Estimating size-specific survival rates of White Sturgeon using a dynamic growth model with capture-recapture data

Fisheries managers in the lower Columbia River basin utilize two models which require survival rate information for conservation and management of White Sturgeon Acipenser transmontanus populations.  Size-based transition matrices are used to forecast abundance in the short term for setting harvest quotas, while long-term population trajectories are modeled in a Population Viability Analysis (PVA) framework.  Managers require a method to estimate survival rates from mark-recapture data with the flexibility to model differential survival among size-classes that explicitly considers growth. Implementing a time-varying individual covariate, such as size, in Program MARK requires an observation at each sampling occasion.  Using generalized additive models (GAMs) fit to observed growth increment data, missing lengths were simulated for all marked White Sturgeon in The Dalles Reservoir. Simulated length data were incorporated as individual covariates in encounter histories and analyzed with a Cormack-Jolly-Seber model in Program MARK.  Length data were simulated many times using predicted growth rates and SEs from the GAMs to account for variation in growth and the effect of imputed lengths on resulting apparent survival estimates.