The Mediterranean and development

I will now discuss the pattern of world development with respect to the model introduced in my last post. You can use the program supplied in that post to reproduce the following discussion and experiment for yourself.

Set up a simple model of the Mediterranean region as shown below.

This uses the default terrain types, representing land, river, coast and sea, as well as the surrounding ocean.

The layout depicts the Mediterranean sea, surrounded by Europe, Asia and North Africa. The regions bordering the sea are designated as coast. The Nile and Tigris-Euphrates river valleys are also represented. However, the main body of Africa is not included, leaving North Africa and the Nile valley as an isolated strip. This represents North Africa being isolated from the rest of the continent by the Sahara desert. (One could include some 'desert' terrain to represent this, but it is easier just to leave the southerly regions as impassable 'ocean'.)

See the diagram below, with red labels showing the terrain types, and white labels showing the geography.



The aim of this experiment is to demonstrate two aspects of historical development:

1. The Nile valley benefited from both its central location and the ease of movement afforded by the river.
2. As (marine) technology improved, the advantage shifted from the river valleys to the regions bordering the sea, especially the Italian peninsula sticking out into the middle of the sea.

We need to make sure the various terrain types have the appropriate properties of habitability and traversibility. The ones we will use are supplied as the default values in the program.

Land, river and coast are assumed to have the same habitabilities. The only difference between them is that coast and river have traversibilities that are respectively 20 and 40 percent higher than that of land. Sea has a habitability of zero, and initially a traversibility of zero. However, when technology reaches a high enough value, the traversibility of sea switches to a value much higher than that of land. The traversibilities (and habitabilities) of land/river/coast do not change at all with technology. This reflects the notion that, over the period we are interested in, roughly 3000 BC to 1 BC, although movement on land improved somewhat, the really significant change was the opening up of sea transport.

Having set up the topography as above, click the button to populate all regions.

Check the Verbose box, to get a display of the status of each region (you may need to move the land to the middle of the map display, so you can see it in verbose mode).

Press Step, to calculate the scale of each region. Compare 'Italy' with the 'Nile delta' (the region of river adjacent to the 'Mediterranean'). You should find that the Nile delta has a higher scale and consequently higher potential technology than Italy (specifically, 0.41 for the Nile delta, 0.142 for Italy, see below).



Now press the Run button and allow the simulation to run till the values for each region have pretty much stopped changing. You should find that Italy has overtaken the Nile delta (potential technologies of 1.739 for Italy, 1.489 for the delta, with both regions probably having reached their potential). The diagram below shows how the development levels of the different regions (Italy, Egypt, Mesopotamia [i.e. Tigris-Euphrates], Levant [i.e. coastal strip at east end of Mediterranean]) change during the run.



Obviously, this model is very crude in terms of the values assumed and the way we have laid out the topography. However, it demonstrates the basic points referred to above: that, with respect to development, Egypt had an initially favoured position and that this advantage shifted elsewhere as technological growth changed the sea from an insulator to a conductor of human interaction.

What happens in the simulation is that, as technology grows (in Egypt and elsewhere), it passes the level that opens the sea up to marine transport. At this point, the regions bordering the Mediterranean receive a boost in scale and in technological potential. For Italy, being surrounded by sea was previously a disadvantage but now becomes an advantage.

If you want to follow the detailed steps by which this change comes about, pause the simulation, click on Clear Population then Populate All again, and just press Step repeatedly.

• You may like to create more realistic representations of world topography, including additional terrain types, and experiment with different values for traversibility and habitability.
• You could also extend this simulation to model the later shift of advantage from the Mediterranean to the Atlantic rim, once technology growth opened up the ocean.

Italy is not the only land sticking out into the Mediterranean. Greece also does so, and the development of civilisation there preceded that on the Italian peninsula. This reflects its greater proximity to the original centres of civilisation in the near east. See the map below.

View Larger Map

Experimentation with development

This program is for exploring some of the ideas in my last post. (Scroll down for explanation.)

(No program? See only a red X? You need to install the Java Runtime Environment (JRE). Click here.)

The above program allows you to investigate how scale and development depend on topography.

The idea is that you can create a land-mass with a particular shape and give it a certain population. This allows you to see how scale varies at different points of the land-mass. Higher scale results in greater development of technology, which permits a larger population and greater ease of movement. Since scale depends on population size and ease of movement, this creates a positive feedback. Having set up your land-mass and initial population, you can run a simulation to watch how things develop.

In the program, the world is divided into a grid of square regions. You create your land-mass by 'painting' different shapes (e.g. oval, rectangle) and different types of terrain (e.g. land, river) on the grid. Similarly, you 'paint' the population on the regions. You can add your own terrain types, and, for each terrain type, define the habitability (maximum population) and traversibility (ease of movement) as a function of technological level. Initially, all regions are set to 'ocean' (pale blue colour).

