Peter Schulze, Jack Mealy

Deevey1
Figure 1. Deevey’s graph of the rise of global population first appeared in a 1960 article in Scientific American. According to his analysis, human numbers rose notably at three times in the past, corresponding to the advent of toolmaking, of agriculture and of industry, but this appearance is an artifact of the graph.


The extent to which human beings affect the environment depends, in large measure, on the number of people in the world. Despite the paramount significance of this statistic, many students, environmental analysts and even policymakers have a distorted understanding of the history of population growth. The confusion stems from a single misleading graph that often appears in the environmental literature.
The graph in question gives the distinct impression that human numbers skyrocketed during three relatively discrete periods—specifically, at the advent of toolmaking, agriculture and industrialization—but in each case subsequently stabilized. Edward S. Deevey, Jr., a noted ecologist and member of the National Academy of Sciences, first presented the problematic plot in 1960, in an article about human population in Scientific American (one of the eight he published in that magazine before his death in 1988). He wrote, “the population curve has moved upward stepwise in response to the three major revolutions that have marked the evolution of culture . . . But the evolution of the population size also indicates the approach to equilibrium in the two interrevolutionary periods of the past.”
Since Deevey penned this description, various renditions of his figure have appeared in at least seven other books or articles on the subject—most of which were published since 1990. What rekindled interest in a 41-year-old graph? The answer is plain: In recent years, many scholars have sought to better understand the links between technology and population growth. And some of them uncritically accepted Deevey’s view that two rapid increases in population were followed byperiods of approximate stasis.

2 thoughts on “Peter Schulze, Jack Mealy

  1. shinichi Post author

    Population Growth, Technology and Tricky Graphs

    by Peter Schulze, Jack Mealy

    http://www.americanscientist.org/issues/postComment.aspx?id=3273&content=true

    The extent to which human beings affect the environment depends, in large measure, on the number of people in the world. Despite the paramount significance of this statistic, many students, environmental analysts and even policymakers have a distorted understanding of the history of population growth. The confusion stems from a single misleading graph that often appears in the environmental literature.


    Deevey1Figure 1. Deevey’s graph of the rise of global population first appeared in a 1960 article in Scientific American. According to his analysis, human numbers rose notably at three times in the past, corresponding to the advent of toolmaking, of agriculture and of industry, but this appearance is an artifact of the graph. Other authors have since repeated Deevey’s misleading presentation (above) and have drawn even more incorrect inferences from it.
     
    Annette DeFerrari


    The graph in question gives the distinct impression that human numbers skyrocketed during three relatively discrete periods—specifically, at the advent of toolmaking, agriculture and industrialization—but in each case subsequently stabilized. Edward S. Deevey, Jr., a noted ecologist and member of the National Academy of Sciences, first presented the problematic plot in 1960, in an article about human population in Scientific American (one of the eight he published in that magazine before his death in 1988). He wrote, “the population curve has moved upward stepwise in response to the three major revolutions that have marked the evolution of culture . . . But the evolution of the population size also indicates the approach to equilibrium in the two interrevolutionary periods of the past.”

    Since Deevey penned this description, various renditions of his figure have appeared in at least seven other books or articles on the subject—most of which were published since 1990. What rekindled interest in a 41-year-old graph? The answer is plain: In recent years, many scholars have sought to better understand the links between technology and population growth. And some of them uncritically accepted Deevey’s view that two rapid increases in population (brought on by toolmaking and by agriculture) were followed byperiods of approximate stasis. Indeed, several of the more recent authors go further than Deevey, arguing that the graph shows that the population has been stabilizing during the last few decades.

    The last few decades have, of course, been a time of remarkable expansion, not stabilization, in human numbers—population having doubled since Deevey wrote his paper. So something is clearly wrong. It appears that Deevey and the authors who adopted his presentation failed to recognize the effect of the plotting format: Deevey’s graph uses logarithmic scales both for human numbers and for time. Time intervals increase by successive orders of magnitude as the scale moves further into the past. The resultant plot does seem to show that the population is now approaching an asymptote (and has done so twice before). But this appearance is purely an artifact of the logarithmic time scale.


