un-Denial

Rob here: It’s a challenge to summarize in a few words Hideaway’s Complexity Accelerated Collapse of a Thermodynamically Unsustainable System (CACTUS) theory, but here’s my latest attempt:

1. modernity depends on many non-renewable resources
2. new resources must continuously be extracted from the earth’s crust to replace those burned or lost to decay, and because 100% recycling is not economical nor technically feasible for most resources
3. reserve quality declines as non-renewable resources are extracted because they are finite, and because we consume the best first
4. therefore, the energy, materials, and technology complexity used for resource extraction must increase to compensate for falling reserve quality to maintain a given extraction rate
5. increasing civilization scale accelerates the development of higher extraction technology complexity
6. increasing civilization scale increases the efficiency of resource use
7. increasing civilization scale requires growth in non-renewable resource extraction
8. therefore, increasing civilization scale BOTH enables and requires non-renewable resource flows to increase
9. therefore, many complex interdependent self-reinforcing positive feedback loops collaborate to grow civilization quickly
10. eventually, a physics limit is reached that prevents one or more non-renewable resource flows from increasing, which triggers a cascade of interdependent self-reinforcing negative feedback loops to collapse civilization’s scale and complexity
11. therefore, modernity will be a short-lived rapidly growing and rapidly collapsing phenomenon anywhere that it emerges in the universe
12. we have hit several limits to resource extraction growth and increasingly violent world affairs reflect stresses in a system preparing to collapse
13. therefore, we are privileged to be alive to witness a rare peak of what is possible in the universe

Today’s essay by Hideaway takes a deep dive into points 5 & 6, the relationships between scale, efficiency, and complexity, and provides an explanation for point 11, why modernity is behaving like a supernova.

Enough fooling around with CACTUS limericks, let’s do some serious CACTUS math…

For me, coming across the scaling laws was like a bolt of lightening that connected everything about the complexity trap humanity has fallen into, and motivated me to research everything I could find about scaling laws and their relevance to all systems.

I knew that modern civilization couldn’t continue after fossil fuels because the EROEI of alternatives and nuclear was too low when taking the full wide boundary approach.

However, there was always the possibility of something new, or more improvements to existing technologies, that might allow modernity to continue, despite the fact that entropy and dissipation are real, and that lower ore grades require more energy to extract the same quantity of minerals and metals, and that we live on a finite planet.

Ingenuity, innovation, and agency are the reasons usually given for why limits don’t apply to for humans. I will show why the scaling laws override all claims that there are no limits.

The topic of how scaling laws will influence our future deserves a large book. This essay is as short as I could make it while still getting across important concepts.

I have used A.I. to help construct the tables and a few times used it to make some points concisely instead of me rambling on too long, so any change in writing style is where I’ve used A.I. to write the point concisely.

As you’re reading, if something is not making sense, wait for the “pivot”, because it didn’t make sense initially to me either.

I learnt a bit about biology scaling laws back in my Uni days many decades ago, however my more recent studies has been on how urban settlements also abide to scaling laws, with different rates than biology, and with some additional rules not seen in biology.

For mammals, as the size of the species increases, food intake also increases, but a doubling of size only leads to a 75% increase in food intake or metabolic rate. This is known as Kleiber’s law. The less specific observation that animals become more metabolically efficient as they grow in size is called the power law, hypometric scaling, or sub-linear scaling.

Plotting mammal species metabolic rate versus size on logarithmic scales results in a straight line with a slope less that 1.

The reason given for efficiency growing with size is usually the mathematical and geometric nature of the networks that distribute nutrients, and carry away waste and heat, as stated in the image above.

These networks are the circulatory system, the nervous system, the lymphatic system, the bone structure, sight and hearing connected to the nervous system, and others I may have missed.

In biology, the study of how the growth of structures and systems is influenced by size is known as allometry.

Of interest to me is that social insect colonies, like ants and bees, also demonstrate scaling laws similar to individual organisms, often also to the ¾ power, though not for everything.

Professor Geoffrey West, a physicist, has done a lot of research about how cities look and act like an organism, with economies of scale, and similar fractal internal networks. His research, and the research of his PhD students, determined that scaling laws for cities are slightly different than those in biology.

