Computer simulation of wolf-removal strategies for animal damage control

摘要: Because of the sustained growth gray wolf (Canis lupus) population in western Great Lakes region United States, management agencies are anticipating removal from federal endangered species list and proposing strategies for management. Strategies needed that would balance conflicting public demands conservation protection with depredation on livestock, poultry, pets. We used a stochastic, spatially structured, individually based simulation model hypothetical population, representing small subset wolves, to predict relative performance 3 wolf-removal strategies. Those included reactive (wolf occurred summer after depredation), preventive (wolves removed winter territories occasional population-size annually all near farms). Performance measures number depredating packs wolves removed, cost, size 20 years. evaluated various scenarios about immigration, trapping success, likelihood engaging depredation. Four robust results emerged simulations: 1) each strategy reduced by at least 40% compared no action, 2) fewer than because were before pups born, 3) was expensive repeated annual kept most farms free 4) none threatened populations unless they isolated took place not wild areas. For populations, alone ensured Such can assist decision makers managing states.