Ecologists working with metapopulations are interested in the rate of migration among several local populations, mortality during migration, and the scaling of migration rate with habitat patch area and isolation. We describe a model of individual capture histories obtained from multisite mark–release–recapture studies, which allows one to measure these parameters using maximum likelihood estimation. The model yields separate estimates of mortality within habitat patches and mortality during migration, on the assumption that only the latter is affected by the isolation of the source population. The model is suitable for studies involving 10 or more populations, with differences in habitat patch areas and isolation, and in which several hundred individuals have been marked and recaptured. We apply the model to a metapopulation of the butterfly Melitaea diamina with 14 local populations, 557 marked individuals, and 1301 recaptures. Immigration and emigration scaled as patch area to power 0.2. Roughly half of the daily losses of individuals from habitat patches of 1 ha in area were due to emigration, <1% of daily migration distances were >1 km, and 16% of all deaths were estimated to have occurred during migration. Programs are available to calculate the parameter estimates, their confidence intervals, and goodness‐of‐fit tests.

The effect of population heterogeneity in capture-recapture, or dual registration, models is discussed. An estimator of the unknown population size based on a logistic regression model is introduced. The model allows different capture probabilities across individuals and across capture times. The probabilities are estimated from the observed data using conditional maximum likelihood. The resulting population estimator is shown to be consistent and asymptotically normal. A variance estimator under population heterogeneity is derived. The finite-sample properties of the estimators are studied via simulation. An application to Finnish occupational disease registration data is presented.

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