Today we introduce the Demographic Transition Model, a way that population geographers organize patterns to better understand and predict population outcomes and trends. The Demographic Transition Model uses simple mathematical concepts to better understand population growth (and decline). The way to test a model is to ask two questions: does it do a good job of explaining the data? And… can it make useful predictions? Remember, models always include trade offs. We usually end up simolifying the natural world to make it fit the model. In exchange, we use the simplicity to get clarity on causal relationships.

A population bottleneck (or genetic bottleneck) is a sharp reduction in the size of a population due to environmental events (such as earthquakes, floods, fires, disease, or droughts) or human activities (such as genocide). Such events can reduce the variation in the gene pool of a population; thereafter, a smaller population, with a correspondingly smaller genetic diversity, remains to pass on gen. es to future generations of offspring through sexual reproduction. Genetic diversity remains lower, only slowly increasing with time as random mutations occur

For most animals in the wild including humans in hunter-gatherer societies), birth rates and death rates are high at the same time. Almost always, the birth rate (slightly) exceeds the death rate, resulting in a low growth population. The size of the population stays relatively stable over long periods of time. Most ancient hunter-gatherer societies were relatively free from catastrophic infectious diseases (which came with domesticated animals).

The Demographic Transition Model seeks to explain the behavior of populations by assigning them to one of five categories based on their Natural Increase Rate as it compares to their Crude Birth and Crude Death Rates. The simple insight that powers the Model is that outside (exogenous) changes first cause death rates to fall dramatically – but birth rates stay high. This dramatically increases the NIR leading to a population explosion.

Stage One of the Model is characterized by a very high CBR and a correspondingly high CDR. Lots of babies, but also lots of death. This is a stable equilibrium and population will grow, but very slightly and over long periods of time. Stage 1 is where we find hunter-gatherer societies like the !Xan of the Kalahari. Simple agricultural societies are also in Stage 1. The drivers of mortality are different – farmers have diseases to worry about that their hunter-gatherer counterparts do not.

The outside shock that shifts a hunter-gatherer or simple farming society from Stage1 to Stage 2 is the Industrial Revolution. The switch from human and animal power to machine power extends both leisure time and life spans. Access to better medicine and health care dramatically drops the death rate. Diseases like cholera that were once a slow death sentence can now be completely cured with a course of antibiotics. This boosts the NIR, resulting in a large and quick increase in population.

As populations increase, more specialization is possible. Economies of scale are possible. Trading is possible. Greater prosperity and lower death rates almost always results in women having fewer children. More education usually results in women having fewer children. A simple way to look at this is that Stage 1 requires a “R” reproductive strategy whereas Stages 2 and 3 work best with a “K” strategy (fewer children but more resources available to them). Eventually, birth and death rates converge, the NIR goes to zero and the population is stable.

If the birth rate ever goes below the death rate (more deaths than babies), the population will begin to shrink, to decline. This transition from no growth to decline marks the boundary between Stage 4 and Stage 5. Parts of Europe and Japan are in Stage 5 now. Declines an be offset by immigration from high growth countries.

Once again, the complete Demographic Transition Model.

Dependency ratios begin high – there are LOTS of babies to take care of (high CBR) but not very many older adults (high CDR). In Stage 2, the dependency ratio reaches a low as the CDR also reaches a low point. Stage 3 is characterized by an increasing ratio of dependents to adults and in Stages 4 and 5, the dependency ratio is high again, as a shrinking population cohort ages 18-65 takes care of their parents and grandparents.

IThe transition from Stage 1 to Stage 2 is easily explainable through the switch from human and animal power to machine power. The second shock is made up of many different factors. Birth rates fall because women have access to education, because women have access to contraception, because women have access to jobs. I would argue that the empowerment of women is the endogenous shock required to shift a society from Stage 2 to Stage 3. Evidence of this is that many cultures still in Stage 2 have religious or societal norms that prevent the empowerment of women.

In the Victorian Era, in both America and Europe, women were considered unfit for a career in the sciences. It was thought that higher education was “wasted” on a woman and that only the Bible was the proper intellectual pursuit for females. Normally, increased access to education decreases a woman’s desire for a large family – but cultural norms such as those prevalent in the Victorian Era can retard or completely block that trend. As birth control (i.e. the Pill) has gotten easier and easier to obtain, cultural norms that encourage frequent childbirth have gotten less effective.