USING EFFORT INFORMATION WITH CHANGE-IN-RATIO DATA FOR POPULATION ESTIMATION

Most change-in-ratio (CIR) methods for estimating fish and wildlife po pulation sizes have been based only on assumptions about how encounter probabilities vary among population subclasses. When information on s ampling effort is available, it is also possible to derive CIR estimat ors based on assumptions about how encounter probabilities vary over t ime. This paper presents a generalization of previous CIR models that allows explicit consideration of a range of assumptions about the vari ation of encounter probabilities among subclasses and over time. Expli cit estimators are derived under this model for specific sets of assum ptions about the encounter probabilities. Numerical methods are presen ted for obtaining estimators under the full range of possible assumpti ons. Likelihood ratio tests for these assumptions are described. Empha sis is on obtaining estimators based on assumptions about variation of encounter probabilities over time.