Abstract # 128:

Scheduled for Friday, August 19, 2005 03:15 PM-03:30 PM: Session 10 (Mayfair Room) Oral Presentation

Population modeling for a captive squirrel monkey colony

C. Akkoc and L. Williams
University of South Alabama, Department of Comparative Medicine, University of South Alabama, Mobile, AL 36688, USA
     Population modeling in a closed breeding colony environment was approached by two different modeling techniques. Initially, deterministic modeling was used to estimate future population figures for animals in various age/sex classes. A stochastic model capable of accommodating long-term trends in population figures, as well as random biological variations, was subsequently developed. Point estimates (means) for input parameters used in the deterministic model were replaced by probability distributions based on historical data from colony records. Commercially available software, CRYSTAL BALL, was used to embed probability distributions in user-selected cells in the spreadsheet model. A Monte Carlo simulation within the spreadsheet drew, on each cycle, random values for input parameters from the distribution embedded in each relevant cell. After several thousand iterations, a probability distribution was formed representing census estimates. The two models were tested against actual colony census records over a period of 10 years. While colony totals kept drifting upward, away from deterministic estimates, reaching a peak deviation of 19% after 10 years, they remained well within 5% of distribution means from the stochastic model. The ‘static’ character of the deterministic model does not allow for trends to be incorporated into the input parameters, The stochastic model, on the other hand, can mimic population growth with long-term tendencies built into the Monte Carlo simulation scheme through probability distributions. Supported by NIH grant P40-001254.