Band reporting rates of waterfowl: does individual heterogeneity bias estimated survival rates?

In capture–recapture studies, the estimation accuracy of demographic parameters is essential to the efficacy of management of hunted animal populations. Dead recovery models based upon the reporting of rings or bands are often used for estimating survival of waterfowl and other harvested species. However, distance from the ringing site or condition of the bird may introduce substantial individual heterogeneity in the conditional band reporting rates (r), which could cause bias in estimated survival rates (S) or suggest nonexistent individual heterogeneity in S. To explore these hypotheses, we ran two sets of simulations (n = 1000) in MARK using Seber's dead recovery model, allowing time variation on both S and r. This included a series of heterogeneity models, allowing substantial variation on logit(r), and control models with no heterogeneity. We conducted simulations using two different values of S: S = 0.60, which would be typical of dabbling ducks such as mallards (Anas platyrhynchos), and S = 0.80, which would be more typical of sea ducks or geese. We chose a mean reporting rate on the logit scale of −1.9459 with SD = 1.5 for the heterogeneity models (producing a back-transformed mean of 0.196 with SD = 0.196, median = 0.125) and a constant reporting rate for the control models of 0.196. Within these sets of simulations, estimation models where σ(S) = 0 and σ(S) > 0 (σ(S) is SD of individual survival rates on the logit scale) were incorporated to investigate whether real heterogeneity in r would induce apparent individual heterogeneity in S. Models where σ(S) = 0 were selected approximately 91% of the time over models where σ(S) > 0. Simulation results showed < 0.05% relative bias in estimating survival rates except for models estimating σ(S) > 0 when true S = 0.8, where relative bias was a modest 0.5%. These results indicate that considerable variation in reporting rates does not cause major bias in estimated survival rates of waterfowl, further highlighting the robust nature of dead recovery models that are being used for the management of harvested species.