A habitat assessment to locate tree of heaven [Ailanthus altissima, (Mill.) Swingle] in Mammoth Cave National Park

Invasive, nonnative plants pose a significant threat to national parks. Effective and efficient tools are needed to help managers detect, prioritize and target nonnative plants for control. I used spatial modeling techniques to predict the occurrence of tree of heaven (Ailanthus altissima, (Mill.) Swingle) in Mammoth Cave National Park (MACA), Kentucky. Tree of heaven is known to be a problematic invasive, nonnative plant species and was identified as a priority for control at MACA. I developed a multivariate habitat model to determine optimal habitat for tree of heaven within MACA. Habitat characteristics of 135 known tree of heaven locations were used in combination with seven environmental variables to calculate the predicted probability of occurrence of tree of heaven in MACA using logistic regression analysis. Variables for predicting habitat were created from public records, MACA databases, and a geographic information system (GIS).Twenty-seven a priori models were developed based on the biological requirements of the species and observations of invasion pattern in MACA and the most parsimonious model was selected using Akaike̕s Information Criteria. The seven variables included in the optimal model were derived from soil, site classification, geology, topography, and canopy coverage. I tested the predictive power of the model with independently collected presence and absence data. Ninety seven percent of test locations for tree of heaven were associated with predicted probabilities in the 0-0.30 range. The model improved the probability of finding tree of heaven compared with random searches by approximately 10%. It had poor discrimination (false positive = 0.31, false negative = 0.38, overall reliability = 0.41) and was not well calibrated. Based on its low predictive power, this habitat model could not be recommended for use in managing tree of heaven populations at MACA.Model failure could be attributed to a number of factors and/or combinations of factors including insufficient data, inappropriate scale and the generalist nature of the species. However, results from this study elucidate areas for future research into the applicability of habitat modeling to invasive, nonnative species at local scales.