Overview (see Mills 91 - 99)
Exponential Growth Model
Unlimited, constant, favorable environment (i.e., population growth rate remains constant).
Age-specific birth and death rates remain constant (i.e., population has a stable-age distribution).
Stochastic Exponential Growth Models (see Humbert et al. in review):
Stochastic: involving a random variable; a random outcome
A random variable (e.g., number of offspring) is one that can take more than one value in which the values are determined by probabilities.
Statistical Distributions and random outcome (Examples: uniform, normal, log-normal)
a. Observation Error
b. 'Process' variation: environmental stochasticity bumps the population around
c. 'State-space' model (both observation error and process variation)
Limited environments cause age-specific birth and/or survival rates to decline with increasing population size.
Logistic (Ricker) Growth Model
Growth rate (i.e., birth rate and mortality rate) is a decreasing linear function of population size
Other Density-dependent Growth Models
Gompertz
Theta-logistic
Begon, M., and M. Mortimer. 1986. Population ecology: A unified study of animals and plants. Blackwell Scientific Publ., Boston, Mass. 220pp.
Caughley, G., and L. C. Birch. 1971. Rate of increase. J. Wildl. Manage. 35:658-663.
Elseth, G. D., and K. D. Baumgardner. 1981. Population biology. D. Van Nostrand Co., New York. 623pp.
Johnson, D. H. 1994. Population analysis. Pages 419-444 in T. A. Bookhout, ed. Research and management techniques for wildlife and habitats. Fifth ed. The Wildlife Society, Bethesda, Md.
Krebs, C. J. 1989. Ecological methodology. Harper & Row, Publ., New York. 654pp.
Wilson, E. O., and W. H. Bossert. 1971. A primer of population biology. Sinauer Assoc., Inc., Sunderland, Mass. 192pp.
