Utilizing the USDA PLANTS database to predict exotic woody plant invasiveness in New Hampshire

Abstract

Disturbance and land transformation seem to enhance the ability of exotic species to invade, possibly due to increased resource levels and greater immigration potential from surrounding disturbed areas. To investigate the role disturbance may play in enhancing exotic species invasion, we used retrospective analysis to discriminate the characters associated with naturalized and non-naturalized exotic woody plants in New Hampshire utilizing the biological information contained in the US Department of Agriculture (USDA) PLANTS database and selected other sources. Exotic plants were partitioned into two groups: those known to have self-sustaining populations and those that did not display self-sustaining populations. To predict membership into these groups, we used stepwise logistic regression. Variables were screened for correlation coefficients higher than 0.5. Model development was constrained using Akaike’s information criteria with the correction factor for sample size. The 11th model step containing 11 characters was selected and it differed significantly from the constant-only model ( χ 2=66.383, P<0.001). Exotic species were correctly classified into the known non-naturalized or naturalized categories in 90% of the cases. The resulting model could be used to reliably screen novel woody plant introductions. Additionally, we provide a framework for preliminarily assessing the importance of different factors in encouraging woody plant invasion in the northeastern US.