Sort of an afterthought i had while i was out but we might want to think about Fukuoka in this context. So Fukuoka’s yields were quantified and his rice yields were comparable or better that surrounding farms using intensive methods. Thing is after Fukuoka died no one was able to replicate his yields even on the same property. So the casual factor seems to be Fukuoka acting as an agent and making well timed structural interventions into the system. That is to say Fukuoka’s acts of will in conjunction the natural systems produced quantitatively higher yields.

So there’s two things to learn from this.

1. Quantifiable data tells us nothing about how Fukuoka (ie. the timed structural interventions that produced more work from less energy) got higher yields so we can’t replicate it.
2. Fukuoka fits my initial definition of magic (causing change to occur in conformity with will) so we could be equally right in saying Fukuoka is wizard, Fukuoka is scientist using careful observation and experimentation, Fukuoka is lucky and an outlier. Each of those claims is epistemologically true but they are ontologically different. Ontological questions are questions of metaphysics so there’s not much that data can tell us about them. They are questions we have to carefully think through.

Lastly people need to stop saying that permaculture is about modern farming methodology at the exclusion of everything else. Ecological agroforestry is just the easy part of permaculture. There was and is always a larger vision.

So getting back to the complexity stuff. Getting good quantifiable data sets is hard and it’s important but what do you do with data? You need a theory. Science involves a balance of induction, deduction, and abduction. Data and quantifiable numbers really only helps with induction. But induction doesn’t tell you much about structure because it relies on generalities. Something that is generally true over a large sample might be untrue or exceptional in a small sample where different conditions and histories apply. So you have to be careful with quantifiable data.

Most of permaculture proceeds by abduction. Complexity usually involves building a model based on theory (deduction) observing what the model does and building a hypothesis (abduction) and taking those results to data to compare (induction). In permaculture we basically have shit all for scientific data and generalities because every food forest is different. We can compare gross generalities like yield per acre but that doesn’t tell us anything about structure (ie. how are the plants interacting). We could survey every permaculture farm and do an inventory of species and proximate interactions but that’s a huge undertaking and we still wouldn’t have much to work with since we’d just have a huge dataset but few theories of interaction. So really the best method is careful observation and hypothesis (abduction) and then testing through repetition. It’s not very quantifiable but it’s practical.

The other issue is you can only quantify what you can measure and much of science has proceeded by only valuing what can be measured and disregarding or dismissing what is unmeasurable. Part of how science has changed in the past 30 years is because advances in computation have allowed us to compute (ie. model) analogies to real world systems and then use those to fill in the gaps where measurement doesn’t tell us anything useful. So really it’s just a bunch of mathematized metaphors compared with statistics that are driving science these days.

Magical thinking is really only different from this in attribution. If we cut down the forest the spirits will be angry and will deny us rain vs. if we cut down the forest it will affect the hydrological cycle and produce less cumulative rainfall. Both are hypothesis driven by observation. It’s better when you have data (the gods are angry and have denied us 75 mm of rain this month) but it doesn’t always help your theory.

Lots of important things aren’t quantifiable. Not everything has a direct material and/or measurable product. Quantifying everything is an idea rooted in science and capitalism and necessarily misses certain marks.

Psychology for instance can be considered a soft-science because it’s mostly based on feelings and ideas with not a very large amount of quantifiable data.

Therefore it doesn’t fit in well with the hard-science, quantify and reproduce everything in double blind studies perspective.

I love science. It’s one of my greatest passions. But it can’t look at everything, at least not right now.

When dealing with gardens you bring in a psychological aspect. Aestetics, quantity, quality, variety, location, accessibility, difficulty, cost, and perhaps even interpersonal relationships. All of these things effect how people feel about the garden. And it’s not all easily quantifiable on all levels from all aspects. At least not right now.