Quantified Tree Risk Assessment (QTRA) - Questions & Answers

[Acer ventura]

Hi Arbtalk

 

RobArb’s thread

 

http://arbtalk.co.uk/forum/general-chat/50770-qtra-im-sorry-i-dont-agree.html

 

has been brought to my attention. It raised a number of questions and had some misconceptions about QTRA, so I thought I would trek over from the UKTC forum, dip my toes into Arbtalk, and chip in to answer some of the questions raised and clarify a few things. By way of introduction, I’m David Evans and outside of my consultancy work at The Arbor Centre I run QTRA and VTA workshops. I’m starting a new thread because the old one died, and it went off topic a fair bit. Please feel free to ask any questions and I’ll do my best to help out.

 

I’ll begin at the beginning, with some of the points raised in RobArb’s first post. I appreciate the thread developed since then, but some of the issues raised are foundations on which everything else is built, so it’s pretty important to get them clear.

 

<<I just can't be drawn into a system that relies on statistics as its main factor.>>

 

QTRA doesn’t rely on statistics as its main factor, it’s founded on probability, which is the language of risk. Risk = Likelihood x Consequences. With QTRA, the likelihood and the consequences of someone or something being hit by a tree, or part of a tree.

 

<<it has been deemed by QTRA that an acceptible risk is 1/10000. This from what i can tell has been derived from historical tree failures>>

 

The 1/10,000 threshold does not come from QTRA, nor does it relate to historical tree failures. In summary, 1/10,000 is a ‘tolerable’ level of risk that can be imposed on the public for the wider good where the risk is As Low As Reasonably Practicable (ALARP); as outlined by the Health and Safety Executive (HSE). This is a really useful defendable threshold for managing tree risk to because it’s a level of risk that has been determined by an independent watchdog appointed by the government on behalf of society at large. It is not a level of risk that has been made up or is the opinion of an arborist.

 

The reason QTRA was created was to enable the user to measure and calculate risk as a numerical probability, so the tree owner/manager can manage their liability and discharge their duty of care to a published and accepted level of tolerable risk. The 1/10,000 that is often cited.

 

Rather than suffer me prattling on about its origins and context, what risk is, the 1/10,000 level of tolerable risk and its position in the HSE’s Tolerability of Risk (ToR) Framework, it can be seen in the first 3 pages of the QTRA Practice Note, which you can be downloaded here;

 

Quantified Tree Risk Assessment

 

The 2007 Goode Judgment from South Australia is interesting for a number of reasons. Not least because the Commissioner criticizes the 'implied precision' of the QTRA risk output and then bizarrely uses QTRA to back up his opinion but makes a fundamental error in applying it. The ‘implied precision’ issue he raised had been dealt with before the Judgment, and the Risk of Harm (RoH) output should not have been expressed with such precision to 4 significant figures, no matter how precise any of the inputs. The RoH with QTRA is expressed to one significant figure only.

 

Mike Ellison did a presentation that included a detailed reply about the Goode judgment which I've extracted and attached.

 

I’ll get onto the ‘subjectivity’ issue tomorrow.

 

Anything to ask in the meantime, then please fire away.

 

Cheers

 

Acer ventura

Goode Judgment Comments - Mike Ellison.pdf

[RobArb]

Hi David,

 

Thanks for taking the time to reply, i normally only read and observe the output at UKTC from an arms length distance as i tend to live over here on the pages of arbtalk:biggrin:

 

I read the "Limitations of Defect led Tree Risk Assessment" with great interest (my phone wouldn't stop bleeping with notifications for days:001_rolleyes:).

 

I think after looking more into it, what i still get stuck on is this factor/tolerability of risk. Some government bod somewhere has pulled a number out of a hat (IMO:lol:) and said "that'll do".

 

 

Now, was that a subjective statement i just issued. Yes, its purely my opinion, and i feel this is how QTRA is. I have no issues with Mike, in fact i've met him twice at ATF events (he probably won't remember little ole me) and i do think he's a decent bloke but the whole QTRA can be wholly misleading when "interpretation" is involved. And that really, is the downfall of any system... interpretation.

 

We still see tree risk through our (the assessor) own eyes, and our own eyes are exactly that. We can draw on numerous years experience, some more so than others and offer an opinion as, with trees and risk, it isn't an exact science or in this case a number.

 

Subjectivity v Objectivity, don't ya just love it:biggrin:

 

I look forward to your thoughts on subjectivity tomorrow, and hopefully i'm sure, more people may "join in"

 

Robin

[Acer ventura]

Hi Robin

 

Good to hear from you, and it would be great to hear from others who have something to say.

