Tree managers, foresters and tree surveyors are frequently lone workers due to the operational and logistical nature of the tasks required and, due to the physical locations of the tree stock under their management. The lone worker group is one that Ghiselin (1982) argues, are predominantly subjective thinkers. Interestingly, Ghiselin (1982) further argues that in the process of reaching a final judgement, such as a tree surveyor reaching a final decision on a tree’s structural condition, the decision maker commonly balances all available elements of objective, science based views, with interpretive subjective views, and ultimately arrives at a final, blended, management decision. de Groot (1992), highlights that the process of externalising subjective opinions and supporting them with descriptive, scientific statements, such as when creating tree related risk reports or forest management plans, is an attempt by the report author to rationalise the subjectivity of their findings. de Groot (1992) consequently describes the conclusions from this blending process as being “subjectivity objectified”. This view is also supported by Dana, Jeschke et al. (2013) who state that in an operational environmental management situation, managers
frequently make their intervention decisions based upon the process of “subjective reasoning” rather than by using the available scientific evidence.
Within the tree management industry, there have been various attempts to minimise the impact of subjectivity in tree assessments, several of which have been published which makes their use relatively common throughout the industry as the practices are adopted by many practitioners (Table 1). While these prescriptive methodologies have an aura of objectivity, and are frequently presented as such, there remains a large degree of guesswork and subjective assessment variables that are compounded in the methodological process as attempts are made to objectively quantify the tree assessment, while at the same time, relying on largely subjective inputs. Table 1 provides an overview of several of these commonly used methodologies:
Table 1 An overview of tree surveying methods currently in use in the forestry, arboriculture or tree management sectors. The word ‘objective’ refers to direct measurement or factually acquired data. The word ‘subjective’ refers to instances where a field operative uses interpretation, estimates or best guess methods to acquire ‘measurements’ for the survey method. This list is not exhaustive, but is representative of tree surveying methods frequently used in the UK, USA and worldwide.
Survey
Type Description Method
BS5837: 2012
British Standard 5837 tree survey method, used in relation to trees on, or near, development sites. Completed at the pre-commencement development stage, this method identifies which trees
Categorical assignment to tree retention groups, which are determined via a subjective ‘quality’ assessments and are ranked in order of value or
significance to the
are worthy of retention in the long term or are best removed
for the successful
implementation of the
development. Used on single trees and woodlands.
immediately considered not worthy of retention. Expert use.
CAVAT
Capital Asset Value for Amenity Trees (CAVAT). A street tree valuation system where trees are considered as public assets which are valued in monetary terms. Used on single trees, tree groups or woodlands in an ‘urban street’ context (or similar).
Accumulative financial value determined by taking a DBH measurement and assigning to a predetermined ‘value band’.
Adjusted by subjective
estimation of life expectancy, population density in the immediate area, and judgement
on public amenity
performance. Expert use.
CTLA Method
Council of Tree and Landscape Appraisers (CTLA) method. A street tree valuation method where trees are considered as private assets, quantified in monetary terms. Used on single trees, tree groups or woodlands in an ‘urban street’ context (or similar).
Accumulative financial value determined by taking a DBH measurement, then adjusted by several variables, including the subjective observation of general condition, location, species class (via a look up table of a variety of previously interpreted characteristics). Expert use.
ISA Method
International Society of Arboriculture (ISA) Tree Hazard Evaluation method. Production of a hazard rating to identify presumed failure potential, and therefore associated risk, from potential tree failure. Used on single trees, but can include single trees in tree groups or (potentially) woodlands
Accumulative hazard rating based on combined objective i.e. is the feature present Y/N?
Plus subjective field
observations, including; tree part most likely to fail, the estimated size of the part, and the potential significance of the target area. Expert use.
TEMPO
Tree Evaluation Method for Preservation Orders (TEMPO). A three-part field guide to decision making that considers; amenity, expediency and the decision process. Trees are assessed for suitability in being legally protected under a tree preservation order (TPO), a
Accumulative suitability score that requires the subjective consideration of a range of variables, including; qualitative
descriptors of assumed
condition, and subjective prediction of life expectancy, potential future visibility after
legal tool under UK planning legislation used for the protection of trees near building development. Used on single trees, tree groups or woodlands.
estimation of foreseeable or perceived threats. Requires expert use.
i-Tree (ECO)
i-Tree is a series of software suites and field survey methods used to provide both urban and forest, analysis and benefits
assessment. I-Tree Eco
quantifies tree structure and the environmental benefits and services, that trees offer a given area. Used on single trees, tree groups, woodlands/forests and
up to wider landscape
application.
Accumulative, model-based street tree value system that can use minimal GR input data to estimate tree structure, function and environmental
benefits by using
predetermined models.
Subjectivity is compounded in the model as this allows users to run analysis with very limited input data fields, potentially only; local geographic and meteorological data, with tree species and DBH measurements. The system can also run the model using estimated DBH, not direct measurements, to output customised benefits and costs data. Also recommended for expert and non-expert use.
QTRA
Quantified Tree Risk
Assessment (QTRA). A tree risk
assessment method to
‘quantify’ the level of risk attributed to trees in their location.
Accumulative ‘probable risk threshold’ score, based on subjective field estimations including; target, size, and probability of failure. Licenced, expert use.
Notes: Target – refers to people or property that are worth of protection (from tree failure or similar),
Size – often refers to the size of the part of the tree most likely to fail. A fundamental problem with this estimated value is that a best guess must be used to predict the future failure, and then also predict the future through guessing how big the failure part will be, and not measuring the potential failure part during the observational assessment. Probability/Likelihood of failure – a simple estimation
from the field operative, based on their individual feelings of how quickly they predict a whole tree, or tree part, may fail. Arrived at by balancing an estimation of their feelings on probability, with a temporal prediction. DBH – tree stem diameter taken at breast height (either 1.3m or 1.5m). Expert use – typically this system is recommended for use by industry specific experts. Non-expert use – this system can also be used by interested laymen. Licenced – this system requires the attendance at a training course and the completion of a formal assessment, and ongoing subscription to the service to be used commercially.
The fundamental issue with tree management subjectivity is that objectivity is the gold standard that foresters, arboriculturists or tree managers strive to achieve in their
managerial decision-making. However, there is a large reliance on a scientific base knowledge that must be vastly interpreted and applied in many unique operational situations. Even where industry best practice, guidance or recommendations are followed, there remains a strong emphasis on the need for estimation, interpretation and assumption (Stewart, O'Callaghan et al. 2013). The current situation for tree managers is that despite many attempts at maintaining professionalism and independence from subjectivity, their judgements on the best way to manage their tree stock remains idiosyncratic. The current suite of available tools, at best, only provide a set of rules that it is hoped give sufficient clarity for the tree managers to be able to (subjectively) classify an observed set of circumstances. With prior knowledge, experience, and benchmarks provided using the surveying procedures, to arrive at the management recommendation of a ‘reasonable’ person (Norris 2007, Stewart, O'Callaghan et al. 2013). While this approach cannot be considered an objective procedure, it is widely accepted within the tree management industries that this approach is the accepted status quo, despite being inherently famed within a large amount of subjectivity.