Partial stratification in two‐sample capture–recapture experiments

Abstract

Capture heterogeneity is known to cause bias in estimates of abundance in capture–recapture experiments. This heterogeneity is often related to observable fixed characteristics of the animals such as sex. If this information can be observed for each handled animal at both sample occasions, then it is straightforward to stratify (e.g., by sex) and obtain stratum‐specific estimates. However, in many fishery experiments, it is difficult to sex all captured fish because morphological differences are slight or because of logistic constraints. In these cases, a subsample of the captured fish at each sample occasion is selected, and additional and often more costly measurements are made, such as sex determination through sacrificing the fish. Our data now consist of two types of marked animals: animals whose value of the stratification variable is unknown, and subsamples at each occasion where the value of the stratification variables are determined. In this paper, we develop and apply new methods for these types of experiments. Furthermore, given the relative costs of sampling for a simple capture and for processing the subsample, optimal allocation of effort for a given cost can be determined. We also develop methods to account for additional information (e.g., prior information about the sex ratio) and for supplemental continuous covariates such as length. These methods are applied to a problem of estimating the size of the walleye population in Mille Lacs Lake, MN.