    DowJones1Figure 2. Dow Jones industrial average rose relatively slowly over most of the 1960s and ’70s; it then climbed sharply during the 1980s and ’90s. This history is well illustrated by a simple graph with linear scales (top). Plotting the Dow using logarithmic scales (bottom), as Deevey and others have done for population growth, completely obscures the pattern of change: On casual inspection of the bottom graph, the stock average appears to be approaching an asymptote.
     
    Annette DeFerrari


    Indeed, with the exception of a catastrophic decline, almost any plausible rate of growth will seem to level off on such a graph. Consider, for example, the Dow Jones industrial average. Although the Dow grew more rapidly in the 1980s and ’90s than it did in the two decades before, plotting it using Deevey’s scheme appears to show the average stabilizing toward the end of the 20th century.

    What changes in population would produce something like Deevey’s bumpy line on a graph with logarithmic axes? Three successive rises followed by plateaus would result from a population that expanded at one rate for one period, increased to a higher rate for a second period and increased again to a yet higher rate during a third period. For example, if one simply takes the estimated population of 1 million years ago, allows it to increase 0.0004 percent per year until 10,000 years ago, then 0.05 percent per year from 10,000 to 300 years ago, and finally 0.7 percent per year during the last 300 years, the resulting plot looks very similar to Deevey’s.

    What sort of growth would be needed to show an obvious increase on a graph with two logarithmic axes? To rise as a straight line, a variable must make its next order-of-magnitude increase in an order of magnitude less time than the previous one. This is a tall order. For example, consider a population that went from 100 to 1,000 in 100 years, an annual increase of 2.33 per cent. To plot as a straight, upward-sloping line, the population would have to reach 10,000 in the next 10 years and then hit 100,000 in the following year. No population of organisms could long keep up such accelerating multiplication. So regardless of the actual situation, all plausible positive rates of growth will appear to plateau on Deevey’s graph.

    Just how should population be plotted? There are several alternatives; the most appropriate choice depends upon the question at hand. For example, one can simply plot both time and population size on linear scales. This technique is well suited for situations where it is important to be able to read numbers directly from the graph. But when a population grows by orders of magnitude, the needed compression of the vertical scale obscures any interesting changes that happen at low population sizes. And using this format to plot the growth of populations over extended periods can produce instances where the slope of the line appears almost vertical, as if the rate of increase were infinite.

    What about using a linear scale for time and a logarithmic scale for population size? This combination is common in the ecological literature. Changes at small sizes remain detectable even with a population that later becomes quite a bit larger. Moreover, figures with a linear time axis and a logarithmic population axis have a convenient feature: A constant percentage rate of increase plots as a constant slope. This attribute makes it easy to detect changes in the rate of growth, which appear as shifts in the slope of the line. Indeed, such log-linear graphs can be very illuminating. Using one to track the Dow would readily show that the annual rate of increase in stock prices tended to be larger during the 1980s and ’90s than it was during the ’60s and ’70s.

    Deevey’s graph suggests the present population is hardly changing, after having grown rapidly at three times in the past. Yet the opposite is actually the case. During the past half-century, population rose roughly 1.8 percent per year while growth rates during Deevey’s three steep phases were only 0.0003, 0.07, and 0.24 percent per year respectively.

    The purpose of a graph is to help detect patterns, or the lack thereof. Plots made with a logarithmic time scale tend to look the same regardless of what they represent. They not only obscure changes, they also give the impression that the variable under study is stabilizing, whatever the actual situation. This is especially dangerous when it lulls people into thinking that the recent expansion of population has effectively ceased. Arguments about when and how the population will stop increasing are more important now than ever before. People should not let these tricky graphs cloud the debates they are intended to illuminate.

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  2. shinichi Post author

    Chance News 10.09

    by J. Laurie Snell, Bill Peterson, Jeanne Albert, and Charles Grinstead, with help from Fuxing Hou and Joan Snell.

    10. Return to population growth and tricky graphs.

    http://www.dartmouth.edu/~chance/chance_news/recent_news/chance_news_10.09.html#item10

    **


    In Chance News 10.05 we discussed an article in the May-June issue of the American Scientist by Peter Schulze and Jack Mealy called "Population growth, technology and tricky graphs." Because we were sending Chance News by e-mail we could not include graphics. Thus it was hard to show what the authors were concerned about in this article. We can now include the relevant graphs and make this clearer.

