Historical demography, oral history, settlement archaeology, and landscape ecology: The North Orkney Population History Project

Timothy M. Murtha, Pennsylvania State University
Patricia L. Johnson, Pennsylvania State University
James W. Wood, Pennsylvania State University
Stephen A Matthews, Pennsylvania State University
Corey S. Sparks, University of Texas at San Antonio
Julia A. Jennings, Pennsylvania State University

Between 1750 and 2000, the northern islands of Orkney (Scotland) underwent a major cycle of population growth and decline. The modern demographic transition, which contributed significantly to population decline over the past century, was atypical in several respects: it was late, the decline in fertility preceded that in mortality, and the transition involved massive net out-migration, resulting in progressive depopulation. The North Orkney Population History Project is investigating these demographic changes within the context of the transition from near-subsistence farming to modern, commercialized livestock rearing. Unusually for historical demography, we are linking parish records, census data, and vital registers to historical archaeological information on houses, farmsteads, and the past environment, and ethnographic/oral history material on local people’s perceptions of change over the past 80 years. Using data from the islands of Westray and Sanday, we compare the spatial distribution of households using multi-scale point pattern analysis to ascertain the extent to which surviving archaeological remains can capture the historically documented settlement pattern of the pre-modern demographic regime. We link archaeologically-surveyed farmsteads to decennial censuses (1851 to 1901) to determine whether household size and composition are reflected in the physical remains of abandoned farmhouses. We also map the spatial distribution of kinship-based social networks, which have already been shown to be important determinants of early childhood mortality and birth spacing during the pre-modern period. Finally, we place the spatial distribution of farmsteads in their environmental context using information from remote sensing, land-productivity surveys, field-walking, and old cadastral and OSGB maps.