and Technical Assistance for Managing Our Natural Resources

Tsehaye, I., M. L. Jones, B. J. Irwin, D. G. Fielder, J. E. Breck, and D. R. Luukkonen. 2015. A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan. Natural Resource Modeling 28(3):348-376.


The proliferation of double-crested cormorants (DCCOs) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased demands from angler communities and aquaculturists to reduce their abundance. We developed a predictive model representing bird–fish interactions to help inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with empirical data suggested that our relatively simple model was able to accurately reconstruct DCCO population dynamics during a period of intensive control in the past. Although parameterization of several model components was based on expert opinion or data for related species, we were able to discriminate among alternative parameterizations of demographic processes, especially site fidelity, based on comparisons of model predictions with observations of annual changes in DCCO numbers under management measures implemented from 2004 to 2012. We also identified remaining critical uncertainties in the spatial distribution of affected fish populations relative to the size of DCCO feeding areas, which could be used to prioritize future research and monitoring needs. Using this model, our forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan. Our model forecasts also suggested that DCCO control may be necessary to achieve management goals for some valued fisheries in Michigan, which were shown to have been impacted by DCCO predation. Finally, our simple DCCO–fish dynamics model could be extended by including more complex assumptions about DCCO and fish population dynamics and can be adopted for other DCCO management programs in North America or elsewhere.