This is the only blog post I’ve actually wanted to write.
All things are dynamic. In our last class, Corey showed that even though we were equipped to portray a river as a dynamic feature, we did so statically. I bet we did this because of the numerous ways we are told to think of our world as static. Relationships are inherently dynamic, but we have static statuses to represent sometimes extensive periods. We take repeated single-point observations to measure some natural phenomena, then interpolate to fill in the blanks. But what are these blanks: evidence of dynamism. Since all phenomena are actually dynamic; falling down some temporal gradient — not dissimilar to Miller’s space-time cubes concept.
Miller brings up scale issues in movement. Traditional movement scientists like kinesiologists, physiotherapists, or occupational therapists think of movement on completely different scales than do movement ecologists. In fact they have a different semantic representation of movement as well, often related to the individual irrespective of the environment. Geographers and human mobility researchers have their own ideas about drivers and detractors of movement that run contrary to ecologists conceptualizations. So, how do we move toward an integrated science of movement? The best option is to start thinking about movement as fractal patterns. There’s a primatologist at Kyoto studying just that in penguins (which are not primates ….) to get an understanding of interactions of complexity, scale, movement, and penguin deep-diving behaviour. Think about this: this researcher is interested in how movement is invariant across scale and can explain behaviour as a complex phenomena. There’s already a unified theory of movement — it’s called fractal analysis of movement.
I am optimistic about the potential of merging scale-invariant disciplines: if physicists could accept Newton’s law of universal gravitational attraction, even when it couldn’t explain solar systems with more than 2 planets, why can we not accept that movement unifies us even if it cannot predict each time-step for each species taking whatever method of transport. It’s a narrow-minded perspective to say that we can’t have unified movement theory because some people take bicycles, while others prefer the Metro. Algorithms cooked up by silicon valley are already capable of differentiating this movement — doesn’t that mean these are already unified in the neural network’s internal representations of movement? Train a neural network to detect directionality of some moving object. Assuming you did the requisite pre-processing, chances are that algorithm will tell you the direction of any moving object. That’s unified movement theory. Not convinced? Take the first neural network and perform transfer learning for another object. The transferred network will outperform a network that didn’t ‘see’ the first objects movement/directionality. This is unified movement theory. There’s a team of researcher’s studying locomotion in ants who strapped sticks onto the legs of ants. They found their ants on stilts would walk past their intended destinations. Doesn’t this indicate that regardless of the interaction between ant and environment (the ecology), movement could be characterized using common conceptualizations: be they step-length, velocity, or the ant’s internal step count?
This paper came about as a discussion Miller had with various mobility/movement researchers; what’s clear is that people don’t have answers. It’s not as simple as ecologists neglecting scale or geographers neglecting behaviour: our silo-ed approach to science is undermining our ability to comprehend unifying phenomena. And I bet movement is that unifying theory. Can you think of anything that’s truly static?