Cross-classification results from each model.

Prob level = value of the cutoff of the probability of observing presence used to classify each prediction into either an event (presence) or non-event (absence). Correct = number of events and non-events properly classified when comparing predicted to observed. Incorrect = number of non-events improperly classified as events and vice versa. Percentages Correct: overall percentage of observations correctly classified. Sensitivity: percentage of actual events correctly identified as such and is complementary to the false negative rate. Specificity: percentage of non-events which are correctly identified as such and is complementary to the false positive rate. False Positive Percentage: percent of predicted event responses that were observed as nonevents. False Negative Percent: percent of predicted nonevent responses that were observed as events.