The traversibility of terrain depends on the technology of the source region. Suppose a region X has a given population. This population contributes to the scale of surrounding regions. To work out X's contribution to the scale at region Y, we have to take into account the difficulty of movement from X to Y, which means taking into account the traversibility of each region between X and Y. In performing this calculation, we use the technological level of X to determine all the traversibilities (i.e. not the local technological level of each region). Conversely, when working out Y's contribution to the scale at X, we use the technological level of Y to work out the traversibilities of the intervening regions. The idea behind this is that a region's ability to project itself depends on its own technology not on the technology of the receiving regions. E.g. America's ability to influence, say, Nigeria depends on American technology (internet, TV, airlines) not on Nigerian technology.

To familiarise yourself with the program, try the following (you may want to open a copy of this window so you can follow these instructions and view the program at the same time):

1. First, we need to activate the applet (program). Click anywhere in the program box to do this. The program has controls at the top, and a display area where you can set up land-masses by painting terrain onto the different regions.

2. To see the regions clearly, click on the check box labelled Grid (top right). You can move the display around by dragging with your mouse, and zoom in/out with your scroll wheel.

3. To create an island in the shape of a rectangle divided into 9 regions with terrain type 'land', do the following:
a. Click on the radio button labelled Rectangle (top left).
b. Click on the button labelled Paint (top centre).
c. Make sure the adjacent drop-down box says Land. If not, select it from the list.
d. Draw a 3x3 square in the middle of the display area by clicking and dragging the mouse. If you make a mistake, click the button Clear Terrain (top right) and try again.

4. To set up each region with an initial population of 100, do the following.
a. Edit the field labelled Population to read 100 instead of 1000 (left hand side of control panel).
b. Click the button labelled Populate All (left of control panel). Dots should appear on the square island. The size of the dot in each region represents the size of the population in that region. (If you want, you can add population to one region at a time, by clicking the Paint button next to the population field, then clicking on the relevant region.)

5. To see the status of a given region of the island, right click on it, and select Region Information from the popup menu. A dialog box will appear with the relevant information. 'Population' is self-explanatory. 'Potential' represents the potential scale generated by all the populations in surrounding regions; the potential generated by each population depends on its size, how far away it is, and the ease of movement between the two regions. 'Scale' is the potential scale multiplied by the population of the region in question; e.g. a large population in region B generates a large potential scale in region A, but, if there is nobody in region A, the actual scale of region A is zero. 'Technology' represents the technological and institutional sophistication of the region; this can reach a maximum level that is a function of the region's scale. 'Habitability' represents the maximum number of people the region can support, given its technological level. Finally, 'traversibility' represents the ease of movement across the given type of terrain. In this case, you should find that the region's population is 100, the habitability is 1000, the traversibility is 0.1, and everything else is 0. Click ok to get rid of the dialog box. If you check the other regions, you will find that they are the same.

6. Now let's look at scale.
a. Click the button labelled Step. This performs one iteration of the simulation and results in the scale of each region being calculated as a function of the populations of surrounding regions.
b. Now click on different regions of the square island and view the Region Information again. Where is scale highest? Where is it lowest? Why is this? You should find that scale is highest in the centre, lowest at the four corners, and intermediate in the remaining regions. This reflects the fact that the central region is overall closest to the other regions, while the corner regions are overall furthest away.

7. Next let's simulate the growth of population and technology. The assumption is that population grows asymptotically towards the level set by the region's habitability, while technology grows asymptotically towards a level that is equal to the region's scale.
a. Select the checkboxes labelled Population and Technology. These variables will now be updated at each iteration of the model. (This feature means you can choose independently whether or not to simulate the growth of population and/or technology, making it possible to isolate one factor and see how it behaves.)
b. Click Step, then inspect the information for each region. You will find that the population of each region has grown by the same amount, but technology has grown to different extents depending on the scale of each region.
c. Let the simulation continue until the populations have just about reached the maximum habitability, which is currently 1000. Rather than repeatedly clicking the Step button, you can click the Run button to do this automatically. The slider to the right of the button controls the speed. Move the slider to the left for the simulation to run faster. (If the simulation seems to freeze, move the slider right to slow it down.)
d. When the centre region's population is say 999.99 (check the region information, as above), click the Run button (now labelled Pause) to pause the simulation. Check all the regions. You will find that the technology in each region is virtually equal to the region's scale, and is therefore highest in the centre, lowest at the corners. The actual values should be about 0.429 for the centre, 0.217 for the corners, and 0.317 elsewhere. If you click Run again, these values will change little, as population has pretty well reached its maximum everywhere.

8. The next thing to learn is how to set the traversibility and habitability for a given terrain type.
a. Make sure that Land is selected in the drop-down list and look at the table labelled Terrain Types. The first row should read Technology=0, Traversibility=0.1, Habitability=1000. This means that, for a technology level of 0 or above, the traversibility and habitability of 'land' have the values indicated.
b. Click in the second row of the table, in the column labelled Technology, and type 0.4. Then edit the values in the second row under Traversibility and Habitability to be 0.15 and 1000 respectively. This means that, for a technology level above 0.4, the traversibility of land is now 50 percent higher, 0.15 instead of 0.1. This represents the fact that a certain level of technology brings innovations like the road, horse-and-cart or motor-car, which allow people to get around more easily.
c. You can also change the colour assigned to a terrain type, by clicking on the coloured rectangle labelled Colour, and create a completely new type of terrain, by clicking on the button labelled New. We won't do either of these in this case.