 

I'll try to help explain and expand on this bit first;

 

I think after looking more into it, what i still get stuck on is this factor/tolerability of risk. Some government bod somewhere has pulled a number out of a hat (IMO:lol:) and said "that'll do".

 

I suppose the conical ToR framework does resemble a hat that could be worn at a party. A party that would be incredibly dull and lacking the kind of physically reckless activities that often make such events memorably entertaining.

 

Nonetheless, it’s a hat that’s had a lot of very careful thought and research go into its appearance and the numbers that make up its dimensions than ‘that’ll do’. From research by the Royal Society in ‘Risk Assessment: A Study Group Report’ in 1983 where 1/1,000,000 was raised as a level of risk that was so low that no benefits were necessary in order for society to accept it. To Henderson’s ‘Living with Risk’ – The British Medical Association Guide, in 1987, which concluded, “few people would commit their own resources to reduce an annual risk of death that was already as low as 1/10,000." Finally, the HSE in 1996, where they concluded, “For members of the public who have a risk imposed on them 'in the wider interest' HSE would set this limit at 1/10,000 per annum.”

 

It goes way beyond our borders though. NASA adopted 1/10,000 as a human casualty threshold in 1995, and it was later accepted by the US government in 2001. The European Space Agency and the Japanese Aerospace Exploration Agency have also adopted the same threshold.

 

Interestingly, satellites are now designed so that upon re-entry, when they fall apart, the pieces that fall back to earth will be small enough so the risk is less than 1/10,000. The same principles can be applied with QTRA, where, with a known target value you can work out the minimum size of part that could result in a risk greater than 1/10,000, or 1/1,000,000, and restrict your tree assessment to defects to those parts, and ignore anything with a smaller diameter.

 

I'll get back to you with objectivity v subjectivity side of things this afternoon. As you've endured the UKTC's "Limitations of Defect led Tree Risk Assessment" thread you've probably already got some insight into this.

 

Cheers

 

Acer ventura

 

PS Excuse me if I screw up the quote protocol, I'm still learning to drive the message box on here.

Edited February 4, 2013 by Amelanchier
fixed quote... :)

[Tony Croft aka hamadryad]

Good to see you engaging on this forum Acer, where one can probably achieve more in regards to the bigger scene.

 

I have a few questions, simple ones to begin with

 

Why do I need QTRA over the VTA approach

 

Why worry about 1/10,000 when there is a one in ten million risk from trees BEFORE we even got involved?

 

Could you share with us the process in a case example?

[Acer ventura]

The next bit.

 

Objectivity and Subjectivity.

 

With an Objective numerical probabilistic threshold of risk to measure against - the 1/10,000 and 1/1,000,000 - what QTRA aims to do is maximise the Objectivity of the assessor and minimise the Subjectivity. It might be easier to illustrate how this works with an example.

 

But first some context. The most important element of tree risk is the Target, because in the risk equation;

 

Risk = Likelihood x Consequence

 

Target = A proportion of the Likelihood of occupation AND the Consequence to what might be hit.

Probability of Failure = A proportion of Likelihood

Impact Potential (as a function of size) = A proportion of the Consequence

 

I’ve attached a Powerpoint slide that illustrates the primary importance of Target in the relationship.

 

Target is not only the most important element of tree risk assessment, it’s also the one that you can be the most Objective about. If we look at a recent site I was involved in, there is a 30mph residential road which was the highest value Target. Before I went to the site, the council’s highway department told me 4,441 vehicles a day used this road. Rounding this figure up to 4,500, and putting it into the QTRA software calculator, I get a Target value of 1/10. In other words, if a branch or tree falls onto this road, there is a 1/10 chance that it will either hit a car, or a car will not have time to stop before hitting the branch or tree. On a sliding scale of Objective – Subjective, I’m not sure it’s possible to get any closer to being Objective than taking this measured and quantified approach to tree risk assessment when assessing the Target.

 

It’s an interesting exercise to compare this measured quantitative approach with trying to so do the same qualitatively, using words or ordinal numbers, even if you knew the road traffic figures. Or how you might then relate that to a tolerable or acceptable level of risk.

 

The element of QTRA, as with any tree risk assessment, that is most Subjective is Probability of Failure (PoF). As you pointed out Robin, this is partially down to experience. We could also reframe a negative term ‘Subjectivity’, with a positive phrase ‘Professional Judgement’. After all, they both have the same factual meaning, but opposite emotional meanings.

