Population Viability Analysis: Theoretical Advances and Research Needs

Article excerpt

Abstract

Population viability analysis (PVA) is a set of tools for forecasting population growth and estimating extinction risk. Recent methdological advances include assessing model reliability by estimating model parameters from time series with observation errors, synthesis of PVA with decision theory, extension of models to sex-structured populations and to density dependence in age-structured populations, and experimental validation of qualitative model predictions. Future research should focus on developing biologically based models of population growth, model selection, and model averaging; extension of models to species with complicated life histories including quiescent stages and seasonal life histories; and developing tools for validly incorporating additional information about species' demography from knowledge of their ecologies and natural histories. PVA is a rapidly developing methodology and users should recognize that a large variety of models and techniques are available for population forecasting.

Resumen

El analisis de la viabilidad de poblaciones (PVA-en ingles) es un juego de herramientas para pronosticar el crecimiento de las poblaciones y para estimar su riesgo de extincion. Avances metodologicos recientes incluyen la evaluacion de la validez de los paramentos de modelos de << time series >> con errores de observacion, sintesis del analisis de viabilidad poblacional con la teoria de decisiones, la extension de modelos a poblaciones estructuradas por sexo con poblaciones estructuradas por edad, y la validacion experimental de modelos cualitativos de prediccion. Modelos futuros de investigacion deberian enfocarse en el desarrollo de modelos biologicos de crecimiento poblacional, la seleccion de modelos, el promedio de modelos, la extension de modelos a especies con historias de vida complejas incluyendo historias de vida temporales y etapas de quiescente, y el desarrollo de herramientas de validacion incorporando informacion adicional sobre la demografia de especies usando conocimiento de su ecologia y su historia natural. El PVA es un metodo en rapido desarrollo y los usuarios deben darse cuenta que disponen de una larga lista de modelos y tecnologias para la prediccion de poblaciones.

Population Viability Analysis (PVA) arose in the 1980's as a set of tools for conservation biologists to determine the risks faced by threatened and endangered species (Soule 1987, Shaffer 1981). Development of PVA was prompted by the emerging extinction crisis and especially by concern for three endangered North American species--Grizzly bear (Ursus Arctos), Northern spotted owl (Strix occidentalis), and Logger-head sea turtle (Caretta caretta), all of which were featured in early applications of PVA. During this period, important theoretical developments from the 1970's and early 1980's were widely publicized and the first case studies were conducted.

In the early 1990's two important developments occurred. First, Dennis et al. (1991) demonstrated how the parameters of the stochastic exponential population growth process could be estimated with regression analysis and how error in these estimates could be propagated through model equations to estimate uncertainty in the chance of extinction. The results from propagating sampling errors are now sometimes called population projection intervals (Lande et al. 2003) and are crucial if management actions are to be adequately informed. Second, software for simulating population trajectories on desktop computers became widely available (Lacy 1993). Notwithstanding more recent developments, especially for the analysis of metapopulations and for nonlinear models of population growth, the combination of the stochastic exponential population growth models and publicly available simulation software probably still represent the majority of PVA' s being conducted now, a decade later.

The apparent simplicity of PVA, especially when it relies heavily on these two techniques, has repeatedly raised concern that it will be used incorrectly when deciding conservation actions. …