Tag Archives: system dynamics

bouncing between layers of limits

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This Asia Times article is dramatically titled The Renewable Energy Transition is Failing. This seems overly dramatic to me, but the point to me is that if we overcome one limit, in this case the atmospheric sink for carbon dioxide, we will encounter other limits. In this article, the author focuses on availability of raw materials like metals. If we overcome that limit, we may have an issue of sinks for these metals and other waste products produced. So we bounce back and forth between sources and sinks being the limiting factor.

Limits to Growth “data check”

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In 2021, Gaya Herrington published a comparison of the World3 model’s (from Limits to Growth) predictions to date. She concluded that we are on a path either to collapse or to a sort of steady state where technology will blunt the worst consequences of pollution but further growth will not be possible.

The scenario that depicts the smallest declines, SW, is also the one that aligned least closely with empirical data. Furthermore, one of the best fit scenarios, BAU2, shows a collapse pattern. The other best fit scenario however, CT, shows only a moderate decline. Both scenarios show a slowdown in industrial and agricultural output. My research results at this point thus indicate that we can expect a halt in economic growth within the next two decades, whether we consider that a good thing or not. (Indeed, as the informed reader knows, economists and organizations like the IMF have been pointing out recently that we’re seeing a “synchronized slowdown in global growth“.) The strongest conclusion that can be drawn from my research therefore, is that humanity is on a path to having limits to growth imposed on itself rather than consciously choosing its own. However, my research results also leave open whether the subsequent declines in industrial and agricultural output will lead to sharp declines in population and welfare levels.

Club of Rome

what’s new with fish?

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Our World in Data has a sprawling and data-dense article on everything to do with fish, fisheries, and aquaculture. It’s well worth digging into if you have five or six hours, but I could stare at the pictures alone for an hour if I actually had that kind of time.

Here were a few highlights for me:

  • Some species are really in trouble, sharks in particular, but on balance the overfishing situation has improved significantly over the past decade or two. When looked at by weight, about 80% of fishing is sustainable, and when looked at by individual fisheries (which vary in size), about 2/3 is sustainable. Tuna, in particular, is pretty well managed these days.
  • They dug into a particular paper which the media summarized as “the oceans will be empty by 2048”, explain why that didn’t even make sense as a summary of what the authors intended at the time, and then explain why this conclusion no longer holds with better data on fish stocks as opposed to just fish catch.
  • Fish catch has largely stabilized over the past few decades while aquaculture has boomed. Aquaculture has become much more efficient – some wild fish are still used to feed animals, but this has declined and animal feed has become more plant-based. Also, environmentally-motivated not-quite-total vegetarians should feel pretty good about eating farmed mussels, clams, and oysters.
  • The most damaging forms of fishing, such as bottom trawling, have declined, although they are still in wide use in developing countries.

Fish are the classic example often used to teach stocks and flows – they illustrate how time lags and feedback loops can lead to counterintuitive results if you are just eyeballing the trend in one particular flow, rather than gaining an understanding of the underlying system structure and how that explains its behavior. This is one reason why the simplistic science communication we have had during the Covid crisis has been ineffective, in my view. Unfortunately, data (sometimes called “facts”, but that assumes we can accurately measure the state of the world, which we never can with 100% uncertainty) doesn’t just transform itself into good policy and good decisions. The media seems to create this expectation in people, and then I think they are disappointed and confused when the story seems to change and evolve from day to day. At some point, they conclude that a made-up opinion is as likely to be accurate as the garbled message coming from the scientists/or and policymakers. And then of course, some cynical people exploit this disillusionment for their own cynical purposes.

the new IPCC physical science basis for we’re fucked

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I suppose I have to say something about the new IPCC science report that came out this week (I’m writing on Thursday, August 12). It’s easy to find summaries of it from actual journalists in the media, for example this one from the AP.

