• Census data;
  • Computational efficiency;
  • Kalman filter;
  • Multivariate normal approximation;
  • Ring–recovery data;
  • State space

Summary. A drawback of a new method for integrating abundance and mark–recapture–recovery data is the need to combine likelihoods describing the different data sets. Often these likelihoods will be formed by using specialist computer programs, which is an obstacle to the joint analysis. This difficulty is easily circumvented by the use of a multivariate normal approximation. We show that it is only necessary to make the approximation for the parameters of interest in the joint analysis. The approximation is evaluated on data sets for two bird species and is shown to be efficient and accurate.