It is well documented that Thomas Robert Malthus’ An Essay on the Principle of Population greatly influenced both Charles Darwin and Alfred Russell Wallace’s independent conception of their theory of natural selection. In it, Malthus puts forward his observation that the finite nature of resources is in conflict with the potentially exponential rate of reproduction, leading to an inevitable struggle between individuals. Darwin took this basic premise and applied it to nature, as he notes in his autobiography:
In October 1838, that is, fifteen months after I had begun my systematic inquiry, I happened to read for amusement Malthus on Population, and being well prepared to appreciate the struggle for existence which everywhere goes on from long-continued observation of the habits of animals and plants, it at once struck me that under these circumstances favourable variations would tend to be preserved, and unfavourable ones to be destroyed. The results of this would be the formation of a new species. Here, then I had at last got a theory by which to work.
The interaction of demographic and evolutionary processes is thus central in understanding Darwin’s big idea: that exponential growth will eventually lead to a large population, and in turn will generate competition for natural selection to act on any heritable variation which conferred a greater fitness advantage. Under these assumptions we are able to interpret the evolutionary record of most species by appealing to two basic causal elements: genes and the environment. As we all know, in most cases the environment generates selection pressures to which genes operate and respond. For humans, however, the situation becomes more complicated when we consider another basic causal element: culture. The current paper by Richerson, Boyd & Bettinger (2009) offers one way to view this muddied situation by delineating the demographic and evolutionary processes through the notion of time scales:
The idea of time scales is used in the physical environmental sciences to simplify problems with complex interactions between processes. If one process happens on a short time scale and the other one on a long time scale, then one can often assume that the short time scale process is at an equilibrium (or in some more complex state that can be described statistically) with respect to factors governed by the long scale process. If the short time scale and long time scale interact, we can often imagine that at each time step in the evolution of the long time scale process, the short time scale process is at “equilibrium.” A separation of time scales, if justified, makes thinking about many problems of coupled dynamics much easier.
The potential problem emerges when you consider the rapid pace of cultural evolution: is there even a separation between demographic and cultural evolutionary time scales? Of the data available to us, it seems throughout most periods of human history there appears to be a time lag. For instance, the Acheulean lasted for around a million years, and even during the Holocene the first states emerge approximately 5,000 years after the origins of agriculture. However, as the authors note, during the modern Industrial Revolution, large scale changes in culture occurred on the same time scale as population growth rates. This also leaves room for the potential situation of culture evolving even more rapidly than population growth. From these observations they argue the most important factor on time scales of a millennium or greater is the rate of intensification by innovation, not population growth:
Thus in the conventional Darwinian picture population pressure plays an exceedingly important role but on a short time scale. The struggle for existence can be taken for granted. Evolution plays out as adaptive innovations on the long time scale increase the carrying capacity for the environment for the population in question […] For example, we do not expect to see any systematic evidence of increased population pressure immediately before major innovations. Population growth is likely to result from innovations, not the other way around, on the time scales that we normally observe in the archaeological record.
Richerson et al use these links between demography and innovation rates to consider three periods of human history: the late Pleistocene, the Holocene, and modern times. The period I’m going to focus on is the Pleistocene. Here, large-brained hominins existed in Africa and west Eurasia for approximately 150,000 years with relatively slow rates of technical innovation. Then following the last glacial period around 50,000 years ago, significant modernisation began to take place – albeit limited to certain geographical locations. Prior to this we do instances of complex tools and symbolic inventions in Africa, yet these cultural advances were frequently followed by retreats. To help explain these patterns, Richerson et al ask the following:
What limited “progress” at different periods of our evolution? Was environmental change leading the trajectory by means of a more or less monotonic increase in selection for larger brains and increased cultural sophistication? Or were genes or culture slow to respond to selection pressures that were exerted from the beginning of the Pleistocene or even earlier?
