Proceedings of the Vertebrate Pest Conference
Population dynamics: The foundation of wildlife damage management for the 21st century
- Author(s): Dolbeer, Richard A.
- et al.
Published Web Locationhttps://doi.org/10.5070/V418110312
To justify and defend lethal or reproductive control programs to solve vertebrate pest problems, wildlife biologists must have a sound understanding of the population status and dynamics of the problem species. Models are essential to project how populations will respond to proposed management actions, providing a scientific foundation to counter the emotional debates that often arise. Four population models (PM1 to PM4) for predicting population responses are described. PM1 and PM2 explore the relative efficacy of reproductive and lethal control for vertebrate species over 10-year intervals. PM3 simulates population responses to actual management actions through 10-year intervals. PM4 simulates population changes for a species at weekly intervals over an annual cycle, exploring the immediate (≤1 year) impact of population management actions. Population simulations using PM1 and PM2 demonstrated that for most vertebrate pest species considered, lethal control will be more efficient than reproductive control in reducing population levels. Reproductive control is more efficient than lethal control only for some rodent and small bird species with high reproductive rates and low survival rates. A simulation (PM3) of the removal of 47,000 laughing gulls (Larus atridlla) from the Long Island-New Jersey population accurately predicted the 33% decline of the population over five years. A simulation (PM4) of the annual cycle of the common grackle (Quiscalus quiscula) population in the eastern United States demonstrated why removing 4.2 million birds in one winter had no discernible impact on subsequent breeding populations. Understanding the population dynamics of wildlife species is the cornerstone to successful management, and population models will be essential for this task in the years to come.