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Batch marking provides an important and efficient way to estimate the survival probabilities and population sizes of wild animals. It is particularly useful when dealing with animals that are difficult to mark individually. For the first time, we provide the likelihood for extended batch-marking experiments. It is often the case that samples contain individuals that remain unmarked, due to time and other constraints, and this information has not previously been analyzed. We provide ways of modeling such information, including an open N-mixture approach. We demonstrate that models for both marked and unmarked individuals are hidden Markov models; this provides a unified approach, and is the key to developing methods for fast likelihood computation and maximization. Likelihoods for marked and unmarked individuals can easily be combined using integrated population modeling. This allows the simultaneous estimation of population size and immigration, in addition to survival, as well as efficient estimation of standard errors and methods of model selection and evaluation, using standard likelihood techniques. Alternative methods for estimating population size are presented and compared. An illustration is provided by a weather-loach data set, previously analyzed by means of a complex procedure of constructing a pseudo likelihood, the formation of estimating equations, the use of sandwich estimates of variance, and piecemeal estimation of population size. Simulation provides general validation of the hidden Markov model methods developed and demonstrates their excellent performance and efficiency. This is especially notable due to the large numbers of hidden states that may be typically required., (© 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.)

Creel surveys are used in recreational fisheries to estimate angling effort, catch, and harvest. Aerial-access creel surveys rely on two components: (1) a ground component in which fishing parties returning from their trips are interviewed at some access-points of the fishery; (2) an aerial component in which the number of fishing parties is counted. A common practice is to sample fewer aerial survey days than ground survey days. This is thought by practitioners to reduce the cost of the survey, but there is a lack of sound statistical methodology for this case. In this article, we propose various estimation methods to handle this situation and evaluate their asymptotic properties from a design-based perspective. We also propose formulas for the optimal allocation of the effort between the ground and the aerial portion of the survey, for given costs and budget. A simulation study investigates the performance of the estimators. Finally, we apply our methods to data from an annual Kootenay Lake survey (Canada)., (© 2015, The International Biometric Society.)

Petersen-type mark-recapture experiments are often used to estimate the number of fish or other animals in a population moving along a set migration route. A first sample of individuals is captured at one location, marked, and returned to the population. A second sample is then captured farther along the route, and inferences are derived from the numbers of marked and unmarked fish found in this second sample. Data from such experiments are often stratified by time (day or week) to allow for possible changes in the capture probabilities, and previous methods of analysis fail to take advantage of the temporal relationships in the stratified data. We present a Bayesian, semiparametric method that explicitly models the expected number of fish in each stratum as a smooth function of time. Results from the analysis of historical data from the migration of young Atlantic salmon (Salmo salar) along the Conne River, Newfoundland, and from a simulation study indicate that the new method provides more precise estimates of the population size and more accurate estimates of uncertainty than the currently available methods., (© 2011, The International Biometric Society.)

Tag loss in mark-recapture experiments is a violation of one of the Jolly-Seber model assumptions. It causes bias in parameter estimates and has only been dealt with in an ad hoc manner. We develop methodology to estimate tag retention and abundance in double-tagging mark-recapture experiments. We apply this methodology to walleyes (Stizostedion vitreum) in Mille Lacs, Minnesota.

Radio tags, because of their high detectability, are often used in capture-recapture studies. A key assumption is that radio tags do not cease functioning during the study. Radio-tag failure before the end of a study can lead to underestimates of survival rates. We develop a model to incorporate secondary radio-tag failure data. This model was applied to chinook smolts (Oncorhynchus tshawytscha) on the Columbia River, Washington. Estimates of fish survival from this model were much larger than those from the standard Cormack-Jolly-Seber analysis.