In human settlements characterized as ‘urban’ centres, a doubling in size results in an 85% increase in many aspects like road surface area, power line length, number of gas stations, etc., all the physical type attributes. Other aspects, like population density in megacities, scale at the 75% power law.

Interestingly though, we are not entirely as efficient as nature, that mostly scales at a 75% for a doubling in mass.

There are some aspects of cities that scale at greater than 100% for a doubling in size, the socioeconomic aspects, as Geoffrey West explains:

“The bigger the city is, the less infrastructure you need per capita. That law seems to be the same in all of the data we can get at. It is a really interesting relationship, and it’s very reminiscent of scaling laws in biology. However, when we looked at socioeconomic quantities—quantities that have no analogue in biology, like wages, patents produced, crime, number of police, etcetera—we found that unlike everything we’d seen in biology, cities scale in a super-linear fashion: The exponent was bigger than 1, about 1.15. That means that when you double the size of the city, you get more than double the amount of both good and bad socioeconomic quantities—patents, aids cases, wages, crime, and so on.”

More can be learned by reading Prof. West’s book “Scale”, or by watching one or two of his YouTube videos.

Two aspects of scaling are massively relevant to our existing civilization: the efficiency gains that resulted from growing towns and cities, around the world, compared if we had stayed a rurally based population, with the same population.

Take an example of a material, let’s call it “K”, it could be bitumen for roads, or wire in overhead transmissions, or bricks in shops or commercial premises, etc., any physical attribute that has scaled at around 85% for every doubling of population. A city that has grown over the last 100 plus years from 100,000 to a current 3.2M has had 5 doublings in population size, while “K” that originally had 85,000 tonnes used for infrastructure has grown to 1.842M tonnes of use with the same doublings of population. It’s still massive growth, but if the growth had matched population growth on a one for one basis, as in scaled at 1, it would have grown to 2.7M tonnes of use. Think of all the energy and materials saved by using only 1.8M tonnes of “K” instead of 2.7M tonnes for the same population if it had scaled a 1:1 instead of sub-linearly at 0.85:1.

While this sub-linear scaling for materials and energy use has been an advantage for efficiency in the cities, it almost always goes unnoticed in our modern world as there is still a vast increase in energy and material use, plus cities are huge vacuums of resources from their hinterlands and we tend to focus just on the increased use of both energy and materials, while not realising the efficiency gains in the background.

Where do all the efficiency gains come from, apart from the usual excuse of human ingenuity? In the case of scaling laws, it’s the other side of the coin. With human settlements we have super-linear scaling or hypermetric scaling (above 1 around 1.15) for just about every aspect of socio economic human interaction. Whether it’s ideas, innovation, patents, arts, wages, GDP, money, debt, research, R&D expenditure, telecommunication volume, social interactions, or even walking speed!!

However, we also get hyperlinear scaling of around the same 1.15 or 115% for every doubling of the population for crime rates, disease spread, police, traffic congestion, pollution, and waste.

Pivot 1!!

I want to stop here for a second, because the theory and research findings, suddenly didn’t make sense to me!!

How can urban areas/cities of which a huge proportion of humans now live in compared to prior historic times be more energy efficient at the rate of 85% for every doubling in their population, when overall energy use has  grown by something like 30 times while the population has grown by 10-12 times, in other words a super-linear scaling of overall energy use?

I track this inconsistency back to the definition of urban areas/cities. What they are measuring has been the residential and old commercial part of cities or central local government areas, where all the people mostly live, not the entire metropolitan area including all the industrial areas and ports!!

The following map/diagram, is a heat map of a city in Northern Italy, Padua. It doesn’t matter which one, as it shows the entropy of a city, but also has where the old city centre is located compared to today’s energy use. Notice how number 6 is the old city centre, which has had the population double and double again over time, where the huge sublinear scaling of an 85% increase in energy use, infrastructure etc. has occurred for every doubling of human population, even though many of those people might work in the Industrial area number 1, that is excluded from the calculations of energy use for the ‘city’. The cities physical limits stay constant in all the research.

