ABSTRACT
Due to climate change, changes in habitat and other such pressures on the environment, there is extensive interest in studying wildlife populations. In order to understand these populations, reliable representations of the underlying processes are required, which is achieved using various statistical models. As these models become more realistic they also increase in complexity. This chapter considers parameter redundancy in a variety of different statistical models used in ecology, demonstrating the different techniques that can be used to investigate parameter redundancy in these models. It demonstrates how the symbolic method and extended symbolic methods can be used to obtain general results in mark-recovery models. The chapter uses capture-recapture models and capture-recapture-recovery models to illustrate the extended symbolic method.
