  1. Accurate estimates of demographic parameters are required to infer
appropriate ecological relationships and inform management actions. Recently
developed N-mixture models use count data from unmarked individuals to estimate
demographic parameters, but a joint approach combining the strengths of both
analytical tools has not been developed. 2. We present an integrated model
combining known-fate and open N-mixture models, allowing the estimation of
detection probability, recruitment, and the joint estimation of survival. We
first use a simulation study to evaluate the performance of the model relative
to known values. We then provide an applied example using 4 years of wolf
survival data consisting of relocations of radio-collared wolves within packs
and counts of associated pack-mates. The model is implemented in both
maximum-likelihood and Bayesian frameworks using a new R package kfdnm and the
BUGS language. 3. The simulation results indicated that the integrated model
was able to reliably recover parameters with no evidence of bias, and estimates
were more precise under the joint model as expected. Results from the applied
example indicated that the marked sample of wolves was biased towards
individuals with higher apparent survival rates (including losses due to
mortality and emigration) than the unmarked pack-mates, suggesting estimates of
apparent survival based on joint estimation could be more representative of the
overall population. Estimates of recruitment were similar to direct
observations of pup production, and overlap of the credible intervals suggested
no clear differences in recruitment rates. 4. Our integrated model is a
practical approach for increasing the amount of information gained from future
and existing radio-telemetry and other similar mark-resight datasets.