It doesn’t matter how the research is not that accurate for overall growth as portrayed by Prof West in so many videos. It is still accurate and important for the efficiency gains we’ve had for where people live and interact.

It also makes a lot of logical sense, as people living in high rise smaller apartments have obvious heating and cooling savings, material savings in construction, less street area per person etc., compared to those living in stand alone housing in rural areas. Plus less distance to the supermarket, or restaurant, or university, or office block, etc..

End pivot.

Back to scaling laws that definitely apply in nature such as in Kleiber’s Law described above. What if we took the entirety of human civilization as a whole, as no city in the modern world can build, exist or operate without inputs from across the world, whereas this might have been restricted to the local area 600 years ago, so we must accommodate for this massive change.

The character of cities has evolved from originally relying solely upon their hinterland thousands of years ago, to being totally dependent upon areas outside their hinterland today.

Using total human population doublings compared to energy and materials growth we get the following over the last few doublings.

  The Long-Term Scaling of the “Bloom”

Population Doubling	Approx. Dates	Total Energy Increase	Scaling Exponent
500M – 1B	~1500 – 1804	~1.3x to 1.5x	~0.4 to 0.6 (Hypometric)
1B – 2B	1804 – 1927	~5x to 6x	~2.3 to 2.6 (Extreme Hyper-linear)
2B – 4B	1927 – 1974	~4.7x	~2.2 (Extreme Hyper-linear)
4B – 8B	1974 – 2022	~2.5x	~1.3 (Hyper-linear)

Population Milestone	Approx. Year	Total Material Use (Gt/yr)	Global “Metabolism” per Person
500 Million	~1500	~1.0 Gt	~2 tonnes
1 Billion	~1804	~2.5 Gt	~2.5 tonnes
2 Billion	~1927	~7.0 Gt	~3.5 tonnes
4 Billion	~1974	~30 Gt	~7.5 tonnes
8 Billion	~2022	~100+ Gt	~12.5 tonnes

Notice how every aspect of energy and materials use is super linear scaled since the start of the fossil fuel era. If I was writing up chapters of a book, I’d break this down further for say a 15-20% increases in population and compared to above energy and materials use.

I’ve also been working on breaking it all up into other categories like net energy use, or total materials moved, that accounts for all the extra earth moving from mining 1% ore grades instead of 10% ore grades etc. None of them really change the big picture shown by just energy and materials above, except for the net energy where we are going backwards. By necessity though, net energy calculations are not possibly fully accurate, but the trend is what’s important…

Net Energy vs. Population Doublings (Estimates)

Population Doubling	Total Energy (EJ)	Estimated EROI	Net Energy (Surplus)	Energy System Cost
1B – 2B	20 – 100	40 – 80	~5.1x Increase	~2.5x Increase
2B  – 4B	100 – 260	80 – 40	~2.6x Increase	~5.2x Increase
4B -8B	260 – 600	40 – 15	~2.2x Increase	~6.2x Increase

Notice how net surplus energy after taking out estimated energy cost of energy is still super-linear in scaling. I therefore took it down to the increases in net energy for every 15% increase in population from more recently, from the end of exponential oil use growth.

Net Energy vs. 15% Population Growth (Post-1974)

Figures based on a weighted average global EROI that includes the shift from conventional oil (100:1) to unconventional (15:1) and renewables (<5:1 in full-system terms).

Window	Pop. Growth	Net Energy Increase	Energy System “Tax”
1974 – 1986	+15.3%	~24%	Baseline
1986 – 1998	+15.1%	~19%	~1.4x
1998 – 2010	+15.2%	~12%	~2.8x
2010 – 2022	+15.0%	~4%	~4.2x

The energy tax is just the growing cost of gaining energy, but the obvious take from above is that since around 1998 while population has kept growing, net energy has not kept pace and the lag between them is growing. Meanwhile ore grades continue to decline and energy use to gain metals and minerals is accelerating. Calvo and Mudd 2016, have shown that a 30% increase in copper production came with a 46% increase in energy use for that production, which means falling ore grades, remoteness, deepness of mines, harder ore indexes have overcome any efficiency gains. This is another part of the story though, so I’ll leave it or this will be a book.

