Archive for the 'Balaton' Category

Tipping points

The concept of tipping points is powerful, but sometimes a bit muddled. Things that get described as tipping points often sound to me like mere dramatic events or nonlinear effects, simple thermodynamic irreversibilities, or exponential signals emerging unexpectedly from noise. These may play a role in tipping points, and lead to surprises, but I don’t think they capture the essence of the idea. You can see examples (good and bad) if you sift through the images describing tipping points on google.

I think of tipping points as a feedback phenomenon: positive feedback that amplifies a disturbance, such that change takes off, even if the disturbance is removed. The key outcome is a system that is stable or resistant to disturbances up to a point, beyond which surprising things may happen.

A simple example is sitting in a chair. The system has two stable equilibria: sitting upright, and lying flat on your back (tipped over). There’s also an unstable equilibrium – the precarious moment when you’re balanced on the back legs of the chair, and the force of gravity is neutral. As long as you lean just a little bit, gravity is a restoring force – it will pull you back to the desirable upright equilibrium if you pick up your feet. Lean a bit further, past the unstable tipping point, and gravity begins to pull you over backwards. Gravity gains leverage the further you lean – a positive feedback. Waving your arms and legs won’t help much; you’re going to be flat on your back.

A more generalized explanation is given  in catastrophe theory. The interesting twist is that a seemingly-stable system may acquire tipping points unexpectedly as its parameters drift into regimes that create new stable and unstable points, leading to surprises. Even without structural change to the system, its behavior mode can change unexpectedly as the state of the system moves from locally-stable territory to locally-unstable territory, which occurs due to shifting loop dominance from nonlinearities. (Think of the financial crisis and some kinds of aircraft accidents, for example.)

Anyone know some nice, simple tipping point models? I think I’ll have to mine my archives for some concrete examples…

Fortress USA

The Fortress World scenario came up in Bert de Vries’ presentation at the Balaton meeting today. It’s a dystopian global future in which the rich retreat into safe havens (a macro version of gated communities) while the rest of the world degenerates into some combination of feudal subsistence, resource extraction and chaos.

On dark days, looks increasingly to me like this is already playing out in the US with the disappearance of the middle class.

The drivers of rising inequity in the US seem fairly simple. With globalization, capital has become mobile while labor remains tied to geography. So, capital investment flees high wage countries (US) and jobs follow. Asset income goes up, because capital is leveraged by cheaper labor and has good bargaining power among hungry host countries. There’s downward pressure on rich world wages, because with less capital per capita employed, the marginal productivity of labor is lower.

It’s not all bad for the rich world working class, because cheaper goods (WalMart) offset wage losses to some degree. If asset and wage income were uniformly distributed, there might even be a net benefit.

However, asset income and wages aren’t uniformly distributed, so income disparity goes up. Pre-globalization, this wasn’t so noticeable, because there was an implicit deal, in which wage earners knew that, even if they didn’t own all the capital in their country, at least they’d be the beneficiaries of it in some sense through employment and trickle down. Free trade and mobile capital turns the deal into a divorce, which puts a sharp point on questions of property rights allocations that were never quite fair, and sows the seeds of future discontent among the losers.

So far, everyone appears to be committed to pursuing this thread to its logical conclusion. Probably most are unwitting participants; workers are as enthusiastic about offshoring of capital in their pension funds as are the captains of industry.

However, it seems to me that there are several corrosive effects. The asset-owning rich appear convinced that their windfall has arrived because they’re smart, that the misfortunes of the masses are due to laziness. Their incentive to invest in services like education for labor they don’t need is no longer palpable. Uneducated masses are easier to manipulate anyway. Meanwhile the masses are desperate (if misguided) to lower tax burdens in order to compete with offshore labor.

The ultimate effect seems likely to hollow out the human capital of the rich world, leaving only tycoons and serfs, with perhaps a few protected sectors of the economy (pilots for tycoons’ jets). But is that a plausible end-state for this game?

If I were an American tycoon endowed with a little enlightened self interest, I’d be worried about several ways things could go wrong:

  • Increasing income disparity and loss of human capital cause a loss of civility at home, requiring wealthy enclaves to become desperate armed camps.
  • Political turbulence abroad leads to loss of control of all that capital that went overseas.
  • The global economy reaches such a vast physical scale that no amount of personal wealth provides adequate insulation against its side effects.

These outcomes could be triggered or amplified by financial or ecological stress. Even if you don’t care about equity or social justice per se, these possibilities seem like a great reason to invest in human and social capital at home and abroad.

