Temporal change in capture probability (Mt)
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This is the most commonly-used model, as experience has shown that the probability of capture varies between samples. Common causes of changes in capture probability are linked to changes in the weather. For example, fewer animals may be captured on cold or windy days or during rainy nights, compared with warm, sunny or dry periods, because of changes in animal activity. If equal sampling effort is used on each sampling occasion then this model may be appropriate if there are significant differences in the number of animals captured on each sampling occasion. Examine the sequence of newly-caught animals; if this shows large variation which you can relate to some environmental variable, then you probably have temporal variation. It is important to note that this model assumes that all animals in the population have an equal probability of capture at any one time. This is sometimes called a 'ball and urn model' since it assumes that the situation can be modelled as if we are sampling well-mixed beans in a plastic bag.
The program uses numerical methods to estimate the maximum likelihood estimator of population size and the probability of capture on each sampling occasion. This is a more mathematically rigorous approach than that originally devised by Schnabel (1938) and further developed by Darroch (1958). When only two samples have been collected, the maximum likelihood estimator is close to Petersen-Lincoln estimator, and this method will give the Chapman (1951) modification of the Petersen-Lincoln index.
The results for an Mt model are displayed by clicking on the Petersen-Schnabel tab, which will appear once the model has been selected from the Closed methods drop-down menu.
Simply Tagging also offers the Chao method for temporal variation in capture probability.