Population movement may be utilised to reconstruct activities during the Mesolithic-Neolithic transition. Recent research particularly that relating to genetics and isotopic analysis, has been employed to assist in this tracking of movement, though issues with this process have arisen, as will be discussed below. Generally when analysing the transition archaeologists have tended to focus primarily on a change in economy, compiling set criteria which indicate either Mesolithic people or Neolithic people, and leaving very little room for additional interpretations. Though efforts are now being employed to allow for other interpretations. The scientific approach, encompassing both genetics and linguistics, when combined with archaeological methods can provide a window into human movements during the Mesolithic-Neolithic transition. Linguistics clearly would have constituted a huge element of culture and social differentiation from other groups or ethnicities (or inclusion within your own group), though evidence of linguistics is vague and circumstantial at present. The archaeology of the transition has been the main focus, which is likely because it is the most tangible evidence which remains. However it is important to remember that this is also subject to the bias of interpretation.
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While addressing the benefits and draw backs of genetics and linguistics we need to remain aware of the general questions surrounding the Mesolithic-Neolithic transition. Was the transition the result of a movement of farmers, foragers who adopted farming or was it a combination of the two? At what speed did the transition occur, was it a gradual or rapid affair? Furthermore the classification of the Neolithic ‘package,’ which refers to, agriculture, domestic animals, polished stone tools, pottery and settlement, are also often questioned. This is directly linked to the question of what we classify as Mesolithic or Neolithic. The recent trend has focused primarily on the mosaic nature of the transition, examining it in a very detailed manner. While this is a valid method archaeologists must be consistently conscious that results derived from individual sites do not necessarily represent larger scale activity (Robb and Miracle, 2007).
Genetics, Archaeology and Mobility during the Mesolithic-Neolithic Transition:
Past genetic processes have embedded specific signatures in the genes of modern populations. Therefore genetic data has the capability to further inform our knowledge of the transition. Increasingly archaeologists have accepted the importance of acknowledging the ‘variety, messiness and localness of the Mesolithic-Neolithic transition’ in direct contrast to those looking specifically at the bigger picture. Amongst those looking at the larger scale view are geneticists and scientists (Cooney, 2007).
The study of genetics, is ‘the science of hereditary and variation in organisms,’ Y Chromosome (male) and Mt DNA (female). The following section refers to the term haplotype which is a set of closely linked genetic markers, it is half of a genotype, which is the specific allelic composition of a cell. An allelic is one or more forms of a gene (Everything Bio 2007).
Genetic evidence generally includes mitochondrial, Y chromosomal and classical marker evidence derived from modern populations. One of the main issues to be considered when reviewing the data from genetic research is the relatively small data sets in addition to distinguishing patterns within the genetic DNA of modern populations when using them to determine ancient DNA patterns. Nevertheless the modern composition of the European gene pool appears to reflect these early colonising movements more strongly than any other demographic event in prehistory. It has been estimated that around 85 per cent of European mitochondrial sequences probably originated in the upper Palaeolithic of Europe.
There have been a number of issues identified with early attempts to use DNA to track mobility of ancient peoples. These were primarily to do with contamination. However it must also be considered that this form of data is statistical and often is recorded and then displayed in huge quantities which in turn complicates the process. Y chromosome is the male line and the mitochondrial DNA is the female line. There is also the additional problem of time depth, as while it is possible to retrieve genetic patterns it is important to note that they are not defined or distinguished in terms of period of existence. So movement of people represented in the data reflects not just the Mesolithic-Neolithic transition but also movement of people in the time since then, such as during the Roman period (Zvelebil 2008).
Data from protein markers (sometimes called ‘classical’ markers) are still more abundant than are data from DNA, although this situation is rapidly changing. Molecular genetic markers have provided previously unavailable resolution into questions of human evolution, migration and the historical relationship of separated human populations. Different evolutionary models are relevant to the different continents. Migration can profoundly affect genomic variation within a population. For most populations are rare exchange of marriage partners between groups occurs and an average of one immigrant per generation in a population is sufficient to avoid fixation of alleles. However, sometimes a whole population (or a part of it) may migrate and settle elsewhere. Thus the frequencies of alleles among the founders of the new population will differ from those of the original population and will inevitably differ again from those among which it settles.
