Return to search

Bootstrap interval estimation of wildlife population sizes from multiple surveys

The research deals with bootstrap interval estimation of wildlife population sizes from
multiple surveys in the Hluhluwe-Umfolosi Park. The jackknife procedure was also used
to provide the standard errors for the survey estimates. The main wildlife speciese studied
in the research were the White and Black Rhino. The survey estimates for the wildlife
species were obtained using line transect sampling and mark-recapture methods
respectively. The bootstrap and jackknife procedures were applied separately to each of
the datasets. Bootstrap estimates for each of the time point were obtained and the
confidence intervals of the bootstrap estimates were constructed using percentile and
standard methods. The coverage probability was assessed using the Monte Carlo
simulations. Only the nonparametric bootstrap was applied in this research and the results
were compared to the jackknife results. The lengths of the confidence intervals were used
to assess the confidence intervals with a shorter confidence interval being more exact.
The estimates used for both the bootstrap and jackknife methodology were based on a
simple state space model. The discrete state space model used was proposed by Fatti et al
(2002). State space models provide a natural framework for estimating and predicting
animal population abundance given partial or inexact information. The model takes into
account the (unknown) birth rate in the population and all known losses (mortalities and
relocations) and gains (introductions) in the population between successive surveys as
well as the errors in the survey estimates.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/4864
Date22 May 2008
CreatorsMutsvairo, Itayi
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format10371 bytes, 597981 bytes, application/pdf, application/pdf, application/pdf, application/pdf

Page generated in 0.0022 seconds