One potential solution lies in genetics: that despite having big brains, our ancestors simply lacked some crucial cognitive ability. After all, we know brain size is not necessarily the overriding feature of complex cognition. It could come down to differences in development, neuroantomical organisation, cortical gyrification, cytoarchitecture etc. We know in the cases of transcription factor-encoding genes, like egr1, social information can lead to changes in brain-gene expression, brain function, and social behaviour throughout the lifetime of an organism. Genes also influence the social behaviour of an individual by effecting brain development and physiology. A commonly cited candidate is foxp2: it’s implicated in underlying many socially embedded behaviours, with some proposing the human variant underwent a relatively recent selective sweep of ~42,000 BP. This is certainly congruent with claims by the likes of Richard Klein, in which this genetic change took place approximately ~50,000 BP.
These issues aside, Richerson et al refer to environmental conditions as being the primary rate-limiting factor on cultural innovation during the Pleistocene. Specifically, the authors refer to instances of high-frequency high-amplitude climate variation known as Dansgaard-Oeschger cycles:
The apparent intensification of the Dansgaard-Oeschger cycles over time may have driven much of the evolution in human cultures in the last 250,000 years. The very intense Dansgaard-Oeschger cycles after 60,000 years ago are a potential explanation for the spread of modern humans out of Africa and the evolution of mode 4 toolmakers in western Eurasia. But why would cold, dry, variable environments have favored increases in the cultural sophistication of humans?
At first, it may appear that fluctuating and variable environments would impede rather than favour human populations. When you factor in culture, however, our species are in a unique situation to exploit an environment far more rapidly than other competing carnivores. This competition may well explain why humans were found at such low-levels prior to 50,000 years ago: even with a certain degree of technical sophistication, humans were unable to compete with large animals that are specially adapted to hunting. We can contrast this situation with contemporary cheetah and wild dog populations: competition with larger predators, such as lions, have forced these smaller predators from habitats abundant in medium and large herbivores. As a consequence, both cheetahs and wild dogs are found at relatively low population levels, displaying low levels of genetic diversity – a feature they share with us.
Unlike cheetahs and wild dogs, one suggestion for humans being able to overcome their low population levels, and move out of their narrow niche, is because our cultural and behavioural sophistication allows us to navigate these complex environmental situations:
Humans could probably have tracked the ever-changing kaleidoscope of large animal prey more easily than their competitors (lions, dogs, wolves, and hyenas). Humans could find the dynamic, ephemeral situations where an herbivore population was temporarily out of equilibrium with their prey and exploit the windfall before our competitors could figure out the rapidly changing ecosystems.
Social organisation and weapon technology are also novel ways to reduce competition. For instance, hunting or trapping the predators themselves would be an active way of getting rid of them. Generally though, the authors provide three instances where hominins produced adaptive solutions to the challenges presented by these dynamic glacial environments: 1) mode 3 toolmakers were able to routinely hunt herbivores, and be marginally successful, even when in competition with other competitors; 2) Increasing social complexity could overcome the challenge of uncertainty that’s inherent to a noisy environment. Here, the larger and denser West Eurasian populations of the Upper Paleolithic may have discovered a better solution to food security problems that eluded Middle Paleolithic people; 3) The ability to maintain a cultural evolutionary system that is responsive to intense millennial and submillennial scale variation.
Based on these points, Richerson et al build up a scenario whereby prior to 50,000 years ago human populations were kept small, probably due to competition with large predators. For humans, another consequence of having a small population is the Tasmanian Effect (which I discussed here): where complex technologies may be lost in small populations by chance. When the Dangaard-Oeschger cycles began to increase in frequency, culture gave humans an adaptive advantage in a situation their competitors could not exploit. Still, the palimpsest of mode 3 and mode 4 industries at different locations and points in history were subject to highly variable conditions. When these were favourable, hominin populations could reach sizes capable of sustaining certain levels of sophistication. However, as the authors note:
If environments remained poor enough for long enough, a population that had achieved Upper Paleolithic complexity might suffer a Tasmanian-style loss of complexity and drop back to the Middle Paleolithic equilibrium. This sort of dynamic is sometimes called a hysteresis loop. Rather than reacting directly to an environmental change, a population will have a strong tendency to remain either large or small. Given a sufficiently large and persistent increase in K [carrying capacity], it will jump to a higher equilibrium, where it will persist under deteriorating environmental conditions under which the high equilibrium can be sustained but cannot be attained by a population at the low equilibrium. Time lags will be built into the cultural system. Complex elements of technology will not be gained or lost instantly.
