Modern governments regularly take detailed censuses to ensure that they have accurate information about population size and composition. In the UK the census in its near-to-modern form began in 1801 and has taken place every 10 years since, with the exception of 1941. Most industrialized countries have their own versions of censuses while others, such as Finland, update their official population count every day in response to daily registrations of births and deaths. Governments need to know how many people live in their territories in order to plan taxation, infrastructure, housing, etc.
Given the pressing need for up-to-date population statistics in the modern world, it is logical that we must approximate population size and density in the past if we are to reconstruct ancient social organization. But estimating ancient population size can prove tricky, as we often lack reliable data that can be related to demography. Even where historic censuses exist they can rarely be directly translated into population densities. The Domesday Book is perhaps the most celebrated historic ‘census’ of all; an exhaustive survey of England, ordered by William the Conqueror following his victory at the Battle of Hastings. However, even a detailed survey such as this cannot be considered entirely reliable for the purposes of reconstructing population size; only heads of household were counted and entire cities were excluded from the survey.
In the absence of reliable census data for the past, how can we reconstruct population size? Archaeological demography is a growing field which uses artefactual, rather than written, remains to reconstruct ancient population patterns. It was the subject of a lively session at the World Archaeological Congress in Kyoto this summer, with a number of different approaches to demography presented in the session. Archaeological demography relies on the principle that for a given area of fixed size, we would expect the density of artefacts found within it to be proportional to the density of the population. Thinking in modern terms, we see larger rubbish heaps on the edge of a busy city than we do in a rural location. Through counting the change in density of artefacts over time we can observe changing population size and density. The method is not perfect; for instance it is entirely possible that a social change could occur that would mean that a society begins to use pottery at a faster rate than previously, independent of population change. Likewise, the method only allows relative population patterns to be reconstructed; we cannot compare the demography of two independent regions using this method. However, if we want to approximate demography in the past, which we should do if we want to answer broader questions of social evolution, then we have to try to say something with the available data. As Peter Turchin discussed in a previous post, we need to abandon negativity and get on with things!
While most demographic methods produce relative population trends, an alternative method is to approach the problem of ancient population size from a different perspective. Modelling the carrying capacity (maximum number of people who could be supported by the natural resources in a region) provides us with absolute numbers of individuals, rather than simply relative trends. Again, this is not a perfect method as it only provides an upper limit to the population, and populations do not always reach this limit. However, the beauty of this method is that it allows us to make comparisons of potential demographic trends between regions. The Seshat Databank contains a wealth of agricultural data that can be used to model carrying capacity. We are currently working through these variables and using them to estimate crop yields for each region of interest over the past 10,000 years, using the method developed by Currie et al (2015).
We are using modern agricultural studies to inform us of the benefits of particular farming practices, such as the use of manure as fertilizer. The agricultural data collected by the Seshat team informs us as to when and if these agricultural techniques were practiced in the past. In this way we are able to adjust the yields predicted by climate-based crop models to produce crop yield estimates that take account of farming practices in the past. These yields will then be translated into total carrying capacities for each region. This method provides a good counterpoint to the other demographic methods available; it is robust to the change in settlement patterns that could masquerade as demographic change and, crucially, it gives us the absolute population numbers that we really need if we are to reconstruct social processes in the past.
Population size is determined by the availability of food resources. Agricultural techniques – such as terracing – improve overall yields and lead to increases in population density.
The use of the systematically-collated agricultural data within the Seshat Databank to model carrying capacity in the past illustrates the utility of the databank in allowing us to truly make comparisons between the historical trajectories of different regions. This is a real advantage, as typically archaeological estimates of ancient populations are not produced in a manner that allows inter-regional comparison. By contrast, population estimates produced from the agricultural data can be compared between different regions. We need comparable data if we are to undertake comparative archaeology, and the Seshat databank makes this possible.