The genetic effects of early forager farmer intermarriages would have multiplied themselves through the hundreds of human generation since the Neolithic. Genetic models that tracing backward from modern populations tend to be highly sensitive to relatively small between hunter gatherers and farmers. For example geneticists studying the y chromosome in modern Europeans often argue that Neolithic farming spread primarily through demic diffusion or the migrations of the farmers themselves.
In addition geneticists, while studying mitochondrial DNA in modern Europeans, have suggested that there is a large Palaeolithic component in modern Europeans. Thus because the Y chromosome is inherited strictly along the paternal line and mtDNA is inherited maternally, it may be the case that small groups of Neolithic men intermarried with indigenous women. An ancient DNA study appears to support this in that a particular mtDNA haplotype n1a found in early Neolithic female skeletons is comparatively rare among modern Europeans (Bentley 2007).
LBK farming, rather than arriving as a wave of advance, is thought to have leap froged from the North East to the Mediterranean. Theories surrounding the movement of LBK farmers tend to suggest that they could move an entire village society 20km or 30 km in a decade but that it would take foragers much longer than this. Foragers are thought to have been mobile over larger territories, for them a distance of 50km may be considered as one journey between one foraging group to the next, but they would encounter many more settled farmers along the way (Robb and Miracle, 2007). It has been proposed that the spread of farming increased local population densities, causing demic expansion into new territory and diffusive gene flow between the Neolithic farmers and Mesolithic groups (Sokal, 1991). It is likely that different regions must have experienced different blends of cultural exchanges and migratory movements.
Researchers have the ability to test the effect of factors such as, prehistoric population sizes, rates of gene flow, and mutation rates, on the likelihood of different scenarios. In the near future, they will also allow users to integrate information from the growing body of ancient genetic diversity, in addition to the broad modern data sets (Cavalli-Sforza and Feldman 2003).
Demographic growth in the well identified, specific areas of origin of agriculture must have stimulated a continuous peripheral population expansion wherever the new technologies were successful. ‘Demic expansion’ is the name given to the phenomenon (that is, farming spread by farmers themselves) as contrasted with ‘cultural diffusion’ (that is, the spread of farming technique without movement of people). Innovations favouring demographic growth would be expected to determine both demic and cultural diffusion. Recent research suggests a roughly equal importance of demic and cultural diffusion of agriculture from the Near East into Europe in the Neolithic period.
Molecular studies using mitochondrial DNA, Y chromosome DNA and nuclear DNA differ in their assessment of the contribution of near eastern farmers to the European gene pool. Some mitochondrial DNA studies suggest that the contribution of near eastern farmers to the European gene pool is about 20%, a similar percent 22% is suggested by a y chromosome study. However the same data was re-examined by Chikhi et al. Who found that by using a different methodology, they resulted with an average contribution of between 50% and 60% from near eastern farmers to the European gene pool.
Estimations depend not only in the markers employed but also on the model used and its inherent assumptions. Nuclear DNA studies support a European gene pool. Thus many genetic studies d to support the idea of demic diffusion at some level but there is still a lack of consensus with regard to the percentage of the contribution of early near eastern farmers to the European gene pool (Pinhasi et al, 2005).
Linguistics and Archaeology, during the Transition
Human languages are an integral aspect of behaviour and culture. Phylogenetic trees are constructed from linguistic elements, portray the evolution of languages (Pagel 2009). There is generally a strong correlation between genetic tree clusters and language families. It is likely that language shifts have become more common recently as a result of massive colonisations made possible by development of mobility due to developed infrastructure, transportation and colonisation.
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In Europe during the nineteenth century much of the archaeological focus of the transition was directed towards classification and sequences of economy. Around the middle of the nineteenth century the whole study of the subject entered a new phase which was linguistic rather than archaeological. It was by now generally assumed that the similarities in the different Indo-European languages were to be explained by their derivation from a single ancestral language, older than Greek or Latin or Sanskrit (Renfrew 1990, p 14).
