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Characterizing and quantifying uncertainty in forest pest risk analyses
PARTNERS: North Carolina State University (NCSU) Department of Forestry and Environmental Resources, Canadian Forest Service
SUMMARY: EFETAC scientists 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. Team members have participated in research on special risk analyses, especially spatially explicit risk analyses (i.e., pest risk maps) for individual alien-invasive species affecting forests. The current analytical framework for such analyses typically overlooks the impact of uncertainty in input data and assumptions, and how these uncertainties propogate to map outputs. The research described here highlights methods for incorporating variability and uncertainty into models of forest pest risk. Developing tools for handling uncertainty in forest pest 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 and the best allocation of often-scarce resources. 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 pest threats.
EFETAC's ROLE: This project is supported by EFETAC funding and collaborative research.
STATUS: Ongoing
PROGRESS: EFETAC research ecologist Frank Koch worked with Canadian Forest Service scientists to adapt a generic bioeconomic modeling framework for examining pest invasions through time for the purpose of mapping risk (i.e., probability of invasion) and associated uncertainties. They chose the sirex woodwasp (Sirex noctilio) as their example pest because it has invaded both Ontario and parts of the northeastern United States during the last few years, offering a relevant opportunity to perform broad-scale, cross-border analyses. Their first study illustrates an integrated risk mapping methodology using stochastic simulation, which is more fully detailed in an article published in the journal Risk Analysis:
- Yemshanov, D.; Koch, F.H.; McKenney, D.W.; Downing, M.C.; Sapio, F. 2009. Mapping invasive species risks with stochastic models: a cross-border US-Canada application for Sirex noctilio Fabricius. Risk Analysis. 29(6): 868-884. (PDF)
Koch was also a co-author on a follow-up article that details common approaches for generating pest risk maps, then uses the example outlined above to highlight the advantages of an integrated approach, including the ability to jointly depict risk and uncertainty in a manner helpful to decision makers. Less technical than the first, this second article is intended for a broader audience of scientists and managers:
- Yemshanov, D.; McKenney, D.W.; Pedlar, J.H.; Koch, F.H.; Cook, D. 2009. Towards an integrated approach to modeling the risks and impacts of invasive species. Environmental Reviews. 17: 163-178. (PDF)
In a third article, again using sirex woodwasp as the test case, Koch and co-authors, including Bill Smith (EFETAC biometrician), analyzed several key invasion model parameters, examining at what level of parametric uncertainty the output invasion risk and uncertainty maps become unstable. This approach attempts to ascertain and illustrate at what level(s) of parametric uncertainty output predictions remain reliable and are thus “robust” to uncertainty (see related discussion of “info-gap” analysis, below). The article received a 2009 Best Paper award from the Society for Risk Analysis:
- Koch, F.H.; Yemshanov, D.; McKenney, D.W.; Smith, W.D. 2009. Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk. Risk Analysis. 29(9): 1227-1241. (PDF)
Info-gap analysis is a non-probabilistic approach to characterizing uncertainty in risk assessment, which attempts to establish where risk estimates remain reliable (i.e., robust) in the face of severe uncertainty. The concept was advanced by Yakov Ben-Haim, from the Techion (Israel) Institute of Technology, who collaborated with Koch, Yemshanov, and Smith on the application of info-gap decision theory to the selection of the most robust pest detection survey network developed from the above-described sirex woodwasp risk map:
- Yemshanov, D.;,Koch, F.H.; Ben-Haim, Y.; Smith, W.D. 2010. Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest. Risk Analysis. 30(2): 261-276. (PDF)
In follow-up work involving info-gap decision theory, the researchers examined the trade-off between robustness to uncertainty and opportuneness, which is the possibility that a certain level of uncertainty in a pest risk model may enable “windfall” success (e.g., unanticipated but timely detections of an invasive pest). This work was published in the Journal of Environmental Management:
- Yemshanov, D.; Koch, F.H.; Ben-Haim, Y.; Smith, W.D. 2010. Detection capacity, information gaps and the design of surveillance programs for invasive forest pests. Journal of Environmental Management. 91:2535-2546. (PDF)
Recently, Koch collaborated with Yemshanov, Mark Ducey (University of New Hampshire), Klaus Koehler (Canadian Food Inspection Agency), and Barry Lyons (Canadian Forest Service) on another approach for quantifying uncertainty. The stochastic dominance concept has been applied in financial analysis as a way to identify the best choice out of a set of possible investment portfolios. The financial concepts of estimated “net return” on investment, and the “volatility” in that estimate, can be seen as analogous to the concepts of predicted invasion risk and the uncertainty of that risk prediction. Stochastic dominance is noteworthy in that it integrates uncertainty by comparing entire distributions of predicted outcomes, rather than adopting a more limited frame of reference (such as comparing only average values). The researchers developed a methodology for analyzing the human-assisted spread of the emerald ash borer (Agrilus planipennis), a major forest pest in North America. They used a spatial simulation model to generate distributions of potential invasion outcomes over eastern and central Canada, and then used stochastic dominance criteria to rank all locations in the study region based on these distributions. This work was published in the journal Diversity and Distributions:
- Yemshanov, D.; Koch, F.H.; Lyons, D.B.; Ducey, M.; Koehler, K. 2012. A dominance-based approach to map risks of ecological invasions in the presence of severe uncertainty. Diversity and Distributions 18:33-46. (PDF)
LINKS:
NCSU Department of Forestry and Environmental Resources
Landscape Analysis and Applications Section, Great Lakes Forestry Centre, Canadian Forest Service
February 16, 2010: Researchers Receive Top Honors For Risk Analysis Paper
CONTACT: Frank Koch, EFETAC Research Ecologist, fhkoch@fs.fed.us or (919) 549-4006
Updated January 2012
