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Rate Distribution Models for Size Structured Population Dynamics

This project was inspired by the wide use of mosquitofish in commercial rice fields as a means to reduce mosquito populations. Field experiments have produced mixed results regarding the effectiveness of mosquitofish for this purpose, and scientists at the University of California -- Davis and the California Department of Game an fisheries have been conducting closely monitored experiments to develop an understanding of the mosquitofish population dynamics. The data collected from these experiments exhibited certain features that were inconsistent with the commonly used Sinko-Streifer population model, which predicts how a population of individuals of different sizes evolves in time. One of the model's weaknesses is that it requires all individuals to have the same growth and mortality rates. In recent years several researchers both in the US and Europe have worked to develop models which are based on the Sinko-Streifer model but contain a distribution of growth rates. More general models involve distributions of birth and mortality rates, as well as nonlinear dependence on the total population size.

CRSC investigators have recently developed some parallel algorithms for estimating these rate distributions, and current fits to the Davis mosquitofish data using these algorithms are quite promising. Avenues of further research include the development of statistical tests of fit to quantify how well the model compares to the data, the incorporation of the mosquitoes into the model (as a predator/prey system), the development of optimization strategies to study how best to use mosquitofish in rice fields, and the investigation and generalization of the rate distributions to other population biology applications.

CRSC researchers on this project include H. T. Banks, K. Gaston and L. Potter. The efforts involve collaboration with scientists at the University of California -- Davis, University of Southern California, and Universitat Graz, Austria.












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