Abstract

One of the elementary questions of the cultural sciences is whether and in which dimension cultural change is due to, or accompanied by population-biological change. This question is not finally decidable on the basis of the available sources of archaeology. The physical anthropology uses analytic tools, which allow access to the only archive containing information about the biological composition of a population: man itself. By the admission of ancient DNA analyses into the canon of anthropological methods, diachronic comparisons of genetic population structures and the clarification of relations under prehistoric populations become possible. The embedment of this study into the scientific framework of the BMBF-Project: Entwicklung und Adaptation archäometrischer Techniken zur Erforschung der Kulturgeschichte allows the transcription of the genetic data into cultural history by the transdiciplinary dialog with the participating sciences. The Palpa region located at the south coast of Peru is a culturally dynamic settlement chamber. In a period of approx. 6000 years the establishment of the first permanent settlements and also the rise and fall of complex societies can be observed. Aim of this study was to reconstruct the diachronic development of the matrilinear population dynamics in the investigation area by the analysis of mitochondrial genetic markers from ancient DNA. Beyond that the development of the Palpa area should be contextualized with the continental population development and colonization history by the comparison with genetic data from other pre-Columbian and recent indigenous South American populations. The genetic, archaeological and environmental data formed the basis for the anthropologic interpretation and reconstruction of the operating migration mechanisms and their influences on the past societies. For the investigations bone and teeth samples of 216 pre-Columbian individuals were acquired. The individuals came from several burial sites associated with settlements, dating into different archaeological periods. The DNA-analysis of the mitochondrial HVRI and different SNPs in the coding region of the mitochondrial genome was accomplished with newly generated analysis systems. Beyond that also analysis systems for Y-chromosomal and autosomal markers were developed and used. The obtained data was used for population genetic calculations and compared with datasets from the literature. The results of the aDNA investigations permit a reconstruction to the population history of southern Peru. It could be proven that the Paracas culture at the south Peruvian coast formed a population-biological unit and was not an accumulation of independent local groups as postulated before. The Nasca culture developed with population-biological continuity in the region. The comparison with other genetic data shows that the inhabitants of the pre-Columbian coast formed a homogeneous population differing genetically from the populations of the adjacent Andean highlands. With the change to a more complex economy and the development of self-sufficient regional (urban) centers in the Nasca time it comes to an increased allochthonous genetic influence, which can be explained by the immigration of specialists, population increase and the intensified trade with other cultural groups. The mitochondrial genetic structure of the recent Peruvian population differs significantly from that found in the pre-Columbian Palpa region. This difference can be best explained by the expansions of following Andean civilizations, particularly the Inca, which led to a genetic superimposition in large parts of western South America. On basis of the genetic data determined in this study and the comparison with recent genetic distribution patterns a more differentiated scenario for the initial colonization of South America could be developed. The present study shows that the investigation of ancient DNA provides a more differentiated picture of population development and prehistoric migration processes as possible by the analysis of modern genetic data alone.

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