 

Let’s stay with the original dichotomy. I’ll explain how we go about minimising the Subjective element of PoF with QTRA. A self-optimised tree with good vitality has a PoF of less than 1/1,000,000, and we take this as a base point reference. So, where we encounter a tree with defects and the tree is perhaps of reduced vitality, isn’t showing positive signs of having mechanically adapted, or has incipient indications of failure, the question the assessor asks themselves is, within broad ranges, how many times more likely is the tree to fail, than the 1/1,000,000 tree. Is x10, x100, x1,000, and so forth. We’ve developed and taken this approach in QTRA training and Update sessions for a couple of years now. What I find interesting is that during the outdoor practical sessions, no matter the range of experience of those that attend, once we have calibrated an agreed starting point, and take this considered and measured approach, a very narrow consensus of PoF Subjectivity/Professional Judgement is reached within quite a short period of time. The widest divergence of opinion is seldom more than 1 x10 range out, and that tends to occur where the RoH is furthest from 1/10,000, so it’s not important when risks are getting down to the one in hundreds of millions. Once we start getting to a RoH that isn't tolerable, towards 1/10,000, there’s a convergence of consensus because the tree defects are more pronounced, and the tree’s poor vitality is more discernable.

 

Apologies for the long post, but after spending a bit of time on it I figured I couldn’t break this part of the discussion down into anything less than one dump, so to speak.

 

Let me know what you guys think. Does all this make sense? Or do you think I’ve been at the two-stroke and am speaking in tongues.

 

Cheers

 

Acer ventura

QTRA Target Importance.pdf

[RobArb]

Objectivity and Subjectivity.

 

With an Objective numerical probabilistic threshold of risk to measure against - the 1/10,000 and 1/1,000,000 - what QTRA aims to do is maximise the Objectivity of the assessor and minimise the Subjectivity. It might be easier to illustrate how this works with an example.

 

But first some context. The most important element of tree risk is the Target, because in the risk equation;

 

Risk = Likelihood x Consequence

 

Target = A proportion of the Likelihood of occupation AND the Consequence to what might be hit.

Probability of Failure = A proportion of Likelihood

Impact Potential (as a function of size) = A proportion of the Consequence

 

 

I understand what you are trying to put across but risk in relation to trees IMO is too subjective to be given a quantifiable "threshold". Statistics unfortunately, within any walk of life, are still open to too much human interpretation. Now i'm not saying QTRA tries to "bend" those statistics, not at all, but it is interpretation of risk that is key here.

 

for example.... taking your example:biggrin:

 

 

Target is not only the most important element of tree risk assessment, it’s also the one that you can be the most Objective about. If we look at a recent site I was involved in, there is a 30mph residential road which was the highest value Target. Before I went to the site, the council’s highway department told me 4,441 vehicles a day used this road. Rounding this figure up to 4,500, and putting it into the QTRA software calculator, I get a Target value of 1/10. In other words, if a branch or tree falls onto this road, there is a 1/10 chance that it will either hit a car, or a car will not have time to stop before hitting the branch or tree. On a sliding scale of Objective – Subjective, I’m not sure it’s possible to get any closer to being Objective than taking this measured and quantified approach to tree risk assessment when assessing the Target.

 

 

I'm not trying to be awkward, i just try to look at things from all angles.

 

So, 4,441 (4500) cars use that road in a day, we can presume that its quite a busy commuting road, even at 30mph. (Without using the QTRA calculator, what is the rationale of the target value being 1/10?) Looking at your sentence in bold, i feel again IMO, that this is too subjective to be quantified

 

Has it been taken into consideration, time of day that the tree/tree part "might" fail? Cars will be less frequent at night, or even the day compared to rush hour times...

 

Has it been taken into account what cars travel on that road? Is it a wealthy affluent ares/poor less affluent area? More affluent areas may have bigger and better/safer cars. Bigger, newer cars "tend" to be safer and more responsive than older models (pure speculation mind, but very subjective:biggrin:)

 

What about the people? We all drive differently, we all respond differently! Who's to say your reaction might not be good enough to react in time to a falling branch/tree and that mine would be (or vice versa). Again, subjective.... one might say clutching at straws or being obstinate but i disagree:biggrin:

 

 

 

The element of QTRA, as with any tree risk assessment, that is most Subjective is Probability of Failure (PoF). As you pointed out Robin, this is partially down to experience. We could also reframe a negative term ‘Subjectivity’, with a positive phrase ‘Professional Judgement’. After all, they both have the same factual meaning, but opposite emotional meanings.