The Insidious Dynamics of Driving to School

When I passed by my old high school a few years ago, I was astonished to see that they’d paved over a nice grass field to make room for a vast parking lot, which must be for students. There’s really no excuse for driving to school in Palo Alto, CA – the weather is great, it’s flat, and no one lives more than a couple miles away.
Most of the responsibility falls to this nest of positive feedback loops:

I’ll start with a perception: parents worried about the safety of their kids start driving them to school (or, in Palo Alto, buy them a BMW so they can drive themselves). All that extra driving adds to traffic density, reinforcing the perceived danger on the roads. Over the long haul, all that traffic demands more lane space, so bike lanes and sidewalks get crowded out. And who wants to bike next to a bunch of hot, smelly tailpipes?

The more students drive, the less fit they get, which diminishes the fun of riding. They also become less tolerant of weather – in spite of Gore Tex, a lot of people react to a little water falling from the sky like the Wicked Witch of the West.

The result of all this is a kind of phase transition – at some point, conditions are right for all these positive loops to kick in, and everyone shifts from bike-dominated transport to driving.

This transition should not be irreversible, if one is patient. One can move the point at which the phase transition occurs, to encourage bicycling. I think there are two leverage points. First, a society that can afford cars for kids can afford to provide Dutch- or Danish-style traffic separation, breaking the safety loop and decreasing the attractiveness of driving by removing traffic lanes, which causes congestion until people go back to bikes. Second, make the cars pay for the infrastructure they use and the environmental and safety externalities they cause. Once people are back on bikes, they’ll get fitter and healthier, and the positive loops will help lock in a more sustainable mode.

Inspired by a comment in Bert de Vries’ talk this morning at the 30th Balaton Group meeting.

The GDP Song

In SD, we often talk about the pitfalls of managing systems with delays and feedback while paying attention to the wrong indicators. The classic example is navigating a car at high speed in the fog on an icy road by looking in the rearview mirror.

A related problem is managing your system to maximize the wrong goals, e.g. running the economy by a problematic metric like GDP. Here’s Alan AtKisson’s musical take on that:

Sharing Systems

I’m at the 30th Balaton Group meeting this week. A group of us just put our heads together to think about online approaches to teaching and sharing systems thinking and systems modeling. The basic question was, if you needed thousands of systems thinkers in a hurry, how could you scale up systems education quickly?

My list of interesting things people might want to do online:

  • Model building
    • Group model building (in the spirit of SUNY Albany work)
    • Collaborative modeling (e.g., a distributed team working on federated modules of a model, but not necessarily involving the client and group conceptualization processes)
    • Collaborative causal loop diagramming
    • Model code sharing and reuse
  • Model consumption
    • Online games (playing through a simulation in real time) – possibly multiplayer
    • Online simulations (interactive experimentation with a model) – possibly with a social aspect as at Climate Colab

Much can already be done through online model services like Forio and other means. However, I think there’s a lot more to be done. In particular, we’re weak on providing shared model transparency and quality control for any but the simplest models.

Some interesting systems & sustainability online learning links that came up in the conversation:

http://www.unep.org/ieacp/iea/

http://www.google.com/tools/dlpage/res/talkvideo/hangouts/

http://ecotippingpoints.org/

http://www.cotelco.net/

http://www.bfi.org/

http://www.seedsystems.net/

http://www.clexchange.org/

http://www.watersfoundation.org/

http://climateinteractive.org

http://www.systemdynamics.org/MITCollectionRoadMaps.htm

http://www.systemswiki.org/index.php?title=Main_Page

http://insightmaker.com/

http://forio.com/

http://dt.asu.edu/

Tim Jackson on the horns of the growth dilemma

I just ran across a nice talk by Tim Jackson, author of Prosperity Without Growth, on BigIdeas. It’s hard to summarize such a wide-ranging talk, but I’d call it a synthesis of the physical (planetary boundaries and exponential growth) and the behavioral (what is the economy for, how does it influence our choices, and how can we change it?). The horns of the dilemma are that growth can’t go on forever, yet we don’t know how to run an economy that doesn’t grow. (This of course begs the question, “growth of what?” – where the what is a mix of material and non-material things – a distinction that lies at the heart of many communication failures around the Limits to Growth debate.)

There’s an article covering the talk at ABC.au, but it’s really worth a listen at http://mpegmedia.abc.net.au/rn/podcast/2010/07/bia_20100704_1705.mp3

Interactive diagrams – obesity dynamics

Food-nutrition-health-exercise-energy interactions are an amazing nest of positive feedbacks, with many win-win opportunities, but more on that another time.

Instead, I’m hoisting an interesting influence diagram about obesity from the comments. At first glance, it’s just another plate of spaghetti.

