A stochastic model is developed that can be used to compute the likelihood of observing a specific time stream of harvests of a wildlife
population. The harvest is assumed to be a count of the total number of animals in each age in each sex in each year removed from the population for a sequence of consecutive years. In the stochastic model it is assumed that the harvest process and the natural survivorship
process can both be treated as binomial processes. The recruitment
process is approximated as a product of normal processes. This formulation allows for the development of an iterative numerical scheme that will reconstruct the most probable underlying unknown population given a set of harvest data and a set of life history parameters.
A heuristic procedure that checks for internal consistency between the reconstructed population, the set of harvest data, and the life history parameters may be used to estimate a number of unknown population parameters together with the unknown population. The scheme has been tested with Monte Carlo simulations and, using only harvest data, has simultaneously estimated the survivorship rate, the recruitment
rate, the male harvest rate, the female harvest rate and the yearly harvest effort together with the unknown population. The scheme has been applied to Alaskan brown bear harvest data demonstrating its potential value as a management tool. / Forestry, Faculty of / Graduate
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/24375 |
| Date | January 1983 |
| Creators | Tait, David E. N. |
| Publisher | University of British Columbia |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Rights | For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
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