Pivot 2 !!

What about the super scaling aspects of human civilization, how do they fit into the big picture??

One aspect of super scaling of anything is that as you move forward in time at some point super-scaling has to reach infinity as it’s exponential growth.

Then there is the vast difference between the super-scaling that happened as populations doubled in urban areas and towns for all socioeconomic metrics, like innovation, GDP, patents, research, R&D expenditure, wages + salaries, wealth creation, higher degrees in specialities, information exchange, cultural output as in restaurants, theatres, creative venues, along with all the negatives of crime, police numbers, disease spread, waste, land rents and taxes, compared to physical super-linear scaling of materials and energy use. The former are all man made concepts, the latter have physical limits.

In the long term it’s impossible for these to reach infinity, so we know it simply cannot go on forever.

 We also changed the scaling rules, instead of a town or city growing organically, we made the world pretty much as one, for a lot of our human interactions and storytelling.

We created the internet where communication is available instantly around the world. We have forums all over the place for sharing of all types of stories, YouTube videos for learning skills, or sharing new ideas on every possible range of topics. We have online journals in most specialist areas where a new article can be instantly shared around the world. All this accelerates the super-linear scaling of every socio economic metric.

The table below shows the rate of increase in our collective complexity, in other words the stories we tell ourselves.

  Global Cumulative Growth per 15% Population Step (1970–2024)

Population Milestone	Year (Approx.)	15% Pop. Step	Global GDP (% Increase)	Scientific Papers (% Increase)	Administrative Loading (% Increase)
3.7 Billion	1970	Base	Base	Base	Base
4.25 Billion	1978	+15%	+44%	+40%	+35%
4.9 Billion	1986	+15%	+31%	+43%	+28%
5.6 Billion	1994	+15%	+28%	+50%	+32%
6.5 Billion	2005	+16%	+46%	+100%	+55%
7.5 Billion	2017	+15%	+40%	+100%	+62%
8.0 Billion	2024	+7%	+18%	+70%	+40%

I’ve included GDP as just a story we tell ourselves, just like every scientific paper (whether true or not!), plus every other nonphysical aspect of our modern world. We cannot live on these stories, we need food, shelter, clothing, etc., and we can earn money by telling these stories to each other and use money (another story humans tell each other!) to buy food, shelter and clothing.

However we don’t tell all these stories in a vacuum. Take the increased administration. This takes people, buildings, heating, air conditioning, paper, computers, etc. I can look at my local government in a rural area where over 40 years ago there was a shire secretary, a building inspector, a health inspector and a couple of administrative assistants. For pretty much the same population as back then, the administration has around 60 people, all using energy and physical resources.

End pivot…

Back to scaling laws in the natural world.

In the natural world, super-linear scaling is extremely rare, while sub-linear scaling occurs in many systems.

As noted early, nearly all life forms have a type of inherent sub-linear scaling and can exist for extremely long periods of time. The ecosystems the lifeforms collectively form also have this sub-linear scaling.

We also have sub-linear scaling in physical non-life systems, that are also extremely long lasting. For example a river length extends by around 0.6 for the increase in size of the river basin (Hack’s Law).

Then there is the surface volume law for planets and stars where the energy loss of a sphere is only 0.67 times the increase in volume (radius squared compared to radius cubed).  This is why a large planet like Earth stays hot for billions of years, while a small satellite like our Moon cools down and “dies” quickly. The larger the mass, the more efficient the “insulation.” (more on stars later!!)

The dissipation of energy in large-scale fluids (like the wind or ocean currents) follows Kolmogorov scaling. The energy contained in small eddies scales sub-linearly relative to the energy in large-scale flows.

Also on the largest possible scale, the way matter is distributed in the universe follows sub-linear fractal patterns. The number of galaxies found within a sphere of radius scales with an exponent of roughly 2.0 (instead of 3.0). The universe isn’t a solid block of matter; it’s a web of filaments. This “under-filling” of space is sub-linear which allows gravity to balance the expansion of the universe without everything collapsing into a single point.

I could but won’t go on. Every one of the above sub-linear scaling laws in the natural world is a huge area of research by itself, with books and high-level research (stories by humans) about it all, if anyone is slightly interested.

