1. Accurate estimates of demographic parameters are required to inferappropriate ecological relationships and inform management actions. Recentlydeveloped N-mixture models use count data from unmarked individuals to estimatedemographic parameters, but a joint approach combining the strengths of bothanalytical tools has not been developed. 2. We present an integrated modelcombining known-fate and open N-mixture models, allowing the estimation ofdetection probability, recruitment, and the joint estimation of survival. Wefirst use a simulation study to evaluate the performance of the model relativeto known values. We then provide an applied example using 4 years of wolfsurvival data consisting of relocations of radio-collared wolves within packsand counts of associated pack-mates. The model is implemented in bothmaximum-likelihood and Bayesian frameworks using a new R package kfdnm and theBUGS language. 3. The simulation results indicated that the integrated modelwas able to reliably recover parameters with no evidence of bias, and estimateswere more precise under the joint model as expected. Results from the appliedexample indicated that the marked sample of wolves was biased towardsindividuals with higher apparent survival rates (including losses due tomortality and emigration) than the unmarked pack-mates, suggesting estimates ofapparent survival based on joint estimation could be more representative of theoverall population. Estimates of recruitment were similar to directobservations of pup production, and overlap of the credible intervals suggestedno clear differences in recruitment rates. 4. Our integrated model is apractical approach for increasing the amount of information gained from futureand existing radio-telemetry and other similar mark-resight datasets.
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