Richerson et al also refer to another process that might contribute to the palimpsest mixture of mode 3 and mode 4 tool traditions in Africa. Given their larger and greater levels of sophistication, human populations could have overhunted. The subsequent collapse of prey populations therefore cause human populations to shrink, which in turn may revert their production capabilities to mode 3 tools. This then allows the prey populations to recover. In west Eurasia, though, hominin populations were quite capable of maintaining mode 4 tool kits for long periods during the upper Paleolithic. One explanation for this is their location: they were situated on the maritime end of a huge Mammoth Steppe biome:
Both Neanderthals and anatomically modern humans lived in central Siberia, at least during the favorable interstadial periods, but apparently never penetrated the Beringian region… [the] fuelwood shortages in the Verkhoyansk mountains on the western boundary of Beringia formed an impenetrable barrier to human settlement until substantial climate warming… Big game animals depended on heavy fur, not fires, as protection from cold and probably spread readily across the Verkhoyansk barrier. Thus Mammoth Steppe hunters would have had what amounted to a large natural protected reserve in Bergingia.
Human populations near these natural reserves could exist at high levels because they did not drive down the populations of Mammoths, and other large game, to low levels. This is compared to Africa, South and East Asia and Australia – all of which consist of warmer climates and no natural refuges for large game. West Eurasia then, seems to be in a unique situation at this point in history, with human populations being able to maintain a large carrying capacity and subsequently sustain mode 4 technologies. Of course, there are alternative explanations as to why hominins were able to maintain a complex culture during the particularly inhospitable parts of the Dansgaard-Oeschger event. One example is that an increased frequency of these cycles prior to the expansion of modern humans selected genes allowing for higher rates of cultural innovation (in contrast to Richard Klein’s proposed mutation).
Aside from the issues raised, the maximum rate of innovation is not necessarily dependent on population density or size. Richerson et al point to several rate-limiting factors, including the possibility of delayed social innovation retarding the rate of technical progress. The gene-culture coevolution process is another instance where the need for major genetic evolution is an impediment to the rate of cultural evolution. And what about the possibility of innovations occurring in punctuated bursts? That is, if large technical revolutions are the basis for change, then the assumption of a smooth innovation rate is incorrect. Their last point, and what I think is an important one, argues the number of individuals may not be the most important demographic factor contributing to the Tasmanian Effect. Rather, it’s the ratio of old to young adult individuals:
Caspari and Lee (2006) used dental wear to roughly estimate the ratio of old to young adult individuals in hominin fossil death assemblages from the Australopithecines to the Upper Paleolithic. Slight increases are evident at each major change of taxa with one major exception: Upper Paleolithic people had an old to young adult ratio of about 2.1, whereas the European Neanderthals had a ratio of only 0.35. In Southwest Asia, where Neanderthals and anatomically modern humans coexisted using Mousterian technology, the small dental sample suggests that both populations had an old to young ratio of about 1… Caspari and Lee suggest that a cultural rather than genetic change was responsible for this difference. The changes are reciprocal in that older adults can accumulate and transmit more culture than young adults and can accumulate more individually acquired knowledge. Caspari and Lee’s analysis lends weight to the idea that large-brained hominins of the late Pleistocene had bi- or multi-stable population dynamics.
All of these are potentially salient factors, but as the authors themselves state:
Our objectives here are limited. We cannot provide a thorough review of the literature on paleodemography, paleoecology, and paleoanthropology. We realize that many elements of our scenarios rest on controversial evidence if not rank speculation. We do hope to clarify the relationship between demographic and cultural evolutionary processes so that we can formulate better hypotheses about several of the puzzling aspects of the paleoanthroplogical record as we currently understand it.
Richerson PJ, Boyd R, & Bettinger RL (2009). Cultural innovations and demographic change. Human biology; an international record of research, 81 (2-3), 211-35 PMID: 19943744