9. Now let's see what difference it makes that a higher technology level produces a higher traversibility.
a. Step the simulation once then check the information for each region. You should find that the scale and technology level of the central region are the same as before, around 0.429. However, the scale of the four side regions should be found to be higher, around 0.356, while the technology level has also increased, to around 0.321. Similarly, the scale of the corner regions should have increased to around 0.235 and their technology level to around 0.219.
b. What is going on here? Well, the technology level of the central region is above 0.4, so for this region the traversibility of Land is higher than before, 0.15 instead of 0.1. This means its contribution to the scale of surrounding regions declines more slowly with distance, so their scale is higher than it was. However, the technology of other regions is below 0.4, and for them the traversibility of Land has not changed. Therefore their contributions to the scale of the central region are also unchanged. Overall, the scale of the central region remains the same, but the scale of all the surrounding regions has increased. (Note that a region does not contribute to its own scale.) This increase in scale of the surrounding regions means their technology is beginning to increase towards the level allowed by the new scale.
c. Click the Run button and allow the simulation to run for a while, then check the regions again. You should find that the situation has stabilised with the technologies of the surrounding regions at the new higher level corresponding to their scale.

10. Now we will allow technology to increase habitability as well. This will create the situation where the technology of all regions goes above 0.4.
a. Pause the simulation. Go back to the Terrain Types table, and change the habitability in the second row to 1500. This represents the fact that a higher technology level produces innovations like farming tools, which allow more people to survive on the same area of land.
b. Step the simulation and check the region information. You should find that things are much the same as before, but the population of the central region has increased slightly, to move towards the new, higher habitability.
c. Continue stepping the simulation and keep a careful eye on the scale of all the regions. You should find that their scale is increasing. The growing population of the central region is making a growing contribution to the potential scale of its neighbours, and hence to their actual scale. The potential scale of the central region remains the same, since the neighbouring populations are unchanged, but its actual scale is increasing in line with the increased population. And as scale increases in each region, technology level follows.
d. Run the simulation for a while, until it reaches a new steady state. Check the state of the various regions. You should find that the technology level of the central region is now around 1.480, while that of the side regions is around 1.101 and that of the corner regions is around 0.773. You should also find that the population of all regions is around 1500.
e. What has happened? Well, the growing population of the central region increased the scale of the surrounding regions, until eventually the side regions broke through the 0.4 barrier. This increased their traversibility and habitability so they made a much greater contribution to the scale of the central region, and its technology grew accordingly. Both they and the central regions also increased the scale of the corner regions to the point at which they too broke through the 0.4 barrier, further enhancing the scale and technology of the other regions. The result was a great increase in technology and population all round.

You should now know the way the program works, and be able to experiment on your own. Some final points to note are:
a. Rather than drawing a rectangle, you can draw an ellipse, line or single cell. Lines have to be drawn from left to right. (Yes, my program is a bit rough, but it does the job, I hope.)
b. If you want to explore the effects of a coastline, it can be tedious to paint the coast manually (changing regions from land to coast). The Outline button can do this for you automatically.
c. The Verbose checkbox causes the grid to be displayed zoomed in, with the details of each region written in. This is convenient if you want to follow the changing numerical values. On the verbose display, P=population, T=technology (maximum possible technology shown in brackets), t=traversibility (at T=0), h=habitability, p=potential scale, s=scale. The pair of numbers at the top of each cell are its co-ordinates (column, row).
d. Each iteration of the simulation involves 3 sub-steps: calculating scale, technology, and population in that order. There is also a sub-step for calculating migration, but this is currently not modelled and does nothing. You can perform one sub-step at a time by clicking the Sub-step button. The next sub-step to be performed is shown in the box to the left of the button.

I will finish with some technical details of the model. In the next post, I will discuss how the above program can be used to illustrate the relative historical roles of Egypt and Rome.

Technical details...

The model involves 3 calculations--scale, technology and population--and a set of constants.

(1) Scale calculation

I take each region (square) in turn and calculate its contribution to the potential scale of all the other regions. Firstly, I set the potential of each region to zero. For each region, the algorithm is then as follows:

a. Call the source region the region now being processed.
b. Set working_potential of the source region to be equal to its population.
c. Set the current region to be the source region.
d. Let current_potential be the working_potential of the current region. Consider each region to north, south, east and west of the current region, in turn, as the target region. If the target region has already had its working_potential set during processing of this particular source region, do nothing (this occurs if potential has been propagated to it by another route, and stops potential being propagated back the way it came). Otherwise, calculate propagated_potential as current_potential x traversibility / (traversibility_threshold + traversibility), where traversibility is the traversibility of the terrain type of the target region given the technology value of the source region (note, not the current region or target region). If propagated_potential exceeds a fixed threshold_potential, set the working_potential of the target region to be equal to propagated_potential.
e. Consider each region whose working_potential was set at the last step, in turn, as the current region, and go back to step d.
f. Once there are no more regions whose working_potential has been set but not propagated to its neighbours, add the working_potential of each region, except the source region, to its potential. Set all working_potentials back to zero.

The above is repeated, taking each region in turn as the source region. The result is a total potential for each region. The scale of each region is then calculated as simply the product of its potential and its population.