ForesightObesity

But when you follow the link (do it now), there’s an interesting innovation: the diagram is interactive. You can zoom, scroll, and highlight particular sectors and dynamics. There’s some narrative here and here.

It took me a while to decide whether I’d call this a causal loop diagram or not. I think the primary distinction between a CLD and other kinds of mindmaps or process diagrams is the use of variables. On a CLD, each label represents a quantity that can vary, with a definite direction – TV Watching, Stress, Use of Medicines. Items on other kinds of diagrams might represent events or fuzzier constellations of concepts. This diagram doesn’t have link polarities (too bad) or loop polarities (which would be pretty incomprehensible anyway), but many other CLDs also avoid such labels for simplicity.

I think there’s a lot of potential for further exploration of this idea. There’s a lot you could do to relate structure to behavior, or at least to explain the rationale for structure (both shortcomings of the diagram). Each link, for example, could have its tale revealed when clicked, and key loops could be animated individually, with stories told. Drill-down could be extended to provide links between top-level subsystem relationships and more microscopic views.

I think huge diagrams like the one above are always going to be overwhelming to a layperson. Also, it’s hard to make even a small CLD good, so making a big one really accurate is tough. Therefore, I’d rather see advanced CLD presentations used to improve the communication of simpler stories, with a few loops. However, big or small, there might be many common technological benefits from dedicated diagramming software.

Dry Lake Mead

The systems story on Lake Mead deepens (unlike the lake itself). I heard about some more interesting dynamics in a side conversation at the Balaton Group meeting in Iceland.

First, it’s not just Mead that’s impacted; upstream Lake Powell is also low. One consequence of this is that hydro generation is down, because the head is lower. Since both lakes are half full, it might make sense to drain Powell into Mead. That would raise the head at Mead, making up for the loss of generation at Powell. Water losses would also decrease. One possible obstacle to this strategy is that stakeholders in Powell fear that it could never be refilled, because endangered species would reinhabit the empty canyons.

Second, as the lakes get lower, bad things happen. Evidently the deep waters are stratified, and there are plumes of nasty saline gunk near the bottom. If lake levels continue to drop, there’s a possibility of serious water quality problems to go with the quantity issues.

One thing that’s striking about the media coverage of data and projections by agencies is that there’s little discussion of the nature or magnitude of variability. The implicit assumption behind current behavior is that droughts are cyclical or just noise. The hope seems to be that, since we’re in a low period for basin rainfall, the magic of reversion to the mean will soon bring forth the waters again. I don’t think there’s any good reason to act as if that will really happen, especially if climate makes the distribution nonstationary. Modelers seem to think that the Southwest will move to a drought regime as the earth warms, but what if they’re wrong, and the hydrologic cycle accelerates? Glen Canyon Dam was nearly lost in 1983, so a healthy increase in rainfall wouldn’t necessarily be a blessing either.

LakeMeadProjection2010Current Bureau of Reclamation projections for Lake Mead elevation. Documentation is pretty opaque, but it looks like the projections are based on quantiles of historic inflows, i.e. they neglect autocorrelation or changes in the distribution of supply.

Edward Abbey must be smiling at least a little at this mess.

Why is the arctic brown?

I’m blogging from a 757, somewhere over the North pole, returning from a sustainability meeting in Iceland. The world below is a wilderness of sea ice and clouds. I’d expect brilliant white, but there’s actually a brown haze over the landscape. It’s stratified, much like the odd sight of half-white, half-brown clouds one occasionally sees when flying into a polluted city. Where does it come from? Chinese coal fumes? Russian fires? American SUV tailpipes? Icelandic airplane exhaust?

You are what you eat

I’m on my way home from the 29th meeting of the Balaton Group, held in Iceland. Iceland seems to be rising gracefully from it’s financial crisis, with introspection into the values that led to it and a renewed interest in sustainability. Author Andri Magnason visited us at dinner, and talked a bit about Iceland and his wonderful book, Dreamland – A Self-help Manual for a Frightened Nation. I picked up a copy in the airport (can’t get it at amazon yet) and got halfway through on the plane – I highly recommend it.

Another Magnason project is a book of Bonus Poetry, named for and spoofing the Icelandic Walmart.

You are what you eat
My grandfather was 70% water
He was 70% the stream
that trickled past his farm
he was the 30%
the sheep that grazed on his mountain
he was the fish swimming in his lake
he was the cow eating
in his field
he was the stream, he was the grass,
the mountain and the lake
I am not 70% water
perhaps 15% mineral water
the rest is beer and coca cola
I am italian pasta, swiss cheese
danish pork and chinese rice
american ketchup
runs through my veins
you are what you eat
I am a miniature of the world
no
I am a miniature of Bonus