    The article was centered on a graph charting the history of the world population that appeared in an article by the famous ecologist Edward S. Deevey Jr. in the September 1960 issue of Scientific American. The graph in question is the following loglog plot of the world population back a million years:


    Fig1


    Recall that such a loglog plot plots the logarithm of years against the logarithm of the population. Schulze and Mealy reamrk that this graph appeared in several articles and books and has been used to argue that the population tends to level off in major periods of human evolution. For example, it appears in the recent book "Human Impact on the Earth", William B. Meyer, Cambridge University Press, 1996 where we read:

    A possibility that this picture raises is that each great transformation of society may raise the globe’s human carrying capacity to some new plateau. Population rises to that height and stabilizes; what happened twice in the past may happen again.

    To show that loglog plots are deceptive in this application, Schulze and Mealy ask: What sort of growth would be neeeded to show an obvious increase on a graph with two logarithmic axes? They write:

    To rise as a straight line, a variable must make its next order of magnitude increase in an order of magnitude less time than the previous one. For example, consider a population that went
    from 100 to 1,000 in 100 years, an annual increase of 2.33 percent. To plot as a straight, upward-sloping line, the population would have to reach 10,000 in the next 10 years and then hit 100,000 in the following year. No population of organisms could long keep up such accelerating multiplication. So regardless of the actual situation, all plausible positive rates of growth will appear to plateau on Deevey’s graph.

    Peter Schulze sent us the data that was used in trying to reconstruct the Deevey graph. Hear it is:


    Fig2gf


    Of course, data back a million years ago cannot be expected to be very accurate. Different researchers have provided different numbers. You can obtain this data in Excel format and references that Schulze and Mealy used here. Similar estimates are provided here by the census bureau.

    We used this data to try to reproduce the Deevey graph. Here is the result:


    Fig3


    Obviously, we cannot expect a smooth curve when we have so little data from the early years. Apparently, Deevey smoothed his curve to make it look more attractive.

    Since we have seen that this graph is deceptive, how should we plot the world population to see what is going on? The most straightforward method would be to use arithmetic scales. If we do this we obtain the graph:


    Fig4


    While not a very interesting looking graph it does that population increased dramatically in a relatively short period. However, it does not show much detail for either before or after this population explosion.

    One of the principle sources of early estimates of the population is the "Atlas of World Population History" by Colin McEvedy and Richard Jones, 1998, Penquin, New York. Here is how the world population is plotted from 400 BC to 1975.


    Fig5


    The time period and used an arithmetic scale for the population they use their own scaling for the time axis. Their data is on the graph. We see only one population decrease which occurred between 1300 and 1400 AD. This decrease was the result of the Black Plague. It was estimated that as many as 25-million people in Europe died as a result of this plague.

    This graph includes Deevey’s industrial period and a good part of his agricultural period. There is certainly no evidence of the population leveling off in either period. Also we note that the authors’ prediction, made in the 1970’s, that the population in 2000 would be 5,750,000,000 was a pretty good estimate since the world population in 2000 was 6,080,000,000.

    Since in population changes it is reasonable to assume that the rate of growth of the population should be proportional to the number of people alive, we should expect the growth to be exponential. If that is the case a log plot would enable us to see the rate of growth. Here is such a log plot for the industrial period.


    Fig7


    We would expect a straight line if the population increased at a constant rate. The graph suggests that this approximtely true until 1600. But after 1600 it increased at an increasing exponential rate.

    What about the future? The census bureau gives us predictions up to the year 2050. They provide us with a graph of the population from 1950 projected to the year 2050:


    fig8


    We see that the Census Bureau predicts that in the next 50 years the rate at which the populations grows will decrease. However it will still increase to about 9 billion by 2050.

    George Cobb wrote an interesting commentary on the Schulze-Mealy article and on the use of log plots as a letter to the editor in the July-August 2001 issue of the American Scientist. Readers will enjoy reading his commentary and the reply by Schulze and Mealy.

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