Variation among Individuals and Reduced Demographic Stochasticity
- 18 January 2002
- journal article
- research article
- Published by Wiley in Conservation Biology
- Vol. 16 (1) , 109-116
- https://doi.org/10.1046/j.1523-1739.2002.00036.x
Abstract
Population viability analysis ( PVA) is a technique that employs stochastic demographic models to predict extinction risk. All else being equal, higher variance in a demographic rate leads to a greater extinction risk. Demographic stochasticity represents variance due to differences among individuals. Current implementations of PVAs, however, assume that the expected fates of all individuals are identical. For example, demographic stochasticity in survival is modeled as a random draw from a binomial distribution. We developed a simple conceptual model showing that if there is variation among individuals in expected survival, then existing PVA models overestimate the variance due to demographic stochasticity in survival. This is a consequence of Jensen's inequality and the fact that the binomial demographic variance is a concave function of mean survival. The effect of variation among individuals on demographic stochasticity in fecundity depends on the mean-variance relationship for individual reproductive success, which is not presently known. If fecundity patterns mirror those of survival, then variation among individuals will reduce the extinction risk of small populations. Resumen: El análisis de viabilidad poblacional (AVP) es un técnica que emplea modelos demográficos estocásticos para predecir el riesgo de extinción. Todo lo demás siendo igual, mayor variación en la tendencia demográfica conduce a un mayor riesgo de extinción. La estocasticidad demográfica representa variación debido a diferencias entre individuos. Sin embargo, los AVP actualmente asumen que el destino esperado para cada individuo es idéntico. Por ejemplo, la estocasticidad demográfica en la supervivencia es modelada como una muestra aleatoria de una distribución binomial. Desarrollamos un modelo conceptual simple que muestra que si hay variación entre individuos en la supervivencia esperada, entonces los modelos de AVP existentes sobrestiman la variación debida a la estocasticidad demográfica en la supervivencia. Esto es una consecuencia de la desigualdad de Jensen y del hecho de que la variación demográfica binomial es una función cóncava de la supervivencia promedio. El efecto de la variación entre individuos sobre la estocasticidad demográfica en la fecundidad depende de la relación media-varianza del éxito reproductivo individual, que actualmente es desconocida. Si los patrones de fecundidad son un reflejo de los de supervivencia, entonces la variación entre individuos reducirá el riesgo de extinción de poblaciones pequeñas.Keywords
This publication has 26 references indexed in Scilit:
- A General and Dynamic Species Abundance Model, Embracing the Lognormal and the Gamma ModelsThe American Naturalist, 2000
- Pessimistic and Optimistic Bias in Population Viability AnalysisConservation Biology, 2000
- Estimating the time to extinction in an island population of song sparrowsProceedings Of The Royal Society B-Biological Sciences, 2000
- EFFECTS OF INDIVIDUAL HETEROGENEITY IN ESTIMATING THE PERSISTENCE OF SMALL POPULATIONSNatural Resource Modeling, 1999
- Experimental Evolution of Senescence: An Analysis Using a 'Heterogeneity' Mortality ModelEvolution, 1998
- On the Use of Demographic Models of Population Viability in Endangered Species ManagementThe Journal of Wildlife Management, 1998
- ESTIMATING THE MAGNITUDE OF ENVIRONMENTAL STOCHASTICITY IN SURVIVORSHIP DATAEcological Applications, 1998
- Quantitative Genetics of Size, Shape, Life-History, and Fruit Characteristics of the Seed Heteromorphic Composite Heterosperma pinnatum. II. Correlation StructureEvolution, 1990
- Polymorphism from environmental heterogeneity: models are only robust if the heterozygote is close in fitness to the favoured homozygote in each environmentGenetics Research, 1985
- The average lifetime of a population in a varying environmentJournal of Theoretical Biology, 1981