Risk analysis and use of stochastic population models for determining the Endangered Species Act status of North Pacific marine mammals. Ph.D. dissertation

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Thesis (Ph. D.)--University of Washington, 1998 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.

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    • "Because the entire distribution for the York et al. model was not available, and the format for the output for the ALEX model is not consistent with that for the Gerber and DeMaster model (see Gerber, 1998), three points on the extinction curve were compared for each of the three models. We propose that consideration of three points on the extinction distribution accurately represented these distributions (Fig. 3). "
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    ABSTRACT: Two distinct viability models are developed for Steller sea lions (Eumetopias jubatus) to evaluate the sensitivity of extinction risk to various levels of stochasticity, spatial scale and density dependence. These models include a metapopulation model, Analysis of the Likelihood of Extinction (ALEX; Possingham et al., 1992; Possingham, H., Davies, I.A., Noble, I. 1992. ALEX 2.2 Operation Manual. Department of Applied Mathematics, University of Adelaide, Adelaide, SA 5005; Australia.), and a model that incorporates both sampling and process error in estimating population parameters from timeseries data (Gerber and DeMaster, 1999; Gerber, L.R., DeMaster, D.P. 1999. An approach to endangered species act classification of long-lived vertebrates: a case study of north Pacific humpback whales. Conservation Biology 13 (5);1203–1214.). Results are compared with a third model that encompasses three different geographic scales (York et al., 1996; York, A.E., Merrick, R.L., Loughlin, T.R. 1996. An analysis of the Steller Sea lion metapopulation in Alaska. In: McCullough, D.R. (Ed.), Metapopulations and Wildlife Conservation. Island Press, Covelo, CA pp. 259–292). The combination of modeling approaches provides a basis for considering how model parameterization and the selection of classification criteria affect both model results and potential status determinations. Results from the models generally agree with regard to central tendency, 25th and 75th percentile times to extinction. For Steller sea lions, the distributions of time to extinction for each model were narrower than the range of extinction distributions between models. If this finding applies generally to listed species, it would suggest that more than one viability model should be considered when listing decisions are made. On a more applied basis, the results of our analysis provide a quantitative assessment of extinction risk of Steller sea lions in the context of its status pursuant to the US Endangered Species Act.
    Full-text · Article · Dec 2001 · Biological Conservation
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    ABSTRACT: The U.S. 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, we developed a new approach to determining classification criteria for long-lived vertebrates. 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. The way to combine these features is to identify a population size and range of population growth rates (where λ denotes the annual multiplicative rate of change of a population) above which there is a negligible probability of extinction. To do so, (1) information on the current population size and its variance is specified; (2) available information on vital rates or changes in abundance over time is used to generate a probability distribution for the population's λ; (3) the lower fifth percentile value for λ (denoted as λ(0.05) ) is obtained from the frequency distribution of λs; and (4) if λ(0.05) is <1.0, a backwards population trajectory starting at 500 individuals for a period of 10 years is performed and the resulting population size is designated as the threshold for listing a species as endangered, or if λ(0.05) is ≥1.0, the threshold for endangerment is set at 500 animals. A similar approach can be used to determine the threshold for listing a species as threatened under the ESA. We applied this approach to North Pacific humpback whales ( Megaptera novaeangliae) and used Monte Carlo simulations to produce a frequency distribution of λs for the whales under three different scenarios. Using λ(0.05), it was determined that the best estimates of current abundance for the central population of North Pacific humpback whales were larger than the estimated threshold for endangered status but less than the estimated threshold for threatened status. If accepted by the responsible management agency, this analysis would be consistent with a recommendation to downlist the central stock of humpback whales to a status of threatened, whereas the status of eastern and western stocks would remain endangered. Resumen: El acta de Especies Amenazadas de los Estados Unidos (ESA) demanda que los planes de recuperación incluyan criterios específicos para determinar cuando una especie debe ser removida de la Lista de Especies de Vida Silvestre en Peligro. Para alcanzar este mandato, desarrollamos una nueva aproximación para determinar los criterios de clasificación para vertebrados de vida larga. La idea clave es que las amenazas dependen de dos aspecto críticos de una población: tamaño poblacional y tendencias en tamaño poblacional debido a la variabilidad intrínseca de las tasas de crecimiento poblacional. La forma de combinar estas características es la identificación de un tamaño poblacional y el rango de tasas de crecimiento poblacional (donde λ denota la tasa anual multiplicativa de cambio de una población) por arriba de la cual existe una probabilidad de extinción neglibible. Para hacer esto 1) Se especifica la información sobre el tamaño poblacional actual y su varianza; 2) Se utiliza información viable sobre tasas vitales o cambios en abundancia sobre el tiempo para generar una distribución de probabilidades para la población; 3) se obtiene el valor del percentil mas bajo para λ (denotado como λ(0.05)) de la distribución de frecuencias de λs; y 4) si λ(0.05) es <1.0, se efectúa una trayectoria hacia atrás iniciando con 500 individuos por un período de 10 años y el tamaño poblacional resultante se designa como el límite para enlistar una especie bajo el estatus de en peligro ó si el λ(0.05) es ≥1.0, el límite para considerar amenaza se establece en 500 animales. Una aproximación similar puede ser usada para determinar los límites para enlistar especies como en peligro bajo la ESA. Aplicamos esta aproximación para la ballena jorobada del Pacífico Norte ( Megaptera novaeangliae) y utilizamos simulaciones Monte Carlo para producir distribuciones de frecuencia de λs para ballenas bajo diferentes escenarios. Utilizando el λ(0.05), se determinó que los mejores estimadores de la abundancia actual para la población central de la ballena jorobada del Pacífico Norte fueron mayores que los límites estimados para ser considerada en el estatus de en peligro, pero menor a los límites de estatus de amenazada. Si este análisis es aceptado por las agencias de manejo responsables, podría ser consistente con una recomendación de desenlistar el grupo central de ballenas jorobadas y pasarlo al estatus de amenazadas, mientras que el estatus de los grupos del Este y Oeste deberán permanecer en el estatus de en peligro.
    Preview · Article · Sep 2008 · Conservation Biology