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 We developed a general statistical model that provides a comprehensive framework for inference about survival rates based on standing age-structure and ages-at-death data. Previously available estimators are maximum likelihood under the general model, but they use only 1 type of data and require the assumption of a stable age structure and a known population growth rate. We used the general model to derive new survival rate estimators that use both types of data and require only the assumption of a stable age structure or a known population growth rate.
Our likelihood-based approach is applicable to either age-structure data or ages-at-death data considered by themselves, or both types of data considered simultaneously. This approach allows use of standard model-selection procedures to test hypotheses about age-structure stability, population growth rates, and age-related patterns in survival.
Many of the survival rate estimators have explicit forms and these are given by Udevitz and Ballachey (1998). In cases where the estimators do not have explicit forms, they can be found numerically with program SURVIV (White 1983). Click on the links below to obtain a copy of program SURVIV and to download examples of input files that can be used with SURVIV to estimate survival rates based on age-structure data.
 (software page of Department of Fishery and Wildlife Biology and Colorado Coop. Fish and Wildlife Unit, Colorado State University).
(and usage notes) for use with SURVIV.
Udevitz, M. S. and B. E. Ballachey. 1998. Estimating survival rates with age structure data. J. Wildl. Manage. 62:779-792.
White, G. C. 1983. Numerical estimation of survival rates from band recovery and biotelemetry data. J. Wildl. Manage. 47:716-728.
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