Partial Stratification in Capture-Recapture Experiments and Integrated Population 7Modeling with Radio Telemetr
In this thesis, we develop and apply three new methods for ecological data sets. We present two new developments related to capture-recapture studies and one development related to integrated population models with capture-recapture, dead recovery, snorkel survey, and radio tagged data.
In the first project, we present new methods using partial stratification in two-sample capturerecapture experiments for closed populations. 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 sub-sample 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. We develop new methods to estimate abundance for these types of experiments. Furthermore, we develop methods for optimal allocation of effort for a given cost. 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 Minnesota, USA.
In the second project, we present new methods using partial stratification in k-sample capturerecapture experiments of a closed population with known losses on capture to estimate abundance. In this study we allow the experiment to be carried out in successive sample times (k _ 2). The population may consist of two or more non-overlapping categories and capture probabilities may vary between categories and also between sample times. We present the new methods using maximum likelihood method and using a Bayesian method for a large population. Simulated data with known losses on capture was used to illustrate the new methods presented in this study.
In the third project, we present an integrated population model using capture-recapture, dead recovery, snorkel survey, and radio tagged data. We apply this model to Chinook salmon on the
West Coast of Vancouver Island, Canada to estimate spawning escapement and to describe the movement from the ocean to spawning grounds considering the stopover time, stream residence time, and snorkel survey observer efficiency.
Keywords: abundance; capture heterogeneity; capture-recapture; integrated population modeling; partial stratification; survey-design and analysis