 

 

I tend to agree with you here on the PoF being subjective and it also being down to experience, but para-phrasing it 'professional judgement' sidesteps the core theme here, that trees and the potential "risk" they may (or may not cause) is a VERY subjective subject.

 

 

Let’s stay with the original dichotomy. I’ll explain how we go about minimising the Subjective element of PoF with QTRA. A self-optimised tree with good vitality has a PoF of less than 1/1,000,000, and we take this as a base point reference. So, where we encounter a tree with defects and the tree is perhaps of reduced vitality, isn’t showing positive signs of having mechanically adapted, or has incipient indications of failure, the question the assessor asks themselves is, within broad ranges, how many times more likely is the tree to fail, than the 1/1,000,000 tree. Is x10, x100, x1,000, and so forth. We’ve developed and taken this approach in QTRA training and Update sessions for a couple of years now. What I find interesting is that during the outdoor practical sessions, no matter the range of experience of those that attend, once we have calibrated an agreed starting point, and take this considered and measured approach, a very narrow consensus of PoF Subjectivity/Professional Judgement is reached within quite a short period of time. The widest divergence of opinion is seldom more than 1 x10 range out, and that tends to occur where the RoH is furthest from 1/10,000, so it’s not important when risks are getting down to the one in hundreds of millions. Once we start getting to a RoH that isn't tolerable, towards 1/10,000, there’s a convergence of consensus because the tree defects are more pronounced, and the tree’s poor vitality is more discernable.

 

 

Even every self-optimised tree with good vitality is open to subjectiveness, OK fair enough the 1/1,000,000 threshold set by HSE and professional bods is now "set" as you state, the base point reference and there is nothing that can change that (is there?), does it take into account 'professional judgement'?

 

We, or at least all those trained with numerous and numerouser years experience, are still fallible, we all get things wrong from time to time, and therein lies objectivenesses problem. What about healthy trees that have signs and symptoms of reduced vitality and vigour mis-read and mis-quantified?

 

Also how can you quantify "how many times more likely is the tree to fail, than the 1/1,000,000 tree" without it being subjective?

 

Lastly, kind of off on a tangent but one i feel is quite pertinent. Veteran and Ancient trees are becoming less and less (yes the ATF is doing a good job of recording the ones we have left and trying to save them) so how would a tree of this category stand up in a case of QTRA assessment in regards to keeping the tree for its important ecosystem/s if it where in a place where it's PoF may be within Targets of RoH?

 

 

And please, don't apologies on the long post, l like it when people have put time, effort and thought into a post reply. We may not agree on all things but debate IS healthy:thumbup:

 

Robin

[Acer ventura]

I have a few questions, simple ones to begin with

 

Why do I need QTRA over the VTA approach

 

Hi Tony

 

Your post has reminded me I still owe you a reply on the UKTC’s "Limitations of Defect led Tree Risk Assessment" thread, which I’d begun to draft and then got distracted from by work, leaving it to curl up at the corners and gather dust, but I think I may have answered it above.

 

The VTA approach is an integral part of QTRA. It’s not separate thing, it's what drives the Impact Potential (Size of Part) and Probability of Failure (PoF) components of the risk assessment. Though VTA is important in helping you work out the SoP and PoF, it alone won’t tell you what the RoH is relative to a published level of tolerable or acceptable risk, unless you quantify it and also measure the Target. This is something that is very much focused on during the VTA day, which runs paired with the QTRA day, and looks at how decay colonises trees, how trees with good vitality are mechanically self-optimising, the limitations of strength loss formulae, mapping decay/soundwood with the Thor 710 hammer, and calibrating PoF.

 

Why worry about 1/10' date='000 when there is a one in ten million risk from trees BEFORE we even got involved?[/quote']

 

You’re right that the general background risk from trees is extremely low at around 1/10,000,000 per annum, which is a really important point about ‘reasonable practicability’ and ‘gross disproportion’ that we may get onto. However, locally the risk can be much higher than 1/10,000.

 

Cheers

 

Acer ventura

[Tony Croft aka hamadryad]

You’re right that the general background risk from trees is extremely low at around 1/10,000,000 per annum, which is a really important point about ‘reasonable practicability’ and ‘gross disproportion’ that we may get onto. However, locally the risk can be much higher than 1/10,000.

 

and it is very easy to see and know when locally the risks are high, I like to think of Kenwood gate on the heath for a great example, a funnel for millions of people per annum.

