Category: Balaton

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. (Update: the interactive link seems to be down, but the diagram is still here: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/295153/07-1177-obesity-system-atlas.pdf)

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

Green labeling is just a waypoint

Alan Atkisson wonders, Can a Glass of Orange Juice in Sweden be “Climate Smart”? He concludes, Maybe consumer items like this could be labeled, “Relatively less climate-stupid.” I agree.

For green labeling to actually work, there must be a “green information” system parallel to the money economy, and people must pay attention to it. That’s a booming business right now.

US_$20_Series_2006_Obverse

Optimistically assuming that all end users have the insight and altruism needed to make the correct environment/money tradeoff, that creates tremendous evolutionary pressure on the production system to evade the intent of the labeling by using cheaper not-so-green alternatives in hidden upstream locations. To paraphrase Groucho, greenness is the key to business success – if you can fake it, you’ve got it made. The evasion need not be so cynical; it simply requires incomplete information, for example sourcing products from places where measurement systems are incomplete. I really rather doubt that we’ll ever have life cycle analysis for every product performed with the same stringency now enforced by money auditing systems.

The optimistic assumptions above are probably misplaced. Altruism is great, but I hate to rely on it, as it’s not clear to me that it’s an ESS. But insight is probably the real constraint. Life cycle analysis is good stuff, but even if it were practical to pass many attributes through the supply chain, with firm-level attribution, the result is complex information about tradeoffs that’s better suited for engineers than for consumers. Add to that the challenges people already face, like making good decisions about saving for retirement and educating children, and I think it’s hard to do much more than muddle minds.

Just as marketers associate cars with love, green labels foster the paradoxical conclusion that some consumption benefits the environment. That may be true for a few goods, but for the most part, it’s not. We should be using green information to examine our broad patterns of consumption, more than to choose what to put in the shopping cart. That might mean non-consumptive tradeoffs, like having more leisure time and less stuff.

Green labeling is great in many cases today, where prices and other incentives are blatantly misaligned with public goods, but ultimately fixing the incentives will get us a lot farther than labeling. That means pricing resources we value upstream, so that value percolates through supply chains as a price signal. In my ideal world, the price tag itself would be a green label.

For green labeling to actually work, there must be a “green information” system parallel to the money economy, and people must pay attention to it. Optimistically assuming that all end users have the insight and altruism needed to make the correct green-money tradeoff, that creates tremendous evolutionary pressure on the production system to evade the intent of the labeling by using cheaper not-so-green alternatives in hidden upstream locations. The evasive response need not be cynical, it simply requires incomplete information, i.e. sourcing products where measurement systems are incomplete. I really rather doubt that we’ll ever have life cycle analysis for every product performed with the same stringency now enforced by money auditing systems. Green labeling is great in many cases today, where prices and other incentives are blatantly misaligned with social goals, but ultimately fixing the incentives will get us a lot farther than labeling.

Sustainable WalMart?

Today at Balaton I heard from Hunter Lovins about WalMart’s sustainability efforts. It’s tempting to question their motives and the likely outcome, but there’s enough going on that EDF is creating a presence in Bentonville. As of today, sustainability features prominently on WalMart’s home page. It’s hard to get excited about their Love, Earth jewelry line, but some of their other activities could have a significant impact. They have some very interesting initiatives, like product labeling for green content based on life cycle analysis (learning from Patagonia).

A few quick reflections:

WalMart’s traditional focus has been cost-saving efficiencies. That can take place through two paths: genuine innovation (good) and pushing costs off on society as externalities (pollution, social consequences of labor policy, etc. – bad). If WalMart’s sustainability efforts represent calling off the latter, that’s a good thing. However, as long as institutions and consumer preferences don’t support verification of such efforts in general, it makes WalMart susceptible to competitors with fewer scruples.

Historically, WalMart’s efforts to outrun its competitors and squeeze value out of its supply chain reduce diversity and enhance its market power. That means we have fewer experiments (and resources) with which to explore ideas – a classic case of optimization of a complex system for a single purpose that inadvertently makes it fragile in changing conditions.

It’s easy to see how dematerializing the supply chain is helpful. As material constraints increasingly become important, the same efficiencies that currently are frequently consumed by rebound effects could become a vehicle for the delivery of greater good per scarce megawatt, TonC, or bushel. However, there’s a second key component of greening the world, which is simply consuming less. It’s easy to see how a cutting edge company can make money selling greener products. It’s not so easy for me to see how a company is going to make money from people trading fewer goods and services for more leisure time or other non-market activity.

This suggests three priorities:

  • Encourage propagation of this idea, so that brown suppliers dumped by WalMart aren’t simply scooped up by Kmart.
  • Help chains to think more deeply about supply chain diversity and how procurement and social practices contribute to resilience.
  • Keep working on the underlying drivers of consumption growth.

Climate War Game – Recap

I presented a brief review of my involvement in the CNAS wargame at Balaton today. My last few slides focus on some observations from the game. They led to a very interesting conversation about targets for future models and games. We have been planning to continue seeking ways to insert models into negotiations, with the goal of connecting individual parties’ positions to aggregate global outcomes. However, in the conversation we identified a much more ambitious goal: reframing the whole negotiation process.

The fundamental problem, in the war game and the real world, is that nations are stuck in a lose-lose paradigm: who will bear the burden of costly mitigation? No one is willing to forego growth, as long as “growth is good” is an unqualified mantra. What negotiations need is a combination of realization that growth founded on externalizing costs of pollution and depletion isn’t really good, and that fixing the institutional and behavioral factors that would unleash large low- or negative-cost emissions reductions and cobenefits would be a win-win. That, combined with a serious and equitable accounting of climate impacts within the scope of present activities and coupling of adaptation and development opportunities to mitigation could tilt the landscape in favor of a meaningful agreement.

Ethics, Equity & Models

I’m at the 2008 Balaton Group meeting, where a unique confluence of modeling talent, philosophy, history, activist know-how, compassion and thirst for sustainability makes it hard to go 5 minutes without having a Big Idea.

Our premeeting tackled Ethics, Values, and the Next Generation of Energy and Climate Modeling. I presented a primer on discounting and welfare in integrated assessment modeling, based on a document I wrote for last year’s meeting, translating some of the issues raised by the Stern Review and critiques into plainer language. Along the way, I kept a running list of assumptions in models and modeling processes that have ethical/equity implications.

There are three broad insights:

  1. Technical choices in models have ethical implications. For example, choices about the representation of technology and resource constraints determine whether a model explores a parameter space where “growing to help the poor” is a good idea or not.
  2. Modelers’ prescriptive and descriptive uses of discounting and other explicit choices with ethical implications are often not clearly distinguished.
  3. Decision makers have no clue how the items above influence model outcomes, and do not in any case operate at that level of description.

My list of ethical issues is long and somewhat overlapping. Perhaps in part that is due to the fact that I compiled it with no clear definition of ‘ethics’ in mind. However, I think it’s also due to the fact that there are inevitably large gray areas in practice, accentuated by the fact that the issue doesn’t receive much formal attention. Here goes: Continue reading “Ethics, Equity & Models”