The Sciences

Are Cities Just Very Large Organisms?

Cosmic VarianceBy Sean CarrollApr 29, 2009 3:13 PM


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A couple of years ago I got to hear Geoffrey West, one of Time magazine's 100 Most Influential People, give a talk on his research at a meeting of the American Association for the Advancement of Science. It was a fantastic talk, and I immediately had the idea to ask him to come to Caltech at some point and give it as a colloquium. So tomorrow he'll be here, and anyone in the neighborhood interested in a semi-technical account of complex systems from physics to biology is welcome to stop by. He might be angling for the record for the longest talk title ever:

The Complexity, Simplicity, and Unity of Living Systems from Cells to Cities: A Physicist's Search for Quantitative, Unified Theories of Biological and Social Structure and Organization Although Life is very likely the most complex phenomenon in the Universe, many of it's most fundamental and complex phenomena scale with size in a surprisingly simple fashion. For example, metabolic rate scales approximately as the 3/4-power of mass over 27 orders of magnitude from complex molecules up to the largest multicellular organisms. Similarly, time-scales (such as lifespans and growth-rates) and sizes (such as genome lengths, RNA densities, and tree heights) scale as power laws with exponents which are typically simple multiples of 1/4. The universality and simplicity of these relationships, together with emergent "universal" invariants, suggest that fundamental constraints underly much of the coarse-grained generic structure and organisation of living systems. It will be shown how these 1/4 power scaling laws follow from underlying principles embedded in the dynamical and geometrical structure of space-filling, fractal-like, hierarchical branching networks, presumed optimised by natural selection. These ideas lead to a general quantitative, predictive theory that potentially captures the essential features of many diverse biological systems. Examples will include vascular systems, growth, cancer, aging and mortality, sleep, cell size, genome lengths, and DNA nucleotide substitution rates. These ideas will be extended to social organisations: to what extent are cities or corporations an extension of biology? Are they "just" very large organisms? Analogous scaling laws reflecting underlying social network structure point to general principles of organization common to all cities, but, counter to biological systems, the pace of social life systematically increases with size. This has dramatic implications for growth, development and particularly for sustainability: innovation and wealth creation that fuel social systems, if left unchecked, potentially sow the seeds for their inevitable collapse.

We've talked before about the difficulty in defining "life," although one safe criterion is that a living organism is going to be pretty complex. What about the other way -- when you have an undeniably complex system like a city or a university or a galaxy, at what point does it become useful to think of it as a "living organism"? Those are hard questions, but one angle is to investigate the similarities that complex systems demonstrate as they are manifested at different sizes. That's the idea of "scaling laws" -- measuring a feature common to a set of complicated systems (number of parts, speed of motion, etc.) and see how they change as a function of scale. You might have imagined that complexity comes in a variety of completely different forms, and there would be no simple relationship that included viruses, house cats, and sprawling urban centers. But the data reveal a remarkable degree of regularity -- many complex systems share certain basic features, just scaled up or down in ways appropriate to their size. Here is one startling example: every living being on Earth gets about a billion heartbeats worth of lifespan. Larger organisms live longer, but their hearts (or other analogous rhythmic processes) beat more slowly. Use those heartbeats wisely! The next challenge, of course, is to understand why. A few stabs have been taken in that direction using ideas about hierarchical networks of smaller systems -- about which I shouldn't say much, at least until I've heard the talk. Those of you who can't make it to LA on short notice can enjoy this video, or check out Blake Stacey's live-blog of a previous talk.

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