Spatial road disturbance index (SPROADI) for conservation planning: a novel landscape index, demonstrated for the State of Brandenburg, Germany

The expansion of roads, and the subsequent changes to the surrounding landscape not only lead to landscape fragmentation but also have been shown to be a key driver of biodiversity loss and ecosystem degradation. Local declines of species abundance as well as changes in animal behaviour have drawn attention to wider ecosystem effects including altered species composition and a degradation of ecosystem functioning. However, methods for measuring and quantifying the distribution and environmental impacts of roads are not yet fully developed. We present a new technique for assessing the potential impacts of roads on biodiversity using a spatial road disturbance index (SPROADI). The index is calculated from three sub-indices: traffic intensity as a measure of traffic volume per time and space; vicinity impact, which is the assessment of edge effect of roads on adjacent habitats (the road-effect zone); and fragmentation grade, which provides an indication of the degree to which the landscape is intersected by roads. SPROADI was then tested using data from the Federal State of Brandenburg in north-eastern Germany. A sensitivity analysis was carried out on the results to assess the robustness of the index. The findings revealed expected patterns of high road disturbance in urban and peri-urban landscapes surrounding Berlin. Less obvious were the high levels of road density and impacts in forest plantations across the southern region of Brandenburg, and low levels of road disturbance in agricultural crop lands of the north-western region. Results were variable for areas under some form of protection. The only national park displayed substantially lower SPROADI values in contrast to the surrounding non-protected areas whilst other protected area categories, which were landscape conservation areas and nature parks, revealed SPROADI values that were equally high as those for non-protected areas. The results of this study demonstrate the strengths and potential applications of SPROADI as a quantitative means for identifying low-traffic areas in the context of conservation and sustainable transport planning.