Super-linear scaling is rare and only tends to last a short period of time.

In the natural world of life, super-linear scale events are things like cancer. A tumor’s metabolic demand and growth rate scale super-linearly relative to its mass. Because it scales faster than the host’s ability to provide energy (the sub-linear “pipes”), it eventually starves the host and itself. It is a “singularity” that ends in the death of the system.

Then there are outbreaks like a locust plague or an algal bloom. When a “pulse” of energy (like nitrogen/phosphorus runoff) hits water, the algae population scales super-linearly. They use the excess energy to replicate at a rate that ignores the usual “checks and balances.”

When environmental triggers (like sudden rain) occur, locusts undergo a “phase change” from solitary to gregarious. Their interaction density scales super-linearly, triggering a massive, coordinated population explosion.

Algal blooms grow so fast (super-linear demand) that they consume all the dissolved oxygen in the water (sub-linear supply). They literally suffocate the environment that supports them. A locust plague consumes every green thing in its path. It is a “vacuum” of energy that strips the landscape faster than the landscape can regenerate.

Because these processes are super-linear, they cannot reach a “steady state.” They always end in a Finite-Time Collapse:

The Algal Crash: Once the nutrients are gone or the oxygen is depleted, the algae die off en masse. This creates a “dead zone”—a state of high entropy and total system failure.

The Locust Die-off: Once the swarm runs out of food or hits a geographical barrier, the population collapses. They simply starve or revert to a solitary, low-energy state.

Interestingly, locust plagues are triggered by information. When locusts’ hind legs are touched enough times in a crowded environment, it triggers a hormonal shift. This is exactly like socioeconomic scaling. The “interaction density” of the crowd changes the behaviour of the individual to prioritize runaway growth over individual survival.

Non-life natural systems.

Super-linear scaling happens in things like nuclear fission. In a prompt critical state, the number of neutrons scales super-linearly with time.

In chemical explosions, the rate of reaction increases as heat is released, which in turn increases the rate of reaction.

The Outcome is a state of high entropy and energy dissipation. It eventually “exhausts” the kinetic energy of the flow unless more energy is constantly pumped in.

Back to stars.

Inside the core, the nuclear fusion rate scales super-linearly with the mass of the star. As a star’s size gets bigger, the internal pressure and temperature spike, causing it to burn fuel at an astronomical rate. This is the “Live Fast, Die Young” reality.

Earlier I mentioned that star’s surface area cooled at a sub-linear rate which is also true and hence a conflict. The reason stars of large magnitude are so unstable is specifically to do with this conflict of 2 scaling laws.

The instability of massive stars stems from a fundamental mismatch in how gravity and pressure scale as a star grows (‘grows’ means comparing stars of different initial masses, as they don’t grow like a plant, etc.). While a star’s mass (and its inward gravitational pull) increases with its volume, the outward radiation pressure required to counter that gravity increases far more aggressively, proportional to the fourth power of temperature (T4). In these giants, light becomes the dominant structural support rather than gas, creating a “squishy,” delicate balance where the outward push of photons nearly overcomes the inward pull of gravity. This forces the star to operate at the Eddington Limit, where it becomes so volatile that it frequently sheds its own mass in violent eruptions or pulses, eventually leading to a catastrophic structural failure when the core can no longer sustain the furious energy output required to stay inflated, as in supernova explosion.

Enough of large stars, there are books written about all this, suffice to say that having 2 different scaling laws applying at the same time make them very unstable.

Finally, let’s put it all together and get to the reason you’re probably reading this essay.

Human civilization has aspects of both sub-linear scaling like most life forms, and super-linear scaling like very few life forms and physical processes in the universe.

When did humans show the first signs of super-scaling? The answer might surprise some, but it was back in our hunter-gathering days, when there was enough social interaction of early religions that allowed the building of such places as Göbeklitepe in Turkey or Pivot Point in the U.S.A. Though super-scaling really took off with the towns and city states that developed with agriculture.

