Arboriculture & Urban Forestry 39(4): July 2013 The 90% confidence interval for this estimate is 0.0125±0.0144, which means that there is 90% probability that the probability of failure lies between 0.0 and 0.0269 (1/37). Calculations such as these help provide an indication of upper and lower bounds. If statistically robust estimates of probability of failure are not available, then the probability of failure of the tree under consider- ation may be compared with an average tree where the probability of failure is known. For example, the probability of failure of trees in public places in the UK is at least 1 in 10 million (assuming tar- get value and impact potential are unity) (HSE 2007; NTSG 2011). An assessment may then conclude that the tree has a risk that is 10 or 100 times higher than a typical tree, or perhaps less. This requires some subjectivity, but helps provide comparative risks. The setting of risk acceptance in the QTRA process should be broadened to include cost-benefit or other decision theory con- siderations. Such considerations are particularly useful where the decision has repercussions well beyond ensuring public safety. Risk mitigating measures, such as site access restrictions and tree removal, can be assessed in a rigorous and methodical manner that aims to incorporate the costs and benefits of all interested parties. A QTRA should use mean estimates for risk calcula- tions as governments mandate risk-neutral risk assessments. While it may seem prudent to select conservative estimates, if the QTRA’s three parameters are doubled, then ROH increas- es eight fold. If excessively conservative values are used at each opportunity then the calculated ROH becomes illogical. A clear example of the consequence of not using the mean (or using the extreme conservative) occurred when an assessor of the figs in Laman Street determined that the probability of tree fail- ure was 1 in 7.5 per tree per year. This figure was derived on the assumption that since two trees failed in 2007 then the likelihood of tree failure would be the same in the following year, disregarding the fact that the weather in 2007 was an extreme event with annual probability of approximately 5% (Stewart 2012). The assessor also ignored the fact that for the previous several decades, no trees failed. Decisions partially or fully based on QTRA can significantly affect the well-being of the public. Thus the decision-making process should include within it quality assurance measures and a peer review to add confidence to any decision made. Quality assurance procedures tend to focus on internal reviews. Peer review is an independent and critical review of risk analysis and risk assessment procedures and should obviously be conducted by recognized experts. If a peer review produces risks or recom- mendations that are in conflict with previous reports, then there should be an opportunity for all parties to see if a consensus can be reached. If not, then the decision-makers can decide if more stud- ies are needed, or can make a decision recognizing lack of consen- sus and the use of alternate decision criterion to reach a decision. Finally, while quantitative decision support tools, such as QRA and QTRA, hold some appeal to decision makers, they cannot capture the full and diverse range of societal con- siderations of risk acceptability. Therefore, a QTRA should be viewed only as an aid to decision support, where deci- sions about public safety will often require social, economic, cultural, environmental, political, and other considerations. CONCLUSIONS A QTRA should be subject to rigorous and independent re- view to judge the veracity of the calculated risks. The QTRA system should develop longer and more intensive training that includes the principles of QRA as a starting point. This could reduce the risk of wide discrepancies between individual QTRA users. There is also a need for any risk management process involving trees, not only to assess the risk but to consider the benefits provided by trees (i.e., to conduct a risk-based cost- benefit analysis). While crude datasets relating to tree failures do exist, as with the International Tree Failure Database for example, considerable work is still required in this area. In the meantime, tree risk assessors should, as far as reasonably possible, rely on benchmarks to ensure that their assessments are not outside of the realms of reality and include at least some form of scientific rigor. LITERATURE CITED BMA. 1990. The BMA Guide to Living with Risk. The British Medical Association. Penguin Books, London, England. Ellison, M.J. 2005. Quantified Tree Risk Assessment Used in the Man- agement of Amenity Trees. Journal of Arboriculture 31(2):57–65. Faber, M.H., and M.G. Stewart. 2003. Risk Assessment for civil engineering facilities: Critical overview and discussion, reliability engineering, and system safety 80(2):173–184. Guggenmoos, S. 2009. Managing tree caused electric service interrup- tions. UAA Quarterly (Special Edition):4–9. HSE. 2007. Agriculture Safety, LAC 23/22, Health & Safety Executive/ Local Authorities Enforcement Liaison Committee (HELA), Health and Safety Executive. September 10, 2007. ISO 31000–2009. Risk Management—Principles and Guidelines, Inter- national Organization for Standardization, Geneva, Switzerland, 2009. Marsden, D. 2009. Assessment of Hill’s Weeping Fig Ficus microcarpa var. hillii in Civic Cultural Precinct, Laman Street, Cooks Hill, New- castle. August 7, 2009. Matheny, N.P., and J.R. Clark. 1994. A Photographic Guide to the Evalu- ation of Hazard Trees in Urban Areas (2nd edition). International Society of Arboriculture, Champaign, Illinois, U.S. Mueller, J., and M.G. Stewart. 2011. Terror, Security and Money: Balancing the Risks, Benefits and Costs of Homeland Security. Oxford University Press, Oxford and New York. Norris, M. 2007. Tree Risk Assessments: What Works - What Does Not - Can We Tell?, ISAAC Conference, Perth, 2007. NTSG. 2011. Common sense risk management of trees – Guidance on trees and public safety in the UK for owners, managers, and advisers. National Tree Safety Group, Forestry Commission Publications. Poll v Bartholomew. 2006. England & Wales High Court [EWHC] Queen’s Bench Division [QB] (Bristol: 4BS50384). QTRA. 2012. User Manual V3.06, QTRA Ltd Licensed Product. QTRA Newcastle. 2010. Schmidlin, T.W. 2009. Human fatalities from wind-related tree failures in the United States 1995–2007. Natural Hazards 50(1):13–25. Smiley, E.T., B.R. Fraedrich, N. Hendrickson, and G. Percival. 2007. Tree Risk Management (2nd edition). FA Bartlett Tree Expert Com- pany, Inc. 171 ©2013 International Society of Arboriculture
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