(2) Technology calculation

For each region, I calculate delta_technology from the formula, delta_technology = time_step x technology_growth_rate x (technology_constant x scale^technology_exponent - technology). Here, scale^technology_exponent means 'scale raised to the power of technology_exponent'.

The new technology of each region is then calculated as technology + delta_technology.

(3) Population calculation

For each region, I calculate delta_population from the formula, delta_population = time_step x population_growth_rate x population x (habitability - population). In this formula, habitability is the habitability of the region's terrain type given the region's current technology.

The new population of each region is then calculated as population + delta_population.

(4) Constants

I used the following values for the various constants introduced above:

traversibility_threshold = 1
threshold_potential = 10^-6
time_step = 0.1
technology_growth_rate = 1
technology_constant = 1
technology_exponent = 1
population_growth_rate = 0.0001

Introducing development

I wish to discuss development, by which I mean the growth of technology and societal complexity.

The simplest and lowest-tech mode of human existence is that of hunter-gatherers. We can take this as about the zero of development.

There are variations even among hunter-gatherers. The American Indians of the north-west Pacific coast lived in a rich environment, and supported a high population by hunting and gathering. They had villages and chiefs. This contrasts with people like the Kalahari bushmen, who live as isolated, nomadic families and do not produce anything as lasting and ambitious as a totem pole.

Let us therefore propose a zero of development (D) without necessarily being able to point to a society that actually has D=0. Kalahari bushmen and the societies of the Upper Paleolithic must be close, but even they have technology and ways of behaving that an outsider would have to learn and that make their societies at least a little bit 'complex'. Zero development is the 'Adam and Eve' condition, an isolated couple living off the land in complete simplicity and with no technology whatsoever.

While I have characterised development in terms of technology and complexity, these are not independent factors. They are linked in the society's eigenmode. A society with high technology must be complex. Consider the activity involved in a new release of the Windows operating system -- not just the code developers, but the managers, marketers and distributors, the hardware manufacturers, the bankers who process payments between consumers and producers. And while all these people are getting the new software on the streets, they have to be clothed, fed and sheltered, which involves yet more people connected in yet more economic relationships. Conversely, a society that is as complex as that needs high technology, to provide the necessary transport and communications, and to allow a small number of primary food-producers to support the people engaging in all this secondary activity.

We know that a society's complexity is related to its scale (see here for the discussion).

We can therefore say that development is linked to scale in an eigenmode. That is, each societal eigenmode is associated with a definite scale and level of development. Given the scale, we know the society's development level, and vice versa.

This discussion suggests an issue we will have to come back to once we have a basic understanding of development:

• Although technology and societal complexity are linked, it is not clear they are in a direct one-to-one relationship. It may be that, within limits, societies with the same technology can vary in complexity, or societies with the same complexity can vary in technology. When, for example, some societies are described as 'underdeveloped', should we understand by this simply 'low in development', or can society's have a development level that is actually below what they ought to have for their given scale/eigenmode'?

What causes development? The case of the Australians suggests that it is not simply an inevitable consequence of time passing.

The eigenmode concept in itself provides little help. It is essentially static, telling us that societies of a particular scale will be developed to a particular extent, but not how societies actually develop and increase in scale. We need to introduce other ideas.

Consider an island that can be divided into five regions: centre, north, east, west and south. And consider three different situations, as follows:

(a) The central region is populated but the rest of the island is empty

(b) All regions are populated, but impassable barriers prevent people in different regions from interacting with each other

(c) The barriers are lifted and interaction between the regions becomes possible

In (a), suppose the population is in an eigenmode (for the moment, do not worry about how it got there, and ignore the possibility of migration ). The population has a certain scale, which corresponds to the amount of interaction among such a population crammed into such an area, and it has the proper development level that both results from and permits that degree of scale. The population is therefore in equilibrium and there is no apparent reason why it should not remain in the same eigenmode for evermore.

In (b), all the regions, being isolated from each other, are identical. The population in each region can be in the same eigenmode as (a). Again, there is no reason why it should not remain in that eigenmode forever.

In (c), the central region experiences interactions with each of the four peripheral regions. (For the moment, assume that the peripheral regions are not in direct contact with each other and remain mutually isolated.) This raises the scale of the central region (remember, scale is a measure of societal interactivity). It also raises the scale of each region with which the central region is in contact. However, the central region experiences four external contributions to its scale, whereas the other regions experience only one external contribution each.

In (c), therefore, the scale of all the regions will increase relative to (b) and the scale of the central region will increase the most. By the logic of eigenmodes, the increase in scale will be associated with an increase in development. And the central region will end up more developed than each of the others.

If we go back to (a) and allow the possibility of migration, the population in each of the peripheral regions will grow, as people move out from the centre. The growth of these populations will raise the scale of the source region. Rather than ending with a situation like (b) where all the regions end up at the same development level as the original, central region, we will actually have the situation described in (c), where all the regions are more developed than the central region was and the central region is developed the most.