I’ve only read the summary for policy makers. I have the best intentions to read the full report, but then I had the best intentions to read the last 16 IPCC reports, not to mention the proliferating ecosystem and biodiversity reports. Anyway, if you don’t mind a collection of random observations, here are a handful of things that caught my eye:

  • The graphics are kind of nice. If you are trying to communicate science-y or tech-y things to general audiences, they are worth a glance.
  • If we stopped emitting carbon emissions today, the earth would continue to warm for decades, if not centuries or millennia. This means the effects we are feeling right now were caused by emissions decades ago. Emissions have not only continued for decades, but they have accelerated. Things are going to continue to get worse, and probably not linearly but exponentially. If we drastically cut emissions today, the results would be detectable in about 20 years or so. The Earth is a dynamic system with lags and feedback loops.
  • Warming of about 1.5 degrees C (I don’t know how to make a degree symbol in WordPress) would be considered a great outcome. The Earth has already warmed by about 1.0 degrees as of right now (2019 actually).
  • Human activity is the overwhelming cause of warming. Come on, don’t be stupid. Natural factors exist but they are small compared to the human activity.
  • One thing that did surprise me is that scientists are pretty sure that human-caused air pollution has had a significant retarding (using this word in the scientific/musical sense of slowing something down) effect on global warming. But again, more than overwhelmed by the sheer magnitude of burning, burning, burning with reckless abandon for centuries now.
  • Scientists are very sure human activity is driving massive ice loss in the Arctic. They are only kind of medium sure it is the main driver in the Antarctic.
  • So what is a good place to live? Well, central and eastern North America are some of the only regions are Earth that are not unequivocally hotter already, meaning scientists disagree on whether they are or not. They are more at risk of flooding though, along with most of Asia. Drought is biting harder in western North America, parts of Europe, Central Asia, Africa, and southern Australia than elsewhere.
  • There are five scenarios in this report. They are called SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.

Compared to 1850–1900, global surface temperature averaged over 2081–2100 is very likely to be higher by 1.0°C to 1.8°C under the very low GHG emissions scenario considered (SSP1-1.9), by 2.1°C to 3.5°C in the intermediate scenario (SSP2-4.5) and by 3.3°C to 5.7°C under the very high GHG emissions scenario (SSP5-8.5)24. The last time global surface temperature was sustained at or above 2.5°C higher than 1850–1900 was over 3 million years ago (medium confidence).

IPCC
  • Coastal property may not be a good investment.
  • Scientists are divided on the tipping point theories involving the global meridional circulation. They agree it is going to weaken though. The tipping point collapse scenarios “can’t be ruled out and are part of risk assessment”. Ha – risk assessment language might say something like “unknown but non-zero probability, existential threat”.
  • The report provides a remaining carbon budget that could be used for policy making, depending on the end point the world would like to target.

modern monetary models

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These two posts have a long explanation of monetary theory in general, and modern monetary theory in particular. It’s a little over my head, although I like challenging myself to try to understand it. It is a very abstract system to try to understand. I think that if you can understand monetary policy, you might have a chance to understand what money actually is. And if enough people understand it, they might stop believing in it and the world might end.

Basically, as I understand it, the government prints money (i.e., borrows money from itself) and spends it, usually more than it takes back in taxes, and this creates a surplus in the private sector. It can control the money supply by changing the amount it borrows and spends, or by changing the tax rate. I think what people find scary about “modern monetary theory” is that it suggests money doesn’t have to be taken seriously and any needed amount can just be printed any time. This is why politicians generally have not been given the keys to the printing press.

I have a metaphor in my mind of the real economy as a machine with pistons and gears turning. The fuel for the machine is maybe human effort and ideas (and some actual fuel). But the gears will grind without grease, so you have to lube it up. Not enough and the system will shut down violently. Adding extra will not make the machine turn faster, but it will not do any serious harm other than maybe a gunky mess someone has to clean up. Better to use a little too much lube than not enough. The lube for the economic machine is money.

