Risk analysis and use of stochastic population models for determining Endangered Species Act status of North Pacific marine mammals

The Endangered Species Act (ESA) mandates that Recovery Plans include specific criteria to determine when a species should be removed from the List of Endangered and Threatened Wildlife. To meet this mandate, I develop several approaches to determine listing and recovery criteria for marine mammals. First, I review the history of marine mammal extinctions, introduce the current approach and associated problems for ESA listing and recovery decisions, describe the existing tools for using biological information for such decisions, and review the currently existing Recovery Plans for marine mammals. This sets the stage for three case studies (Steller sea lions, humpback whales, gray whales) in which I provide quantitatively robust and practical tools to classify marine mammals under the ESA.; In my first case study, the World Conservation Union (IUCN) classification scheme is applied to the western population of Steller sea lions to classify the population pursuant to the ESA. Three distinct Population Viability Analysis (PVA) models are developed and results of all models meet the classification criteria for vulnerable. As a second case study, a new approach to classifying large whales under the ESA is developed, and applied to North Pacific humpback whales and eastern North Pacific gray whales. The key idea is that endangerment depends on two critical aspects of a population: population size and trends in population size due to intrinsic variability in population growth rates. Analysis leads to a recommendation to downlist the central stock of humpback whales to a status of threatened, while maintaining the eastern and western stock as endangered. As a third case study, for eastern North Pacific gray whales, I used nineteen years of survey data to show that a quantitative decision to delist is unambiguously supported by eleven or more years of data, but precariously uncertain with fewer than ten years of data.; These three case studies illustrate the breadth of feasible approaches for using different quantities and qualities of scientific information for ESA conservation decisions. The development of this type of explicit and quantitative approach from which mistakes can be identified and understood is critical to effective conservation of threatened and endangered species.