PARTNERS: North Carolina State University (NCSU) Department of Forestry and Environmental Resources

SUMMARY: The Forest Health Monitoring (FHM) Program is a long-term, national research and monitoring effort focusing on forest ecosystems. Part of the mission of the Forest Service’s FHM Research Work Unit of the Southern Research Station is to conduct research resulting in national-scale databases and reports that address forest health and sustainability, and the development, demonstration, and transfer of new protocols for assessing forest health. As part of this mission, this research work unit has participated in research on special risk assessments. The current analytical framework for most risk assessments focuses on estimates of central tendency. The project, proposed in September 2006, would incorporate variability and uncertainty into models of ecological risk to increase the ability of the FHM Program to monitor and report on ecosystem health. Developing tools for handling uncertainty in forest ecosystem risk assessments will provide important information to the Forest Service, States, and other stakeholders who are faced with making critical and timely decisions on forest management. In particular, such tools will enable Forest Service and other scientists to incorporate uncertainty into their risk assessments and thus provide better appraisals of current forest ecosystem threats.

STATUS: Ongoing

PROGRESS:    

• Researchers have worked with collaborators from the Canadian Forest Service and U.S. Forest Service Forest Health Technology Enterprise Team (FHTET) to adapt a generic bioeconomic modeling framework for examining pest invasions through time--with sirex woodwasp (Sirex noctilio) in eastern North America as a specific example--for the purpose of mapping risk (i.e., probability of invasion) and associated output uncertainties. Briefly, instead of generating separate risk mapping products (risk of introduction, risk of establishment, etc.), researchers use a Monte Carlo-style approach to create maps integrating the various stages of invasion (introduction, spread, establishment) into a single spatial output. Using thousands of repeated replications, researchers assembled maps of invasion probabilities across the time horizon of interest (30 years), along with associated maps of output uncertainty (standard deviation of the probability as well as binary entropy). The analysis is more fully detailed in a manuscript submitted to the journal Risk Analysis: Yemshanov, D.; Koch, F.H.; McKenney, D.W.; Downing, M.C.; Sapio, F. Mapping invasive species risks with stochastic models: a cross-border US-Canada application for Sirex noctilio Fabricius.
• Researchers are nearing completion on a follow-up manuscript that details common approaches for generating risk maps, then uses the example outlined above to highlight the advantages of an integrated approach, including the ability to jointly depict risk and output uncertainty in a spatially explicit manner helpful to decision makers (and to characterize potential impacts both ecologically and economically). This second manuscript is intended for a broader audience of scientists and managers: Yemshanov, D.; McKenney, D.W.; Pedlar, J.H.; Koch, F.H. (tentatively) An integrated approach to modeling the risks and impacts of invasive species.
• In a third manuscript, again using sirex woodwasp as the test case, researchers are performing a series of detailed “sensitivity analyses” (through Monte Carlo-style simulation) for important model parameters, examining at what level of parametric uncertainty the output invasion risk and uncertainty maps become unreliable. In other words, researchers are attempting to ascertain and illustrate at what level(s) of parametric uncertainty output predictions remain reliable and are thus “robust” to uncertainty. Notably, some portions of the risk map remain reliable even in the face of great introduced uncertainty. To the researchers' knowledge, this is the first time that this sort of analysis has been applied in a pest risk mapping context. This manuscript is also near completion: Koch, F.H.; Yemshanov, D.; McKenney, D.W. (tentatively) Characterizing critical uncertainty thresholds in a spatial model of forest pest invasion risk.
• Researchers are currently working on a fourth manuscript that relates the above-described analyses of a pest risk map’s robustness to uncertainty to an “info-gap” decision theory framework.

LINKS: NCSU Department of Forestry and Environmental Resources

CONTACT: Frank Koch, NCSU Department of Forestry and Environmental Resources, fhkoch@ncsu.edu or (919) 549-4006