Every one of these city states, though, ended up collapsing as the growth in the socio-economic sphere of complexity outgrew the surrounding supply of energy and materials. Every anthropologist has their own description of exactly what happened with city states and their collapses, but they just about always stick to ‘human’ factors and certainly don’t embrace falling EROEI, and diminishing returns on materials, as playing an important role.

Prof Joseph Tainter, certainly does cover the increasing complexity of administration or problem solving, which acts as a tax on the prosperity of the culture, but doesn’t quite go as far as attributing a super-scaling aspect to this problem solving.

Fast forward to today’s civilization, where the complexity is growing at a growing rate.

With the help of A.I. I’ve created the following table…

 Complexity Growth per 15% Population Addition

Statistics based on proxies including regulatory volume, R&D expenditure, and global supply chain nodes.

15% Pop. Window	Approx. Years	Complexity Growth (%)	Scaling Ratio	Major Driver
Window 1	1974 – 1982	~28%	1.8x	Early Automation / Fuel Efficiency
Window 2	1982 – 1991	~42%	2.8x	Personal Computing / Global Debt
Window 3	1991 – 2001	~65%	4.3x	The Internet / Just-in-Time Logistics
Window 4	2001 – 2012	~88%	5.9x	Carbon-Silicon Fusion / Social Media
Window 5	2012 – 2024	~112%	7.5x	AI / High-Tech Governance (ESG)

Everyone that has been around for enough decades, intuitively knows the above to be true in every facet of their lives. If you want to build a nuclear power plant, or a shed in your backyard, or sell some produce at a market, anywhere in the Western World, there are layers of more rules and regulations compared to a few decades ago.

Back when we bought our farm, if you wanted to put up an agricultural shed, you just built it. Now in 2026 you require a planning permit ($cost), which requires different experts to perform tests to make sure the land isn’t too steep, and the ground has the geotechnical strength to support the shed, plus bushfire overlays, environmental overlays, vegetation management overlays, etc. Then you apply for the building permit ($cost), that another expert must make sure all the engineering calculations, colour of building, appropriate materials, etc. are used. Then if you want to use the shed for any commercial purposes, more sets of rules come into play ($larger costs).

The above table, is just a best guestimate, but there are different actual statistics that back it up, like reports on ESG rules and regulations growth over the last 25 years, etc.

I’ve lost count of the number of politicians that promise if they are elected then they will cut the red tape for ….. (name your own businesses, companies, level of govt, etc) but it just doesn’t happen on any scale, as all rules, regulations, extra complexity are about ‘helping’ people or making everything ‘safer’ for workers, public, school kids, nurses, farmers, the poor, the homeless, the environment, the whales, the dolphins, the rare double breasted red herring, etc, etc, etc.

Where did this more recent explosion in the super-linear scaling of complexity come from? It’s easily accounted for by the internet that has made the social interactions of the whole world as if we were one large super city. Ideas, knowledge, concepts, stories, research papers all are instantly available around the world once posted online. Anyone here not think that a new set of rules or a tax thought up in Timbuktu won’t be recognized as a possibility in your own area very quickly if it serves a distinct purpose?

People will argue that the rules, regulations and increased complexity are a choice, and despite the increasing energy and material cost of these growing phenomena, it is a choice humans have made, so humans could also choose to undo it.

What they always fail to recognize is that money, debt, patents, stock markets, bond markets, religions, etc., are also just stories that humans have told ourselves and convinced each other are real, when realistically they are all part of the socio-economic fabric of the world we’ve built and are real as this super-linear scaling is what keeps modernity functioning.

As a civilization, we have super-linear scaled our use of energy, materials, and every socioeconomic metric, as we’ve grown to this scale on a finite planet. We have a 6 continent supply chain based on so many factories, processing plants, mines, banks, letters of credit, ports, ships, trucks, railways, flights, markets, organisations, trade blocks, that work in such a complex fashion, that it’s impossible to understand it all.

If there is anything we can learn from all other types of super-linear scaling it’s simply that they all end, and always very abruptly, compared to the time they were in the super-linear scaling phase.

Again I’ve used A.I for this last bit..

Is there any type of super-linear scaling that has ended gently?

