Apparent survival estimation from continuous mark–recapture/resighting data


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  1. The recent expansion of continuous-resighting telemetry methods (e.g. acoustic receivers, PIT tag antennae) has created a class of ecological data not well suited for traditional mark–recapture statistics. Estimating survival when continuous recapture data is available ensues a practical problem, because classical capture–recapture models were derived under a discrete sampling scheme that assumes sampling events are instantaneous with respect to the interval between events.
  2. To investigate the use of continuous data in survival analysis, we conducted a model structure adequacy simulation that tested the Cormack–Jolly–Seber (CJS) and Barker joint data survival estimation models, which mainly differ through the Barker's inclusion of secondary period information. We simulated a population in which survival and detection occurred as a near continuous (daily) process and collapsed detection information into monthly sampling bins for survival estimation.
  3. While both models performed well when survival was time-independent, the CJS was substantially biased for low survival values and time-dependent conditions. Additionally, unlike the CJS, the Barker model consistently performed well over multiple sample sizes (number of marked individuals). However, the high number of parameters in the Barker model led to convergence difficulties, resulting in a need for an alternative optimization method (simulated annealing).
  4. We recommend the use of the Barker model when using continuous data for survival analysis, because it outperformed the CJS over a biologically reasonable range of potential parameter values. However, the practical difficulty of implementing the Barker model combined with its shortcomings during two simulations leaves room for the specification of novel statistical methods tailored specifically for continuous mark–resighting data.