Many animals lack obvious sexual dimorphism, making assignment of sex difficult even for observed or captured animals. For many such species it is possible to assign sex with certainty only at some occasions; for example, when they exhibit certain types of behavior. A common approach to handling this situation in capture-recapture studies has been to group capture histories into those of animals eventually identified as male and female and those for which sex was never known. Because group membership is dependent on the number of occasions at which an animal was caught or observed (known sex animals, on average, will have been observed at more occasions than unknown-sex animals), survival estimates for known-sex animals will be positively biased, and those for unknown animals will be negatively biased. In this paper, we develop capture-recapture models that incorporate sex ratio and sex assignment parameters that permit unbiased estimation in the face of this sampling problem. We demonstrate the magnitude of bias in the traditional capture-recapture approach to this sampling problem, and we explore properties of estimators from other ad hoc approaches. The model is then applied to capture-recapture data for adult Roseate Terns (Sterna dougallii) at Falkner Island, Connecticut, 1993-2002. Sex ratio among adults in this population favors females, and we tested the hypothesis that this population showed sex-specific differences in adult survival. Evidence was provided for higher survival of adult females than males, as predicted. We recommend use of this modeling approach for future capture-recapture studies in which sex cannot always be assigned to captured or observed animals. We also place this problem in the more general context of uncertainty in state classification in multistate capture-recapture models.
|Publication Subtype||Journal Article|
|Title||Estimation of sex-specific survival from capture-recapture data when sex is not always known|
|Contributing office(s)||Patuxent Wildlife Research Center|
|Other Geospatial||Falkner Island|
|Google Analytic Metrics||Metrics page|