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Assessing recovery feasibility for piping plovers using optimization and simulation

January 1, 2003

Optimization and simulation modeling can be used to account for demographic and economic factors simultaneously in a comprehensive analysis of endangered-species population recovery. This is a powerful approach that is broadly applicable but underutilized in conservation biology. We applied the approach to a population recovery analysis of threatened and endangered piping plovers (Charadrius melodus) in the Great Plains of North America. Predator exclusion increases the reproductive success of piping plovers, but the most cost-efficient strategy of applying predator exclusion and the number of protected breeding pairs necessary to prevent further population declines were unknown. We developed a linear programming model to define strategies that would either maximize fledging rates or minimize financial costs by allocating plover pairs to 1 of 6 types of protection. We evaluated the optimal strategies using a stochastic population simulation model. The minimum cost to achieve a 20% chance of stabilizing simulated populations was approximately $1-11 million over 50 years. Increasing reproductive success to 1.24 fledglings/pair at minimal cost in any given area required fencing 85% of pairs at managed sites but cost 23% less than the current approach. Maximum fledging rates resulted in >20% of simulated populations reaching recovery goals in 30-50 years at cumulative costs of <$16 million. Protecting plover pairs within 50 km of natural resource agency field offices was sufficient to increase simulated populations to established recovery goals. A range-wide management plan needs to be developed and implemented to foster the involvement and cooperation among managers that will be necessary for recovery efforts to be successful. We also discuss how our approach can be applied to a variety of wildlife management issues.

Publication Year 2003
Title Assessing recovery feasibility for piping plovers using optimization and simulation
Authors M.A. Larson, M.R. Ryan, R.K. Murphy
Publication Type Article
Publication Subtype Journal Article
Series Title Wildlife Society Bulletin
Index ID 70025247
Record Source USGS Publications Warehouse