In our example, the central region experienced the most development as a consequence of the assumption that the peripheral regions could interact with the centre but not with each other. More realistically, the peripheral regions might be able to interact to some extent. Nevertheless, the north, say, would still tend to interact more with the centre than it would with the south, which is that much further away. In general, if we divide a landmass up into regions, some regions will be better placed than others to interact with their neighbours, and will have higher scale and development.

To summarise, the ability of a population to expand into empty lands can produce an overall increase in development while the highest increases in development will be in the more centrally located regions.

We therefore have a simple understanding of why the ancient spread of humans across the earth would not result in a planet populated entirely at the D=0 condition but would both allow development to take place and lead to a patchy picture with more development in some areas than in others. The development of each region would reflect its centrality and its ease of access to other regions (e.g. regions up and down a river would have more interaction and development than regions with a desert between them).

I want to finish with a question, which takes us more deeply into the issues and which we will have to tackle in later posts.

Let us think back to situation (c). Immediately after the barriers are lifted (if we imagine this hypothetical scenario), the population in each region will have the same technological level as before but can interact with more people (i.e. those in neighbouring regions). Interacting with more people is enough to increase scale. However, that then increases development/technology, and, in general, the increase in technology will itself tend to increase interaction. E.g. development could mean the ability to grow more food and support more people or it could mean better transport allowing people to interact over longer distances. Therefore, the development that results from increased scale will in turn produce an increase in scale. This increase in scale will then generate more development, and so on.

What will happen? Two things are possible. Either increases in scale and development will continue to reinforce each other without limit. Or diminishing returns will set in and the increases in scale and development will peter out, eventually reaching equilibrium in a new eigenmode.

The long term prospects for societal development therefore become a question of the nature of the relationship between scale and development. The case of the Australian aborigines suggests that, at low levels of scale and development, diminishing returns dominate and equilibrium is reached. With the world as a whole, the situation is less clear. There has obviously been positive reinforcement to date, but as global scale and development continue to increase their relationship may move into a region of diminishing returns. After all, one might imagine that there are limits to how many people earth can support, and to transportation speeds and communications bandwidth, all of which would set a cap to scale and development. If we get off this planet into outer space, we could break through those limits into a region of continuing positive reinforcement, but what if diminishing returns set in first, causing us to stagnate before we fully master space travel?

Had Australia been the earth's only landmass, it seems humanity might never have developed beyond the level of the aborigines and never got into space. The earth's landmass is much bigger than that, but the question we would like to answer is, is it big enough?

To all corners of the earth

Long before Europeans developed an ocean-going capability, humans had reached the furthest corners of the earth. This included not only every continent but even the remote Easter Island, thousands of miles from habitation in every direction. Some other Pacific islands, such as Christmas Island, showed signs of human settlements that had died out before Europeans first arrived.

This tells us something about people. Humanity, like nature, abhors a vacuum. Humans do not naturally stick together and congregate in large numbers. There is rather a continual outward pressure as people try to get away from each other.

The stone age lifestyle, based on hunting and gathering, requires a large amount of land area per person. If human numbers were going to grow, people had the choice of staying where they were and developing more advanced food production technologies (to support more people from the same land area) or move steadily out into virgin territory. In reality, people did not make a conscious choice. Moving to new territory would have seemed like the only option, and it was only when the world had filled up that humans had to confront and solve the problem of feeding more people from the same area of land.

The hunting-gathering lifestyle naturally draws people on. Rather than moving a little each day, hunter-gatherers tend to stay in one place for a while and then relocate in one big jump. It has been said they eat their way out of camp. The longer they stay, the further they have to travel to find new food sources. In a matter of weeks, the daily round trip exceeds twenty or thirty miles, and it becomes necessary to make a major move.

This outward pressure can take people a long way in a short time. It often seems to be assumed that for early humans to migrate, say, a thousand miles would have taken many generations. Yet even in the stone age, people could in principle have travelled from one end of the earth to the other in their own lifetimes. Consider that the circumference of the earth is roughly 25,000 miles. For a stone age person with an active life of 25 years, it would be necessary to travel 1000 miles per year, or under 3 miles per day, to cover this distance. People who follow stone-age lifestyles today can easily do that kind of mileage.

Of course, humans would not have gone directly around the equator, with several oceans in the way. Nor would they have walked directly across the continents, where the way can be barred by mountains and deserts.

Their easiest route would have been along the coastline. Since people reached Australia very early, they may have had simple boats from the very beginning, as they came out of Africa. This would have sped them on their way.

At the beginning of the upper paleolithic, 40,000 years ago, sea level was lower than it is today. This left a continuous land route from Africa to the Americas, with no ice barriers. Here is a map of the world at that time:

The above image was created using a program at the site of Sebastien Merkel. This allows you to enter a given sea level and view the resulting map. Information about how sea level has changed over time is available at this site.

With sea level as above, travel to Australia still required crossing open water. However, this could be done by island-hopping, with each island visible from the previous one. Only the final crossing, of about 100 miles, required a leap into the unknown, but Australia was a large target and people could have spotted it during short sea trips to and from their home base. (Humans could also have arrived at Australia via New Guinea, which was then connected to Australia by land. However, it is believed they did not take that route and New Guinea was settled after Australia.)

I do not accept that humans only gradually diffused through the world. I believe that, following initial speciation in Africa, humans exploded across the planet, so that the world was occupied almost simultaneously at around 40,000 years ago.

