One of my top resources on the environment is the book Limits to Growth. Reading it was revelatory. They approached the environment the way I thought made sense, then created a model, researched the numbers, plugged them in, and got answers.
What made sense was what they call a systemic approach—not to look at one of all the interacting parts, but to look at the whole system, including how the parts interacted. For example, I sensed that just improving technology didn’t feel like it would solve everything. The Green Revolution, for example, led to more food, but used fossil fuels to do so and increased the population. Just saying it saved lives missed that it may have delayed an inevitable outcome of people starving, now affecting more people.
- Birth rate
- Death rate
- Renewable resources
- Non-renewable resources
- Food per capita
- Services per capita
- Industrial output per capita
which they quantified and modeled relations between.
Since the data were uncertain and future projections depended on unknowns, they assumed many numbers. They projected possible outcomes for different models based on different assumptions. One model assumed business as usual, another assumed more non-renewable resources, another assumed we were able to cap our population, and so on.
Some models resulted in disaster, others in long-term stability. Their goal was to show systemic patterns more than specific outcomes.
The media, people who disagreed, and organizations who disagreed tended to look at the worst results, call them predictions, and say the book was wrong. I found these misrepresentations and misunderstandings based on preconceived notions unconvincing.
For years I wanted to communicate meaningfully about the book. Those I knew who cared about the environment didn’t seem to understand the mathematical modeling. Those who understood the mathematical modeling didn’t seem to care about the environment. Plus the book was long and challenging so getting people to read it was hard.
At last, new resources
Hacker News posted about the book a couple weeks ago. I responded. My response generated discussion, which contained a few links to research done since. Here is my response:
I remember the first time reading this book, or rather the 30 year update — https://www.amazon.com/Limits-Growth-Donella-H-Meadows/dp/19… — thinking, “this is the approach to take to understand how the economy, ecology, pollution, and so on interact.”
Everything else was just looking at elements. Technology is important, for example, but exists within a system. They looked at the system. They had to simplify and assume a lot, which the media didn’t understand (probably benign ignorance) and critics blew out of proportion (probably maliciously), but I found their approach the most meaningful.
Sadly, I know many people who care about the environment but don’t understand the (relatively simple) math in their approach, and many people who understand the math but don’t care about the environment, but almost no one who cares and understands. So in about a decade since reading it, I haven’t found anyone I can talk to about it meaningfully.
A great companion by one of the authors is Thinking in Systems by Donella Meadows — https://www.amazon.com/Thinking-Systems-Donella-H-Meadows/dp….
Both changed my views more than almost any other books.
To somebody who responded, “Much of their predictions haven’t stood the test of time,” (click to read that person’s full response), I wrote
You’ve mischaracterized their work.
They didn’t predict what you said they did. They showed a range of possible outcomes based on assumptions, among many. You seem to have picked one outcome as their only one and called it their prediction.
They created a model based on a systems approach whose output depended on assumptions on physical properties of the planet and future human choices. Given the large uncertainties, they ran the model under many sets of assumptions and presented the outcomes.
The point of the book is to illustrate and promote a systems perspective, not just a linear, event-based approach, which you seem to prefer.
Amid the discussion were links to two resources I found valuable. They’re from 2014, but new to me.
First, Limits to Growthâ€“At our doorstep, but notÂ recognized, from Gail Tverberg‘s Our Finite World blog. The post describes how recent trends suggest that our global system is nearing points of collapse that Limits to Growth projected in several of its models. Tverberg concluded
Wrong thinking and wishful thinking seems to abound, when it comes to overlooking near term limits to growth. Part of this may be intentional, but part of this lies with the inherent difficulty of understanding such a complex problem.
There is a tendency to believe that newer analyses must be better. That is not necessarily the case. When it comes to determining when limits to growthÂ will be reached, analyses need to be focused on the details that seemed to cause collapse in the 1972 studyâ€“slow economic growth caused by the many conflicting needs for investment capital. The question is: when do we reach the point that oil supply is growing too slowly to produce the level of economic growth needed to keep our current debt system from crashing?