There were a few other interesting things in the articles that I didn’t know or hadn’t thought about recently. It refers to the late Wynne Godley at Cambridge University as the “father of stock-flow consistent modeling”. I think a few people in a few different disciplines might claim that mantle, but that is the neat thing about system theory, it’s interdisciplinary. There is a certain irony if anyone is into it and doesn’t realize it is interdisciplinary.

There is a free(?) system dynamics system called Minsky, something like Stella but tailored specifically to finance and economics. Matlab also has a sort of stock-flow simulation module call Simulink that I hadn’t heard of. I am still waiting for that system dynamics R package.

The Minsky model also made me think of the late Jay Forrester, who advocated for a long time for stock-flow modeling in economics.

Traditional mainstream academic economics, by trying to be a science, has failed to answer major questions about real- life economic behavior. Economics should become a systems profession, such as management, engineering, and medicine. By closely observing the structures and policies in business and government, simulation models can be constructed to answer questions about business cycles, causes of major depressions, inflation, monetary policy, and the validity of descriptive economic theories. A system dynamics model, as a general theory of economic behavior, now endogenously generates business cycles, Kuznets cycles, the economic long wave, and growth. A model is a theory of the behavior that it generates. The economic model provides the theory, thus far missing from economics, for the Great Depression of the 1930s and how such episodes can recur 50–70 years apart. Simpler system dynamics models can become the vehicle for a relevant and exciting pre-college economics education.

Jay Forrester, quoted in a blog called Viewpoints that Matter (including the blogger’s viewpoint, presumably)

Imagine if the average high school graduate really had an intuitive understanding of how important systems like the economy are structured and why they function the way they do as a result. The world might be a different place.

I’ve been working on one more metaphor for awhile. Maybe the real economy is like a tightrope, and the financial economy is like a safety net stretched above a concrete floor. If we use too much food, water, energy, saturate the atmosphere and ocean with our waste, etc. we will fall off the rope. Hitting the concrete floor would be a failure of the real economy like starvation or freezing to death. The safety net would be a spike in prices for food or energy that slows down the economy short of (most people, right away) actually dying of exposure. The fall would still be very painful and you might break bones or even your neck if you fall just the wrong way. What about something like nuclear proliferation or all the ice in Antarctica suddenly melting? I don’t know, maybe dry rot in the old net that we are failing to do anything about. No price signal is going to save us from those.

youcubed

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This site is all about fresh ideas for teaching high school math. Apparently a lot of people agree that the traditional U.S. approach of algebra 1, geometry, algebra 2, and calculus is not working. A lot of people seem to think data science is the answer. It sounds okay to me to start with interesting data and then work backward to math theory and systems concepts. I do use geometry pretty much daily in my work, at least concepts like areas and volumes. Are those geometry? I think I originally learned them in high school chemistry class. I almost never use calculus symbols, but I use calculus concepts like rate of change and accumulating and depleting stocks daily. I solve those numerically rather than symbolically. So maybe this is what we should be teaching in high school, then working our way to the symbols for people who really need it, for example the ones who are going to be programming the computers that the rest of us use to solve various problems. A little statistics and probability is a good idea, but even that can be more experiment based and less symbolic at first.

R and differential equations

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Here’s a new R package for solving differential equations. Sounds like something that might be of interest to only a few ivory tower mathematicians, right? But solving differential equations numerically is the critical core of almost any dynamic simulation model, whether it is simulating water, energy, money, ecology, social systems, or the intertwinings of all of these. So if we are going to understand our systems well enough to solve their problems, we have to have some people around who understand these things on a practical level.

reservoirs, resilience and system dynamics

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This article in Water Resources Research uses a system dynamics simulation to examine the resilience of a reservoir. Some of these concepts may be adaptable to other types of water resources systems or systems in general.