 

I do think this inherently low risk generally from trees is always going to be a thorny issue.

 

I would be very interested in your views on "the limitations of strength loss formula"

[Acer ventura]

I understand what you are trying to put across but risk in relation to trees IMO is too subjective to be given a quantifiable "threshold". Statistics unfortunately, within any walk of life, are still open to too much human interpretation.

 

Hi Rob

 

I don't follow the argument that the management and assessment of risk from trees should not be measured and relate to what we know are published tolerable or acceptable levels of risk because a part of the risk assessment requires some subjective judgement. How do we know what we’re doing otherwise?

 

Don’t underestimate the immense value to duty holders of managing tree risk to a published tolerable or acceptable level of risk because they can adopt it as policy. Not only can they then compare their exposure to tree risk with all the other risks they have to manage, but defend claims against them in the event of acceptable risks being realised.

 

What are the statistics which are subject to too much human interpretation?

 

Without using the QTRA calculator' date=' what is the rationale of the target value being 1/10?) Looking at your sentence in bold, i feel again IMO, that this is too subjective to be quantified. [/quote']

 

I’ve attached a slide showing how the Likelihood of vehicle occupancy is calculated. More detail is in the QTRA Practice Note. All the assessor needs to know is the speed limit and number of cars/day (to fit into one of the 6 broad Target ranges) to get the Target value. I have considerable difficulty in seeing how you can come to a IMO that valuing a vehicular Target in this manner is ‘too subjective’. Within the realms of being reasonably practicable, I can’t envisage an approach that is less subjective.

 

Has it been taken into consideration' date=' time of day that the tree/tree part "might" fail? Cars will be less frequent at night, or even the day compared to rush hour times... [/quote']

 

The RoH is an annual risk. Which fits with the published levels of risk and accounts for the range of weather conditions that can affect tree stability over a year. So the Target value is an annual average as well. As is the PoF.

 

Has it been taken into account what cars travel on that road? Is it a wealthy affluent ares/poor less affluent area? More affluent areas may have bigger and better/safer cars. Bigger' date=' newer cars "tend" to be safer and more responsive than older models (pure speculation mind, but very subjective:biggrin:)

 

What about the people? We all drive differently, we all respond differently! Who's to say your reaction might not be good enough to react in time to a falling branch/tree and that mine would be (or vice versa). Again, subjective.... one might say clutching at straws or being obstinate but i disagree:biggrin: [/quote']

 

Don’t forget the Taylforth.

 

I doubt whether any authority, even a highways department who love nothing more than measuring traffic, would try to account for any of these variables. The reason being, it’s not ‘reasonably practicable’. Reasonable practicability is the Rosetta Stone of the Occupier’s Liability Act, and a central tenet of law, in relation to the duty of care when considering how to manage any risk. It is also core component of risk management. To try and measure these variables would also be ‘grossly disproportionate’ in relation to the level of risk. Notwithstanding the politically explosive issue of valuing the rich and poor.

 

How would you go about valuing the Target in this scenario?

 

Also how can you quantify "how many times more likely is the tree to fail' date=' than the 1/1,000,000 tree" without it being subjective? [/quote']

 

You can’t. So what you do is acknowledge it, use professional judgement, apply reason to that judgement, then apply that reasoned judgement in a structured manner within broad ranges to allow for margins of error and acknowledge the uncertainty. The reason you do this is because it enables you to plug this information into measuring the risk rather than pondering the possible failure of a tree defect.

 

Lastly' date=' kind of off on a tangent but one i feel is quite pertinent. Veteran and Ancient trees are becoming less and less (yes the ATF is doing a good job of recording the ones we have left and trying to save them) so how would a tree of this category stand up in a case of QTRA assessment in regards to keeping the tree for its important ecosystem/s if it where in a place where it's PoF may be within Targets of RoH? [/quote']

 

Veteran and Ancient trees usually have a very low RoH because of their locations and the Target value is so low. If the RoH is higher than 1/10,000 then the first and most obvious way to manage the risk would be by managing the Target. For example, something as simple as leaving grass unmown can make a significant difference to pedestrian traffic. An advantage of using QTRA is that can you work out what the Target value has to lowered to in order to achieve a tolerable or acceptable level of risk. It might also be possible to prune the tree to reduce the RoH. Yet again, if you quantify you can back calculate to work out what size of branch will be required before the RoH becomes unacceptable. In this scenario, another advantage of referencing the ToR framework for tolerable and acceptable levels of risk, is that the benefit attached to the risk is an integral part of the risk. So for a particularly valuable tree an argument could be made to manage the RoH to a higher level, up to the Extraordinary Limit of Tolerability, between 1/1,000 – 1/10,000.

