NATURAL RESOURCE MODELING Volume 28, Number 3, August 2015 A PREDICTIVE MODEL TO INFORM ADAPTIVE MANAGEMENT OF DOUBLE-CRESTED CORMORANTS AND FISHERIES IN MICHIGAN IYOB TSEHAYE* and MICHAEL L. JONES Quantitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University, 293 Farm Lane, Room 153 East Lansing, MI 48824 E-mail: tsehaye@msu.edu, jonesm30@msu.edu BRIAN J. IRWIN US Geological Survey, Georgia Cooperative Fish and Wildlife Research Unit, Warnell School of Forestry and Natural Resources University of Georgia, Athens, GA 30602 E-mail: irwin@uga.edu DAVID G. FIELDER Michigan Department of Natural Resources, Alpena Fisheries Research Station, 160 E. Fletcher Alpena, MI 49707 E-mail: fielderd@michigan.gov JAMES E. BRECK Michigan Department of Natural Resources, Institute for Fisheries Research 400 North Ingalls Building, Ann Arbor, MI 48109 E-mail: breck@umich.edu DAVID R. LUUKKONEN Michigan Department of Natural Resources, Rose Lake Research Center, 562 E. Stoll Road East Lansing, MI 48823 E-mail: luukkonend@michigan.gov Abstract. The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their po- tential negative impacts on game, cultured and forage fishes, island and ter- restrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a determinis- tic predictive model representing bird–fish interactions to inform an adap- tive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately recon- struct past DCCO population dynamics. These comparisons helped discrim- inate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future re- search and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in the state and that DCCO control may be necessary to ∗ Corresponding author: Iyob Tsehaye, Wisconsin Department of Natural Resources, Science Services, 2801 Progress Road, Madison, WI 53716, USA, e-mail: iyob.tsehaye@wisconsin.gov Received by the editors on 4 th February 2015. Revised 19 th June 2015. Accepted 16 th July 2015. Copyright c  2015 Wiley Periodicals, Inc. 348