• Title of article

    Extinction risk of a meta-population: aggregation approach

  • Author/Authors

    Hakoyama، نويسنده , , HIROSHI and IWASA، نويسنده , , Yoh، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2005
  • Pages
    14
  • From page
    203
  • To page
    216
  • Abstract
    Aggregation of variables of a complex mathematical model with realistic structure gives a simplified model which is more suitable than the original one when the amount of data for parameter estimation is limited. Here we explore use of a formula derived for a single unstructured population (canonical model) in predicting the extinction time for a population living in multiple habitats. In particular we focus multiple populations each following logistic growth with demographic and environmental stochasticities, and examine how the mean extinction time depends on the migration and environmental correlation. When migration rate and/or environmental correlation are very large or very small, we may express the mean extinction time exactly using the formula with properly modified parameters. When parameters are of intermediate magnitude, we generate a Monte Carlo time series of the population size for the realistic structured model, estimate the “effective parameters” by fitting the time series to the canonical model, and then calculate the mean extinction time using the formula for a single population. The mean extinction time predicted by the formula was close to those obtained from direct computer simulation of structured models. We conclude that the formula for an unstructured single-population model has good approximation capability and can be applicable in estimating the extinction risk of the structured meta-population model for a limited data set.
  • Keywords
    Aggregation , extinction , Correlation of environmental fluctuation , Migration rate , Mean extinction time
  • Journal title
    Journal of Theoretical Biology
  • Serial Year
    2005
  • Journal title
    Journal of Theoretical Biology
  • Record number

    1536785