 

If you don’t measure and quantify risk because you think it’s too subjective, what threshold of risk do you suggest duty holders manage tree risk to, and how do you go about assessing it?

 

Cheers

 

Acer ventura

QTRA Vehicular Occupation.pdf

[RobArb]

Hi Rob

 

I don't follow the argument that the management and assessment of risk from trees should not be measured and relate to what we know are published tolerable or acceptable levels of risk because a part of the risk assessment requires some subjective judgement. How do we know what we’re doing otherwise?

 

Don’t underestimate the immense value to duty holders of managing tree risk to a published tolerable or acceptable level of risk because they can adopt it as policy. Not only can they then compare their exposure to tree risk with all the other risks they have to manage, but defend claims against them in the event of acceptable risks being realised.

 

What are the statistics which are subject to too much human interpretation?

 

 

 

I’ve attached a slide showing how the Likelihood of vehicle occupancy is calculated. More detail is in the QTRA Practice Note. All the assessor needs to know is the speed limit and number of cars/day (to fit into one of the 6 broad Target ranges) to get the Target value. I have considerable difficulty in seeing how you can come to a IMO that valuing a vehicular Target in this manner is ‘too subjective’. Within the realms of being reasonably practicable, I can’t envisage an approach that is less subjective.

 

 

 

The RoH is an annual risk. Which fits with the published levels of risk and accounts for the range of weather conditions that can affect tree stability over a year. So the Target value is an annual average as well. As is the PoF.

 

 

 

Don’t forget the Taylforth.

 

I doubt whether any authority, even a highways department who love nothing more than measuring traffic, would try to account for any of these variables. The reason being, it’s not ‘reasonably practicable’. Reasonable practicability is the Rosetta Stone of the Occupier’s Liability Act, and a central tenet of law, in relation to the duty of care when considering how to manage any risk. It is also core component of risk management. To try and measure these variables would also be ‘grossly disproportionate’ in relation to the level of risk. Notwithstanding the politically explosive issue of valuing the rich and poor.

 

How would you go about valuing the Target in this scenario?

 

 

 

You can’t. So what you do is acknowledge it, use professional judgement, apply reason to that judgement, then apply that reasoned judgement in a structured manner within broad ranges to allow for margins of error and acknowledge the uncertainty. The reason you do this is because it enables you to plug this information into measuring the risk rather than pondering the possible failure of a tree defect.

 

 

 

Veteran and Ancient trees usually have a very low RoH because of their locations and the Target value is so low. If the RoH is higher than 1/10,000 then the first and most obvious way to manage the risk would be by managing the Target. For example, something as simple as leaving grass unmown can make a significant difference to pedestrian traffic. An advantage of using QTRA is that can you work out what the Target value has to lowered to in order to achieve a tolerable or acceptable level of risk. It might also be possible to prune the tree to reduce the RoH. Yet again, if you quantify you can back calculate to work out what size of branch will be required before the RoH becomes unacceptable. In this scenario, another advantage of referencing the ToR framework for tolerable and acceptable levels of risk, is that the benefit attached to the risk is an integral part of the risk. So for a particularly valuable tree an argument could be made to manage the RoH to a higher level, up to the Extraordinary Limit of Tolerability, between 1/1,000 – 1/10,000.

 

If you don’t measure and quantify risk because you think it’s too subjective, what threshold of risk do you suggest duty holders manage tree risk to, and how do you go about assessing it?

 

Cheers

 

Acer ventura

 

Its not something i normally do in my day-to-day work, measure risk in that instance (im just a climber at present). I hope, in the not too distant future to be able to have an "on-level" debate with like minded professional's where i can hold down my side of the "arguement" with pertinent data and experience from my own wealth of years.

 

I do understand the points you are putting across, my learning pathway though tends to question anything i don't fully understand until i do fully understand it. I have been told that this is both a good and bad way to learn:biggrin:

 

I fully appreciate the time and effort you are putting into the replies here and your explanations are clear enough to me and please don't take my argumentative questionings any other way than a desire and curiosity to learn:thumbup1:

 

I'm sure QTRA has its place otherwise it wouldn't exist in the way that it does now, but until it is possibly part of my day to day work life there's just something that "doesn't fit" and i can't thoroughly explain why?

 

I have been known to turn though:biggrin: