Review of Methods for Developing Probabilistic Risk Assessments. Part 2: Modeling Invasive Plants, Pests, and Pathogens

P.B. Woodbury and D.A. Weinstein

Cornell University

We conducted a state-of-the-science review of probabilistic regional risk assessment methodologies to identify the methods that are currently in use and capable of evaluating the threats to ecosystems from fire and fuels, invasive species, loss of open space, unmanaged outdoor recreation, and other key stresses.  In a companion paper we highlight methods useful for evaluating the risk to fire.  In this paper we give the results of our survey of methods available for evaluating the risk of invasive species.

The issue of invasive species is large and complex because there are thousands of potential invasive species, and there is constant movement of new and established plants, plant material, pests and pathogens. The most cost-effective approach is to control invasive species very early in the process of transport from the native range and entry. However, even a semi-quantitative “rule-based’ approach can help to identify locations that contain susceptible host species for specific pathogens or insect pests, and where propagules are more likely to enter based on the current locations of the invasive species, ports of entry, and methods of spread.  Predicting long distance movement is much more difficult, as such events are rare, often poorly understood, and are often influenced by human behavior. Published methods to make probabilistic predictions of pest establishment could be expanded to provide quantitative estimates of spread beyond an initial port of entry. Many invasive species are transported along roads, and so road networks provide some information about the likelihood of introduction into a new region. Unmanaged recreation and land use change including forest fragmentation and ex-urban development are key interacting factors for assessing the risk of invasive species. .

Models based on fundamental biological and physical processes, such as population demographics and movement of organisms, are preferable to correlative statistical approaches. These may be useful to quantify the overlap in spatial distribution of stressors and ecological receptors. Process-based models may be extended with some confidence beyond the range of available data because they use predictor variables that represent physical and biological processes.  The use of data on non-indigenous species to predict the occurrence of much rarer invasive species may be quite useful because the correlation is based on the key processes of human-influenced transport, establishment, reproduction, and dispersal of propagules. If the number of non-indigenous species in a region can be predicted based on some measure of the transportation network, or other environmental factor, one could extrapolate to future conditions with more roads or a higher traffic volume. Ecological niche modeling approaches are useful because they can use data from museum collections in other countries to make estimates of potential new range areas in the U.S.

As for any regional stressor, the use of multiple models and a weight of evidence approach would help to increase confidence in predictions of ecological risks from invasive species. Two approaches to predicting the risk of Asian long-horned beetle throughout U.S. forests make quite different predictions because they focus on different stages in the process of establishment and spread.  Invasive species management must be addressed at multiple spatial scales, including reducing importation of new species at border crossings and ports, national and regional mapping of locations of invasive species, methods to reduce long distance transport, and methods to reduce local movement.

Thursday Morning Plenary

corresponding author:

P.B. Woodbury
Department of Crop and Soil Sciences
Cornell University
1017 Bradfield Hall
Ithaca, NY 14853
607-254-1216
pbw1@cornell.edu