How to identify climate signals within a GIS site catchment analysis

In the River Oder region, an abandonment of the settlements of the migration period has been identified. As the archaeological finding site analysis shows, the region was virtually uninhabited from 450 to 700 AD. Was an ecological crisis the reason for that exodus? Unfortunately, we have only very few scientific data sets from the German-Polish border region. So I had to find new ways to generate arguments and answer this question. By a systematic site catchment analysis I could find out signals of the paleoclimate. They are the evidence of dramatic climate fluctuations. And this is the biggest reason of the emigration of the inhabitants. At the same time the results of the site catchment analysis are the base for a predictive modeling with has clearly defined areas of high and low probabilities of finding sites.

In the context of the present study, an analysis in a GIS of sites from the Iron Age to the Early Middle Ages was applied to the River Oder Region. A site catchment analysis of the topographical setting, the soil and broader parameters was conducted as a GIS examination. In this the spatial data information in a probable operating radius around the respective settlements of the individual periods was collected and evaluated statistically. In this way, statistically significant climate proxies on the relative humidity index and temperature pattern of the paleoclimate could be demonstrated. Through the use of weighted average means it was possible to describe climate signals of the compared periods. The quantitative analysis of the data of more than 500 finding sites allows identifying significant signals. As a result I found out that at the end of the Iron Age and at the beginning of the migration period, dramatic climate fluctuations are recognized. The climate fluctuations are the main reason for emigration out of this region. In the migration period, and again at the end of the Iron Age, the region was virtually uninhabited for 250 years. The data from the site catchment analysis is in a next step the base for a predictive modeling with has clearly defined areas of high and low probabilities of finding sites.

A site catchment analysis of the topographical setting, the soil and broader parameters was conducted as a GIS examination, in which the spatial data information in a probable operating radius around the respective settlements of the individual periods was collected and evaluated statistically. In this way, statistically significant climate proxies on the relative humidity index and temperature pattern of the paleoclimate could be demonstrated. In addition, the deciding location factors of the soil and the geoecological environment of the settlement as well as distortionary anthropogenic and natural superimpositions were discussed. The ecological indicator values were rearranged into concise categories in a transformation process in consideration of their usability and informative value for matters concerning prehistoric, agronomically orientated cultures and checked for climate signals.  The identified climate signals do not represent absolute data, but rather indirect, relative data, which permit comparative statements concerning the previous and subsequent level.

With the use of comparative climate research, palynology, dendrochronology, the status of glaciers, river levels and models of paleotemperature, the climate signals that were produced in the context of the GIS environmental analysis could be verified. In this way, the probability and concision of the environmental analysis developed here and its particularly detailed chronological value were substantiated.

The final step of the GIS analysis is based on Voronoi diagrams of the sites mapped as prehistoric space models. They show concepts of space in time. In a cartographic reconstruction of settlement clusters, the relationship between the anthropogenically influenced agricultural area and extensive natural forest areas was visualised. These methods are a part for the predictive modeling to clarify for example the most interesting regions of the settlements in the migration period.

http://armin-volkmann-geoarchaeology.de/


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