We can estimate how long it would have taken people to spread to fill every continent.

Modern hunter-gatherers live at densities of around 1 person per 15 square miles (compared with 67,000 persons per square mile in Manhattan). However, they tend to occupy marginal environments, the best land having been taken over long ago by agriculturalists. Average population densities in the old stone age might have been higher, perhaps as high as 1 person per square mile. Since the habitable area of the world is about 15 million square miles, the total human population of the world, with paleolithic technology, would have been somewhere between 1 million and 15 million.

Let us define the following:

A =	total area of the world habitable by hunting and gathering (say, 15 million square miles)
ρ =	population density of hunter-gatherers (say, 1 person per square mile)
T =	time for an unconstrained human population to double in numbers (say, 10 years, which was observed on Pitcairn Island during the first thirty years after it was settled by the Bounty mutineers)
t =	time

The number of hunter-gatherers that would saturate the world is A ρ, while, starting from a population of 1 (a pregnant woman), the number of humans after time, t, would be 2^t/T.

The time taken to populate the world is therefore given by

A ρ = 2^t/T

or

t = T log₂(A ρ)

Putting in the numbers suggested above, this comes to about 240 years, for humans to cover the planet.

Of course, this figure should not be taken literally. It is just to give us a feel for the issue. A larger starting population (1 pregnant woman is a little unrealistic) would reduce the time, as would a lower population density, while a longer doubling time would increase it. The point is that humanity's spread through the world does not need to have taken a hugely long time, and in fact it is unlikely that it took a hugely long time.

Note that, once the world was fully populated, population growth would have had to stop until technological improvements allowed more people to be supported from the same land surface. Modern hunter-gatherers are adept at keeping their numbers in tune with their environment, or in fact in tune with what the environment can support in its leanest years. There would therefore have been a short population explosion, followed by near-stagnation (until the development of farming).

Three factors would have slowed down human expansion relative to this simple picture:

1. Obstructions, such as deserts, mountains and waterways. Crossing the Amazon at its mouth, for example, is like crossing the English channel.
2. Varying ecological conditions. People who knew how to exploit the flora and fauna of one environment (grassland, forest, seashore) would have had to learn new skills to survive in a different one.
3. Presence of other hominids. Neanderthals and other hominids already occupied the lands outside Africa. Modern humans would have been competing with them for resources, and might for some time have been kept out of their territories by fear or force.

Nevertheless, people could still have reached every continent in a short time, even if actually filling the continents was slower than the simple argument suggests. Having boats and following the coastline, humans would have remained within a familiar environment while being able to bypass obstacles. As for conflict with other hominids, it might even have been a factor drawing the more capable humans onwards.

The problem of the Australians

The (aboriginal) Australians worry me.

These folks settled their continent 40 thousand years ago -- or, as many scholars now believe, 65 thousand years ago.

Yet in all that time, they failed to develop beyond the old stone age. They developed no agriculture, metal, or permanent settlements. They scarcely even had clothing.

If Australia had not been discovered from outside, there is every reason to suppose its inhabitants might have remained at the stone age level for ever more -- or until the sun burned itself out.

It is frightening to think that a branch of the human species could have continued in this way forever, never realising its potential, and never knowing anything of the science and technology we have developed.

If the Australians had been typical of humanity as a whole, the human story would have looked something like this...

We can attempt to explain the Australians' lack of development in terms of dark age theory.

Scale (a measure of interactivity) is a critical determinant of a society's institutional and technological complexity. Low-scale societies are inevitably simple, as small groups of isolated people cannot support elaborate economies and political systems. Stuck at the end of the world's main landmass, and separated from it by a lengthy sea-crossing, Australia experienced low scale. It was exposed to few influences. The effective size of the population within reach, i.e. the scale, was too low to sustain development beyond paleolithic levels.

We can refine this argument. For an isolated region, scale depends on the population contained within that region. But the population that exists within the region depends on the technological level (because sophisticated food-production techniques support more people on the same amount of land). And the technological level depends on the scale. What appears to have happened in Australia is that humans achieved an equilibrium, or eigenmode, where technology supported a population that generated enough scale to support that level of technology...and no more. This eigenmode, i.e. self-consistent solution to the problems of social existence, was quite stable and there was no reason why the Australians should ever have broken out of it.

This argument suggests several points of concern:

1. New Guinea is also small and isolated, yet its inhabitants achieved the neolithic level, unlike the Australians. New Guinea was actually joined to Australia, as the continent of Sahul, until about ten thousand years ago, so why did the Australians not achieve the sophistication of New Guinea? The Polynesian islands are even smaller and even more isolated, yet many had chiefdoms, surpassing New Guinea in sophistication, let alone Australia. We might be able to explain this in terms of humans bringing the relevant technologies and institutions to these islands, so that they were already in a more complex eigenmode. But why were people not able to carry this eigenmode to Australia?
2. If Australia was too small to support developmental growth like that of the Afro-Eurasian and American world islands, it suggests that, had the world's landmass been more broken up than it is, then humans would not have been able to develop anywhere. The fact that humans have developed must then be seen, in part, as a geographical accident, not an inevitable result of human talents.
3. Australia is a big place. If we are saying Australia was too small, then just how big does a continent have to be before humans are able to develop beyond the paleolithic? It is true that Australia has large areas of desert, but the Nile Valley is surrounded by desert. And climatic conditions in Australia have changed a lot over the millennia. Why could civilisation not have developed along the valleys of Australia's Orange or Murray-Darling rivers? If we are saying environmental conditions here were never quite right, then just how flukey was the development of civilisation elsewhere?
4. If Australia reached equilibrium at a technological level commensurate with its size, then could this be the fate of the world as a whole? Will we stagnate at a (much higher) technological level where the planet is able to support just enough population to sustain that level of technology? Could the human race flat-line until the sun goes supernova or something else wipes us out?

