Food Production

Multicausal Theories

The recovery revolution has spawned complex multivariate models which take into account the emerging realization that many early Holocene hunter gather societies were more complex and well preadapted to food production before anyone started planting wild cereal grasses or penning animals. For example as recently as the eighteen century C.E. the Kumeyaay Indians of southern California reduced the risk of starvation by domesticating their landscape. They lived in semiarid valleys encouraging the growth of wild grasses by burning of harvested stands then broadcasting some of the seed over the burnt ground. They created groves of oaks and pines by planting edible nuts at high elevations and planted agave and other desert plants in suitable habitats. In this way they flourished by means of a complex mosaic of manipulated wild plants.

Population and Resources Theories

All of us take risks in our lives and try to protect ourselves against the dangers of a sudden catastrophe. This is why wise investors diversify their holdings and why parents carry life insurance polices. This is known as risk management. In the case of prehistoric people it meant minimizing anything that would threaten long term survival. All environments however favorable involve some form of risk for foraging societies drought cycles ling cold winters and unpredictable floods to mention only a few. Often people respond to these risks by moving away or by developing new storage and food preservation technologies.

One logical and straightforward solution to rising population resulting food shortages or risks factors may be to go one step further to cultivate familiar plants domesticate common prey so that people can draw on familiar stored food during scarce periods. In other words food production arose as a result of risk management as a way of increasing food supplies.

Ecological Theories

Proponents of ecological models talk of so called opportunities for the introduction of food production of people turning to superior local resources when the moment arrived. In this kind of scenario some resources say wild wheat or barley or wild oats are seen as attractive. People use then more and more to the extent that they eventually become domesticated. Ecological theories are founded on the assumption that human societies are cultural systems operating within much larger environmental systems.

The classic exposition of this point of view is that of University of Michigan archaeologist Kent Flannery who works in Mexico’s southern highlands. He discovered that between 8000 and 4000 B.C.E. the local people relied on five basic food sources deer rabbits maguey legumes and prickly pears for their sustenance. By careful prediction of the seasons of each food they could schedule their hunting and gathering at periods of the seasons of each food they could schedule their hunting and gathering at periods of abundance and before animals gained access to the ripe plants. Flannery assumed that the southern highlands and their inhabitants were part of a large open environmental system consisting of many subsystems economic botanical social and so on the interacted with one another. Then something happened to jolt the food procurement system toward the deliberate growing of wild grasses.

Flannery's excavations at dry caves dating to between 5000-2000 B.C.E. showed maize cobs slowly increasing in size as well as other signs of genetic change. Thus, he suggested that the people began to experiment with the deliberate planting of maize and other crops, intentionally expanding the areas where they would grow. After a long period, these intentional deviations in the food procurement system caused the importance of wild grass collecting to increase at the expense of other collecting activities until it became the dominate one. Eventually, the people created a self-perpetuating food procurement system, with its own vital scheduling demands of planting and harvesting that completed with earlier systems and won out because it was more durable. Therefore, by 2000 B.C.E., the highly nutritious bean and corn diet of the highland people was well established.

The crux of all these theoretical approaches is to identify the processes that caused people to shift to deliberate cultivation and domestication. For example¸ were there new cost-benefit realities that favored farming? What about such factors as the nutritive value and seasonal availability of different foods? Did genetic changes in plants and animals play a role? Unfortunately¸ it is difficult to link complex theoretical models with actual filed data¸ largely because the factors involved in such profound cultural change (the reasons why people make the changeover) do not lend themselves to easy documentation.

Many variables must be understood before we can reconstruct the conditions under which agriculture was first regarded as a profitable activity. We are searching for sets of conditions in which population pressure¸ the distribution of plants, the rate at which the environment was changing¸ and even the techniques of harvesting wild grasses all played their part in making agriculture work. Then there are variations among the potentially domesticable plants and animals, some of which resisted domestication because of their long life span or because parts of their lives took place outside human control. The seasonal distribution of wild vegetable foods or game may also have prevented experiments in domestication¸ when the seasons during which these wild foods were exploited coincided with the times of year when it was important that experimenting farming stay near their growing crops. Under these circumstances¸ people would tend to pursue their traditional food-getting habits.

Science

Accelerator Mass Spectrometry (AMS)
Radiocarbon Dating

Until about ten years ago¸ dating the rate of decay (beta counts) from different radiocarbon samples had a calculated radio that gave only approximations. Using carbon 14 (C14) and carbon 12 (C12)¸ scientists could detect and count individual decay events with radiocarbon. They would observe the emission of beta particles to determine the rate of radioactive breakdown and so estimate the number C14 atoms remaining in the sample. Since only a small number of C14 atoms break down over the many hours of the sample count¸ the samples had to be large enough to provide an adequate number of beta counts.

Back in the 1960´s¸ archaeologists collected handfuls of charcoal from hearths in plastic bags¸ the rule being¸ the larger the sample¸ the better. Scientists could not date small objects like maize cobs or tiny wood fragments embedded in the sockets of prehistoric bronze spearheads. Furthermore¸ minute samples such as seeds can easily move upward or downward into other occupations layers¸ either through human agencies such as trampling¸ or through natural phenomena such ass burrowing animals. The development of a new radiocarbon method based on accelerator mass spectrometry (AMS) in 1983 revolutionary radiocarbon chronologies and the study of early food production.

An accelerator mass spectrometer can date the age of sample material by counting the number of C14 atoms present. Rather than counting decay events (beta counts¸) researchers estimate the remaining C14 by directly counting C14 atoms. By doing this ¸ they can date samples 1¸000 times smaller than the handful of charcoal used a generation ago.

The development of small¸ high–energy mass spectrometers solved a major problem¸ that of background noise from ions or molecules of a similar mass to the C14 masking their presence. The new instruments filter out background¸ as a proportion of the sample´s atoms are propelled through an accelerator. A magnet bends the beam¸ so lighter atoms turn more sharply than heavier ones and move to the inside of the diverging beam. A filiter blocks the passage of all charged particles except those of atomic mass 14. The accelerator pushes the stripped beam through a second beam–bending magnet filtering out any last non–C14 particles. A magnetic lens focuses the beam as a C14 detector counts the number of remaining the calculation of the sample age.