404 Norris and Moore: How Tree Risk Assessment Methods Work perceiving the assessment process as dishonest. How- ever, it is important that any method is transparent and legally defendable (Fischhoff 1994). To create an outcome, tree risk assessment methods Figure 1. Risk Assessment process derived from the AS/NZS 4360:2004. (Note that Establishing Context and Treating Risk are considered risk management functions that sit outside the assessment process.) well with established general risk frameworks such as ANSI or Standards Australia standards, there is still a lack of agreed upon arboriculture industry standards, as the diversity of tree risk assessment methods used in different countries and by different organisations within countries attests. Despite the wider use of methods such as Tree Risk Assessment Qualification (TRAQ)(Dunster et al. 2017) or Quantitative Tree Risk Assessment (QTRA) (Ellison 2005a, 2005b), which provide an opportu- nity for the standardisation of terminology and pro- cesses, many other and often older methods are still in wide use. These newer methods may be used by a sector of the arboriculture industry, particularly those who are members of professional and industry asso- ciations, but they can be expensive of both time and money and require users to register and to commit to ongoing professional development. As a result, they are used by a minority of those undertaking tree risk assessment. There is concern about the credibility and validity of existing methods, limited use of hard data, and highly judgemental and subjective inputs. In many industries, it is rare to find disclosure of the degree of judgement used in defining a risk due to the belief that disclosure would result in the public ©2020 International Society of Arboriculture need to answer a series of questions, such as: “What can go wrong?” “What is the likelihood that it will go wrong?” “What are the consequences if it does go wrong” “How does this risk compare?” “Is the risk acceptable or unacceptable?” “What treatment options are available?” and “What is the residual risk?” (Haimes 1998; Standards Australia 2004a, 2004b; Koeser et al. 2016; Smiley et al. 2017). From an arbo- ricultural perspective, these questions can be grouped. “What can go wrong?” is an assessment of identifi- able structural defects and their severity, other non-tree hazards created by the tree (raised pavements, low branches, poisonous fruits), and an assessment of the existing and potential targets (Figure 2). A second, more difficult question is composed of two elements: the likelihood of failure and the likelihood of the target being affected (a target being present when failure occurs). The latter can be analysed and a prob- ability derived (possibly predefined in a method); how- ever, the former is essentially judgement- based with a high degree of uncertainty. Arborists are rarely trained to quantify consequences of failure, which involves iden- tifying the target, determining how often the target is in the vicinity of the tree, and what level of injury or damage might be done to the target if failure occurs. Most tree risk assessment methods use size of part to define con- sequence, which often fails to reflect the likely conse- quences well. The question of risk evaluation including acceptability and treatments is dependent on the ear- lier questions. Without broadly accepted industry guide- lines, what is considered acceptable risk will continue to remain in the domain of individual assessors. Trees are currently assessed for risk under three types of systems: Qualitative: where the person undertaking the assessment visually inspects the tree for risk and pro- vides a written (oral) report and recommendations. Subjective terms tend to be used to describe the risk, such as high, medium, or low. Quantitative: quantitative risk assessment (QRA) uses true numerical values and is common in many industries but rare for tree risk assessment. For tree risk assessment, each and every likelihood and consequence element of the method would be assigned a numerical value.
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