Scale matters: Indicators of ecological health along the urban–rural interface near Columbus, Georgia

Abstract

Abstract Ecological data obtained from field plots can provide detailed information about ecosystem structure and function. However, this information typically reflects processes that occur over small spatial areas. Accordingly, it is difficult to extrapolate these data to patterns and processes that take place at regional scales. Satellite imagery can provide a means to explore environmental variables over a larger area. Therefore, our main objective was to examine the utility of a regional ecological assessment tool using landscape indicators of ecosystem health in a rapidly developing area of West Georgia near the city of Columbus. Indicator variables included in the assessment were: population density and change, road density, percent forest land-cover, forest patch density, landscape Shannon's Diversity Index, proportion of all streams with roads within 30 m, proportion of area that has agriculture on slopes >3%, proportion of all streams with adjacent agriculture, and proportion of all streams with adjacent forest cover. Cluster analysis was used to combine these variables into different groups, and resulting cluster means were used to rank regional areas according to degree of environmental impact. To assess the spatial accuracy of this tool results were compared to those obtained from a separate plot-level field-based forest condition study. Results derived using the landscape ecological assessment tool suggest that rural areas were the least environmentally impacted (or most healthy) of all areas in West Georgia, and support the findings from the field study. Results for developing areas were mixed between the two different studies and may be attributed to differences in scale. Overall, it appears that this tool is useful for broad generalizations about a given landscape, but is not detailed enough for site-specific management goals due to its inherent coarse spatial resolution (30 m × 30 m). However, these site-specific goals may be achieved using higher resolution (1 m × 1 m) satellite imagery and warrants further research. In any case, this tool is a useful asset for anyone needing a rapid diagnosis of ecosystem health in an inexpensive and timely manner.