CHAPTER 4
 CONCLUSIONS AND DISCUSSION

 Animal abundance is a very important parameter from a wildlife management perspective.

However, most estimation methods require very large sample sizes to obtain reliable estimates of

abundance and seldom does such information help for a wildlife manager. The progressively

subjective nature of Bayesian approaches at abundance estimation can to some extent be more

informative to the wildlife manager (Stow, Carpenter & Cottingham, 1995). Such approaches do

facilitate this process of updating parameter estimates on improved prior beliefs and will help

wildlife managers use such approaches more effectively in monitoring animal populations

(Hilbom and Mangel, 1997).

 The simulation results from my study show that the Royle and Nichols (2003) can still be a

valuable tool for determining abundance, specially since it is relatively inexpensive to obtain

presence-absence data from sites. The data gathered from my study on sloth bears were

insufficient for good estimates of animal abundance. However, improving the quality of field

data in terms of improving r will go a long way in making this model more useful for

determining sloth bear abundance.