The point of these questions is not to deny that Australia's lack of development can be related to its situation, but to show some of the complicating issues that a full theory must take into account and be able to explain.

We should also note two other points:

1. There is no reason to think, as some might, that the aboriginal Australians lacked the mental capacity of humans elsewhere. All humans today are members of a single species, descended from common ancestors living at most 100-200,000 years ago. On an individual level, aboriginal Australians operate perfectly competently in technologically advanced society; high achieving aborigines include academics, politicians and writers. Australian traditional culture is also sophisticated in its own way; languages and kinship systems are more complex than those of 'advanced' societies; art and mythology are well developed; the boomerang is a clever device; aborigines found honey by gluing feathers to bees, slowing them down so they could be followed. [As far as dark age theory is concerned, the sameness of humans everywhere and at all times is axiomatic. Only when it has proved impossible to build an adequate theory of history on that assumption will the axiom need to be abandoned - we are nowhere near that yet.]
2. Australians seem to have taken up agriculture at various points, then abandoned it again. Therefore, the situation is not as simple as achievement of an everlasting equilibrium. Stagnation was not total, and perhaps changing climatic conditions sometimes elevated scale sufficiently to promote development in some areas.

Finally, there is the argument of Jared Diamond, in Guns, germs and steel, which is that the move to neolithic (farming) lifestyles depended on the availability of crop plants and domesticable animals. While Eurasia had barley/wheat/rice on the one hand and sheep/cattle/horses/pigs on the other, suitable equivalents in the rest of the world were lacking.

Diamond's argument comes back to the issue of continental size. There is a well-known relationship between the size of an island/landmass and its biodiversity. Hence, the largest continent, with the greatest biodiversity, inevitably had the most suitable species for agriculture. The second largest continent was a runner up, while the smallest continent had too litte variety to provide species with the right characteristics for human exploitation.

This argument is not endorsed by dark age theory, which starts from the assumption that history is a sociological phenomenon, not dictated by random background features such as climatic conditions or availability of domesticable species. In dark age theory, necessity is the mother of invention, so that people would be expected to have found ways of supporting complex society if conditions were right for it. Diamond says attempts to use the zebra as a beast of burden have failed, which he suggests helps explain Africa's lack of development. However, over thousands of years the zebra might have been domesticated as the horse was, had people really needed such an animal. Dark age theory looks for explanations in terms of the inherent logic of human affairs, not in terms of chance, external factors. (This viewpoint may be wrong, but we start from it as an assumption, to be abandoned only when it has demonstrably failed.)

Human speciation

I want to discuss why my view of the early migrations of the human species differs from the broad academic consensus.

Firstly, to work out when and how humans came to be distributed through the world, we rely on archaeology and, more recently, genetics. Neither perspective is without its problems.

• Archaeology depends on sites. The discovery of new sites may change the picture. Archaeologists are biased towards a constantly changing picture. Careers are made by saying something new and interesting, not by confirming what has long been common knowledge.
• Genetic dating depends on mutation rates. These are estimated and, since mutations are random and do not occur at fixed intervals, there is an inevitable margin of error. Furthermore, external factors could have an unknown, systematic effect on the mutation rate. If, for instance, the earth's magnetic field weakened, it would allow more cosmic radiation to reach the surface, possibly elevating the mutation rate.

Archaeologists' and geneticists' models of migration history are evidence-based. This sounds good -- surely our models must be based on evidence -- but means they are subject to caprices of evidence discovery, and uncertainties and revisions of evidence interpretation.

My model is theory-based. Rather than considering only direct evidence for the issue in question, it reflects a broader theory of how human societies operate, based on theories and evidence from a wide range of cultures and historical periods. The point is to build a coherent explanation of the whole of history from a few principles. Incompatibility with specific facts or interpretations, which are subject to the vagaries of academic fashion, does not make or break the theory.

This approach is by no means unscientific. The model makes predictions to be tested against reality. It could be wrong. If it continues to disagree with facts that become increasingly well established, it must either change to accommodate the facts or be abandoned altogether.

I say all this because I choose to start my account of history with a big bang -- the sudden appearance of 'true' human beings in Africa 40 kya (kya = 'thousand years ago'), and their near-instantaneous spread to Europe, Asia, Australia and America. I associate this big bang with a newly evolved ability to manipulate symbols, which I believe underlay art, speculative thinking and 'true' language. In the archaeological record, it corresponds to the transition to the Upper Paleolithic, marked by a new sophistication and variety of stone tools.