This proto-Indo-European could be reconstructed by studying what was common to specific cognate words in the different languages. Renfrew discusses Childes extreme views published regarded ‘superiority in physique’ and ‘the vehicles of a superior language’ (Renfrew 1990, p15-16). Marija Gimbutas has located the Indo European homeland in the Steppes of South Russia. She refers to Kurgan culture and states that it is the last candidate for a Proto-Indo-European homeland based on the common words compiled to reconstruct the original ancient language. Renfrew has difficulty with this as it is still dependent on the construction of the mother language. Renfrew also highlights the problem of how to explain the historical circumstances within which languages would be replaced?
Taken in isolation neither archaeological nor genetic evidence can shed much light on the linguistic identity or ethnicity of the colonising population although when combined together some suggestion can be made. It is generally assumed that the western population were either rare indo-European or proto indo-European setting the stage for North central Europe as the homeland of indo Europeans. Large sections of this population in northern Europe would have to adopt indo European speech subsequently from indo European farming groups penetration central Europe from the near east and east Mediterranean as suggested by Renfrew and modified for temperate and northern Europe.
Another key figure within the field of linguistics is Oppenheimer. In his text The Origins of the British (2007), he has suggested of Celtic origin, that neither Anglo-Saxons nor Celts had much impact on the genetics of the inhabitants of the British Isles, and that British ancestry mainly traces back to the Palaeolithic Iberian people, now represented best by Basques. He also argued that the Scandinavian input had been underestimated. It has also been put forward that geography and climate have had an influence on the genetics and culture of Britain (Oppenheimer 2007, 21-26).
Languages, like genes, provide vital clues about human history. As mentioned already the origin of the Indo-European language family is “the most intensively studied, yet still most recalcitrant, problem of historical linguistics”. Numerous genetic studies of Indo-European origins have also produced inconclusive results (Gray and Atkinson 2003).
Glottochronology is an approach in historical linguistics for estimating the time at which languages diverged, based on the assumption that the basic (core) vocabulary of a language changes at a constant average rate. This term is sometimes interchangeable with lexicostatistics though the latter refers to statistical manipulation of lexical material for historical inferences and is not necessarily associated with dates (Campbell, 2004). It is not usually accepted as a valid methodology, as it has certain inherent issues.
The derivation of modern languages mostly or completely from a single language spoken in East Africa does not mean that this was the only language in existence at the time. When analysing Indo-European language data, the following are often included: the ancient Celtic language of Gaul (modern France), within which is a split between Gaulish (Continental Celtic) and the British form (Insular Celtic), with Insular Celtic subsequently splitting into Brythonic (Welsh, Breton) and Goidelic (Irish and Scottish Gaelic). Taken together, the network thus suggests that the Celtic language arrived in the British Isles as a single wave (and then differentiated locally), rather than in the traditional two-wave scenario (“P-Celtic” to Britain and “Q-Celtic” to Ireland).
In 1786 Sir William Jones discovered remarkable similarities between Sanskrit, Greek, Latin, Gothic, Celtic, and Persian, indicating a common source for these languages, possibly Indo-European language. Then in 1863 Schleicher proposed an evolutionary tree of descent for the Indo-European language family, followed by Charles Darwin who introduced the evolutionary tree concept to the descent of species. Schmidt (1872) published the wave model which denotes that distinct languages increasingly acquire similarities through borrowing. More recently it has been proposed to unite these two models into a single network diagram of language evolution (Forster and Toth, 2003).
Simple explanations at odds with a complex human history
Critique: complex data, requires degree of manipulation to display
How does this relate to and affect archaeology? And what we know about mobility and migration during the transition?
Confusion between names and genetics. Ancient dna NIa very rare in Europe, haplotype, example that lineages do die out and not all colonisation works. This is further complicated when you look at animals. Cattle and pigs are descendnt fomr the north east but pigs are descendant from a combination of north west domestication. Bear deliberately introducted to Ireland.
The past decade of advances in molecular genetic technology has heralded a new era for all evolutionary studies, but especially the science of human evolution. Data on various kinds of DNA variation in human populations have rapidly accumulated. Haploid markers from mitochondrial DNA and the Y chromosome have proven invaluable for generating a standard model for evolution of modern humans. Co-evolution of genes with language and some slowly evolving cultural traits, together supports and supplements the standard model of genetic evolution. The advances in our understanding of the evolutionary history of humans attests to the advantages of multidisciplinary research (Cavalli-Sforza and Feldman 2003).
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