Scale Area Slope Indices Using Spatially Incomplete Data

Records of individuals at either random locations on a landscape or from a systematic survey of points on a landscape can be used to quantify the occurrence of a species across a landscape and how this varies with spatial scale. Specifically a grid can be overlaid and the presence and absence of the species in each cell recorded. As grid cells are made larger (or adjacent grid cells summed), the number of records can be plotted as a function of cell size; specifically, the map area occupied by a species can be plotted against the size of the cells sampled and a power function can be fitted using regression. Such plots will have shallow slopes if species are uniformly distributed across space, which is taken as an indicator of highly connected landscapes. Conversely, steep slopes are likely to result from aggregated distributions and these are presumed to arise because of limited movement. The slope is called the scale-area slope and is a measure of connectivity. Such approaches cannot distinguish whether steep slopes are because habitat is aggregated in its distribution across the landscape or whether habitat is uniformly distributed and the organisms are restricted in their movement for some reason other than habitat connectivity. The approach also assumes that proximity is the major determinant of connectivity, an assumption that had predictive power for the long-term dynamics of populations of fishes in desert springs and streams in the southwestern US. The validity of the approach for other study systems requires evaluation.

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