Forty-eight years of landscape change on two contiguous Ohio landscapes

Abstract

This study analyzes the current and historic structure of two contiguous, rural landscapes covering approximately 242 km2 in central Ohio, USA: a till plain landscape with relatively homogeneous topography and soils, and a moraine landscape with greater geomorphological diversity and heterogeneity. These landscapes were chosen because they were both heavily dominated by agriculture during 1900–1940 and were both initially surveyed by the metes-and-bounds system. They differed, however, in the temporal pattern of settlement and development and in the inherent agricultural capability of their soils. We combined analysis of aerial photographs from 1940, 1957, 1971, and 1988 with historical archives and other available mapped data in a GIS data base to facilitate analysis of both spatial and temporal patterns of change. On the moraine, the agricultural matrix decreased over time as forest, urban/suburban areas, and industry increased. In contrast, on the till plain agricultural landcover increased through 1988, with concommitant decreases in upland forest and oak savanna. The moraine landscape exhibited greater diversity and equitability than the till plain on each date. The till plain had its greatest diversity and equitability in 1940, whereas the moraine increased in diversity and equitability during each time period. The undulating topography of the moraine encouraged landcover dynamism rather than stability, whereas the more homogeneous till plain exhibited considerable inertia. Patch and matrix shape remained constant and predominantly angular over the 48 year study period. Differences in the physical environment, especially topography and soil capability, and the socioeconomic environment, especially agricultural policies and patterns of urbanization, resulted in these two contiguous landscapes having different trajectories of change. It is clear from this study that socioeconomic factors must be combined with the physical setting to fully understand patterns of change in human-dominated landscapes.