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More energy means more people – lots of humans are alive because of coal

Twelve thousand years of human history show that more energy leads to more people. There is also positive feedback, where more people means more energy too. Growth rates rose faster and earlier in England and Wales than Sweden (see Fig 3), where coal use became dominant about a hundred years later.

Given a constant resource supply to a population, the per capita availability of resources declines as the population grows. As resources become scarce, individuals consume less, driving down birth rates and/or raising death rates.

Although many resources may influence birth and death rates (e.g., water), energy is a uniquely universal currency because all forms of work require energy expenditure. This applies to the metabolic rates of individuals in wild populations [18] as well as to the industrial energy use of modern human populations, as energy is used to harvest food, deliver water, and provide health care [1922].

Population, Energy, Global, Sweden, England, Wales, USA

Fig 1. Relationship between energy use (W) and population size for the world, the United States, Sweden, and England and Wales through time. The relationships are highly variable, but overall, the slopes are greater than one (that is, the exponent in the power-law function relating energy use to population size overall), indicating support for a positive feedback between population size and energy use. Lines with slopes of one (ε = 1) are shown as reference. The black lines show overall fits and gray shaded regions show 95% confidence intervals on the regression lines. doi:10.1371/journal.pone.0130547.g002

As well as energy helping to increase population, there are feedbacks the other way as well. More people leads to more energy being available for us — possibly thanks to efficiencies of scale, specialization, and technological advances. Total population of England and Wales in 1760 was 7 million. Assuming that the bell-curve IQ distribution hasn’t changed (and perhaps it has thanks to nutrition and education, or maybe subtle environmental effects and smaller families) there will be ten times as many people in the smartest of smart cohort today as there were then (for whatever that is worth). Success feeds on success.

Interestingly, the history of global human population growth has included periods characterized by all three growth regimes (density-dependent, exponential, and super-exponential; Fig 1 [25]). For example, super-exponential occurred around the mid-1900s, exponential growth occurred from ~4000 to ~1000 BC, and sub-linear growth has been occurring ~1980 through today (Fig 1, inset). It is well known that throughout this time, global energy use increased with the size of the human population [26], yet it is unclear what the level of energy yield (ε) has been and whether it has varied in time or space. That is, it is only known that ε > 0 on average, but not which of the three regimes have been characteristic at which periods or how the value of ε varies through time. Nonetheless, there is growing support for the idea that the exponential and super-exponential growth seen historically for industrial human populations was enabled by positive feedbacks from population size to carrying capacity [5, 16,27–29]. This feedback could happen in several ways. First, harnessing novel energy sources may free societies from “photosynthetic” energy constraints, as seen in England in the early phases of the Industrial Revolution [30]. Second, information and transportation networks may improve the efficiency of extraction, processing, storage, and transportation of energy [28,31–34]. And finally, an increasing diversity of economic roles could enhance the ability of the population to extract and use resources [35].

Humans hit “super exponential” growth with the industrial revolution. This was when the positive feedback kicked in. Though population growth has slowed since 1963.

Population, Global, graph, holocene, civilization, medieval, ancient, modern

Fig 2. The inset shows a period of sub-exponential growth in recent history. Data from [25].doi:10.1371/journal.pone.0130547.g001

The industrial revolution spread through England and Wales from  about 1760, and population growth rates shot up.

We used long-term data on total energy use and population size for Sweden (from 1800 to 2000 [43]) and England and Wales (from 1560 to 2000 [44]). We paired long-term data on energy use in the United States [45,46] with population size data from the US Census Bureau [47–49].

The “scaling parameter” on the graph seems to also be called the “scaling exponent” in the text (helpful if they’d used the same phrase).

Generally, the relationship between energy use and population size can be written as a power law: Etot = e0Nε, where Etot is the total energy used by the population, e0 is a scaling constant, N is population size, and ε is a scaling exponent [18,23,24].

Figure 3, Graph, Population, Energy, Little Ice Age, Industrial Revolution, Effects of Wars, Effect of Oil Crisis, Sweden, England, Wales, USA

Fig 3. The scaling parameter for ε has been highly variable through time. Each panel shows the running mean of ε (slope of the regression of logE on logN, see methods) with a 19-year window smoothed over 20 years. The light brown bar shows the confidence range of mean slope over the entire time period. A. For the world, ε showed a pronounced shift from a little over 2 to 1 from the 1960’s to the 1980’s, with the beginning of this decline coinciding with the peak world population growth rate in 1963 [9]. B. For England and Wales, ε was highly variable, plummeting during the Little Ice Age and during World War I and the Oil Crises of the 1970s. C. Sweden showed an increase in ε after the Industrial Revolution but also showed a decline in ε during both world wars. D. The United States showed a steadily increasing e until about the 1960s when it showed a severe drop coinciding with the Oil Crises of the 1970s. doi:10.1371/journal.pone.0130547.g003

Population growth and  coal use peaked earlier in England compared to Sweden, which did not come into common use ’til the end of the 1800s.

The pre-Industrial Revolution energy yields were approximately linear for England and Wales but were sublinear for Sweden. This difference suggests a qualitatively different population dynamic in the two countries before the Industrial Revolution began. One possible explanation for the difference is in the speed at which the Industrial Revolution began in the two countries. Although there is debate, the consensus view is that the time at which the Industrial Revolution took hold in England was around 1760–1780, and this is based on particularly visible signs of economic growth, like increases in foreign trade, and less so on the development of extractive technologies that reduced the Malthusian constraints of labor and land [52–54]. Indeed, coal did not become a major part of the energy use in Sweden until the end of the 19th Century, with firewood and human muscle carrying most of the energy burden until post-1900 [43]. This delayed shift to fossil fuel reliance may underlie the later increase in exponent for Sweden as compared to England. Likewise, the technologies that made industrial economies possible were developed gradually in England, which could have kept the value of ε closer to 1 for some time before the Industrial Revolution really began to have a dramatic impact on economic productivity

 This graph is about volatility of the “scaling parameter”.

The paper suggests that the oil crisis of the 1970s had an effect on population growth, but they don’t mention the word “contraceptive”.

Figure 4, Graph, Population, Energy, Little Ice Age, Industrial Revolution, Effects of Wars, Effect of Oil Crisis, Sweden, England, Wales, USA

Fig 4. Variation in the scaling parameter e increased as major socio-political events approached and during the Little Ice Age for England and Wales. The world data set is not long enough to include in this analysis. doi:10.1371/journal.pone.0130547.g004



DeLong and Burger (2015) The Scaling of Energy Use with Population Size, PLOS One, [PDF]

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