LE3 .A278 2017

2017

Zhang, Ying
Teismann, Holger

Acadia University

Master of Science

Masters

Mathematics and Statistics

Mathematics & Statistics

Population reconstruction models are commonly used by wildlife managers to analyze animal populations, although realistic and accurate population information is gener- ally unavailable for evaluating these methods. To aid in the evaluation of population reconstruction models, we developed a stochastic harvest Leslie matrix simulation model that generates population and harvest data. The ergodic results of the pro- jection by the stochastic harvest Leslie matrix simulation model and the stochastic growth rate under such a projection were studied. The stochastic harvest Leslie ma- trix simulation model was proved to generate at least weakly-ergodic population pro- jection results. Through extensive simulation studies, the population age distribution generated by the simulation model was shown to be convergent, which is the usual model assumption underlying population reconstruction methods. A new modeling approach for analyzing population age distribution based only on harvest data was also proposed. Through extensive simulation studies, this new modeling approach was shown to provide accurate estimation of the population age distribution while imposing no strict assumptions on the fertility and the natural mortality of animals. A new R package, Wildlife 1.0, contains the main results from this thesis.

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https://scholar.acadiau.ca/islandora/object/theses:2172