Abstract:
Invasive exotic species are an international threat to biodiversity. Management of invasive species is divided into three approaches: prevention of introduction outside of native range; eradication of invasions; and containment and control strategies. Prevention is unfortunately limited by accurate predictions and border control measures which are difficult to implement. Similarly, eradication is made difficult due to the fast acting and aggressive behavior of many invasive species, some of which are naturalized for many years before control measures are implemented. This leaves containment and control as management strategies for many managers today. Land protection groups in the United States including non-profit land trusts and governmental agencies – local to national -- address invasive species on nearly all protected lands. I have consulted with the Eno River Association of Durham and Orange counties in North Carolina to address the management of three invasive plant species of concern: tree of heaven (Ailanthus altissima), Chinese privet (Ligustrum sinense), and multiflora rose (Rosa multiflora). After assembling an observational data set of these three species, I used Maxent, a maximum entropy based machine-learning software, to model the potential distribution of each species within the Eno River watershed. Distributions of all three species were best predicted by soil type and distance to rivers. Properties of the Eno River State Park master plan -- a land protection priority list for the Eno River Association and the Eno River State Park -- were analyzed and ranked for the total area and the percent coverage of invasive plants from the modeled distributions.
