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A Dynamic Principal-Agent Model of Human-Mediated Aquatic Species Invasions

Published online by Cambridge University Press:  15 September 2016

Alexander J. Macpherson ,
Rebecca Moore  and
Bill Provencher
Alexander J. Macpherson
Affiliation:
School of Forest Resources and Conservation at the University of Florida in Gainesville, Florida
Rebecca Moore
Affiliation:
Department of Agricultural and Applied Economics at the University of Wisconsin in Madison, Wisconsin
Bill Provencher
Affiliation:
Department of Agricultural and Applied Economics at the University of Wisconsin in Madison, Wisconsin
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Abstract

This paper presents a dynamic principal-agent model of aquatic species invasions in which a manager, concerned about the spread of invasive species across lakes by boaters, sets interseasonal management controls on a lake-by-lake basis, and boaters make a series of intraseasonal trip decisions to maximize random utility during the course of the season, conditional on the controls imposed by the manager. The results of a simulated invasion of Eurasian watermilfoil (Myriophyllum spicatum) highlight interesting aspects of the optimal management policies under two different management objectives: maximizing boater welfare and minimizing milfoil spread.

Keywords

invasive speciesrandom utility modelEurasion watermilfoildynamic optimizationprincipal-agent
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 35 , Issue 1 , April 2006 , pp. 144 - 154
Copyright
Copyright © 2006 Northeastern Agricultural and Resource Economics Association 