Comparison of static and dynamic resilience for a multipurpose reservoir operation

Reliability, resilience and vulnerability are the traditional risk measures used to assess the performance of a reservoir system. Among these measures, resilience is used to assess the ability of a reservoir system to recover from a failure event. However, the time independent static resilience does not consider the system characteristics, interaction of various individual components and does not provide much insight into reservoir performance from the beginning of the failure event until the full performance recovery. Knowledge of dynamic reservoir behavior under the disturbance offers opportunities for proactive and/or reactive adaptive response that can be selected to maximize reservoir resilience. A novel measure is required to provide insight into the dynamics of reservoir performance based on the reservoir system characteristics and its adaptive capacity. The reservoir system characteristics include, among others, reservoir storage curve, reservoir inflow, reservoir outflow capacity and reservoir operating rules. The reservoir adaptive capacity can be expressed using various impacts of reservoir performance under the disturbance (like reservoir release for meeting a particular demand, socio-economic consequences of reservoir performance, or resulting environmental state of the river upstream and downstream from the reservoir). Another way of expressing reservoir adaptive capacity to a disturbing event may include aggregated measures like reservoir robustness, redundancy, resourcefulness and rapidity. A novel measure that combines reservoir performance and its adaptive capacity is proposed in this paper and named ‘dynamic resilience’. The paper also proposes a generic simulation methodology for quantifying reservoir resilience as a function of time. The proposed resilience measure is applied to a single multi-purpose reservoir operation and tested for a set of failure scenarios. The dynamic behavior of reservoir resilience is captured using the system dynamics simulation approach, a feedback-based object-oriented method, very effective for modelling complex systems. The results of dynamic resilience are compared with the traditional performance measures in order to identify advantages of the proposed measure. The results confirm that the dynamic resilience is a powerful tool for selecting proactive and reactive adaptive response of a multipurpose reservoir to a disturbing event that cannot be achieved using traditional measures. The generic quantification approach proposed in the paper allows for easy use of dynamic resilience for planning and operations of various civil infrastructure systems.

ecosystem disservices

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This paper proposes the idea of “ecosystem disservices” to address criticisms scientists have made of the ecosystem services concept.

Limitations of the Ecosystem Services versus Disservices Dichotomy

Ongoing debate over the ecosystem services (ES) concept highlights a range of contrasting views and misconceptions. Schröter et al. (2014) summarise seven recurring arguments against the ES concept, which broadly relate to ethical concerns, translation across the science—policy interface, and how the concept’s normative aims and optimistic assumptions affect ES as a scientific approach. In particular, recent criticism has focused on how the concept is unable to address ecological complexity due to the limitations of the economic stock–flow model that ES is based on (Norgaard 2010). Acknowledging ecosystem disservices (EDS) (i.e. outcomes of ecosystem functions that negatively affect human communities) has been suggested as a way to account for this ecological complexity (McCauley 2006; Lyytimäki 2015). The impact of EDS on communities (i.e. the ‘cost’ of the action) can be measured financially, or through changes in individual or social well-being. McCauley (2006) and Lyytimäki (2015) list EDS examples like pest damage to crops, or trees removing water from watersheds.

credit, interest, and a steady state economy

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This article in Ecological Economics says that a positive interest rate and a no-growth economy could coincide.

Does credit create a ‘growth imperative’? A quasi-stationary economy with interest-bearing debt

This paper addresses the question of whether a capitalist economy can ever sustain a ‘stationary’ (or non-growing) state, or whether, as often claimed, capitalism has an inherent ‘growth imperative’ arising from the charging of interest on debt. We outline the development of a dedicated system dynamics macro-economic model for describing Financial Assets and Liabilities in a Stock-Flow consistent Framework (FALSTAFF) and use this model to explore the potential for stationary state outcomes in an economy with balanced trade, credit creation by banks, and private equity. Contrary to claims in the literature, we find that neither credit creation nor the charging of interest on debt creates a ‘growth imperative’ in and of themselves. This finding remains true even when capital adequacy and liquidity requirements are imposed on banks. We test the robustness of our results in the face of random variations and one-off shocks. We show further that it is possible to move from a growth path towards a stationary state without either crashing the economy or dismantling the system. Nonetheless, there remain several good reasons to support the reform of the monetary system. Our model also supports critiques of austerity and underlines the value of countercyclical spending by government.