My view is by no means original -- the association of a biological event, language skills and the beginnings of human ingenuity was the mainstream view until not long ago. However, it disagrees with some major points of the current academic consensus, which are:

1. Modern humans appeared in Africa as much as 190 kya. (Nevertheless, it was long believed, and still is in some quarters, that the emergence of the human species was linked to the appearance of the Upper Paleolithic, which is dated to 40 kya)
2. Australia was settled 65 kya. (This was believed to be 40 kya until the 1980s.)
3. America was settled about 12 kya. (Increasing numbers of archaeologists think this date should be pushed back at least a few thousand years, with some arguing for dates as early as 40 kya.)

The reason I do not like to believe the human species is as old as 190 ky is that it makes the acceleration of recent times look even more extreme. If it took 150 thousand years to make the step to the Upper Paleolithic, but a hundred years to develop electricity, computing and space flight, it seems we really are in the grip of a runaway process and it can be at most a few thousand years before we conquer the entire universe -- something I find hard to accept.

Such an early date for human origins -- and the implied slowness to move outside Africa and colonise the rest of the world -- also makes humans look much less adventurous than I believe we are.

My prejudices therefore lead me to identify human speciation with the beginning of the Upper Paleolithic -- the point from which growth of mastery over this planet seems to have been almost continuous.

This belief in a link between new technology and a new species can nevertheless be very reasonably criticised. Oppenheimer points out that there is a vast technological gulf between industrial societies and, say, the tribal societies of highland New Guinea, yet both are composed of fully modern humans. There is no compelling reason why the technological revolution of the Upper Paleolithic should have been associated with a step forward in biological evolution.

So I cannot really justify my choice of starting point. All I can say is, let us run with it and see where it gets us.

Genetic trees and the peopling of the world

I would like to go back to discussing how humans spread through the world.

Numerous books have appeared on this subject in recent years, stimulated by new techniques of genetic research. I find these interesting but I question their claimed definitiveness.

Imagine photocopying documents, where you photocopy the photocopies, perhaps making dozens of copies from each copy. In the course of this, blemishes will occasionally appear. When you photocopy the blemished copy, the same blemishes will be reproduced in all subsequent copies. If you look at two copies and see that they share the same blemish, you know they must "descend" from the same original, blemished copy. If you also see that the two copies have additional, different blemishes, and you know how often blemishes arise--say, once every thousand copies--you can work out how many copying generations it is since the copy from which they are descended. E.g. if they differ by three blemishes, it must be three thousand generations since the "ancestor" photocopy passed through the photocopier.

Photocopier genetics

A similar principle has been used to determine the family relationships between human populations.

It does not work with ordinary DNA, which is mixed and matched at every generation (half from each parent) by sexual reproduction--as if the photocopies were cut in half and taped together in new combinations, so that blemishes are spread around and clear distinctions between lines are not maintained.

Instead, it relies on parts of the genome that do not undergo recombination. These are mitochondrial DNA, which people inherit only from their mother, and the Y-chromosome, which is passed down intact (or almost so) from father to son. When these genes are passed down, copying mistakes occasionally occur, so that people today show many variations deriving from ancient errors. As with photocopier blemishes, such variations make it possible to estimate how long ago any two people shared a common ancestor (female ancestor for mitochondrial DNA and male ancestor for the Y-chromosome).

Stephen Oppenheimer, in his book Out of Eden: the peopling of the world, describes how geneticists have used this principle to trace the ancestral connections between human populations and to work out how long ago they split off from one another.

The message he likes to convey is that archaeologists and historians were fumbling around in the dark until these new genetic techniques came to shine the clear light of day on their disciplines.

For instance, the geneticists have apparently instantly and conclusively resolved an issue that archaeologists might have been arguing about until kingdom come. While archaeologists once saw changes in the distribution of pottery as indicating the wholesale movement of the people who produced the pottery, more recently they have argued that people remained put and only styles and technology spread from one region to another. The genetic evidence seems to show that, indeed, most modern populations have been where they are for a long time and the formerly hypothesised migrations never took place.

Nevertheless, I suspect that, in the fullness of time, the geneticists' arguments will come to seem as problematic as those of the archaeologists' and historians', which themselves once seemed so obvious and compelling. It will be revealed that there are other ways of interpreting the results and doubt will creep into this young discipline where today certainty is supreme.

After all, according to Oppenheimer, the entire non-African population of the world is descended from a single group that left Africa via the Arabian peninsula about 80,000 years ago. Yet the notion that, over the entire lifetime of the human species, no other people had the idea of leaving Africa is hard to credit. Right there lies a reason for having doubts about the completeness of the genetic picture.

Even if the geneticists prove to be completely correct in their picture of ancient population movements, there remains a vital role for historians and archaeologists in advancing understanding of the past. The things that make, say, Britain what it is today are Magna Carta, the Elizabethan Age, the Civil War, the Industrial Revolution, and so on--i.e. sociological things that are not passed down in our DNA. History and society, the concerns of this website, are the subject of cultural, not genetic, transmission, and the connection between genes and culture is probably looser than people like Oppenheimer tend to assume.