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References

Bettoli, P.W. Maceina, M.J. Noble, R.L. and Betsill, R.K. 1992. “Piscivory in Largemouth Bass as a Function of Aquatic Vegetation Abundance.” North American Journal of Fisheries Management 12: 509–516.Google Scholar
Bossenbroek, J.M. Kraft, C.E. and Nekola, J.C. 2001. “Prediction of Long-Distance Dispersal Using Gravity Models: Zebra Mussel Invasion of Inland Lakes.” Ecological Applications 11(6): 1778–1788.Google Scholar
Boylen, C.W. Eichler, L.W. and Madsen, J.D. 1999. “Loss of Native Aquatic Plant Species in a Community Dominated by Eurasian Watermilfoil.” Hydrobiologia 415: 207–211.Google Scholar
Buchan, L.A.J. and Padilla, D.K. 1999. “Estimating the Probability of Long-Distance Overland Dispersal of Invading Aquatic Species.” Ecological Applications 9(1): 254–265.Google Scholar
Carpenter, S.R. 1980. “Enrichment of Lake Wingra, Wisconsin, by Submersed Macrophyte Decay.” Ecology 61(5): 1145–1155.Google Scholar
Feather, P.M. 1994. “Sampling and Aggregation Issues in Random Utility Model Estimation.” American Journal of Agricultural Economics 76(4): 772–780.Google Scholar
Feather, P. Hellerstein, D. and Tomasi, T. 1995. “A Discrete-Count Model of Recreational Demand.” Journal of Environmental Economics and Management 29(2): 214–227.Google Scholar
Finnoff, D. Shogren, J.F. Leung, G. and Lodge, D. 2005. “The Importance of Bioeconomic Feedback in Invasive Species Management.” Ecological Economics 52(3): 367–381.Google Scholar
Haab, T.C. and Hicks, R.L. 1997. “Accounting for Choice Set Endogeneity in Random Utility Models of Recreation Demand.” Journal of Environmental Economics and Management 34(2); 127–147.Google Scholar
Haab, T.C. and Hicks, R.L. 1999. “Choice Set Considerations in Models of Recreation Demand: History and Current State of the Art.” Marine Resource Economics 14(4): 271–281.Google Scholar
Halsted, J.M. Michaud, J. Hallas-Burt, S. and Gibbs, J.P. 2003. “Hedonic Analysis of Effects of a Nonnative Invader (Myriophyllum heterophyllum) on New Hampshire (USA) Lakefront Properties.” Environmental Management 32(3): 391–398.Google Scholar
Hicks, R.L. and Strand, I. 2000. “The Extent of Information: Its Relevance for Random Utility Models.” Land Economics 76(3): 374–385.Google Scholar
Johnson, L.E. and Carlton, J.T. 1996. “Post-Establishment Spread in Large-Scale Invasions: Dispersal Mechanisms of the Zebra Mussel Dreissena polymorpha.” Ecology 77(6): 1686–1690.Google Scholar
Lupi, F. and Feather, P.M. 1998. “Using Partial Site Aggregation to Reduce Bias in Random Utility Travel Cost Models.” Water Resources Research 34(12): 3595–3603.Google Scholar
Macpherson, A.J. 2004. “A Model of Human-Mediated Aquatic Species Invasions: A Eurasian Watermilfoil Case Study.” Master's thesis, Department of Agricultural and Applied Economics, University of Wisconsin-Madison.Google Scholar
Madsen, J.D. 1999. “Predicting the Invasion of Eurasian Watermilfoil into Northern Lakes.” Technical Report No. A-99-2, Waterways Experiment Station, U.S. Army Corps of Engineers, Vicksburg, MS.Google Scholar
Madsen, J.D. Eichler, L.W. and Boylen, C.W. 1988. “Vegetative Spread of Eurasian Watermilfoil in Lake George, New York.” Journal of Aquatic Plant Management 35: 63–68.Google Scholar
Mittelbach, G.G. 1988. “Competition Among Refuging Sunfishes and Effects of Fish Density on Littoral Zone Invertebrates.” Ecology 69(3): 614–623.Google Scholar
Olson, M.H. Carpenter, S. R. Cunningham, P. Gamy, S. Herwig, B.R. Nibbelink, N.P. Pellett, T. Storlie, C. Trebitz, A.S. and Wilson, K.A. 1998. “Managing Macrophytes to Improve Fish Growth: A Multi-lake Experiment.” Fisheries 23(2): 6–12.Google Scholar
Parsons, G.R. 2003. “The Travel Cost Model.” In Champ, P.A. Boyle, K.J. and Brown, T.C. eds., A Primer on Nonmarket Valuation. Boston: Kluwer Academic Publishers.Google Scholar
Parsons, G.R. and Kealy, M.J. 1992. “Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation.” Land Economics 68(1): 93–106.Google Scholar
Parsons, G.R. and Needelman, M.S. 1992. “Site Aggregation in a Random Utility Model of Recreation.” Land Economics 68(4): 418–433.Google Scholar
Peters, T. Adamowicz, W.L. and Boxall, P.C. 1995. “Influence of Choice Set Considerations in Modeling the Benefits from Improved Water Quality.” Water Resources Research 31(7): 1781–1787.Google Scholar
Schneider, D.W. Ellis, C.D. and Cummings, K.S. 1998. “A Transportation Model Assessment of the Risk to Native Mussel Communities from Zebra Mussel Spread.” Conservation Biology 12(4): 788–800.Google Scholar
Settle, C. Crocker, T.D. and Shogren, J.F. 2002. “On the Joint Determination of Biological and Economic Systems.” Ecological Economics 42(1-2): 301–311.Google Scholar
Settle, C. and Shogren, J.F. 2002. “Modeling Native-Exotic Species within Yellowstone Lake.” American Journal of Agricultural Economics 84(5): 1323–1328.Google Scholar
Unmoth, J.M.L. Hansen, M.J. and Pellett, T.D. 1999. “Effects of Mechanical Harvesting of Eurasian Watermilfoil on Largemouth Bass and Bluegill Populations in Fish Lake, Wisconsin.” North American Journal of Fisheries Management 19(4): 1089–1098.Google Scholar
Wiley, M.J. Gordon, R.W. Waite, S.W. and Powless, T. 1984. “The Relationship Between Aquatic Macrophytes and Sport-fish Production in Illinois Ponds: a Simple Model.” North American Journal of Fisheries Management 4: 111–119.Google Scholar
Wisconsin Department of Natural Resources. 2004. “The Facts of Eurasian Water Milfoil.” Technical Publication No. PUB-WT-781, Wisconsin Department of Natural Resources, Madison, WI.Google Scholar
Woodward, R.T. Wui, Y.S. and Griffin, W.L. 2005. “Living with the Curse of Dimensionality: Closed-Loop Optimization in a Large-Scale Fisheries Simulation Model.” American Journal of Agricultural Economics (87) 1: 48–60.Google Scholar