There are no examples of super-linear scaling ending “gently.” In physics and biology, super-linear scaling is inherently unstable because it creates a positive feedback loop that accelerates until it reaches a physical limit.

In every known natural case, the ending is a discontinuous “break” or a catastrophic phase transition. Here are the three ways nature “ends” super-linear scaling:

The large star. It never “tapers off.” It burns faster and hotter until it hits the Iron Wall. The end is the Supernova—a sudden, violent collapse followed by an explosion. The system doesn’t “downsize”; it is physically obliterated, leaving only a tiny, dead remnant (a neutron star or black hole).

The bloom model of Algae or Locusts.   These systems grow until they hit the Metabolic Ceiling of their environment. Because they have no “brakes,” they consume their host or their food supply entirely. The Result: A total population crash. 99.9% of the organisms die in a matter of days or weeks once the “Iron Wall” of resources is hit. The “scaling” ends in a wipe, not a transition.

The wildfire. A wildfire or a forest fire exhibits super-linear energy release as it grows (heat creates wind, which feeds the fire more oxygen). The Ending: The fire does not “gently” decide to become a candle. It accelerates until it either runs out of fuel or exhausts its oxygen. The Result: A sudden “flicker and out” or a massive “flashover” collapse. The system leaves behind a high-entropy state (ash) that cannot support any further scaling for a long time.

To conclude an already too long essay on a topic that deserves a book, this video of Prof Geoffrey West on Nate Hagens’ Great Simplification podcast opened my eyes to the world of scaling laws and its importance in our civilization.

On this episode, physicist Geoffrey West joins Nate to discuss his decades of work on metabolic scaling laws found in nature and how they apply to humans and our economies. As we think about the past and future of societies, there are patterns that emerge independently across cultures in terms of resource use and social phenomena as the size of a city grows. Does Kleiber’s law, which describes the increasingly efficient use of energy as an animal gets larger – also apply to human cities? How have humans deviated from this rule through excess social consumption beyond a human body’s individual metabolic needs? What could we learn from these scaling laws to adjust our communities to be more aligned with the biophysical realities of energy and resource consumption? Can an understanding of social metabolism impact our social metabolism?

I recommended you watch the entire video, but the most important part is from 32.30 to around the 42.00. Be cognisant that the scaling laws Dr. West refers to are inside the main residential areas and it seems from lots of research I’ve read to exclude the heavy industrial areas, which explains the actual amount of energy and materials our civilization uses.

Most of the video past the 42 minute mark demonstrates the usual human denial by looking for ways to overcome fundamental laws of physics that clearly show anything that grows exponentially (aka super-linear scaling) comes to a rapid end.

To conclude, civilization is a physical phenomenon, not really different to a large star that has both sub-linear and super linear scaling, nor that different to a locust plague or algal bloom, consuming every available resource until it reaches a limit, and then the entirety of the system just dissipates.

You will not find any physicists arguing that civilization is not an energy dissipative structure, so why should civilization end differently than any other energy dissipative structure?

Even in Prof Geoffrey West’s findings of scaling laws that apply to cities, he and his colleagues still find that “innovation”, being the important element (not total energy use), must keep increasing at a faster rate and still reaches a point of “singularity” anyway. Singularity is a polite physics term for collapse. (He explains this in the video link above anyway).

All past civilizations have collapsed, and some people like to use them as models for our potential slow collapse. However all past civilizations were agriculturally based for their energy in the cities, with the proportionally massive rural population living a mostly subsistence lifestyle, so could easily carry on exactly as they had prior to the town/city or state developing.

Even the Roman Empire at its peak only had around 2% of the population in Rome itself, with around 7% of the total population in all urban areas. Our modern world is vastly different to this, with the developed world often having 70-80% or more of the population in urban areas, and the farming relying upon all of modernity to take place. We have neither the skills nor the equipment/animals to go back to a subsistence type of agriculture, like those in collapsed civilizations of the past.

I attribute just as much human ingenuity to those living in prior civilizations as we have, yet this never stopped them from collapsing, nor did human agency, and we could argue that they had more agency than we do in modern democracies, as it’s easier to change rules and how people live in monarchies with absolute rule, than in modern democracies where governments come and go every few years.