Estimating individual survival using territory occupancy data on unmarked animals

Authors


*Correspondence author. E-mail: t.roth@unibas.ch

Summary

1. Survival estimation forms the basis of much ecological research, and usually requires data on marked animals. In population studies of territorial animals, however, data are often collected on animal territory occupancy without identification of individuals. Previously, these data could not be used to estimate demographic parameters such as survival.

2. We developed a hierarchical site-occupancy model for estimating survival from territory occupancy data without individual identification. We defined survival as the probability that an individual occupying a territory survives until the next reproductive period and settles in the same territory again. To evaluate our model, we used simulated data as well as real data from a long-term study on nightingales Luscinia megarhynchos, from which mark-recapture data and territory occupancy data were available.

3. When applied to simulated data sets on territory occupancy, with parameter settings that are typical for different monitoring programmes (i.e. 10 years duration, three or eight visits per season, and 55 or 200 territories surveyed), our model yielded unbiased estimates of survival if the probability of detecting an occupied territory during a single visit was p = 0·5 or p = 0·7.

4. When applied to the data on nightingale territory occupancy, estimates of survival from our model were very similar to the estimates obtained from a traditional mark-recapture model (Cormack–Jolly–Seber model) applied to the ringing data from the same nightingale population.

5.Synthesis and applications. Data collection for mark-recapture analysis is usually invasive and labour intensive, and suitable data are rarely available from large-scale monitoring programmes covering entire regions or countries. Applying our model to territory occupancy data from such monitoring programmes could make large amounts of data available for research on animal demography.

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