It seems to me that we are already near such a point of collapse. Most people have not realized how vulnerable our economic system is to crashing in a time of low oil supply growth.
Second, Is Global Collapse Imminent?, by Graham Turner at the University of Melbourne’s Melbourne Sustainable Society Institute. Turner looks at numbers updated more than 40 years after Limits to Growth and finds the fit to the book’s “business as usual” projection accurate enough to consider seriously. While the fit on any of the curves below aren’t great, given that they are over a range of disparate physical properties, the trends seem accurate enough to take seriously (amid many caveats).
Read the paper and Limits to Growth to understand the plots in more detail.
The big takeaway, if you agree the fit is worth taking seriously, is the trends around 2020-30. All three parts of the economy plummet, then the death rate increases and the population drops, yet all the signs look good just before, which is now.Â Limits to Growth projected this possibility decades ago, yet nearly everyone ignored it. In the recent paper’s words
Based simply on the comparison of observed data and the Limits to Growth scenarios presented above, and given the significantly better alignment with the Business As Usual scenario than the other two scenarios, it would appear that the global economy and population is on the cusp of collapse. This contrasts with other forecasts for the global future, which indicate a longer or indeterminate period before global collapse.
When you ignore relationships, you can imagine fixing each element as problems arise, but systems effects make solving problems move around, not disappear, when you act on each element alone. Then, at the risk of too-long quotes
In terms of social changes, it is pertinent to note that while the authors of the LTG caution that the dynamics in the World3 model continue to operate throughout any breakdown, different social dynamics might come to prominence that either exaggerate or ameliorate the collapse (eg. Reform through global leadership, regional or global wars).
Unfortunately, scientific evidence of severe environmental or natural resource problems has been met with considerable resistance from powerful societal forces, as the long history of the LTG and international UN initiatives on environmental/climate-change issues clearly demonstrate. Somewhat ironically, the apparent corroboration here of the LTG BAU implies that the scientific and public attention given to climate change, whilst tremendously important in its own right, may have deleteriously distracted from the issue of resource constraints, particularly that of oil supply. Indeed, if global collapse occurs as in this LTG scenario then pollution impacts will naturally be resolvedâ€”though not in any ideal sense! A challenging lesson from the LTG scenarios is that global environmental issues are typically intertwined and should not be treated as isolated problems. Another lesson is the importance of taking pre-emptive action well ahead of problems becoming entrenched. Regrettably, the alignment of data trends with the LTG dynamics indicates that the early stages of collapse could occur within a decade, or might even be underway. This suggests, from a rational risk-based perspective, that we have squandered the past decades, and that preparing for a collapsing global system could be even more important than trying to avoid collapse.
That last sentence seems dark. My hope is in the parenthetical note in the paragraph above: “Reform through global leadership.” More than hope, I see it as the best and possibly only place to act.
Presenting systemic approaches so people understand them is hard because of their complexity. People seem to prefer to see events in isolation or to attribute them to simple causes, not as parts of ongoing systems. Even if they get that some things act as part of systems, they misunderstand how systems work. In particular, people tend to think that changing technology alone—for example, switching to renewable or nuclear energy and electric vehicles, sequestering CO2, etc—will solve most problems.
Systems analysis suggests that improving technology alone will extend overshoot and steepen collapse. Few things that don’t include reducing the birth rate seem to lower the chance of collapses involving death rates shooting up and population dropping, which is about the worst outcome you can imagine.
Based on these resources, my challenge is
- To check more about their accuracy. I’d love to find them wrong.
- To find ways to present this perspective so people understand it.
- To find ways to motivate people to act on it.
Most people who understand systems approaches seem to have resigned from wanting to do something about the situation to accepting that collapse is inevitable and figuring out how to manage through it. How to manage death rates quadrupling and population halving in a lifetime seems beyond difficult.
I hope we make a difference in time.