Patterns of Scalability and Pathways in Systems

Note: this is just a draft – I was trying to fall asleep, started to think, and this is what I thought about.

In college I wrote a 300-page senior thesis entitled, “Energy Pathways In Biological Systems”. It was within the context of genetics to microbiology up through complex pathways of micro-climates to ecosystems and even pathways of migratory animals (Arctic Wolves that cover at least 1,000 mile territories to Terns and Whales that have annual migration patterns covering half the earth). For each there is movement of elements in space and time. I had a blast researching and writing it but my fascination revolved around that shared concept over seemingly vast discrepancies of scale that were actually sharing massive similarities, being only sizable to other scales, can only be in a relative framework of complexity.

Think of systems as an atom. There are layers or levels and activity going on all the time. Now think of this atomic model with pathways repetitively used for resources to move, kind of like corridors. Resources behave differently from other resources, thus the corridors are different, the speed of motion is different and the size is different. Also production and consumption of those resources is different. Entropy works differently based on environment, among other factors.

The pathways of genetic information through a cell move in a seemingly small scale to Nitrogen pathways in a rain forest but the complexity in a cell looking down to the smaller elements in that system is great. Also in a rain forest, Nitrogen molecules and everything they interact with as they move through that system, looking up to larger components, are equally great and yet looking down to the components that amass that system we see the same thing.

Think about that – scale, if only quantifiable by the scale of other systems, is relative. So what could lend to differentiation? Complexity could be an important part of the equation. So what about this – System A is larger and has more components than System B. System B is less complex than System A. If both systems are replicated many times and distributed which may fare better? Hard to say with such a limited theoretical idea but what about Okham’s Razor – the simplest way is the best, essentially. In mechanics, the less moving parts, the less points of failure. A human is a complicated system, a virus is a very simple system and yet a virus can so easily attack the more complicated system. Cells replicate very quickly, and each new cell gets its own copy of the genetic instructions the original parent cell had. I’m rambling but just trying to give some simple examples to think about.

So how do we properly think about scale in systems? What can we learn from successful patterns of scalability that are all around us?

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