Abstract # 72:

Scheduled for Thursday, August 17, 2006 07:00 PM-09:00 PM: Session 8 (Regency West 1/3 ) Poster Presentation

Demographic Analysis and Forecast Modeling: A Case Study using the Rhesus Monkey Colony at Cayo Santiago

C. Akkoc1, L. Williams1, M. Gerald2, E. Maldonado2, J. Gonzalez-Martinez2 and E. N. Kraiselburd2
1University of South Alabama, Center for Neotropical Primate Research and Resources, Mobile, AL 36688, USA, 2Caribbean Primate Research Center, University of Puerto Rico, Puerto Rico
     The rhesus monkey (<i>Macaca mulatta</i>) colony located in Cayo Santiago, Puerto Rico, offers a unique opportunity to investigate population forecast models on a long-term, well documented population of animals. Census reports indicate three distinct periods of heavy animal removal, followed by periods of almost uninterrupted growth. Historical demographic information on mortality and fertility was obtained from the colony records and used as input for the forecast models. Two different approaches were used to compare actual colony growth against model projections; a “deterministic” model using demographic parameter means to estimate future population figures; and a “stochastic” model where probability distributions surrounding demographic means are sampled using a Monte Carlo simulation to generate probability distributions for the target forecast population. Both models accurately predicted the population growth following the three separate animal removal episodes, R2 = 99.4%-99.6%. These growth curves were consistent among themselves and independent of the colony age-sex distributions at the beginning of each growth period. This suggested a robust, intrinsic growth pattern not significantly influenced by initial conditions. This pattern is described by a standard exponential growth function. The two modeling techniques can be extended to investigations of “control” problems. Such tools allow for asking “what-if” types of questions involving variables, e.g. harvesting strategies, necessary for any colony to meet specific management targets. Supported by NIH, NCRR grants CM-5-P40RR003640, R24 RR020052, & P40-RR001254.