|
 This research addresses the development and evaluation of theory and methods for using age-structure data to make inferences about survival rates. Age-structure data have a long history of use for estimating survival rates in wildlife populations. Survival rates can be estimated from age class proportions in either the standing population (standing age-structure data) or the natural deaths (ages-at-death data). Most estimators have required often unreasonable assumptions of a known population growth rate and a stable age structure. Age structures will become stable only if recruitment and survival rates remain constant for a long enough period of time. Also, in many cases, previous methods had insufficient theory to support anything other than point estimates of survival rates.
We developed a general statistical model that provides a comprehensive framework for inference about survival rates based on either, or both, types of age-structure data. We are using this model to derive new estimators of age-specific survival rates that relax previously required assumptions; statistical tests of hypotheses about age structure stability, population growth rates, and age-related patterns in survival rates; and model selection procedures that provide more parsimonious and therefore more precise estimates of survival rates. Our earlier work focused on using age structure data from a single year and applications to estimating survival rates for sea otters in Prince William Sound, Alaska (software). Our current research focuses on extending the theory and methods to use additional information provided by multiple years of data and on developing software that will make these techniques easily accessible to a wider audience. These developments will provide new theory and methods for more precise monitoring of survival rates in cases where age structures are not necessarily stable.
Udevitz, M. S. and B. E. Ballachey. 1998. Estimating survival rates with age-structure data. Journal of Wildlife Management 62(2):779-792. |
