solution

Although Schoener [1968] reported four species of Anolis lizard in the paper, only two species were included in the data set. A Poisson regression does not constrain the total number of lizards in a given habitat condition, which may be misleading because the number of lizard cannot be unlimited. A different way of analyzing the same data is using logistic regression. Assuming that there are only two competing species, we can model one species habitat preference as the probability of seeing one species over the other. The data set we used has two parts. The first 24 rows are the number of times of species A. opalinus and the second 24 rows are the number of times of species A. grahamii. Use logistic regression to predict the probability of seeing one species (e.g., A. grahamii). That is, use response of A. grahamii as success and the response of A. opalinus as failure, and develop a model to predict the probability of success. If the probability of success is high for one condition, the habitat defined by this condition is preferred by A. grahamii; if the probability is low, the habitat is preferred by A. opalinus; if the probability is close to 0.5, the habitat is shared by both. Discuss whether your interpretation of species habitat preference changes from the results using a Poisson regression model.