Calculating a functional value for trees is the next big game changer in urban forestry.
If a functional value for trees is achieved, trees as natural assets will far exceed the value of an engineered footpath. Those who demonstrate expertise in tree health can contribute to a global initiative to put a premium on world best practice urban forestry. We are on the cusp of providing following generations with an impressive legacy based on scientific environmental baseline knowledge.
Urban forestry is a global endeavour. Some of us relocate to another urban environment, and urban forestry is still part of our environment, no matter where we reside. Funding best practice urban forestry is essential now, and into the future.
Urban forest funding goes into a few basic areas:
- Buying trees
- Planting trees
- Pruning and removing trees
- Addressing complaints by homeowners
Making sure established trees are healthy and providing benefits is an aspect not quantified through measurable factors and such work is not widely funded. Just keeping trees alive is not best practice. The existing tools for tracking tree data such as iTree, Tree Plotter, Open Tree Map and the like focus on inventory trees and calculating ecosystem benefits, based on a general algorithm.
In the world of urban forestry, this focus makes sense – city councils get excited the day a tree gets planted and a speech delivered, when a map is shared of their tree inventory through social media, and then again when figures of how much carbon will be sequestered for their annual report. After that, they don’t appear to quantify measurable tree health and function.
Making tree health a priority
In short, striving for the highest state of tree health and function doesn’t excite stakeholders because they can’t see the benefit, and it’s hard to justify an expense if the benefit isn’t measurable. At most, city budgets provide arborists enough time to do ‘drive-by’ evaluations of trees, checking for obvious problems based on an educated subjective human interpretation. Tree removal and pruning are the result, to ensure a human perceived risk is the priority and the driver of any reactive work.
Arborists and urban forest management departments are keenly aware of this, and they genuinely care about trees. Still, no one has figured out how to make quantified tree health and function a budget priority.
There is movement in the right direction. The proliferation of iTree as a global urban forest platform shows there is interest in the data. This shows growing political will to value ecosystem benefits and carbon sequestration, and reduce the urban heat island effect, all of which increase the value of keeping trees alive. The use of drones to measure canopy density and color means we can now plug more information into models than just “is there a tree? That incentivizes healthy trees, and DE incentivizes dying trees.
Two major hurdles remain – cost and consistency. Measuring tree health and function (vigor, pest/disease identification and so on) is expensive and requires manpower to do well. Worse yet, baseline data is required to see changes over time, so trees need to be tracked for years to identify trends. Finally, the current set of tree health assessments are varied and do not address all situations and all trees. They are usually based on a small number of observations or data sets collected by academics in isolation. There are few if any individual tree and soil health,measurables. This by no means implies those assessments are poorly thought out – just that assessments are slow to improve because they lack direct feedback from experienced experts in the field and the changes in the real world.
Technology is not a catch-all answer
It is true that some can now build software to collect and share data quickly and easily, in part because everyone already has a smartphone. In addition, the decreasing cost of electronic parts and simplification of manufacturing have brought down the price of scientific quality instrumentation.
PhotosynQ. is a good example, but more will be coming. In short, building a platform to inexpensively collect scientific-quality data and put it on the cloud for immediate analysis is now possible.
Furthermore, advances in data analysis deep learning neural networks (AI) are allowing computers to learn from large, complex datasets to generate useful predictions in real time. For example, with enough pictures of cats and dogs, a computer can tell the difference between the two. The same idea holds true for healthy oak trees and sick oak trees. In effect, we help machines learn through experience, just like humans do. But machines learn from data we collect using sensors we control.
The real question is: who is the “we” in this equation? That’s not a technology question.
Right now, the “we” generally refers to a company such as Arborcheck with proprietary technologies for evaluating tree vigor. Those technologies require large reference datasets to calibrate the sensors, so Arborcheck controls (or licenses) nurseries to grow ‘model’ trees to build their prediction algorithms. The data is proprietary, and so is the prediction model. Most of the value created by the technology will go to Arborcheck, and whoever pays Arborcheck for the data (akin to Google and AdWords).
Competing with Arborcheck will become more expensive as Arborcheck acquires more data, so arborists will see higher prices and less competition over time. Arborcheck will be highly motivated to control and not change tree health assessment methods while keeping their reference data proprietary.
Furthermore, there’s no guarantee their ‘standard’ trees are consistent with real trees in the field. Without getting information back from actual arborists or urban foresters (did the tree die or not? Did it perform functional value after planting? Is it on track to increase in functional value in future?) there’s no way to even tell if they are wrong. They will likely make some data or hardware public someday, but only when they have enough market control that there is no danger from competition.
Regardless of the motivations of Arborcheck today, the long-term incentives created by that system do not favor the tree managers on the ground.
In exchange for allowing a single company to control the future of the industry by monopolizing core data of technology, arborists get to charge for an additional service. This is the track the arboriculture community is headed down today.
Imagine instead if machines learn from data arborists collect using sensors arborists control and urban foresters interpret.
The arborist and urban forestry community could collaboratively create a public reference library using open source tools. Instead of relying on Arborcheck ‘standard’ trees, arborists could collect enough data in their normal operations to account for variability. There will be ample competition among sellers of measurement devices as the designs are public, driving down costs.
By making the reference data public, anyone can create, test improvements, critique, and validate tree health assessments, and in future develop a tree health calculator using a common open data platform. Anyone in the community can quickly compare assessments, identify the best ones for their application, and spread successful ones quickly across the industry. Arborists and urban foresters could select which tree health assessment they want to use and compare their utility in real time in the field.
Arborists have collaborated successfully before: iTree is an open source project collaboration. The software and models are freely provided for others to use, and have massively benefited the industry by adding real value to the services arborists can provide to their customers. iTree was driven by a small group (the US Forest Service and collaborators) who saw the value in collaboration.
As with iTree, collaboration does not eliminate competition. Arborists will continue to compete for work, but that competition will occur using comparable, verifiable data collected over a lifetime. The results will be competition based on competence, experience, and skill rather than the ability to access expensive technology.
Don’t misunderstand – open platforms are not a panacea and meritocracy is not magic. Without centralized control, the community can sometimes do silly things like chasing shiny objects (or funding ‘slimy objects’ in the case of Kickstarter). Bad actors can even cheat or try to game the system. But urban foresters won’t be the first to address these problems: eBay, Amazon, Kickstarter and many others have developed systems to identify bad actors, motivate data sharing, validate users, and enable feedback to allow the system to self-regulate. These are known problems with functional, though imperfect, solutions.
Ultimately, it is up to the urban forestry and arborist community to determine which future is right for them. The goal is to move the discussion away from technology and toward values. Do arborists and urban foresters want to control their own technological destiny, or do they want someone else to control it under a user-pays platform? Do they want algorithms to replace large portions of the work currently done by arborists, the same way they’ll replace doctors in identifying sickness, lawyers in navigating the legal system, and other industries without people really noticing.
Do arborists and urban foresters want to just be the hands collecting the data, or the collective brain guiding the system?